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CYBER BULLY IDENTIFICATION

SYSTEM

IRRNA IZZATE MOHD ALI

BACHELOR OF COMPUTER SCIENCE (SOFTWARE

DEVELOPMENT)

WITH HONOURS

UNIVERSITI SULTAN ZAINAL ABIDIN

2018

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CYBER BULLY IDENTIFICATION

SYSTEM

IRRNA IZZATE MOHD ALI

Bachelor of Computer Science (Software Development)

With Honours

Faculty of Informatics and Computing

Universiti Sultan Zainal Abidin

May 2018

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DECLARATION

I hereby declare that this report is based on my original work except for quotations and

citations, which have been duly acknowledged. I also declare that it has not been previously

or concurrently submitted for any other degree at Universiti Sultan Zainal Abidin or other

institutions.

Signature : ________________________________

Name : IRRNA IZZATE BT MOHD ALI

Date : ..................................................

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CONFIRMATION

This is to confirm that:

The research conducted and the writing of this report was under my supervision.

Signature : ________________________________

Supervisor : DR. WAN AEZWANI BT WAN ABU

BAKAR

Date : ..................................................

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DEDICATION

I would like to take this opportunity to express my heartfelt gratitude to all those who helped

me to make my thesis work a success. First and foremost I would like to thank ALMIGHTY

who has provided me the strength to do justice to my work and contribute my best to it so that

it has turned out to be a successful work.

I express my sincere and whole hearted thanks, to my supervisior Dr. Wan Aezwani bt. Wan

Abu Bakar, Lecturer of Universiti Sultan Zainal Abidin for her regular advice, guidance,

suggestion and encouragement throughout the course of present research. I am highly

indebted to his untiresome perseverance, which helped me to present this work in the right

perspective, assuming the full form of the thesis.

There are no words to express my gratitude and thanks to my beloved mother, family

members and friends for always standing by me. Their love has been the major spiritual

support in my life. As a final word, I would like to thank each and every individual who have

been a source of support and encouragement and helped me to achieve my goal and complete

my work successfully.

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ABSTRACT

Cyberbullying is the action that takes place over digital devices. It can occur through

social media, forums, apps and others. It can include sharing personal or private

information about someone else causing embarrassment or humiliation. In Malaysia,

there are many cases that happened because of the cyber bully. Hence, it can cause

mental problems such as phobia, stress, and depressed. Generally, the generation that

commonly involve with cyber bully is young generation which is university′s student.

Student did not know whether their actions such as comment, post status, share post

and also personal message become as a threat toward others. Unfortunately, most of

students have depression on using social media because of the cyber bully. The cyber

bully itself can give negative effect toward students′ performance in academic.

Sometimes student that been cyber bullied take suicide as a solution. The importance

of the system is to analyse the status of the student whether the student is being cyber

bullies or cyber bullied or in the middle between being cyber bullies and cyber

bullied. Through this identification system, the students can know their category of

cyber bully and they can gain with the tips and also consultation to overcome the

cyber bully′s problem.

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ABSTRAK

Siber buli adalah tindakan yang berlaku di atas peranti digital. Ia boleh berlaku melalui media

sosial, forum, aplikasi dan lain-lain. Ia boleh termasuk berkongsi maklumat peribadi atau

peribadi tentang orang lain yang menyebabkan malu atau penghinaan. Di Malaysia, terdapat

banyak kes yang berlaku kerana siber buli. Oleh itu, ia boleh menyebabkan masalah mental

seperti fobia, tekanan, dan tertekan. Umumnya, generasi yang sering terlibat dengan pembuli

siber adalah generasi muda yang merupakan pelajar universiti.

Pelajar tidak tahu sama ada tindakan mereka seperti komen, status pos, jawatan berkongsi

dan juga mesej peribadi menjadi ancaman terhadap orang lain. Malangnya, kebanyakan

pelajar mengalami kemurungan menggunakan media sosial kerana siber buli. Siber buli itu

sendiri boleh memberi kesan negatif terhadap prestasi pelajar dalam akademik. Kadang-

kadang pelajar yang telah dibuli siber membunuh diri sebagai penyelesaian. Kepentingan

sistem ini adalah untuk menganalisis status pelajar sama ada pelajar itu adalah pembuli siber

atau dibuli siber atau di tengah-tengah antara pembuli siber dan dibuli siber. Melalui sistem

pengenalan ini, pelajar dapat mengetahui kategori siber buli mereka dan mereka boleh

mendapatkan dengan tip dan juga perundingan untuk mengatasi masalah siber buli.

