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`MOSQUITO EGG PREDICTION SYSTEM USING TIME SERIES
ANALYSIS
NUR AMIRAH BT MOHD AMRAN
BACHELOR OF COMPUTER SCIENCE
(SOFTWARE DEVELOPMENT) WITH HONOURS
UNIVERSITI SULTAN ZAINAL ABIDIN
2020/2021
DECLARATION
I here by declare that the 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.
NurAmirah
_____________________________
Name: Nur Amirah Bt Mohd Amran
Date: 27th January 2021
ii
CONFIRMATION
This page is to confirm that this project entitled Mosquito Egg Prediction System Using
Time Series was prepared and submitted by Nur Amirah Bt Mohd Amran (Matric
Number: BTAL18051045) and has been satisfactory in terms of scope, quality and
presentation as partial fulfilment of the requirement for the Bachelor of Computer
Science (Software Development) with honours in Universiti Sultan Zainal Abidin. The
research conducted and the writing of this report was under my supervisor.
_______________________________
Name: En Abd Rasid Bin Mamat
Date: 27th January 2021
iii
DEDICATION
In the Name of Allah, the Most Gracious and the Most Merciful. Alhamdulillah all
praise to Allah s.w.t, I completely finish writing this report successfully. This report
could not have been finished without the support, encouragement and cooperation of
my friends, supervisor, parents and other peoples. Here I would like to thank a lot to my
dedicated supervisor, En Abd Rasid Bin Mamat who has always given ideas and help
me a lot in developing this project successfully despite of lack of time and to the panels
who helped me a lot by reprimanding and improving the shortcomings that arose during
the presentation session. Also not to forget to all lectures who taught me throughout this
semester directly or indirectly because without their guidance, knowledge and
brilliance, I would never could have finish this project. Last but not least, I want to thank
to all my friends that helped me through this project with their moral support. Their
collaboration and support whenever I need them is priceless and without them,
completing this work would not have been possible.
Thank you.
iv
ABSTRACT
World Health Organization (WHO) has shown data that the number of deaths caused
by mosquitoes is the highest compared to deaths caused by other wild animals. Due to
this problem, it urges researchers to explore strategies for mosquito control such as
interrupting their egg development. For the process of mosquito breeding control and
mosquito-borne disease control it is important to know the data on mosquito breeding
in a particular place especially the data on mosquito eggs produced in a day and weekly
to predict the number of eggs in for months and years to come. Therefore, this system
is build. A system of predicting mosquito eggs using time series methods which
involves research officers, admins, stations and stakeholders. Prediction involves taking
data about an event and using it to predict future observations. Time series is a way of
forecasting about anything that is observed in sequence over time. The objective of the
construction of this system is to facilitate the parties involved to update the data on the
number of mosquito eggs taken from certain places and to facilitate the researchers to
control the existence of mosquitoes and mosquito-borne diseases through mosquito egg
data. In addition to predict mosquito eggs during the month and the coming year
according to a particular season. The scope of this system are admins, research officers
and registered stakeholders such as district health offices. Admin can add, update and
delete information of PA (research officer), station and the stakeholders. PA (research
officer) will insert the number of mosquito eggs into the system from each station on a
daily basis. The registered stakeholders can search and view data of mosquito eggs
according to the area they want to see. Admin, PA (research officer) and stakeholders
also can print report on the number of mosquito eggs per station in the form of graph /
table. This system works by PA (research officer) entering data daily and each weekend
the system will calculate the number of eggs then data will be stored in a temporary
v
table. The forecasting method using time series will be used to predict mosquito eggs
in the coming months and years using data that has been stored in a temporary table.
That is how this process will be repeated until the following weeks. The expected result
of this system is to make it easier for the parties involved to update, record and view
predictions on the number of mosquito eggs at each particular station. It will also help
the health officer to control mosquito breeding through data obtained from this system.
