COMPUTERIZED DATA MINING TECHNIQUES
IN STUDENTS INFORMATION SYSTEM
TABLE OF CONTENTS
Table of Contents
CHAPTER ONE: INTRODUCTION
1.1 Background of the Study
1.2 Statement of the Problem
1.3 Objectives of the Study
1.4 Scope of the Study
1.5 Significance of the Study
1.6 Limitations of the Study
1.7 Definition of Terms/ Variables
CHAPTER TWO: LITERATURE REVIEW
2.0 Data Mining Techniques
2.5 Sequential Patterns
2.6 Decision Tree
2.7 Introduction to Data Mining Architecture
2.7.2 Loose Coupling
2.7.3 Semi-Tight Coupling
2.7.4 Tight Coupling
2.8 Data Implementations and Preparation
2.9 Building on SQL/Creating Database
CHAPTER THREE: SYSTEM ANALYSIS AND DESIGN
3.0 Existing System
3.1 Problems of Existing System
3.2 The Proposed System
3.3 Benefits of Proposed System
3.4 System Design
3.5 Input Design Specification
3.6 Output Design Specification
3.7 Database Design
3.8 Program Flow Chat
CHAPTER FOUR: PROGRAM DESIGN AND IMPLEMENTATION
4.1.1 Choice of Programming Language and Justification
4.1.2 Justification of the Choice of PHP
4.2 System Implementation
4.2 Results and Screen Shots
4.2.1 Admin Login Page
4.2.2 Student Registration Page
4.2.3 View Student Record Page
4.2.4 The Search Page
4.3 Test Results
4.4 Report Phase for Test Results
CHAPTER FIVE: SUMMARY, RECOMMENDATION AND CONCLUSION
In this study, we proposed that quality evaluation system and evaluation methods are important and students are made as the main object and multi-level fuzzy comprehensive simplify evaluation model that is suitable for teaching, Predicting students’ performance by tracking, analyzing and monitoring the student progress and performance is established. In this context, this work proposes that a recommendation system based on data mining techniques should be put in place to help students take decisions on their academic itineraries. More specifically, it provides support for the student to better choose how many and which course to enroll on, having it as a basis from the experience of the previous students with similar academic achievements. It is important to study and analyses educational data especially students’ performance.
Keywords—Data Mining, Education, Students Performance, information technology
1.1 BACKGROUND OF THE STUDY
With the development of computer technology and the wide application of database technology and the industry has accumulated a large amount of data which is stored in different forms. But discovering valuable information or knowledge to achieve for decision-making purposes becomes very difficult. Data mining technology is born at the right moment, which makes people have the ability to finally recognize the true value of the data (Feibeng, 2006).
In recent years, data mining technology is widely used in business decision-making, such as business management, production control, market analysis, engineering design and scientific exploration. However, the data mining technology in colleges, universities or in are higher educational system is few. Therefore, we can apply data mining technology to obtain valuable knowledge in our data and guide our student (Binhua and Rui, 2001; Hongdan, 2011).
Improvement and effect on applying data mining in student information system is an important research topic and people generally improved through questionnaires or evaluation, this process is generally achieved through teaching and examinations. (Yanli, 2010).
The student information system is designed using data mining techniques. Data mining is a process of collecting useful data from the dataset. Data mining which is also named as knowledge discovery. This is the process which is carried out for the extraction of useful information from the huge data sets. Data Mining is carried out step by step to get useful information from large data sets. Using data mining we can analyses data of years stored in the database to get the stats etc. For example if a company is checking their stats graph up and down charts like Google analytics, they use Data mining to process the data’s. Analyzing students’ data and information to classify students, or to create decision trees or association rules, to make better decisions or to enhance student’s performance is an interesting field of research, which mainly focuses on analyzing and understanding students’ educational data that indicates their educational performance, and generates specific rules, classifications, and predictions to help students in their future educational performance.
1.2 STATEMENT OF THE PROBLEM
Firstly, we must understand the problem we want to solve then analyzes it. The application target is to effectively get student related data and information, to easily analyses students records, to determine the purpose, requirements and importance, we applied data mining. Understanding the needs of students, we clearly define the problem to be solved, and to prepare high-quality system of data collection of student’s information’s and records and also keep tracks of correctly analyze mining results which provides useful information.
