PROCEEDING - Website Personal - Institut Teknologi Sepuluh ...personal.its.ac.id/files/pub/4349-anasution-ep-ICOWOBAS 2011 paper.pdf · PROCEEDING THIRD ... Surabaya‐Indonesia i

PROCEEDING THIRD INTERNATIONAL CONFERENCE AND WORKSHOP ON BASIC AND APPLIED SCIENCES

ENABLING RESEARCH INNOVATION ON SCIENCES AND TECHNOLOGY TO MEET GLOBAL CHALLENGES

SEPTEMBERT 21st - 23st

FAKULTAS SAINS DAN TEKNOLOGI UNIVERSITAS AIRLANGGA

Kampus C, Jl Mulyorejo, Surabaya, 60115 Tel.: 62-31 5936501; Fax: 62-31 5936502

Website: http//www.fst.unair.ac.id; email: [email protected]

Third International Conference ICOWOBAS 2011 And Workshops on Basic and Applied Sciences September 21st‐23rd, 2011,

Surabaya‐Indonesia

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FOREWORD BY THE DEAN Faculty of Science and Technology, Airlangga University, Indonesia

Assalamu’ alaikum warahmatullahi wabarakatuh

On behalf of all member of The Faculty of Science and Technology, Airlangga University, It gives me a great pleasure to extend my sincere and warm welcome to the participants of the International Conference and Workshop on Basic and Applied Sciences /ICOWOBAS 2011, in Elmi Hotel, Surabaya. It is an honor and joy for us to be host of this congres, where all participants have a chance to present and discuss our knowledge about development of basic and applied science.

The International Conference and Workshop on Basic and Applied Sciences 2011 is organized as implementation of existing collaboration between Airlangga University with Universiti Technology Malaysia (UTM), in order to promote the development of science and their prospects in industry application.

Basic science is become basic for development of multi applied science and has grown very rapidly into more specified fields, including biotechnology, material science, techno biomedical, informatics, computer and Biophysics.

Hopefully, this conference provides a great opportunity for lecturers, researchers and industries to build better communications. A better communication between university and industry is one of the best ways to share the development of research in the basic and applied science which will be used in industries.

Finally let me congratulate to all of you once again for organizing and participating in this conference. Also to the committee members, speakers, moderators, editor boards, sponsors and participants for your kind contributions, I would like to express my gratitude for all the hard work on the succeeding this congres. Hopefully the new friendship and new collaboration will start from this moment, and for UTM’s delegates please do not forget to pleasure by visiting a nice places for examples new Suramadu Bridge and other places that Surabaya can be offered.

Thank to Allah SWT for His blessing so far.

Win Darmanto



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FOREWORD

International Conference and Workshops on the Basic and Applied Sciences (ICOWOBAS) is organized as implementation of existing collaboration between Airlangga University with Universiti Teknologi of Malaysia (UTM) in order to promote the development of sciences and their prospect of application in industry. The programs of this activity are the scientific program involves the presentation of paper and poster in the area of chemistry, biology, physics, and mathematics and their applications. It also conducts the workshop program that will be presented the current issues in biological product. Thus it invited many participants as academic researcher, scientist, industrial practitioners, industrial professionals, government officers, students and other participants. The meeting intends to bring together researchers, scientists, and scholars to exchange and share their experiences, new ideas, and research results in related fields and discuss the practical challenges encountered and the solutions adopted.

These proceedings hold the full papers presented at the 3rd ICOWOBAS. The conference took place in Surabaya (Indonesia) at the Mercure Grand Mirama Hotel Convention Centre, September 21‐22, 2011, and the workshops were conducted at the Faculty of Sciences and Technology, Airlangga University, September 22‐23, 2011..

Highlights of the conference include: Prof. Dr. Zuhaimy Ismail (Faculty of Science/ Mathematics, University Teknologi Malaysia), Dr. Yoshiaki Takaya (Faculty of Pharmacy, Meijo University, Japan), Prof. Dr. Noriah Bidin (Faculty of Science/Physics, University Teknologi Malaysia) and Dr. Xavier Daniel, Ph.D (Lab. Cell and Molecular Biology, JUNINE Neuchatel, Switzerland) as plenary speakers.

In total, we received 144 submissions for oral publications and 39 for posters, and 137 submissions for publication‐based full papers. Of these, the numbers of acceptances were 139 conference, and 39 poster publication. As the acceptance rates illustrate, competition was stiff, and the accepted submissions reflected high rates of reviewer enthusiasm. By design, these are lightly reviewed and almost always accepted.

ICOWOBAS is a lot of work. We could not have done it without help from many people. We would especially like to thank:

− The Scientific Board of ICOWOBAS, for inviting us to chair the meeting

− The Rector of Airlangga University, for permiting and supporting us to conduct the conference

− Our colleagues in the Faculty of Sceinces and Technology Airlangga University, for their help in the conference organization

− The Program Committee, for managing the review process

− The Scientific Committee for assisting in selecting debates and symposia

− The Dean of Faculty of Sceinces and Technology Airlangga University, for his support in the conference planning

− The Local Committee, for organizing and handling the conference

− The 11 reviewers, for providing professional reviews.

− Our sponsors: Diastika Biotekindo, Pupuk Kaltim and dr. Agus Subagjo SpJP (K) FIHA.

And above all, the authors, symposium participants, and attendees. Surabaya, September 21, 2011



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Hery Purnobasuki, PhD. ICOWOBAS 2011 Chairperson



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Conference Venue

Mercure Grand Mirama Hotel Jl Raya Darmo 68‐78 Surabaya East Java‐Indonesia Tel.: +6231‐562300 Fax.: +6231‐5678383 e‐mail: [email protected]

Organizer

Faculty of Science and Technology, Universitas Airlangga, Indonesia

Faculty of Science, Universiti Teknologi Malaysia

Patrons:

Rector of Airlangga University

Advisory Board:

Dean of Faculty of Sciences and Technology

Organizing Committees Chair person: Hery Purnobasuki, M.Si., Ph.D Co Chair persons: Airlangga University:

1. Dr. Nanik Siti Aminah, M.Si. 2. Dr. Retna Apsari, M.Si.

Universiti Teknologi Malaysia (UTM): 1. Prof. Dr. Mazlan Bin Aziz 2. Prof. Dr. Wan Aini Wan Ibrahim

Secretary : 1. Dr. Fatmawati, M.Si. 2. Yanuardi Raharjo, S.Si., M.Sc.