vi
CONTENTS
PAGE
DECLARATION Error! Bookmark not defined. CONFIRMATION ii DEDICATION iii ABSTRACT iv
ABSTRACT Error! Bookmark not defined. CONTENTS vi LIST OF TABLES vii LIST OF FIGURES viii
CHAPTER 1 INTRODUCTION 1 1.1 Project Background 1 1.2 Problem Statement 2
1.3 Objectives 3 1.4 Scope 4 1.5 Limitation of Work 5 1.6 Expected Result 6
1.7 Implementing and planning (Gantt Chart) 7
CHAPTER 2 LITERATURE REVIEW 8 2.1 Introduction 8 2.2 Research On Related Techniques 9
2.3 Research On Existing System 12
2.4 Solution Approach 16
2.5 Summary 19
CHAPTER 3 METHODOLOGY 20 3.1 Introduction 20 3.2 Iterative Model 20
3.3 Hardware and Software Requirement 24
3.4 Framework Design 26
3.5 Context Diagram 27
3.6 Data Flow Diagram 28
3.7 Entity Relationship Diagram 32
3.8 Data Dictionary 33
3.9 Summary 35
REFERENCES 36
vii
LIST OF TABLES
Table No. Title Page
Table 1.7.1 : Gantt Chart Table 7
Table 2.2.1 : Table comparisons of research articles 10
Table 2.3.1 : Table comparison of three existing systems in terms of advantages
and disadvantages 15
Table 2.4.2.1 : Mosquito Egg Data 17
Table 3.3.1 : Development software requirement 24
Table 3.3.2 : Development hardware requirement 25
Table 3.8.1 : Table Admin 33
Table 3.8.2 : Table Researcher 34
Table 3.8.3 : Table Registered Stakeholders 34
Table 3.8.4 : Table Station 34
Table 3.8.5 : Table Mosquito Egg Data 35
Table 3.8.6 : Table Temporary 35
viii
LIST OF FIGURES
Figure No. Title Page
Figure 2.3.1 : Mosquito Alert Application Interface 12
Figure 2.3.2 : Mosquito Tracker Application Interface 13
Figure 2.3.3 : Break Dengue Website Interface 14
Figure 3.2.1 : Iterative Model 21
Figure 3.4.1 : Framework Design 26
Figure 3.5.1 : Context Diagram 27
Figure 3.6.1 : Data Flow Diagram Level 0 28
Figure 3.6.2 : Data Flow Diagram Level 1 for Admin 29
Figure 3.6.3 : Data Flow Diagram Level 1 For Researcher 30
Figure 3.6.4 : Data Flow Diagram Level 1 for Registered Stakeholders 31
Figure 3.7.1 : Entity Relationship Diagram 32
1
CHAPTER 1
INTRODUCTION
1.1 Project Background
World Health Organization (WHO) has shown data that the number of deaths
caused by mosquitoes is the highest compared to deaths caused by other wild animals.
Diseases transmitted by mosquitoes have contributed to the death and suffering of
millions throughout human history. Mosquitoes are among the fastest growing animals.
With just one spawn, mosquitoes can produce hundreds of mosquito larvae. Forecasting
are one of the best ways to find out the data on the number of mosquitoes through its
eggs in a place to control its existence and mosquito-borne diseases.
In order to facilitate the management of mosquito egg calculations and
prediction, Mosquito Egg Prediction Website is created. Researchers and related party
no longer need to store data in the form of paper or files which may be easily lost and
difficult to carry everywhere. They just need to enter the data into the system that has
been prepared for their research and the data will be stored securely in the system so
there is no problem of data dropouts or something like that. They also do not have to
calculate and predict manually to know the trend of something. In this system, it
proposed to use the time series method forecasting technique to predict the amount and
trends of mosquito eggs in selected area for the coming month and years. That is how
technology has facilitated various activities and tasks in people lives.
2
1.2 Problem Statement
After conducting research and discussion with the stakeholders, among the
problems presented are: -
1.2.1 Difficulties in data management and storing data
Data lost problems and data damage may occur if the data is stored manually
in the form of booklet or files. Due to the large collection of data on a daily
basis, its have a great risk for data lost or there may be some data missing.
1.2.2 Difficulties in sharing information between related parties
This system is to facilitate the parties involved to share information about the
investigation and related data as they only need to access this system to view
the desired data and store the data.
1.2.3 Difficulties in predicts production of mosquito eggs
In order to control mosquito breeding, it is important for researchers to predict
mosquito eggs to find out the trend of mosquito breeding and take steps to
control it but it is quite difficult to predict it with traditional calculation
methods. It will take a long time and may be less accurate.