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CONTENTS

SubTopic No Content Page

DECLARATION i

CONFIRMATION ii

DEDICATION iii

ABSTRACT iv

ABSTRAK v

CONTENTS vi-vii

LIST OF TABLES viii

LIST OF FIGURES ix

LIST OF ABBREVIATIONS x

CHAPTER 1 INTRODUCTION

1.1 Project Background 2

1.2 Problem Statement 3

1.3 Objectives 4

1.4 Scope 4-5

1.5 Limitation 6

1.6 Strength 6

1.7 Thesis Organization 7

CHAPTER 2 LITERATURE REVIEW

2.1 Introduction 9

2.2 Related Research 9-12

2.3 Rule Based algorithm 12

2.4 Summary 13

CHAPTER 3 METHODOLOGY

3.1 Introduction 15

3.2 Research Analysis 15-16

3.3 Methodology for CBIS 16-18

3.4 Software and Hardware Requirements 19-20

3.5 Summary 20

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CONTENTS

SubTopic No Content Page CHAPTER 4 DESIGN

4.1 Introduction 22

4.2 System Design and Modelling 22

4.2.1 Context Diagram 23

4.2.2 Data Flow Diagram 24-33

4.2.3 Entity Relationship Diagram 34

4.3 Data Dictionary 35-47

REFERENCES 48-49

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LIST OF TABLES

TABLE

TITLE

PAGE

2.1 Comparison of Journals 11-12

3.1 CBIS Software Requirements 19

3.2 CBIS Hardware Requirements 20

4.1 CBIS USER Data Dictionary 35

4.2 CBIS STUDENT Data Dictionary 36

4.3 CBIS ADMIN Data Dictionary 38

4.4 CBIS PSYCHOLOGIST Data Dictionary 40

4.5 CBIS QUESTION Data Dictionary 42

4.6 CBIS ANSWER Data Dictionary 43

4.7 CBIS CATEGORY Data Dictionary 44

4.8 CBIS APPOINTMENT Data Dictionary 45

4.9 CBIS CONSULTATION Data Dictionary 46

4.10 CBIS TIPS Data Dictionary 47

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LIST OF FIGURES

FIGURES

TITLE

PAGE

3.1 Waterfall Model 16

4.1 CBIS Context Diagram 23

4.2 CBIS DFD Level 0 24

4.3 CBIS DFD Level 1 Manage User 27

4.4 CBIS DFD Level 1 Manage Profile 28

4.5 CBIS DFD Level 1 Manage Questions 28

4.6 CBIS DFD Level 1 Manage Category 30

4.7 CBIS DFD Level 1 Manage Appointment 31

4.8 CBIS DFD Level 1 Manage Tips 32

4.9 CBIS DFD Level 1 Manage Consultation 33

4.10 CBIS ERD 34

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LIST OF FIGURES

CD Context Diagram

DFD Data Flow Diagram

ERD Entity Relationship Diagram

FYP Final Year Project

HCI Human Computer Interface

GUI Graphical User Interface

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CHAPTER 1:

INTRODUCTION

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1.1 PROJECT BACKGROUND

Cyber bullying is any behaviour that is performed through electronic or digital media by

individuals or groups that repeatedly communicates aggressive messages intended to impose

harm or discomfort on others.1 Nowadays, there are many cyber bullying cases happened in

the world of technology. One of the main platforms that cyber bullying is occurs in social

media. Through social media itself, most of society opens to share their opinions with others.

Sometimes there are few people dislike and uncomfortable with the opinion that been shared

and they preferred to humiliate people without thinking others feeling.

Cyber bullying also can include sharing personal or private information about someone else

causing embarrassment or humiliation. Sometimes cyber bullying also can be easy to spot by

text, tweet or response that is harsh, mean or cruel. Cyber bullying also can happen

accidentally by impersonal nature of text message or email that is very hard to detect the

senders’ intention.

The examples of forms of cyber bullying are exclusion, trolling, catfishing, cyberstalking

and many more.4 Exclusion means rejection of a person from an online group provoking

his/her social depreciates. Next, trolling is the deliberate act of provoking a response through

the use of insults or bad language on online forums and social networking sites. Meanwhile,

the meaning of catfishing is when another person steals your online identity, usually photos,

and re-creates social networking profiles for deceptive purposes. Cyberstalking refers to the

practice of adults using the Internet to contact and attempt to meet with young people for

sexual purposes.

Generally, the generation that commonly that had been targeted with cyber bullying is

young generation which is among students. Students are tends to expose with cyber bullying.

Most of the students that are experienced cyber bully problems do not know how to manage

it. As a result, it can distract student and can cause the students at greater risks in mental

disorder problems such as depression, stress, anxiety and other related disorder.

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1.2 PROBLEM STATEMENT

The problem that usually arise when students did not know whether their actions such

as comment, post status, share post and also personal message on the social media

become as a threat toward others.

Besides, students also did not how to overcome the cyber bullying problems. Most of

the student that been experienced cyber bully feels embarrassed to share with others about

being cyber bully and they tend not to give attention about it.

Therefore, based on all problem statements it is important to develop a web based

system to help student overcome the cyber bullying.

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1.3 OBJECTIVE

The objectives of Cyber Bully Identification System are to solve the problems that

experienced by students.

o To develop an efficient system for cyber bully identification among the students.

o To analyse the category of the student whether the student is being cyber bullies or

cyber bullied or in the middle between being cyber bullies and cyber bullied.

o To provide tips and consultation based on the student category.

1.4 SCOPE

The scopes for this system are identified to make the development of process easier. The

scope is users that are divided into three which are admin, students and psychologist.

1.4.1 Admin

Login

Manage profile

Manage question

Manage category

View report

Student list.

List of student based on category of cyber bullying.

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1.4.2 Student

Register.

Manage profile.

Follow the cyber bully questionnaires.

View the category of student.

View tips or deal appointment.

1.4.3 Psychologist

Login

Manage profile

Manage tips

Manage consultation

View Report

List of student based on category of cyber bullying.

List of consultation.

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1.5 LIMITATION

Limitation of work for this Cyber Bully Identification System is the system is only

useful for the students who that experienced the cyber bullying and this system not

available for others.