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Treasurer : 1. Drs. Pujiyanto, M.Si. 2. Dra. Yayuk Wahyuni, M.Si. 3. Aminatun, S.Si., M.Si.

TECHNICAL COMMITTEE PUBLIC RELATIONS/PROMOTION:

1. Drs. Hery Suwito, M.Si. 2. Dr. Prihartini Widiyanti, drg, M.Kes 3. Dr. rer.nat. Ganden Supriyanto, M.Sc.

SECRETARY CHAIRS :

1. Alfa Akustia Widati, S.Si, M.Si. 2. Nuril Ukhrowiyah, S.Si, M.Si. 3. Cicik Alfiniyah, S.Si, M.Si. 4. Purbandini, S.T., M.T. 5. Dwi Hastuti, S.T. 6. Handayani 7. Catur Dwi Cahyono, SKM

PROGRAMS: A. Conference and Poster :

1. Dr. Alfinda Novikristanti, M.Si. 2. Ina Kuswandari, Dra., M.Si. 3. Dr. Dwi Winarni, M.Si. 4. Drs. Siswanto, M.Si. 5. Drs. Suliyanto, M.Si. 6. Franky Chandra Satria Arisgraha, S.T., M.T.

B. Workshop:

1. Prof. Dr. Ni Nyoman Tripuspaningsih, M.Si. 2. Dr. Y. Wulan Manuhara, M.Si. 3. Dr. Retna Apsari, M.Si.

SCIENTIFIC COMMITTEE :

1. Prof. Dr. Ni Nyoman Tripuspaningsih, M.Si. 2. Prof. Dr. Suhariningsih, M.Si. 3. Prof. Dr. Ir. Agoes Sugianto, DEA 4. Dr. Y. Sri Wulan M, M.Si. 5. Dr. Moh. Yasin, M.Si. 6. Dr. Soegianto Soelistiono, M.Si. 7. Dr. Bambang Irawan, M.Sc. 8. Dr. Eridani, M.Si. 9. Dr. Miswanto, M.Si. 10. Dr. Pratiwi Pudjiastuti, M.Si. 11. Dr. Muji Harsini, M.Si.

PROCEEDING TEAM :

1. Dr. Alfiah Hayati, M.Kes. 2. M. Zakki Fahmi, S. Si, M.Si. (Chemistry) 3. Eko Prasetyo Kuncoro, ST, DEA (Biology) 4. Nita Citrasari, S.T., M.T. (Physics) 5. Eva Hariyanti, S.Si., M.Si. (Mathematics & Technology)



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EQUIPMENT CHAIRS : 1. Drs. Hamami, M.Si. 2. Syaiful Anwar, S.Sos 3. Drs. Suryanto

DOCUMENTATION:

1. Drs. M. Affandi 2. Fajar Sodiq, S.T. 3. Asmari

TRANSPORTATIONS AND ACCOMODATIONS :

1. Drs. Adri Supardi, M.S. 2. Fadli Ama, S.T., M.T.

FOOD AND BAVERAGES:

1. Lies Wismaningtyas, S.Sos 2. Dra. Trijas Sarwendiah

SECURITY :

1. Imam Sapuan, S.Si., M.Si. 2. Rizqi 3. Giman

SPONSORSHIP:

1. Dr. Ni’mahtuzahroh 2. Mahniza, S.H.,CN 3. Dra. Suzyanna, M.Si. 4. Drs. Kartono, M.Sc. 5. Drs. Arif Wibowo, M.Si. 6. Drs. Yusuf Syah, M.Si. 7. Drs. Sediono, M.Si.

WEBSITE :

1. Farid Ardiansyah, S.Kom 2. Yoseph Ghita Y, S. Si 3. Taufik, ST, M.Kom

Keynote Speakers Prof. Dr. Zuhaimy Ismail Department of Mathematics, Faculty of Science, Universiti Teknologi Malaysia “Optimal Design Of Parameter Estimation In Double Exponential Smoothing Using Genetic Algorithms And Other Evolution Programs”

Dr. Yoshiaki Takaya Natural Product Chemistry, Faculty of Pharmacy‐Meijo Univ‐Japan “A Stilbenetetramer from Corks of Vitis vinifera ‘Kyohou’ ”



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Prof. Noriah Bidin, Ph.D Department of Physics, Faculty of Science, Universiti Teknologi Malaysia “Thermal Effects In Diode Pumped Vanadate Laser” Dr. Xavier DANIEL, Ph.D Lab. Cell and Molecular Biology, UNINE Neuchatel, Switzerland

Invited Speakers Prof. Dr. Mohd. Marsin Sanagi Department of Chemistry, Faculty of Science, Universiti Teknologi Malaysia “Determination of Triazine Herbicides in Sugarcane Samples by Dispersive Liquid‐Liquid Microextraction‐Gas Chromatography–Mass Spectrometry” Dr. rer.nat. Ganden Supriyanto, M.Sc Department of Chemistry, Faculty of Science and Technology, Airlangga University “(Bio)Sensor For Disease Detection And Food Quality Testing” Prof. Dr. Suhariningsih Department of Physics, Faculty of Science and Technology, Airlangga University “Electric Field Optimization On Diabetes Mellitus Therapy Type II and Hypertension”

Dr. Herry Suprajitno, M.Si Department of Mathematics, Faculty of Science and Technology, Airlangga University “Solving Biobjective Linear Programming Problem Using Interval Arithmetics” Dr. Yosephine Sri Wulan Manohara, M.Si Department of Biology, Faculty of Science and Technology, Airlangga University “Plant Hairy Root Culture: A Promising System To Produce Secondary Metabolite” Dr. Eko Prasetyo Kuncoro, ST, DEA Department of Biology, Faculty of Science and Technology, Airlangga University “Biosorption: A Sustainable Technology for Heavy Metals Removal”



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CONTENTS

FOREWORD i

ORGANISER & COMMITEE iii

CONTENS vii

KEYNOTE

Optimal Design of Parameter Estimation in Double Exponential Smoothing using Genetic Algorithms and Other Evolution Programs ................................................................................