Secondly, as we all know, education is the backbone in the development of any nation, both socially and economically. The key to development is good education and information system. In our country, students face a lot of problems during their educational career. They are the most unguided due to their ignorance they can’t make better decision. Due to the large volume of data in educational databases student have problem in making the right decision in relation to their academic itinerary and most times staff have problems in compiling student records or searching for their data’s but by applying of data mining student records, data and information can be generated or accessed with just one search .
1.3 OBJECTIVES OF THE STUDY
To research on the application of data mining techniques in student’s information system. The main goal is to develop and evaluate the student information system by specific methodology for predictive and explorative data mining in student information and records. The methodology shall address the issues typical for data mining in student records, by defining the activities and the deliverables to tackle them. In addition, an evaluation model is needed to provide the compliance assessment to the methodology. In order to achieve this goal, the following objectives and corresponding tasks have been formulated:
1. To analyze the existing data mining application methodologies by investigating data mining as part of a knowledge discovery process model.
2. To propose a novel, specific to the student information system, data mining application methodology, which resolves the issues of the existing methodologies.
3. To evaluate the proposed data mining methodology in the student information records by creating the required student data, such as course of study, examinational records, student bio data and its processing methods.
4. To propose a multi-relational clustering method implementation for mining data in a multi-relational format.
1.4 SCOPE OF THE STUDY
Data mining is a powerful technology that can be best defined as the automated process of extracting useful knowledge and information including, patterns, associations. The knowledge discovered by data mining techniques would enable the higher learning institutions in divers ways not limited to making better decisions, having more advanced planning in directing students, predicting individual behaviors with higher accuracy, and enabling the institution to allocate resources and staff more effectively. It results in improving the effectiveness and efficiency of the processes
1.5 SIGNIFICANCE OF THE STUDY
These days, everywhere we go or everything we do is based on data. When a student is applying for admission data is been collected and generated, if a student visit an office data is continuously generated, if a student visit an hospital data is generated. But what kind of data is been generated each time, are those data useful or required each time or are they just for formality? Yes all the data are useful and important and No all the data are not useful but few are important. A data that is relevant for (Mr A.) myth not be relevant to (Mr B.) so for the organization all data are important but to are individual only few data are needed and that is where data mining comes in. So organization collect data and this data are very useful and it’s not for formality but to show evidence of the past and present and also use to predate the future by analyzing those data.
1.6 LIMITATIONS OF THE STUDY
This project had its challenges based on finding new and more effective ways to implement and applying data mining in a more advance ways to get more effective result on student information system and these has consumed lots of time, finance and now, a new experience and structure was born.
1.7 DEFINITION OF TERMS/ VARIABLES
Data Mining: Can be defined as “The nontrivial extraction of implicit, previously unknown, and potentially useful information from data, and “The science of extracting useful information from large data set or databases”. It involves sorting through large amounts of data and picking out relevant information.
System: an assembly of interrelated elements which we find interesting to study, it could be a process or machine.
Computer network: is a group of connected, communicating devices such as computers and printers.
Online: is the condition of being connected to a network of computer or other device.
Information Retrieval: The act of locating quantities of data stored in a Database and producing useful information from the data.
Internet: is composed of hundreds of thousands of interconnected networks.
Record: It is a unit of data representing a particular transaction or a basic element of a file consisting in turn a number of interrelated data elements.
Database: is a collection of data or file purpose to assist many users at the same time.
Database management system or DBMS: is software designed to assist in maintaining and utilizing large collections of database.
Artificial Intelligence: It is a branch of computer science that is dedicated to the study of the ways in which computers can be used to emulate or duplicate most human function.
Website: is a collection of web pages which have image and/or text for the purpose of passing information to the users.
Model: Is a pattern or mathematical/symbolic representation of real life System and or abstract system behaviors.
Server: is a process that provides requested services for clients.
Knowledge Base: Is an organized collection of declarative and procedural relationships that represents expertise in a focused area