Besides, this system cannot prevent the cyber bullying from happened, but it can

reduce the cyber bullying from occur among the students by gaining the consultation.

1.6 STRENGTH

The strength of the system is to analyse the category of the student whether the student

is being cyber bullies or cyber bullied or in the middle between being cyber bullies

and cyber bullied. Through this identification system, the students can know their

category and they can gain with the tips and make appointment for the consultation to

overcome the cyber bullying problem. The psychologist can manage the tips and

consultation.

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1.7 THESIS ORGANIZATION

This thesis consists of six chapters. In chapter 1, the content consists of system

background, problem statement, objective, scope, limitation, strength of the system and also

thesis organization.

In chapter 2, consist of the literature review. Literature review itself is about reviewing the

previous system. It is require study the related things about the system to gain better

understanding and knowledge based on the system. For this proposed system is using rule

based algorithm.

In chapter 3, consist of the methodology. There has been having the description of the

methodology and also about what model is used for the development. In chapter 4 which is

system design, there are context diagram (CD), data flow diagram (DFD) and also entity-

relationship diagram (ERD).

In chapter 5, the implementation of system, testing and result that describe all of the

processes involved during the development of the system. This chapter also consist of the

interface of the system. For the last chapter which is chapter 6 consist of the conclusion of the

whole system.

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CHAPTER 2:

LITERATURE

REVIEW

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2.1 INTRODUCTION

Basically, in this chapter is reviewing about the previous projects. The related journals and

articles were analysed to find out what are the differences between the previous system and

the proposed system. The related system to cyber bullying identification is studied to gain the

understanding about the development of this research and also gain knowledge to implement

the system in the real situation. This proposed system is using rule based algorithm

2.2 RELATED RESEARCH

Based on the literature review, a few existing system related to proposed system are found.

First, Cyberbullying Detection: A Step Toward a Safer Internet Yard (Lyon, France - April

2012) is about cyberbullying detection system in a social network is to prevent or at least

decrease the harassing and bullying incidents in cyberspace. This system is using rule based

algorithm. The detection system will gives warnings if something suspicious is detected

would greatly help the moderator to only focus on these. It will compared the foul words used

most frequently by each gender and, based on a Wilcoxon signed rank test, determined that

male and female authors used significantly. The system used a supervised learning approach,

Support Vector Machine classifier using WEKA to detect cyberbullying.

Next system is a Cyberbullying Detection using Time Series Modeling (Nektaria Potha,

Manolis Maragoudakis – 2014). This cyberbullying detection system is about study the

accuracy of predicting the level of cyberbullying attack using classification methods and also

to examine potential patterns between the lingustic style of each predator. The method that

been used by this system is Dynamic Time Warping (DTW). The identification of such a

correlation between the aforementioned signals could assist the dialogue annotation process

or even be used to identify repeated offenders that use the same dialogue style in their

attacks. Particularity of DTW is that it compares two time series together by allowing a given

point from one time series to be matched with one or several points from the other. There

were two more methods that apply in this system which is Support Vector Machines (SVM)

and Singular Value Decomposition (SVD). SVM is derived from statistical learning theory

by Vapnik and Chervonenkis. It builds a model that assigns new examples into one category

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or the other, making it a non-probabilistic a binary linear or non-linear classifier. SVD is

mathematical technique called singular value decomposition (SVD) to identify patterns in the

relationships between the terms and concepts contained in an unstructured collection of text.

The last existing system that been research is Cyberbullying Identification Using Participant-

Vocabulary Consistency (Elaheh Raisi, Bert Huang – 2016) is about Machine learning

methods can potentially help provide better understanding of this phenomenon, but they must

address several key challenges: the rapidly changing vocabulary involved in cyberbullying,

the role of social network structure, and the scale of the data. The Ranking algorithm is been

used in the system. This system introduces an automated, data-driven method for

cyberbullying identification. The eventual goal of such work is to detect such harmful

behaviors in social media and intervene, either by filtering or by providing advice to those

involved. For each user ui, the system assign a bully score bi and a victim score vi. The bully

score measures how much a user tends to bully others; likewise, victim score indicates how

much a user tends to be bullied by other users. For each feature wk, the system associate a

feature-indicator score that represents how much the feature is an indicator of a bullying

interaction.

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Table 2.1: Comparison of Journals

Author/Journal/Yea

r

System Name Method Description Advantages

Lyon, France - April 2012

Cyberbullying Detection: A Step Toward a Safer Internet Yard

Rule based Algorithm

This research is about the main application of an effective cyberbullying detection system in a social network. It is used to prevent or at least decrease the harassing and bullying incidents in cyberspace.

1. Cyberbullying detection can be used to provide better support and advice for the victim as well as monitoring and tracking the bully.

2. allows the people in charge (for instance, teachers) to provide the required help and guidance for the victim or the bully.

Nektaria Potha, Manolis Maragoudakis - 2014

Cyberbullying Detection using Time Series Modeling

Dynamic Time Warping (DTW)

This research is about study the accuracy of predicting the level of cyberbullying attack using classification methods and also to examine potential patterns between the lingustic style of each predator. By using feature weighting and dimensionality reduction techniques, each signal is straightforwardly parsed by a neural network that forecasts the level of insult within a question given a window between two and three previous questions.