3
1.3 Objectives
The objectives of this system are identified as below :-
1.3.1 To study how time series forecasting technique can be implemented in the
system.
1.3.2 To design a process flow, structure of user interface and database for the
Mosquito Egg Prediction System .
1.3.3 To evaluate capabilities of the Mosquito Egg Prediction Website whether that
system can meet the requirements and generate the report to the user.
4
1.4 Scope
The scope can be described by how the system works in relation to the
activity
between system users and systems, which is information that flows between
systems
and users. The scope of this system are Admin, Research Officers (PA) and
registered stakeholders such as district health offices.
1.4.1 Admin
➢ Can view and approve registration of PA (research officer)
➢ Can view and approve registration of Station
➢ Can view and approve registration of Registered Stakeholders
1.4.2 Research Officer (PA)
➢ Can update, delete and view profile.
➢ Can add, delete and update data of mosquito eggs
➢ Can view mosquito eggs data
➢ Can view prediction report of mosquito eggs in each station
➢ Can print the report
1.4.3 Registered Stakeholders
➢ Can update, delete and view profile.
➢ Can view mosquito eggs data
➢ Can view prediction report of mosquito eggs in each station
➢ Can print the report
5
1.5 Limitation of Work
Mosquito Egg Prediction Website is not for public, only for related parties. In this
system, inserting data of the mosquito eggs only can be done by PA(research officer).
This system can be access through a mobile phone or computer and the mobile data or
Wi-Fi connection is needed.
6
1.6 Expected Result
The expected results of this project are to facilitate admin, PA(research officer) and
registered stakeholders in manage the information, store data, view the number of
mosquito egg and forecast the mosquito eggs. This project has been designed to
monitor current situation of mosquito breeding and in the future so that appropriate
action can be taken.
The goals that are achieved by the system are:
i) Instant access
ii) Efficient management of records
iii) Simplification of the operations
iv) Less processing time and getting required information
v) User friendly and flexible for further enhancement
7
1.7 Implementing and planning
Table 1.7.1 below shows the Gantt chart as a timeline guide for the development
of this system.
ACTIVITY/WEEK 1 2 3 4 5 6 7 8 9 10 11 12 13 14
Initiating
Discuss topic with
supervisor
Project title
proposal
Planning
Proposal writing :
introduction
Proposal writing :
literature review
Proposal progress
presentation
Proposal solution
methodology
Proof of concept
Analysis and
design
Design system
model
Design database
Design interface
Drafting report of
proposal
Final presentation
Final report
submission
Table 1.7.1 : Gantt Chart Table
8
CHAPTER 2
LITERATURE REVIEW
2.1 Introduction
This chapter will show about the research done directly or indirectly on the
project. It is important at the project development stage to refer to the research
that has been done. Analysis, observation, summary and evaluation of existing
systems will be made in this chapter. With the information obtained, it can be
used to develop new systems that can provide better functionality compared to
the existing systems and to determine the best approach in order to continue this
project. In my research its related to the method on forecasting. There are so
many methods that had been used in order to make an accurate forecasting but
each method are different approach for different system.
9
2.2 Research On Related Techniques
Evaluations and research conducted on several research papers on how
forecasting using time series methods and other forecasting method that can be
applied to the prediction system. The article that had been chosen in table 2.2.1
is observed the problem statement and method used in this research article.
Using this article, we can sum up the best method to use to develop as a special
feature in this system. As a result of these observations, there are three article
that had been chosen to study in this research.
Table 2.2.1 below shows the comparisons made for some research articles.
Year Authors Title Objective Problem
Statement
Method
Algorith
m Used
Result Future
Work
2012 Abhishek
Agrawal,
Vikas
Kumar,
Ashish
Pandey,
Imran
Khan
An
applicati
on of
time
series
analysis
for
Weather
forecasti
ng
To develop a
model which
comprises this
intelligent
behaviour
which defining
weather
conditions
like
temperature
(maximum or
minimum),
rainfall
etc.
Weather
forecasting has
been one of the
most
challenging
problems
around the
world for more
than half a
century. Not
only because
of its
practical
values in
meteorology,
but it is also a
typical
unbiased time
series
forecasting
problem
Neural
Network
(NN)
The network
is trained
with 60
years of data
for both
maximum
and
minimum
temperature.