K 001

A Stilbenetetramer from Corks of Vitis vinifera ‘Kyohou’......................................................... K 002

Thermal Effects In Diode Pumped Vanadate Laser .................................................................... K 003

INVITED

Application of Dispersive Liquid‐Liquid Microextraction for the Analysis of Triazine Herbicides in Sugarcane Samples ...............................................................................................

I 001

Electric Field Optimization On Diabetes Mellitus Therapy Type II and Hypertension ............... I 002

Plant Hairy Root Culture: A Promising System To Produce Secondary Metabolite ................... I 003

Biosorption: A Sustainable Technology for Heavy Metals Removal .......................................... I 004

B. BIOLOGY

The Limiting Nutrients of Algae Biomass During Dry Season in Mrica Reservoir of Banjarnegara, Central Java .................................................................................................

B 001

Detection of Motile Aeromonas Existence at Golden Fish and Its Sensitivity on Novobiocin .... B 002

Exploration of Indigenous Bacteria from Pond Brackish Water at Gresik as Candidate Water Bioremediation and Vibrio harveyi biocontrol (as Agent Vibriosis at Prawn) ....................

B 003

Growth Kinetics of Biosurfactant Producing Bacteria (Acinetobacter sp. P2(1)) In Glucose ...... B 004

Evaluation of Hyperthermia Effect on Cell Viability by a Simple Crystal Violet Method of MDA‐MB 231 Cell Line ............................................................................................................

B 005

Role of Microbial Consortium on Nitrogen and Phosphorus Accumulation in Leaf of Jackbean (Canavalia ensiformis) .......................................................................................................

B 006

Biodegradation of Diesel Oil Using Variation of Hydrocarbonoklastict Microbial Consortium . B 007

Kesum Leaf Extract Potential as Anti‐ulcer Agent .............................................................. B 008

Antibacterial Coatings of Natural Product Prevents Bacterial Attachment ........................ B 009

Structure of Lenticels on The Pneumatophores of Avicennia marina: as Aerating Device B 010



viii

Deliver Oxygen in Mangrove’s Root ..................................................................................

The Effect of Rhizobium Bacteria on The Anatomy Characteristics and Chlorophyll Content in Leaf of Jackbean Plant (Canavalia ensiformis l.) ................................................................

B 011

Community Structure of Phytoplankton in Plawangan, Klaces, and Donan Segara Anakan Lagoon Between February and June 2005 ........................................................................

B 012

Active Side of Lactonase, a Barrier to Bacterial Communication, an Anti‐infective Alternative of Shrimp Disease ..........................................................................................

B 013

Effect Of Rhizobium Bacteria To The Growth And Production Of Jackbean Plant (Canavalia ensiformis l.) ..................................................................................................................................................

B 014

Effectiveness of Acinetobacter sp. Biosurfactant on Oil Sludge Solubilisation .................... B 015

The Effect of Microbial Consortium Fertilizer on The Characteristics of Leaf Anatomy and Clorophyll Content of Jackbean Plant (canavalia ensiformis l.) .........................................

B 016

Optimization of Protoplast Production from Leaves Mesophyl Phalaenopsis zebrina and Dendrobium stratiotes ......................................................................................................

B 017

The Effectiveness of Pseudomonas putida T1(8) Biosurfactant in Bioremediation of Crude Oil Contaminated Soil ...........................................................................................................

B 018

A Taxonomic Study of Annona, i.e. Annona muricata, A. Squamosa, and A. reticulata Based on Numericalll Method by Alkaloid Characters Documents .............................................

B 019

Response of Rhizobium on Nitrogen Accumulation in Leaf by Jackbean Plant (Canavalia ensiformis L.) ...................................................................................................................

B 020

Neural Tube Defects (NTDs) of Mice Embryo As Effect of 2‐Metoxyethanol Treatment ........ B 021

Somatic Embryogenesis of Sambiloto (Andrographis paniculata Nees) Callus Culture on MS Medium With Added by 2,4‐D and BAP ...........................................................................

B 022

The Effect of Alkaloid Fraction Jarong (Achyrantes aspera linn) Leaf on Viability and Mitotic Myeloma Cell Mice ...........................................................................................................

B 023

The Effect of Arbuscular Mycorrhiza Fungi (amf) on Leaf Anatomical Characteristics and Chlorophyll Content of Canavalia ensiformis, L. .......................................................................

B 024

Spermatozoa Binding Constrains Towards The Goat Oocyte Zona Pellucida by Antibodies Induced from 116 kda Protein Human Spermatozoa Membrane .......................................

B 025

ICP11 as a Marker for Identifying Vannamei (Penaeus vannamei) Shrimp Against WSSV Diseases ............................................................................................................................

B 026

The Effect of Subculture on Hairy Root Development of Java Ginseng (Talinum paniculatum gaertn.) ............................................................................................................................

B 027

Ball Sea Cucumber Phyllophorus sp. Improved Interleukin‐12 Response Against B 028



ix

Mycobacterium Tuberculosis ............................................................................................

Maximum length as an Indicator to Examine Overall Selectivity of a Multi‐Species and Multi‐gear Fishery of an African lake, Lake Mweru ......................................................................

B 029

Growth Factors (BMP‐15 and GDF‐9) Gene Expression of Mice Oocytes in Vitro ................. B 030

C. CHEMISTRY

Coated Wire La3+ Ion Selective Electrode Using Carboxymethoxytertierbuthyl Calix[6]arene Compound as Ionophore ..................................................................................................