1. By applying a Dynamic Time Warping algorithm, the similarity of the aforementioned signals was proved to exist, providing an immediate indicator for the severity of cyberbullying within a given dialogue.

Elaheh Raisi, Bert Huang - 2016

Cyberbullying Identification Using Participant-Vocabulary Consistency

Ranking Algorithm

This research is about Machine learning that can be useful in addressing the cyberbullying problem. The system identify three significant challenges for supervised cyberbullying detection. First, annotation requires expertise about culture, examination of the social structure of the individuals involved in each interaction. Second, reasoning about which individuals are involved in bullying should do joint, or collective, classification. Third, language

1. To detect such harmful behaviors in social media and intervene, either by filtering or by providing advice to those involved.

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is rapidly changing, especially among young populations, making the use of static text indicators prone to becoming outdated.

2.3 RULE BASED ALGORITHM

A rule based system is a set of “if-then” statements that are used as a way to store and

manipulate knowledge to interpret information in a useful way. In software development, rule

based algorithm can be used to create software that can provide solution. For example, there

is a person that has been experienced cyber bullying. That person used the system and the

system can provide the solution or consultation toward that person. Rule based algorithm

itself is corresponding with the problem in place of human experts2.

Machine learning rule based can be used in this proposed system because the data sets are

provided to these algorithms, termed training sets, are used to learn a predictive model based

on the observations within the data. The annotation of training sets may be used with

supervised Machine Learning Rule Based is by using a categorical output describing the

sample as belonging to a given category. The students need to answer question before can

analysis their result. Due to the result, the system give the status of the students that are

corresponding with category of cyber bullying.

The partitioning process used by rule-based learning methods focuses on identifying

subgroups of samples contained within the training set. In the context of the analysis of large-

scale biological data sets, discrete developmental states can be identified within the training

set given that samples belonging to a given state are likely to have similar characteristics. An

additional benefit of rule-based learning methods is that they produce human-readable rules.

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2.4 SUMMARY

This chapter provide an overview regarding the concept to the proposed system. Based on the

study that has been made, it shows that the literature review is the one of the important part in

research or study of new idea. Through literature review, the researcher may know whether

the idea has been studied or not.

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CHAPTER 3:

METHODOLOGY

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3.1 INTRODUCTION

In this chapter, it has cover the details of explanations of methodology that used in this

project. This project use waterfall model consists of a detailed plan describing how to

develop, maintain, replace and alter also enhance specific software. The life cycle of SDLC

defines a methodology for improving the quality of software and the overall development

process.

3.2 RESEARCH ANALYSIS

In developing the system, the Software Developing Life Cycle (SDLC) model chosen is

Waterfall Model. The model also referred to as a linear-sequence life cycle model as shown

in Figure 3.1. It is very simple to use and understand the model itself. In a Waterfall model,

each phase must be completed fully before the next phase can begin. If there is any change, it

cannot turn since it must follow the sequence phase. Usually, this model is useful for the

small project and there is no uncertain requirement.

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Figure 3.1: Waterfall Model

The phases that involve in waterfall model are system and software requirements, analysis,

program design, implementation or coding, testing and operations.

3.3 METHODOLOGY for CBIS

In this section, each phases of Waterfall Model is briefly described in developing

Cyberbully Identification System (CBIS).

3.3.1 System Requirements Phase

In this phase, determine the problem that facing in cyberbully and determine the objective

to overcome the problem. Identify the CBIS features and also the requirements. The features

that are relevant to the CBIS are study through the use of similarities system. Besides, the

references from the related journals also act as a guideline to develop the CBIS. For the time

planning, a Gantt chart is created as the project planning timeline of CBIS.

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3.3.2 Software Requirement and Analysis Phase

The system requirement acquired and analysed. The problem statement, objective, system

scope, limitation, strength and also literature review are also defined. For this phase, it can be

referred in Chapter 1 and Chapter 2 in this report. Data related to CBIS is collected by

referring to selected articles, journals and internet surfings. Based on the research study, the

selected criteria pertaining to cyberbully issues have been rectified. The detail of system’s

software also hardware requirements is illustrated in Chapter 3.4.

3.3.3 Program Design Phase

In this phase, the design of the system is identified and the prototype is developed based on

the system functionalities. The data or requirement that is obtained during requirement

analysis phase is converted into the system design. Few diagrams have been built such as

Context Diagram (CD), Data Flow Diagram (DFD) level 0 and 1, Entity Relationship

Diagram (ERD), Data Dictionary and also Interface Design. The detail of design phase is

depicted in Chapter 4.

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3.3.4 Implementation Phase

For implementation or coding phase, the CBIS need to be developed using PHP and

MySQL for the web based system. The editor tools to write the programming part is

Notepad++ by using PHP language and MySQL for the database. In this phase, the Rule

Based method provide the category to the students as the students need to answer the

questionnaires first. Based on the category, the students can choose whether want to make

appointment with psychologist or not. Xampp is run as localhost server to connect between

the coding and databases. This phase is critical phase where based on the user requirement

need to be developed.

3.3.4 Testing Phase

Testing of CBIS is vital to ensure the functionality of cyberbully identification module.

Intention of testing is to discover error so that the error found can be corrected and thus lead

to a better system built. This process helps in discovering the vulnerabilities that are not

discovered in the previous phase.