After
training
phase the
network is
simulated by
using 40%
of data so
that the
predicted
result can be
verified.
-
10
in scientific
research.
2017 Elvi
Fetrina,
Meinarin
i Catur
Utami,
Anita
Permatas
ari
Forecast-
ing
System
of Office
Supplies
Demand
To compare
two techniques
of forecasting,
namely simple
moving
average (MA)
and simple
exponential
smoothing
(SES) with the
least of
forecasting
error of Mean
Absolute
Deviation
(MAD) in
order to get
high accuracy
of future
office supplies
demand.
Based on the
background
described
above, then the
underlying
problems are:
How to
compare and
choose the
most effective
forecasting
methods to
calculate and
predict the
demand in
order to
determine the
number of
quantity to
order. All of
these are
required to
avoid the the
inventory
problems of
stock out.
Simple
Moving
Average
and
Simple
Exponen
tial
Smoothi
ng
The forecast
method that
has the least
forecast
error is
Simple
Exponential
Smoothing
(SES) with
smoothing
constant of
0.5.
-
2020 Sumi Na
and
Hoonbok
Yi
Applicati
on of
smart
mosquito
monitori
ng
traps for
the
mosquito
forecast
systems
To obtain the
mosquito
prediction
formula by
using the
mosquito
population
data and the
environmental
data of the
past.
As the global
warming
accelerates, the
number of
mosquito
population and
the incidence
of diseases due
to mosquito-
borne diseases
rise, so
research on
mosquito
control and
population
Linear
Regressi
on
Models
The
generalized
linear model
analysis was
conducted
and the
mosquito
population
prediction
formula with
high
accuracy
was gained.
-
11
After studying some research papers as in the table 2.2.1 above, it shows that
Simple Moving Average is the most suitable method to be applied to this system.
monitoring is
urgently
required.
12
2.3 Research on Existing System
As a result of the study's observations on several existing systems, these three
systems were selected for comparison as a guide and improvement for this
system.
Mosquito Alert Application
Figure 2.3.1 show interface of Mosquito
Alert Application. This system is
developed as a Citizen science project to
investigate and control disease-carrying
mosquitoes. Objective of this system is to
study, monitor and fight against the spread
of disease-carrying mosquitoes. User will
be able to report mosquito observations,
mosquito breeding sites, and keep a record
of mosquito bites.
Figure 2.3.1 : Mosquito Alert Application Interface
13
Mosquito Tracker Application
Figure 2.3.2 show interface of Mosquito Tracker
Application. This system is like a report sites for
public to report where mosquitoes like to breed
such as in stagnant water, trash containers,
abandoned pools or fountains, discarded tires, tree
holes, areas of industrial or commercial debris. The
app will automatically upload a GIS-tagged photo
to a global map that will alert local public health
officers to the problem. This will help
epidemiologists and public health agencies make
better decisions.
Figure 2.3.2 : Mosquito Tracker Application Interface
14
Break Dengue Website
Figure 2.3.3 : Break Dengue Website Interface
Figure 2.3.3 above show Break Dengue Website interface. This website is an open
platform to anyone who concerned about the problem of dengue. This online interactive
tool collects information about dengue outbreaks and offers tailored advice to reduce
the spread of the disease.
15
Table 2.3.1 below shows the comparison made between the above three systems in
terms of advantages and disadvantages.
Table 2.3.1
Benchmark
System
Advantage Disadvantage
Mosquito Alert
Application
Easy for user to identify and
notify the presence of five
species of mosquitoes, report
their breeding places in their area
and report the bite received.
Mosquito breeding forecasts
only focus on five specific types of
mosquitoes that may cause
insensitivity to other types of
mosquito breeding.
Mosquito
Tracker Application
Ease for user to report
potential mosquitoes breeding
sites according to the
characteristics of the mosquito
breeding ground.
Type of breeding areas in one
place may not be known in some
other areas so there may be
misinformation
Break Dengue
Website
Provide a lot of dengue
information that make it easier
for users to refer and take
preventive measures based on
advice given.
Descriptions and advice on
preventing dengue are quite general
may not meet the needs of users
16
2.4 Solution Approach
Solution approach is about the possible approach that will be chosen in
developing this system. In order to find the solutions, research on a few related
approaches in time series analysis has been done. Thus, as a result from the
observations. the technique that will be used for this system is Simple Moving
Average (SMA) as SMA are frequently used to estimate the current level of a
time series, with this value being projected as a forecast for future
observations.