C 001

Optimation of Mixture Ratio of Intracellular and Extracellular Recombinant α‐L‐arabinofuranosidase to Hydrolysis Rice Straw ...................................................................

C 002

Potentiometric PVC Membrane Sensor for Thiocyanate Based on Chitosan as A Carrier in A Coated‐Wire Membrane Electrode ...................................................................................

C 003

Corrosion Inhibition Studies by Thiophene Derivatives in the Presence of Cationic Surfactant on Carbon Steel in Hydrochloric Acid ...............................................................................

C 004

Preparation and Microstructure of Nanostructured Transition Metal Tin ........................... C 005

Preparation and Physical Characterization of Vanadium Doped LiFePO4 ........................... C 006

Structural and Morphological Studies of LiFePO4 Nanostructures ...................................... C 007

Isolation of Alkaloid from the Leaves of Erythrina crista‐galli ............................................ C 008

Phytochemicals and Biological Activities of Selected Piper Species .................................... C 009

Preparation and Characterization of Coated Wire Ion Selective Electrode with Ionofor Calyx[4]arena .....................................................................................................................

C 010

Characterization of Flavonoid Compound and Hypoglicemic Effect of Leaves Extract Bungur (Lagerstroemia speciosa Pers.) on Alloxan‐induced Diabetic Mice ........................................

C 011

Preparation of Glycerol from Castor Oil of Ricinus communis l ................................................ C 012

Different strategies for functionalization of Carbon nanotubes in Drug delivery system ..... C 013

Determination Of Optimum Conditions Of Buffer Solutions And Sodium Thiosulfate (NA2S2O3), Tin (II) Chloride (SnCl2) Concentration As Reductor In Iron Using Spectrophotometry Visible Method .........................................................................................

C 014

Determination of Protein Profile Streptococcus mutans Biofilm For Biomarker Exploration of Dental Caries Risk .......................................................................................................................

C 015

Isolation and identification of 8‐oxo‐erythraline from the stembark of Erythrina crista‐galli .. C 016

Discovery of New Potential Antimalarial Compounds using QSAR Modeling and Database Mining .....................................................................................................................................

C 017



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Analysis of Melamine With Adsorptive Stripping Voltammetry ............................................... C 018

Specific Protein Profiling of Candida albicans Biofilms ...................................................... C 019

Synthesis of Iron(III) Organometallic Compound ................................................................ C 020

Synthesis of Fendiline Derivative f 551: A New Class of Positive Allosteric Modulators at GABAb Receptors in Rat Neocortex ....................................................................................

C 021

Synthesis of Fendiline Derivative f 551: A New Class of Positive Allosteric Modulators at GABAb Receptors in Rat Neocortex ...................................................................................

C 022

Protein from EM‐Fermented Prawn Waste for Aquaculture Diet ............................................. C 023

Comparative The Ability Reducing Sodium Thiosulfate (Na2S2O3) and Potassium Oxalate (K2C2O4) to Analysis Total Iron Concentration by Spectrophotometer Visible ...........................

C 024

A CFD Study of Gas Lift Technology in Hydrocarbon Production through Continuous Artificial Lift .....................................................................................................................................

C 025

The Production and Characterization of Cellulose Diacetate Membrane from Cane Pulp (Saccharum officinarum L.) Hybrid Zeolite Active for Raw Sugar Cane Purification ............

C 026

Erythrinan Alkaloids as Inhibitor of Plasmodium berghei Dihydrofolate Reductase (pbDHFR) C 027

The Increase Percentage of Aldehyde Dehydrogenase After Acute Alcohol Consumption in Sera Rats Wistar ................................................................................................................

C 028

Benzyl Triethyl Amonium Chloride (BETAC) as Inhibitor Corrosion on Steel .......................... C 029

Effect of Pretreatment Methods on Carrageenan Extraction from Kappaphycus alvarezii and Eucheuma spinosum .............................................................................................................

C 030

Synthesis of Nanosodalite as Solid Base Catalyst for Knoevenagel Condensation Reaction C 031

Utilization of The Phenolic Compounds in The Flesh of Kepel Fruit (Stelechocarpus burahol) as Antioxidant ...................................................................................................................

C 032

Different Strategies for Functionalization of Carbon Nanotubes in Drug Delivery System C 033

A Novel Photometric Method for Melamine Determination in Milk ................................... C 034

The New Strategies Destroying The Biofilm Extracell Matrix Of Candida albicans................................... C 035

The Influence of Addition Fenton Reagent and TiO2 on the Phenol Degradation ..................... C 036

Photocatalytic Degradation of NaLS Surfactant with Combination Reagent Fenton and TiO2 C 037

Ligand Binding Studies of Mutation Effect on β‐Xylosidase from Geobacillus thermoleovorans IT‐08 .............................................................................................

C 038

Determination of Triazine Herbicides in Sugarcane Samples by Dispersive Liquid‐Liquid C 039



xi

Microextractio‐Gas Chromatography‐Mass Spectrometry ..................................................

Separation of Vinpocetine Enantiomers using Cyclodextrin‐Electrokinetic Chromatography and Cyclodextrin‐Modified Micellar Electrokinetic Chromatography .................................

C 040

Kinetics Study on Water Treatment of Hg Metal by Adsorption‐Fluidization with Chitosan‐Urea as Adsorbent ....................................................................................................................

C 041

Purification of Simulated Natural Gas Using Alumina Supported Manganese Oxide Doped Noble Metal Oxides Over Catalytic Methanation Process ....................................................

C 042

The Esterification of Palmitic Acid Using Al3+‐Bentonite .................................................... C 043

Performance of Public Cluster Molecular Dynamics for Protein Analysis ........................... C 044

Comparison Study Of Capability Sodium Thiosulfate (Na2S2O3) And Tin (II) Chloride (SnCl2) Reductants For Analysis Total Iron By Uv‐Vis Spectrophotometry Methods ........................