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3.4 Software and Hardware Requirements

When developing the system, the standard requirement would use in software and

hardware. Each of these requirements is related one to another to ensure the system could be

done smoothly.

3. 4.1 Software Requirements

The list of the software used in CBIS is as below.

Table 3.1: CBIS Software Requirements

SOFTWARE DESCRIPTION

Microsoft Office 2010 As the platform for the documentation and

presentation.

NotePad ++ Editor write coding using PHP language for

develop a system.

Microsoft Edge, Google Chrome Browser for run a system and fine research

about the system.

Xampp Server version 3.2.2 Act as local server to run and test the system.

It contains Apache and MySQL.

phpMyAdmin Open source relational database management

system that uses structured Query and stored

the data of the system.

Dropbox version 48.4.58 Application for backup the file system and

the data.

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3. 4.2 Hardware Requirements

The list of the hardware requirements is illustrated in Table 3.2

Table 3.2: CBIS Hardware Requirements

HARDWARE DESCRIPTION

Laptop ASUS Processor: Intel BYT-M4Core @ 2.66GHz

RAM: 2GB

OS: Windows 10

Printer Canon

3.5 SUMMARY

This chapter discusses the methodology used for the system development, hardware and

software required to develop this system. Each methodology can be chose according to the

complexity of the system. Choosing the right development methodology is important since it

can affect the development process. The right methodology can help to accomplish the

project timely manner as referred to project Gantt chart and also fulfil the requirement of the

system.

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CHAPTER 4:

DESIGN

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4.1 INTRODUCTION

Design is the method that is used to define and analyse data requirements to support the

software development project. The main function of this section is to show the flow how the

system goes during the design phase. Modelling of the project can be explained by Context

Diagram (CD), Data Flow Diagram (DFD) and Entity Relationship Diagram (ERD).

4.2 SYSTEM DESIGN AND MODELLING

In this subtopic, the flow of the system is organized so that the system development can

progress smoothly. Conceptual data modelling is the representation of data available in the

organization and also display the overall structure of the data available, regardless of the

physical technology involved. Modelling process involves graphical representation of the

functions and processes for the development of the system before the system was developed.

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4.2.1 CONTEXT DIAGRAM

Figure 4.1: CBIS Context Diagram

The Figure 4.1 shows the context diagram for Cyberbully Identification System which

includes 3 entities which are STUDENT, ADMIN and PSYCHOLOGIST. There are twelve

data flows involved in the interaction between the entities and the central process. The

STUDENT entity has one incoming data flow; category details and also has one outgoing

data flow; user details. The ADMIN entity has two incoming data flow; student report and

student-category report. There are three outgoing data flows which are user details, category

details and question details. The PSYCHOLOGIST entity has three incoming data flows and

two outgoing data flows. The three incoming data flows are appointment details, consultation

report and student-category report. The two outgoing data flows are user details and

consultation details.

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4.2.2 DATA FLOW DIAGRAM

Data Flow Diagram (DFD) is a process that all users have to face.

4.2.2.1 DATA FLOW DIAGRAM Level 0

Figure 4.2: CBIS DFD Level 0

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The Figure 4.2 shows the data flow diagram (DFD) of level 0 for Cyberbully Identification

System. The data flow diagram has three entities which are STUDENT, ADMIN and

PSYCHOLOGIST. The processes that involved in Cyberbully Identification System are

MANAGE USER, MANAGE PROFILE, MANAGE QUESTION, MANAGE CATEGORY,

MANAGE APPOINTMENT, MANAGE TIPS, MANAGE CONSULTATION and

GENERATE REPORT. There were nine data stores created in the system which are USER,

STUDENT, ADMIN, PSYCHOLOGIST, QUESTION, CATEGORY, APPOINTMENT,

TIPS and CONSULTATION.

1. USER enters IC number and password to MANAGE USER process which outputs IC

number and password into USER data store.

2. The USER whether the STUDENT, ADMIN or PSYCHOLOGIST can manage their

profile with input such as student, admin and psychologist details to MANAGE

PROFILE process which outputs student, admin and psychologist record into three

data store that are STUDENT, ADMIN and PSYCHOLOGIST data store. The three

data stores do store all information about the STUDENT, ADMIN and

PSYCHOLOGIST.

3. The ADMIN can manage the questions by insert the question details into MANAGE

QUESTION process and become output question record then store in QUESTION

data store.

4. The ADMIN can manage the category by insert category details into MANAGE

CATEGORY process and become output category record then store in CATEGORY

data store.

5. The STUDENT can manage the appointment by insert appointment details using

category details into MANAGE APPOINTMENT process and become output

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appointment record then store in APPOINTMENT data store. The PSYCHOLOGIST

also does receive the appointment details from the process.

6. The PSYCHOLOGIST can manage the tips by insert tips details into MANAGE TIPS

process and become output tips record then store in TIPS data store. Meanwhile, the

PSYCHOLOGIST also manage the consultation by insert the consultation details into

MANAGE CONSULTATION process and become output consultation record then

store in CONSULTATION data store.

7. There are a few reports that output by process GENERATE REPORT by input all

details in all data store.

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4.2.2.2 DATA FLOW DIAGRAM Level 1

4.2.2.2.1 DFD Level 1 Process 1: Manage User

Figure 4.3: CBIS DFD Level 1 Manage User

Description:

1. The STUDENT, ADMIN and PSYCHOLOGIST can inputs user details and ADD

USER process send the user record to the USER data store.