2.4.1 Simple Moving Average
The moving average value can be used directly to make predictions. It
is a naive model and assumes that the trend and seasonality
components of the time series have already been removed or adjusted
for. A simple moving average (SMA) is an arithmetic moving average
calculated by adding recent data and then dividing that figure by the
number of time periods in the calculation average.
SMA (Simple moving average) = (P𝑛+P𝑛)
𝑛
Pn = the collected data at period n
n = the number of total periods
17
2.4.2 Implementation on Data and Calculation for Forecasting by Using Simple
Moving Average Method
Table 2.4.2.1 below shows the data collected for four weeks in January,
and forecasts for February will be made based on data taken in January
Table 2.4.2.1 : Mosquito Egg Data
Month Week(n) Number of
Mosquito Eggs
(P)
January
1 40
2 48
3 50
4 35
February
5 41
6
7
8
18
SMA (Simple moving average) = (P𝑛+P𝑛)
𝑛
W2 -------- 40 + 48
2 = 44
W3 -------- 48 + 50
2 = 49
W4 -------- 50 + 35
2 = 42.5
W5 -------- 35 + 41
2 = 38
2 weeks moving average is used to find the number of mosquito eggs
in the week 6. The forecast for the sixth week is using the moving
average for the previous month which is w5 = 38 so the prediction for
mosquito eggs in week 6 is 38. That is the calculation method for
predicting the number of mosquito eggs in the following weeks and
months.
To decide whether to use 2 weeks or 4 weeks moving average, it
depends on the situation. If in that month a large number of mosquito
eggs are recorded then use 2 weeks moving average but if a small
number of mosquito eggs in that month 4 weeks moving average can
be used.
19
2.5 Summary
This chapter discuss literature reviews that have been collected and reviewed along
the studies. Literature review important for developer to discover any problems in any
existed system or research that can be improve in future. As a result, the integration of
Mosquito Egg Prediction System Using Time Series with Simple Moving Average
(SMA) technique is the most suitable in developing this system. SMA technique will
help researcher to predict the number of mosquito eggs accurately based on previous
data taken.
20
CHAPTER 3
METHODOLOGY
3.1 Introduction
Methodology is the set of the complete guideline that includes the Software
Development Life Cycle (SDLC) tool models for carrying out activities. A
methodology is used in a systematic ways to solves the problem during system
development. It defines the steps involved in the software development process. It is
necessary to ensure that the implementation of the framework is achieved systematically
and effectively. The proposed system, therefore, uses Iterative Model as a guideline to
develop it.
3.2 Iterative Model
The methodology that will be used in developing Mosquito Egg Prediction System
Using Simple Moving Average Method is Iterative Model. This model does not attempt
to start with a full specification of requirements. The system development begins by
specifying and implementing some part of the system, which can then be reviewed in
order to identify further requirements. This process is then repeated until the final
products produced satisfy all the requirements that were evolved before. Figure 3.2.1
below show that there are six phases involved in the iterative model which is planning
phase, analysis and design phase, implementation phase, testing phase, deployment and
evaluation phase.
21
Figure 3.2.1 : Iterative Model
3.2.1 Initial Planning Phase
Initial Planning is a pre-planning where in this phase the brainstorming session
started and some ideas and project title is proposed.
3.2.2 Planning Phase
At this phase, the project title chosen is Mosquito Egg Prediction System Using
Simple Moving Average. From the brainstorming, the problem statements,
objectives and scope are identified in this phase. Planning phase is the most
crucial phase as it is a guideline to develop the system so Gantt chart will be
needed as a reference to make sure that this project still on track and can be done
on estimate time.
3.2.3 Requirement Phase
In this phase, requirement is gathered through research on articles and related
existing system to choose suitable method that can be applied to make sure this
system meet the system requirement and functionality requirement. Based on the
22
information gathered, suitable method and technique for the system have been
decided.