C 045

Determination of Uric Acid by Stripping Voltammetry using Molecularly Imprinted Polymethacrylic Acid Modified Hanging Mercury Drop Electrode ........................................

C 046

Determination Of Protein In Milk Contaminated Melamine By Precipitation With Trichloroacetic Acid Using Kjeldahl Modified .....................................................................

C 047

The Usage Of Bilimbi Wuluh Flowers (Averrhoa Bilimbi Linn) Dye Extract As Ph Indicator ....... C 048

Construction of Secretion Vektor for α‐L‐Arabinofura nosidase Gene from Recombinant Escherichia coli DH5 α/p TP510 in Saccharomyces cerevisiae ..................................................

C 051

Synthetis Studies of Functionalised Porphyrins ................................................................. C 052

Catalytc Cracking of Palm Oil to Produce Biogasoline using H‐Almcm‐41 Catalyst ............. C 054

P. PHYSICS

On the Origin of Inverted Modulation in HHG Signal of Aligned CO2 ........................................ P 001

The Effect of Composition Co:CR Variation to Mechanical Properties and Cytotoxicity Co ‐ Cr ‐ HA Composite ..........................................................................................................................

P 002

The Predict Of Ionosphere Fof2 Using Multivariat Analyse ...................................................... P 003

The Growth and Characterization of III‐V Nanostructures Grown Using MOCVD ..................... P 004

The Effect of High kV Technique on Pediatric Thoracic Examination in Image Quality and Dose ......................................................................................................................................

P 005

Enhancement of Sensitivity in Surface Plasmon Resonance Biosensor Using Graphene Materials: A Theoretical Predictions .......................................................................................

P 006

The Investigation Of Energy Level Of Even‐Even 104‐112Cd isotopes under the framework of IBM‐1 .................................................................................................................................

P 007



xii

Features And Structural Yields Of Isomer In Deep‐Inelastic Collisions ..................................... P 008

Effect of Exogenous ALA to Increase the Production of Endogenous Porphyrin Staphylococcus aureus Bacteria For Applying Photodynamic Inactivation of Bacteria .............

P 009

Synthesis of Barium M‐Hexaferrites BaFe12‐2xCoxZnxO19 Doped by Co2+/Co3+ and Zn2+ were

Produced by Co‐Precipitations ................................................................................................... P 010

Detection of Dissociation and Association Effects of NO2 – NO Gases by Laser‐based Photoacoustic and Wavelength Modulation Spectroscopy Methods ........................................

P 011

Design Of Fiber Optic Temperature Sensor .............................................................................. P 012

First Principle Study Of Strucutral Properties Of Some III‐V Alloys Using SQS Approach ..........................................................................................................................................

P 013

The Determination Of The Total Elektron Content By Gps Data .......................................... P 014

Double Frequency Spacing Brillouin/Erbium doped Fiber Laser .............................................. P 015

Transfer Factor Measurements of Uranium, Thorium and Potassium from Soil to Rice ........ P 016

Effect Of Polystyrene Coating Characteristic To The QCM Sensor Performance ....................... P 017

Study Of Dynamic Freedericksz Transition In Nematic Liquid Crystals ...................................... P 018

Ab initio Study of Structural and Electronic Properties of Amorphous Ge‐Te‐In Material .. P 019

Fuzzy System Based on Laser Speckle Imaging for Diagnosis of Human Enamel Quality Induced By Q‐switched Nd:YAG Laser ..................................................................................

P 020

M. MATHEMATICS

Analysis of Sentence Feature for Automatic Text Summarization in Indonesian Language ..... M 001

Stabilizability and Detectability of Reduced‐Order Model for Unstable Infinite‐Dimensional Systems ................................................................................................................................

M 002

Consistency Of The Bootstrap Estimator For Parameter Of Ar(1) Process Using Delta Method M 003

Linear Representation of Dual Right Module ............................................................................ M 004

EstimateThe Valueof Logarithm Tendsto 1 ............................................................................ M 005

Locating and Total Dominating Sets of Direct Products of Complete Graphs ........................... M 006

Distrubution Estimation of Heat Conduction using Kalman filtering which Implemented on Reduction Model .................................................................................................................

M 007

Modelling the English Football League Using Constraint Satisfaction ...................................... M 008



xiii

A Model Development of Tutorial Scheduling System Through Decision Support System in Universitas Terbuka: A Case Study in Surabaya Regional Technical Unit ..................................

M 009

Intracranial Pressure Classification Using Support Vector Machines Sequential ...................... M 010

A Conservative Nonstandard Finite Difference Scheme for SIR Epidemic Model ..................... M 011

Least Squares History Matching for Reservoir Identification ..................................................... M 012

Super (a,d)‐cycle‐antimagic Total Labelings For The Vertex And Edge Amalgamation Of N Copies Of Isomorphic Cycles .....................................................................................................

M 013

Local Polynomial Estimator In Three Responses Nonparametric Regression Model With Unequal Variances of Errors .....................................................................................................

M 014

Brain Cancer (Astrocytoma) Classification Using Support Vector Machines Sequential ...... M 015

Local Existence of Classical Solution to the Nonlinear Schrödinger Equation ...................... M 016

Gompertz Model To Describe Infant Weight Growth Pattern (Case Study) ............................ M 020

An Exploration of Sampean Watershed Rainfall Data .................................................................... M 021

Analysis of Stationary of Spatial‐Temporal Extreme Rainfalls in Malang Residence ............................. M 022

Discrete Wavelet Transform and Partial Least Squares on Calibration Models and Applications With OSS‐R ..................................................................................................................................

M 023

T. TECHNOLOGY

Automated Visual Surface Defects Detection of Ball Bearing 6904 Outer‐Ring Based on Digital Image Processing ...................................................................................................

T 001

Design of Artificial Intelligence Software for Lung Cancer Diagnosis using Adaptive Neuro Fuzzy Inference Systems .......................................................................................................