2. STUDENT, ADMIN and PSYCHOLOGIST can update their details by input student

details, admin details and psychologist details into UPDATE USER process and the

process send all of the records to the USER data store.

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4.2.2.2.2 DFD Level 1 Process 2: Manage Profile

Figure 4.4: CBIS DFD Level 1 Manage Profile

Description:

1. STUDENT, ADMIN and PSYCHOLOGIST can edit their profile by input their

details; student details, admin details and psychologist details into EDIT PROFILE

process. The process sends all of the records to the STUDENT, ADMIN and

PSYCHOLOGIST data stores.

2. VIEW PROFILE process can be accessed by the STUDENT, ADMIN and

PSYCHOLOGIST after they make any changes in the EDIT PROFILE process.

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4.2.2.2.3 DFD Level 1 Process 3: Manage Question

Figure 4.5: CBIS DFD Level 1 Manage Questions

Description:

1. The ADMIN can input the question details to the ADD QUESTION process. The

process sends the question record to QUESTION data store. Then, data store send

back the question record to the ADD QUESTION process.

2. The ADMIN can edit question details by input question details to EDIT QUESTION

process and the process sends the question record to QUESTION data store. The data

store send back about the question record.

3. The ADMIN can also delete about question details by input the question details to

DELETE QUESTION process and the process send the record to QUESTION data

store. Then, data store send back about the record.

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4.2.2.2.4 DFD Level 1 Process 4: Manage Category

Figure 4.6: CBIS DFD Level 1 Manage Category

Description:

1. The ADMIN can input the category details to the ADD CATEGORY process. The

process sends the category record to CATEGORY data store. Then, data store send

back the category record to the ADD CATEGORY process.

2. The ADMIN can edit category details by input category details to EDIT CATEGORY

process and the process sends the category record to CATEGORY data store. The

data store send back about the category record.

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4.2.2.2.5 DFD Level 1 Process 5: Manage Appointment

Figure 4.7: CBIS DFD Level 1 Manage Appointment

Description:

1. The STUDENT can input the appointment details to the ADD APPOINTMENT

process. The process sends the appointment record to APPOINTMENT data store.

The appointment has made is based on the category that the student gain. Then, data

store send back the appointment record to the ADD APPOINTMENT process.

2. The STUDENT also can edit appointment details by input appointment details to

EDIT APPOINTMENT process and the process sends the appointment record to

APPOINTMENT data store. The data store send back about the appointment record.

3. The PSYCHOLOGIST does receive the appointment details after process ADD

APPOINTMENT and EDIT APPOINTMENT had been done.

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4.2.2.2.6 DFD Level 1 Process 6: Manage Tips

Figure 4.8: CBIS DFD Level 1 Manage Tips

Description:

1. The PSYCHOLOGIST can input the tips details to the ADD TIPS process. The

process sends the tips record to TIPS data store. Then, data store send back the tips

record to the ADD TIPS process.

2. The PSYCHOLOGIST can edit tips details by input tips details to EDIT TIPS process

and the process sends the tips record to TIPS data store. The data store send back

about the tips record.

3. The PSYCHOLOGIST can also delete about tips details by input the tips details to

DELETE TIPS process and the process sends the record to TIPS data store. Then,

data store send back about the record.

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4.2.2.2.7 DFD Level 1 Process 7: Manage Consultation

Figure 4.9: CBIS DFD Level 1 Manage Consultation

Description:

1. The PSYCHOLOGIST can input the consultation details to the ADD

CONSULTATION process. The process sends the consultation record to

CONSULTATION data store. Then, data store send back the consultation record to

the ADD CONSULTATION process.

2. The PSYCHOLOGIST can edit consultation details by input consultation details to

EDIT CONSULTATION process and the process sends the consultation record to

CONSULTATION data store. The data store send back about the consultation record.

3. The PSYCHOLOGIST can also delete about consultation details by input the

consultation details to DELETE CONSULTATION process and the process send the

record to CONSULTATION data store. Then, data store send back about the record.

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4.2.3 ENTITY RELATIONSHIP DIAGRAM

Figure 4.10: CBIS ERD

The Figure 4.10 shows the entity relationship diagram for Cyberbully Identification System

which includes 10 entities. There are user, admin, student, psychologist, question, answer,

category, appointment, tips, and consultation.

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4.3 DATA DICTIONARY

Data dictionary shows how the data been stored in the database of the system.

1. Table USER

Table 4.1: CBIS USER Data Dictionary

No. ATTRIBUTE DESCRIPTION TYPE KEY LENGTH DEFAULT NULL

1. USER_username Unique id that holds by user. It can be used to verify their authorization to the system.

VARCHAR (12)

Foreign key

12 - -

2. USER_password The key to allowed authorized admin to login into the system. e.g password in the system is ‘123’

VARCHAR (40)

- 40 NULL YES

Table 4.1 shows that the attributes of table USER in the database. There are two attributes

which is USER_username and USER_password.