3.2.4 Analysis and Design Phase
In analysis phase, every requirement on method and technique for the system is
analysed for more understanding on selected forecasting technique compare to
other technique that has been used by other researchers. Simple Moving Average
Method was decided to be an approach in this project. Methodology, technique,
software and hardware requirement are also decided during this phase to ensure
that every requirement are compatible with the system. Design phase of this
system is done based on output of analysis phase. System interface and database
are design based on requirement. The Context Diagram (CD), Data Flow Diagram
(DFD) Level 0 and 1 and Entity Relationship Diagram (ERD) are designed at this
phase to interpret the process flow of Mosquito Egg Prediction System.
3.2.5 Implementation Phase
This is a phase where activities that have been planned during previous phase are
executed. This system is developed by using XAMPP, MySQL and Notepad++.
During
this phase, database and interface that has been designed are started to be
developed. The process of writing coding is started during this phase and this is
the phase where Simple Moving Average Technique is implemented
3.2.6 Testing Phase
After system has fully developed, testing is being done on the system. Repeated
test will be done to ensure that the system is working smoothly as it should and
there is no bug in that module. There are mainly four Levels of Testing in testing
phase which are Unit Testing to checks if software components are fulfilling
23
functionalities or not, Integration Testing to checks the data flow from one module
to other modules , System Testing to valuates both functional and non-functional
needs for the testing and Acceptance Testing to checks the requirements of a
specification or contract are met as per its delivery. Technique that will be used
in the testing phase are Blackbox testing where the functionalities of software
applications are tested without having knowledge of internal code structure,
implementation details and internal paths and Whitebox testing is used in which
internal structure is tested. Black Box Testing mainly focuses on input and output
of software applications and it is entirely based on software requirements and
specifications. The error found will be fixed as much as possible during the testing
phase, it is possible to use the results from this phase to reduce the number of
errors within the software program.
3.2.7 Deployment and Evaluation Phase
In this phase, the system is ready to be tested by end-user after the bugs and
defects spotted during the test phase are removed. The users will evaluate this
system and give their feedback based on their experienced. The evaluation and
feedback given will be used to improve the system to make sure that it fulfils all
the requirements and well functioning or not.
24
3.3 Hardware and Software Requirement
There are two requirement that needed to develop the system which are the software
requirement and hardware requirement. This is important to ensure the development of
the
project went well and for future references.
3.3.1 Software requirement
Table 3.3.1 shows the software requirement for the proposed system.
Table 3.3.1 Development software requirement
No. Software Description
1. Microsoft Office Word 2016 Use to prepare
documentation of the
report
2. Draw.io An online software
use to draw Context
Diagram and Data Flow
Diagram
3. Google chrome Browser to run
localhost and searching
information
4. MYSQL For system database
5. Notepad++ Used to code the
program of the project,
especially connection
application to the database
6. Adobe XD Application to create
prototype
7. PhpMyAdmin Programming
language
25
3.3.2 Hardware requirement
Table 3.3.2 shows the hardware requirement for the proposed system.
Table 3.3.2 Development hardware requirement
No. Hardware Description
1. Laptop HP Laptop
2. Processor Intel(R) Core(TM) i5-
8250U CPU @ 1.60GHz
1.80 GHz
3. Random Access Memory (RAM) 4.00 GB
4. Operating system Windows 10
5. System type 64-bit operating
system, x64-based
processor
26
3.4 Framework Design
Figure 3.4.1 show the flow of this system which is what the user can do with
Mosquito Egg Prediction Website. Researcher need to register and login profile, insert
data of mosquito egg and sum up total every weeks for future prediction ,view
mosquito data and can view report. Registered Stakeholders also need to register and
login profile, view mosquito data and can view report while Admin needs to approve
trusted researcher, stakeholders and station to register with the system and can view
report.
Figure 3.4.1 : Framework Design
27
3.5 Context Diagram
Figure 3.5.1 : Context Diagram
Figure 3.5.1 shows context diagram for Mosquito Egg Prediction System
Using Time Series Analysis. There are 3 entities involve in this context
diagram which is ADMIN, RESEARCHER and REGISTERED
STAKEHOLDERS,
28
3.6 Data Flow Diagram
3.6.1 Data Flow Diagram Level 0
Figure 3.6.1 : Data Flow Diagram Level 0
Based on Figure 3.6.1 above, there are fifteen processes involve in this system
include process for Admin, Researcher and Registered Stakeholders.