T 002

Prototype of Outer Race Bearing Defect Detection System Using Laser Scanner ............... T 003

Fabrication and Characterization of Planar Ion‐Exchanged Waveguides .............................. T 004

Recognition of Alphabet Sound Base on Linear Predictive Coding Using Neural Network .. T 005

An Information Technology Strategy in Learning Organization (towards Achieving the Sustainable Competitive Advantage) .................................................................................

T 006

Analysis Of Inverse Kinematics In Simulator Stewart Platform (Using Newton‐Raphson Method) ............................................................................................................................

T 007

A CFD Study of Gas Lift Technology in Hydrocarbon Production through Continuous Artificial Lift .....................................................................................................................................

T 008

Optimizing The Acupoints Related with Inner Ear Disease In The Case of Tinnitus and Vertigo by Using Interface Based On Artificial Intelligence (Supervised Neural Network) ................

T 009

Aulia Nasution

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xiv

Relative Humidity Sensor Based On Plastic Optical Fiber With Gelatin + CoCl2 Cladding ..... T 010

The Influence of Filling Weights of Liquefied Petroleum Gas Off Take Rates ....................... T 011

Phase Transformation of Cu‐30%Zn Alloy Produced By Mechanical Alloying With Variation of Ball To Powder (BPR) and Milling Time ...............................................................................

T 012

Development of Public Cluster Computing for Molecular Dynamics Simulation ................. T 013

Design of Control System of Automatic Guided Vehicle (AGV) Navigation System by Using Fuzzy Logic Method to Overtake Another Vehicle .............................................................

T 014

Saron Transcription based on Time‐Frequency Analysis of Onset Detection using Short‐time Fourier Transform ...............................................................................................................

T 015

Determine the Pattern of Birds Sound Melody Using Short‐Time Fourier Transform (STFT) .... T 016

Design and Operation of Fiber Optic Angle Sensor Based on Flat and Concave Mirror ......... T 017

An Optical Tomography System for Flow Monitoring .......................................................... T 018

News Topic Discovery Based On Key Phrase Identification Algorithm ............................... T 019

Effectiveness of Nutrient Types and Concentrations in Bioremediation of Crude Oil‐Contaminated Soil Augmented with Bacterial Consortium ................................................

T 020

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3rd International Conferences and Workshops on Basic and Applied Sciences 2011 ISBN: 978-979-19096-1-7

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Automated Visual Surface Defects Detection of Ball Bearing 6904 Outer-Ring Based on Digital Image

Processing

Agustian K. Herdianta1 and Aulia MT. Nasution2

Engineering Physics Departement Institut Teknologi Sepuluh Nopember, Surabaya, Indonesia

e-mail: [email protected] , [email protected]

Abstract

Defects on a bearing is usually determined by observing its vibration characteristics. This method unfortunately can not detect possible surface defects on the inner and outer ring, whichare resulted from collisions during the production process. A pattern recognition of visual defect on the bearing surface based digital image processing and artificial neural network is implemented to cope with the problem. Original bearing samples image is preprocessed from RGB image into grayscale image, which then resized to 0.25 times from its original size. A backpropagation algorithm neural network architecture is used to recognize the pattern. Recognition rate obtained for good bearing at 93.5 %, meanwhile for scratch, shoemark, and blackspot type defects are 95.2 %, 57.9 %, and 77.8 % respectively. This fair recognition rate of shoemark and blackspot defect were caused by the low resolution camera. Results show integrated artificial neural network with digital image processing can be implemented as foundation of bearing visual defect detection system.

Keywords : bearing, digital image processing, backpropagation

1. Introduction

Decision to replace ball bearings on a motor is determined by detecting whether the bearing is still fulfill the standard range or not [1]. Common way to determine bearing’s defect is by observing its vibration and noise characteristics. Bearing with defect will have different noise characteristics in comparison to the good ones. Unfortunately, noise characteristic test can not detect the presence of visual defect on bearing. To solve this problem, concepts in digital image processing, integrated with artificial neural networks as a recognition algorithm, can be used to recognize the defects. One example of such

detection system is for monitoring production of small pin for the electronic circuits[2]. The concept of an artificial neural network architecture with time delay also adopt similar concept. This architecture can be used in finding boundaries, direction and speed of motion of moving images [3].

It is then necessary to design an automation system that can detect the presence of surface defects on the outer ring. In this paper we describe efforts to implement a concept of integrated digital image processing with artificial neural networks as a customized recognition algorithm to detect surface defects on the outer-ring of bearing. Problem to be resolved is how to recognize the presence of surface defects of ball bearings 6904’s outer ring. Three types of visual defects to be recognized are shoe marks, scratch and black spots, respectively.

Fig 1(a). Shoe Mark Fig 1(b). Scratch

Fig 1(c). Black Spot

As result as production process chain, visual defects on bearing can occur on three different parts: i.e. surface of bearing, chamfer and seal/shield[4]. This surface defect can be crack, poor polishing surface and so on. This paper restrict the visual defect to three different defects: i.e. scratch, shoemark and blackspot. Scratch appears like white small mark on ball bearing, meanwhile shoemark appears like black thin line circles around bearing surface. Both don’t change the roundness and rounghness of bearing surface. Blackspot appears like deep grinded mark. Types of visual defect occur on outer

Agustian Krido Herdianta , Automated Visual Surface Defects Detection of Ball Bearing 6904 Outer-Ring Based on Digital Image Processing

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ring can be seen in figure 1(a), figure 1(b) and figure 1(c).

Nowadays image processing applications are used in various fields, ranging from medicine to engineering [6]. Various problems related to image processing can be solved with steps called image processing chain[7]. Typical chain of image processing consists step of preprocessing, data reduction, segmentation, object detection and image understanding.

This concept of image processing chain can be applied as foundation of the defect detection system. Converting from RGB images to grayscale image is the preprocessing steps. This step is necessary to be performed in order to simplify the defect information in acquired images. Usage of Region of Interest (ROI) is used as the step of segmentation and followed by artificial neural network (ANN) as the object recognition step. ROI usage will reduce size of the image and affect for speed of program execution. Assesment of the ANN will show the meaning of acquired image before. This image processing chain was then implemented in software to detect the presence of bearing visual defects. All image processing steps used in this paper are illustrated in figure 2.