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2. Table STUDENT

Table 4.2: CBIS STUDENT Data Dictionary

No. ATTRIBUTE DESCRIPTION TYPE KEY LENGTH DEFAULT NULL

1. STUDENT_IC Unique id that holds by user. It can be used to verify their authorization to the system.

VARCHAR (12)

Primary key

12 - -

2. STUDENT_name Represent the name of the student of the system. e.g: STUDENT_name in the system is ‘Ahmad Fulan’

VARCHAR (50)

- 50 - -

3. STUDENT_gender Represent the student gender. e.g: STUDENT_gender in the system is ‘male’

VARCHAR (10)

- 10 - -

4. STUDENT_address Represent the email of the student. e.g: STUDENT_email in the system is ‘123@gmail.com’

VARCHAR (100)

- 100 - -

5. STUDENT_dob Represent the date of birth of the student.

DATE - - - -

6. STUDENT_email Represent the email of the student. e.g: STUDENT_email in the system is ‘123@gmail.com’

VARCHAR (50)

- 50 - -

7. STUDENT_contactNo Represent the contact number of each student in the system e.g: STUDENT_contactNo in the system is ‘012323211’

VARCHAR (13)

- 13 - -

8. STUDENT_ universityName

Represent the name of university for each student in the system e.g STUDENT_ universityName in the system is ‘UKM’

VARCHAR (150)

- 150 - -

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Table 4.2 shows that the attributes of table STUDENT in the database. There are eight

attributes which is STUDENT_IC, STUDENT_name, STUDENT_gender,

STUDENT_address, STUDENT_dob, STUDENT_email, STUDENT_contactNo and

STUDENT_universityName.

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3. Table ADMIN

Table 4.3: CBIS ADMIN Data Dictionary

No. ATTRIBUTE DESCRIPTION TYPE KEY LENGTH DEFAULT NULL

1. ADMIN_IC Unique id that holds by user. It can be used to verify their authorization to the system.

VARCHAR (12)

Primary key

12 - -

2. ADMIN _name Represent the name of the admin of the system. e.g: ADMIN _name in the system is ‘Ahmad Fulan’

VARCHAR (50)

- 50 - -

3. ADMIN _gender Represent the admin gender. e.g: ADMIN _gender in the system is ‘male’

VARCHAR (10)

- 10 - -

4. ADMIN _address Represent the email of the admin. e.g: ADMIN _email in the system is ‘123@gmail.com’

VARCHAR (100)

- 100 - -

5. ADMIN _dob Represent the date of birth of the admin.

DATE - - - -

6. ADMIN _email Represent the email of the admin. e.g: ADMIN _email in the system is ‘123@gmail.com’

VARCHAR (50)

- 50 - -

7. ADMIN _contactNo Represent the contact number of each admin in the system e.g: ADMIN _contactNo in the system is ‘012323211’

VARCHAR (13)

- 13 - -

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Table 4.3 shows that the attributes of table ADMIN in the database. There are seven

attributes which is ADMIN_IC, ADMIN_name, ADMIN_gender, ADMIN_address,

ADMIN_dob, ADMIN_email and ADMIN_contactNo.

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4. Table PSYCHOLOGIST

Table 4.4: CBIS PSYCHOLOGIST Data Dictionary

No. ATTRIBUTE DESCRIPTION TYPE KEY LENGTH DEFAULT NULL

1. PSYCHOLOGIST _IC

Unique id that holds by user. It can be used to verify their authorization to the system.

VARCHAR (12)

Primary key

12 - -

2. PSYCHOLOGIST _name

Represent the name of the psychologist in the system. e.g: PSYCHOLOGIST _name in the system is ‘Ahmad Fulan’

VARCHAR (50)

- 50 - -

3. PSYCHOLOGIST _gender

Represent the psychologist gender. e.g: PSYCHOLOGIST _gender in the system is ‘male’

VARCHAR (10)

- 10 - -

4. PSYCHOLOGIST _address

Represent the email of the psychologist. e.g: PSYCHOLOGIST _email in the system is ‘123@gmail.com’

VARCHAR (100)

- 100 - -

5. PSYCHOLOGIST _dob

Represent the date of birth of the psychologist.

DATE - - - -

6. PSYCHOLOGIST _email

Represent the email of the psychologist. e.g: PSYCHOLOGIST _email in the system is ‘123@gmail.com’

VARCHAR (50)

- 50 - -

7. PSYCHOLOGIST _contactNo

Represent the contact number of each psychologist in the system e.g: PSYCHOLOGIST _contactNo in the system is ‘012323211’

VARCHAR (13)

- 13 - -

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Table 4.4 shows that the attributes of table PSYCHOLOGIST in the database. There are

seven attributes which is PSYCHOLOGIST_IC, PSYCHOLOGIST_name,

PSYCHOLOGIST_gender, PSYCHOLOGIST_address, PSYCHOLOGIST_dob,

PSYCHOLOGIST_email and PSYCHOLOGIST_contactNo.

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5. Table QUESTION

Table 4.5: CBIS QUESTION Data Dictionary

No. ATTRIBUTE DESCRIPTION TYPE KEY LENGTH DEFAULT NULL

1. QUESTION_questionID

Unique id that holds by question.

VARCHAR (10)

Primary key

10 - -

2. QUESTION_description

Represent the description of each question in the system.

VARCHAR (100)

- 100 - -

3. QUESTION_marks Represent the marks of each question in the system.

INT(10) - 10 - -

4. QUESTION_IC Represent of the unique id that holds by student.

VARCHAR(12)

Foreign Key

12 - -

Table 4.5 shows that the attributes of table QUESTION in the database. There are four

attributes which is QUESTION_questionID, QUESTION_description, QUESTION_marks,

and QUESTION_IC.