29
3.6.2 DFD Level 1 for Admin
Figure 3.6.2 : Data Flow Diagram Level 1 for Admin
Based on Figure 3.6.2 above, there are six processes involve in Admin module,
where Admin can log in as a first step to get into the system. After login,
Admin need to approve registration requested by Researcher, Registered
Stakeholders and Station and Generate Report from the system. At the end of
process, Admin can log out from the system.
30
3.6.3 DFD Level 1 for Researcher
Figure 3.6.3 : Data Flow Diagram Level 1 For Researcher
Based on Figure 3.6.3 above, there are seven processes involve in Researcher
module, where Researcher can log in as a first step to get into the system.
After login, Researcher can Manage Profile, Manage Mosquito Egg Data,
Manage Mosquito Egg Prediction, Manage Station Data, and Generate Report
from the system. At the end of process, Researcher can log out from the
system.
31
3.6.4 DFD Level 1 for Registered Stakeholders
Figure 3.6.4 : Data Flow Diagram Level 1 for Registered Stakeholders
Based on Figure 3.6.4 above, there are four processes involve in Registered
Stakeholders module, where Registered Stakeholders can log in as a first step
to get into the system. After login, Registered Stakeholders can Manage
Profile, and Generate Report from the system. At the end of process,
Registered Stakeholders can log out from the system.
32
3.7 Entity Relationship Diagram
Figure 3.7.1 : Entity Relationship Diagram
An entity relationship diagram (ERD) illustrates an information system’s
entities and the relationship between those entities. ERD composed of three
things such as identifying and defining the entities, determine entities
interaction and the cardinality of the relationship. Figure 3.9 above shows the
relationship between entities that exist in this system.
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3.8 Data Dictionary
Data dictionary is a collection of names, attributes, and definition about data
elements that being used in a database. A data dictionary also provides metadata about
data elements.
1. Table Admin
2. Table Researcher
3. Table Registered Stakeholders
4. Table Station
5. Table Mosquito Egg Data
6. Table Temporary
3.8.1 Table Admin
Field Name Data Type Field
Length
Constraint Description
admin_email INT 10 Primary Key Admin registered email
password VARCHAR 50 Not Null Admin password
Table 3.8.1 : Table Admin
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3.8.2 Table Researcher
Field Name Data Type Field
Length
Constraint Description
researcher_email VARCHAR 50 Primary Key Researcher registered
password VARCHAR 50 Not Null Researcher password
researcher_name VARCHAR 50 Not Null Researcher name
researcher_id VARCHAR 10 Not Null Researcher id
researcher_phone INT 15 Not Null Researcher phone
researcher_department VARCHAR 50 Not Null Researcher department
authentication_proofresearch
VARCHAR 20 Not Null Researcher proof
certificate
Table 3.8.2 : Table Researcher
3.8.3 Table Registered Stakeholders
Field Name Data Type Field
Length
Constraint Description
stake_email VARCHAR 50 Primary Key Stakeholder registered
password VARCHAR 50 Not Null Stakeholder password
stake _name VARCHAR 50 Not Null Stakeholder name
stake _id VARCHAR 10 Not Null Stakeholder id
stake _phone INT 15 Not Null Stakeholder phone
stake _department VARCHAR 50 Not Null Stakeholder department
authentication_proofstake
VARCHAR 20 Not Null Stakeholder proof
certificate
Table 3.8.3 : Table Registered Stakeholders
3.8.4 Table Station
Field Name Data Type Field
Length
Constraint Description
station_id VARCHAR 10 Primary Key Station id
35
station_addr VARCHAR 50 Not Null Station Address
Table 3.8.4 : Table Station
3.8.5 Table Mosquito Egg Data
Field Name Data
Type
Field
Length
Constraint Description
daily_data INT 100 Not Null Daily data collected
weekly_data INT 100 Not Null Daily data collected
Table 3.8.5 : Table Mosquito Egg Data
3.8.6 Table Temporary
Field Name Data Type Field
Length
Constraint Description
station_id VARCHAR 10 Foreign Key Station id
calculated_data INT 100 Not Null Calculated data of
mosquito egg
Table 3.8.6 : Table Temporary
3.9 Summary
This chapter briefly explain methodology used in this project. Iterative method
used to develop the proposed system. Every phase in this method was explain
deeply. List of software and hardware used to develop this system also stated
in the table above.
36
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