The customised software mentioned above is used together with a hardware configuration as a compact automated detection system. A webcamera as frame grabber, LED and diffused light as lighting system, and shaft as bearing sample place, are set as the hardware components. Those components are placed at a solid base to support the whole system.

Future works will be devoted for gaining possibilities to increase the recognition rate of the visual defects and speed of recognition, through modification on the camera resolution and framerate. This modification can be implemented for the industrial need.

2 Methodology

Below is the system design of defects determination on the ball bearings outer ring surface, based on digital image processing. Designing and manufacturing of prototypes are required to get an overall picture of how the system works. Prototype was built with the lighting system as shown in Figure 5. The lighting system consists of two light sources, LEDs are placed perpendicularly to the

sample and diffused light are placed close to the sample. A shaft is placed in front of the camera as a place to put the sample bearing. The distance between the sample and the camera is at a distance of the camera's focus, which is between 3 cm and infinity. LED, camera, diffuse light and bearing samples are located in same plane. The sample is placed right in front of the camera. ANN architecture used in this research is backpropagation. ANN learning is ANN process of recognition on the input patterns and targets arranged in a data packet, which begins with the reading of data and calculation of weight and weight update [9].

Artificial neural network architecture with backpropagation mode has several parameters and conditions for training, ie the number of nodes in the input layer is 325 and 580, the number of hidden layers is 2, the number of nodes in the output layer is 1, the maximum number of epochs is 100,000, the average squared error (MSE) is 10-10, the momentum coefficient of 0.9, Goal error is 1x10-6, the time for training is infinite and the learning algorithm is backpropagation (Traingdx).

Shaft9

cm

9,5 cm

WebCamera

48,0°

LED

WebCamera

Diffuse Light

3 cm

60,4°

Figure 5: Lighting in Detection System

Acquisition of data in each learning will be conducted with variation of the neurons of each hidden layers. Activation function used in the first hidden layer and second hidden layer is sigmoid tangent function, while for the hidden layer activation function output using purelin. Data is collected by doing a variation on the rate of learning, the first hidden layer and the second hidden layer. Variations in the rate of learning is in the amount of 0.01 and 0.001. These rates of learning is example of learning rate used in pattern recognition [10]. The design of ANN architecture can be performed with the addition of the layers of hidden layer nodes [11]. At any learning rate, data acqusition is performed by variation of the first hidden layer of 10 nodes, 30 nodes and 50 nodes. In each variation of the first hidden layer, data acquisition is performed by variation of the second hidden layer, which is 1 node to 20 nodes. Data for learning ANN architecture is the image of the 25 bearings. The sample bearings consists of 10 OK

Figure 2: Chain of Image Processing


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bearings, 4 bearings with scratch defects, 6 bearings with shoemark defects, 4 bearings with blackspot defects, a bearing with chatter defect. Target value for OK bearing is 1 and target value for NG bearing is 0.

This visual defect detection system using two ANN architectures. Lighting system on this system using the lighting system in Figure 5. First ANN architecture has number of nodes in the input layer of 325 neurons. Region of Interest (ROI) used in the first architecture is x = 638; y = 497; x-width = 247; y-width = 126. The second ANN architecture with number of nodes in the input layer of 580 neurons. Region of Interest (ROI) used in the second architecture is x = 484; y = 498; x-width = 191; y-width = 132. These formats of ROI is adjusted to the ROI format used in the image acquisition toolbox in Matlab R2009a. Algorithm of decision making on defect detection system software is illustrated in Figure 6.

3 Result

In this visual defect detection system, the obtained image as raw data is the bearing image of size 247 x 126 as many as 10 pieces in the first ROI and the size of 191 x 132 as many as 3 pieces in the second ROI in a single acquisition.

Figure 7(a) and 8(a) shows an example of raw data for this detection system. Then the image was processed with the grayscale process, so we get a new image of a grayscale image with the same size with the previous image. Figure 7(b) and 8(b) shows a grayscale image of the raw data. Figure 7(a) and 7(b) is an example image with scratch defects. Figure 8(a) and 8(b) is an image example with shoemark defect in the bearing. Then image resizing operation was performed with 0.25 times its original size. The image, that has been resized, will become a data matrix that will be processed in the ANN architecture.

After performed learning on the ANN architecture, the obtained configuration is the best architecture to be embedded in the software. To get the appropriate neural network architecture for the detection of visual defects on bearing, then the detection system of visual defect I, tests will be conducted on various possible layers and nodes used in the ANN architecture.

Configuration of the best first ANN architecture that can be embedded in the software is with backpropagation architecture with the number of nodes as many as 50 neurons on first hidden layer and number of nodes as many as 3 neurons on second hidden layer with learning rate of 0.001. The desired MSE is 1 x 10-10 and as expected before. The best results are obtained at the number

of nodes in second hidden layer of 3 neurons. Accuracy on the number of nodes is 100%. MSE on the number of nodes is obtained after learning as many as 6809 epoch, the least among the other nodes on the same hidden layer.

Figure 6: Decision-making Algorithm for Detection System Software

Figure 7(a): Original

image for first ROI with size of 247 x 126 pixel

Figure 8(a): Original

image for second ROI with size of 191 x 132 pixel

Figure 7(b):

Grayscale image of figure 7(a)

Figure 8(b): Grayscale

image of figure 8(a)

The best test results on second ANN architecture at the learning rate of 0.001 with number of nodes on first hidden layer is 30 neurons. Results of the best learning is on number of nodes on second hidden layer of 2 neurons. The desired MSE is 1 x 10-10 and as expected before. The best results are obtained at the number of nodes in second hidden layer of 2 neurons. Accuracy at the number of nodes is 100%. MSE at the number of nodes is

Agustian Krido Herdianta , Automated Visual Surface Defects Detection of Ball Bearing 6904 Outer-Ring Based on Digital Image Processing

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obtained after learning as many as 7143 epoch, the least among the other nodes on the same hidden layer.