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6. Table ANSWER

Table 4.6: CBIS ANSWER Data Dictionary

No. ATTRIBUTE DESCRIPTION TYPE KEY LENGTH DEFAULT NULL

1. ANSWER_IC Represent of the unique id that holds by student.

VARCHAR (12)

Primary key

12 - -

2. ANSWER_Marks Represent the marks of question in the system.

INT(10) - 10 - -

3. ANSWER_Date Represent the date of the student answer the question in the system.

DATE - - - -

Table 4.6 shows that the attributes of table ANSWER in the database. There are three

attributes which is ANSWER_IC, ANSWER_Marks, and ANSWER_Date.

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7. Table CATEGORY

Table 4.7: CBIS CATEGORY Data Dictionary

No. ATTRIBUTE DESCRIPTION TYPE KEY LENGTH DEFAULT NULL

1. CATEGORY_categoryID

Represent of the

unique id that holds by each category.

VARCHAR (10)

Primary key

10 - -

2. CATEGORY_IC Represent of the unique id that holds by admin.

VARCHAR(12)

Foreign Key

12 - -

3. CATEGORY_minMarks

Represent the min marks of each category in the system.

INT(10) - 10 - -

4. CATEGORY_maxMarks

Represent the max marks of each category in the system.

INT(10) - 10 - -

Table 4.7 shows that the attributes of table CATEGORY in the database. There are four

attributes which is CATEGORY_categoryID, CATEGORY_IC, CATEGORY_minMarks

and CATEGORY_maxMarks.

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8. Table APPOINTMENT

Table 4.8: CBIS APPOINTMENT Data Dictionary

No. ATTRIBUTE DESCRIPTION TYPE KEY LENGTH DEFAULT NULL

1. APPOINTMENT _appointmentID

Represent of the

unique id that holds by appointment in the system.

VARCHAR (10)

Primary Key

10 - -

2. APPOINTMENT _categoryID

Represent of the

unique id that holds by each category.

VARCHAR (10)

Foreign Key

10 - -

3. APPOINTMENT_IC Represent of the unique id that holds by student.

VARCHAR(12)

Foreign Key

12 - -

4. APPOINTMENT _appDate

Represent the date of the student make the appointment in the system.

DATE - - - -

Table 4.8 shows that the attributes of table APPOINTMENT in the database. There are four

attributes which is APPOINTMENT_appointmentID, APPOINTMENT_categoryID,

APPOINTMENT_IC and APPOINTMENT_appDate.

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9. Table CONSULTATION

Table 4.9: CBIS CONSULTATION Data Dictionary

No. ATTRIBUTE DESCRIPTION TYPE KEY LENGTH DEFAULT NULL

1. CONSULTATION _consultationID

Unique id that holds by consultation.

VARCHAR (10)

Primary key

10 - -

2. CONSULTATION _description

Represent the description of each consultation in the system.

VARCHAR (50)

- 50 - -

3. CONSULTATION _consDate

Represent the date of the consultation in the system.

DATE - - - -

4. CONSULTATION _categoryID

Represent of the

unique id that holds by each category.

VARCHAR (10)

Foreign Key

10 - -

5. CONSULTATION _IC

Represent of the

unique id that holds by student.

VARCHAR(12)

Foreign Key

12 - -

Table 4.9 shows that the attributes of table CONSULTATION in the database. There are five

attributes which is CONSULTATION_consultationID, CONSULTATION_description,

CONSULTATION_consDate, CONSULTATION_categoryID and CONSULTATION_IC.

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10. Table TIPS

Table 4.10: CBIS TIPS Data Dictionary

No. ATTRIBUTE DESCRIPTION TYPE KEY LENGTH DEFAULT NULL

1. TIPS_tipsID Unique id that holds by tips.

VARCHAR (10)

Primary key

10 - -

2. TIPS_description Represent the description of each tips in the system.

VARCHAR (50)

- 50 - -

3. TIPS_categoryID Represent of the unique id that holds by each category.

VARCHAR (10)

Foreign Key

10 - -

4. TIPS_IC Represent of the unique id that holds by student.

VARCHAR(12)

Foreign Key

12 - -

Table 4.10 shows that the attributes of table TIPS in the database. There are four attributes

which is TIPS_tipsID, TIPS_description, TIPS_categoryID and TIPS_IC.

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REFERENCES

49

JOURNALS AND ARTICLES

1. Cyberbullying Detection: A Step Toward a Safer Internet Yard ( Lyon, France - April 2012)

2. Cyberbullying Detection using Time Series Modeling ( Nektaria Potha, Manolis Maragoudakis – 2014)

3. Cyberbullying Identification Using Participant-Vocabulary Consistency (Elaheh Raisi, Bert Huang –

2016)

4. Thesis Final Year Project Early Prediction of Lung Cancer System By Using Rule-Based ( Nurul

Athirah Bt. Aziz – August 2016)

INTERNET SURFINGS

1. https://www.stopbullying.gov/cyberbullying/what-is-it/index.html

2. http://www.endcyberbullying.org/5-different-types-of-cyberbullying/

3. https://kids.kaspersky.com/10-forms-of-cyberbullying/

4. http://www.plantcell.org/content/23/9/3101

http://www.endcyberbullying.org/5-different-types-of-cyberbullying/http://www.plantcell.org/content/23/9/3101