By using the same architecture configuration, then tests were performed with new bearings. Table 1 shows the accuracy of the visual defect detection system on the new bearings that are not the learning bearing. Figure 9 shows the comparison between the bearings that can be detected and bearings that can not be detected. Figure 10 shows the accuracy percentage of detection on each visual defect, either scratch, shoemark and blackspot.

Table 1: Accuracy of the Visual Defect Detection System on New Bearings

Sample Population Matched with

Visual Inspector

Not matched with Visual Inspector

OK Sample

1047 979 (93,5 %)

68 (6,5 %)

NG Sample

61 48 (78,7 %)

13 (21,3 %)

From the simulation results, it is obtained for the recognition accuracy rate for OK bearing at 93.5%. accuracy for recognition of NG the overall bearing at 78.7%. Accuracy for scratch defects pattern recognition at 95.2%, for shoemark defects at 57.9%. and for blackspot defects at 77.8%.

On the recognition of bearing with OK category, there is a mismatch pattern recognition of system with visual inspector assessment. This is because the pattern of the samples of OK bearings have similarities with the pattern of NG bearing. The bearing has a pattern resembles shoemark defects with a pattern of dark thin - bright thick - dark thin - bright thick - dark thin. The pattern of thin dark lines in the middle resembles a circular shoemark defect.

Defects pattern recognition accuracy rate have a high percentage at scratch recognition. This is because this defect can be easily detected using a direct lighting system with perpendicular direction to the bearing surface area. But there are still bearing with this kind of defect that can not be detected. This is because the camera can not capture the scratch due to the camera low framerate at 7 fps. Thus, the scratch can not be captured by the camera clearly.

The accuracy of shoemark defects pattern recognition is still quite low when compared with the pattern of blackspot or scratch defects. This is because the size of some shoemark defects are thin, thus it is not perfectly captured by the camera. The

size of shoemark defects that can be detected is which has a size of more than 0.54 mm. Defect type of blackspot which can not be detected because the camera framerate and resolution is still low. Therefore, the captured bearing defect image is not very clear.

Figure 9: Comparison between the bearings that can be detected and bearings that can not be

detected

Figure 10: Accuracy percentage of detection on each visual defect

4 Conclusions

The conclusion can be drawn about the determination of the presence of surface defects on ball bearings outer ring 6904 using digital image processing is as follows. It has been performed designing and manufacturing of prototype on a ball bearings 6904 outer ring surface defects detection system by using digital image processing.

Pattern recognition of visual defects on the surface of bearing can be performed using integrated artificial neural network with digital image processing as foundation of bearing visual defect detection system.. Lighting systems used in this research are two LEDs and diffused lamps installed vertically and has same plane with samples bearing and the camera. All of artificial neural network architectures used in this paper are backpropagation.

Some recommendations as reference in the future are designing prototypes by using a camera with high resolution and framerate. Development of


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lighting systems by using indirect lighting can be performed in future studies to improve the accuracy of image recognition.

References

[1] Taribuka, Semuel Marthen. 2010. Pengambilan Keputusan Penggantian Ball Bearing pada Motor Bakar Torak Berbasis Monitoring Kondisi. Institut Teknologi Sepuluh Nopember : Surabaya

[2] Furukawa, Yuji. 1992. Automatic Detection of Defects among Small Pins Group - Inspection of Connector-Plug Pins by the Use of lmage Processing Associated with Neural Network. Tokyo Metropolitan University : Tokyo.

[3] Wohler, Christian. 1998. A time delay neural network algorithm for estimating image-pattern shape and motion. Image and Vision Computing 17 (1999) 281–294

[4] NSK. 2008. New Bearing Doctor. NSK Ltd : Japan.

[5] Gonzales, R.C., and Woods, R.E. 2002. Digital Image Processing Second edition. New Jersey: Prentice Hall.

[6] Acharya, Tinku., and Ray, Ajoy K. 2005. Image Processing: Principles and Applications. New Jersey: John Wiley & Sons.

[7] Petersen, M. 2002. Image Processing with Neural Network – A Review. Pattern Recognition 35 (2002) 2279–2301

[8] Fausett, Laurene. 1994. Fundamentals of Neural Network. Prentice-Hall : Englewood Cliffs

[9] Firdaus, M. Indra. 2010. Perancangan strategi kontrol switching variabel input bikarbonat dan dilution pada bioreaktor anaerob untuk mencegah wash out berbasis artificial neural network dan fuzzy logic control. Institut Teknologi Sepuluh Nopember : Surabaya

[10] Wiyanti, Atmisya. 2010. Klasifikasi komposisi sel darah putih dengan menggunakan multilayer perceptron network . Institut Teknologi Sepuluh Nopember : Surabaya

[11] Liu,Y ; Yao, X. 1996. Evolutianary design of artificial neural networks with different nodes. Proceedings of IEEE International Conference on Evolutianary Computation

Agustian K. Herdianta was born in Sumenep on August 22nd, 1988. He finished his senior high school in SMAN 3 Pamekasan in 2007. Since 2007, He is studying at Engineering

Physics Departement – ITS Surabaya. During this period, He won achievement in Most Outstanding Student Competition 2010 of Engineering Physics Departement. He was awarded as finalist in PIMNAS XXI Semarang 2008. His research interest are in photonics and artificial intellligence.

Aulia MT Nasution was born in Surabaya in 1967. He got his Ir. Degree in Engineering Physics from ITB Bandung and M.Sc in Medical Physics from the USM Penang, Malaysia. In October 2006, he received his Dr.rer.nat degree in Experimental Physics (Optical Diagnostics). His research interests are related to bio-photonics, optical diagnostics based on spectroscopy, optical metrology, and medical engineering. In period of Sept – Nov 2009, he is doing research stay as visiting scientist at the Clinical Photonics Lab of the Erlangen Graduates School in Advanced Optical Technologies (SAOT).