Prediction System for stock ordering by using Naïve Bayes technique / Muhammad Hafizuddin Rozi

This project is about a decision-making system that can help a restaurant named Mama Chop Papa Grill at Kota Bharu to decide ordering of the products. Decision making system has been a tool for business to help them to grow. As we know, good decision-making system can help companies to make a better...

Full description

Saved in:
Bibliographic Details
Main Author: Rozi, Muhammad Hafizuddin
Format: Thesis
Language:English
Published: 2015
Subjects:
Online Access:https://ir.uitm.edu.my/id/eprint/41570/1/41570.pdf
Tags: Add Tag
No Tags, Be the first to tag this record!
id my-uitm-ir.41570
record_format uketd_dc
spelling my-uitm-ir.415702024-04-04T00:13:01Z Prediction System for stock ordering by using Naïve Bayes technique / Muhammad Hafizuddin Rozi 2015 Rozi, Muhammad Hafizuddin Prediction analysis Electronic Computers. Computer Science Database management This project is about a decision-making system that can help a restaurant named Mama Chop Papa Grill at Kota Bharu to decide ordering of the products. Decision making system has been a tool for business to help them to grow. As we know, good decision-making system can help companies to make a better decision for their business process. Currently, there is not much decision-making system that is built for a fast food restaurant or any small restaurants.it is because not many small or medium restaurants have the urge to have a decision-making system. In order to make a good decision-making system for the restaurant, this project was proposed. To develop the system, first this research has identified the problem. After the problems were identifies, objectives were created. A technique has been chosen to analyse the relation between stocks and sales as to make prediction for the restaurant. To develop the system, a methodology has been created as to make sure that this project can be done smoothly. The data was gathered from the owner of the restaurant and the data was from the month of January until December of 2014. After gathering the data, the data then was cleaned using techniques from data mining. After that, Naïve Bayes was implied as to extract the rules from the data. That rule that was extracted was then embedded into a prototype that was developed. The prototype was developed to show how the rules worked. Lastly, conclusion and recommendations of the project was provided in the last chapter of this thesis. Other researchers that want to continue this project can have an insight of what are the limitations that this project has faced before. 2015 Thesis https://ir.uitm.edu.my/id/eprint/41570/ https://ir.uitm.edu.my/id/eprint/41570/1/41570.pdf text en public degree Universiti Teknologi MARA, Cawangan Melaka Faculty of Computer and Mathematical Sciences Suhaimi, Nur Suhailayani
institution Universiti Teknologi MARA
collection UiTM Institutional Repository
language English
advisor Suhaimi, Nur Suhailayani
topic Prediction analysis
Prediction analysis
Database management
spellingShingle Prediction analysis
Prediction analysis
Database management
Rozi, Muhammad Hafizuddin
Prediction System for stock ordering by using Naïve Bayes technique / Muhammad Hafizuddin Rozi
description This project is about a decision-making system that can help a restaurant named Mama Chop Papa Grill at Kota Bharu to decide ordering of the products. Decision making system has been a tool for business to help them to grow. As we know, good decision-making system can help companies to make a better decision for their business process. Currently, there is not much decision-making system that is built for a fast food restaurant or any small restaurants.it is because not many small or medium restaurants have the urge to have a decision-making system. In order to make a good decision-making system for the restaurant, this project was proposed. To develop the system, first this research has identified the problem. After the problems were identifies, objectives were created. A technique has been chosen to analyse the relation between stocks and sales as to make prediction for the restaurant. To develop the system, a methodology has been created as to make sure that this project can be done smoothly. The data was gathered from the owner of the restaurant and the data was from the month of January until December of 2014. After gathering the data, the data then was cleaned using techniques from data mining. After that, Naïve Bayes was implied as to extract the rules from the data. That rule that was extracted was then embedded into a prototype that was developed. The prototype was developed to show how the rules worked. Lastly, conclusion and recommendations of the project was provided in the last chapter of this thesis. Other researchers that want to continue this project can have an insight of what are the limitations that this project has faced before.
format Thesis
qualification_level Bachelor degree
author Rozi, Muhammad Hafizuddin
author_facet Rozi, Muhammad Hafizuddin
author_sort Rozi, Muhammad Hafizuddin
title Prediction System for stock ordering by using Naïve Bayes technique / Muhammad Hafizuddin Rozi
title_short Prediction System for stock ordering by using Naïve Bayes technique / Muhammad Hafizuddin Rozi
title_full Prediction System for stock ordering by using Naïve Bayes technique / Muhammad Hafizuddin Rozi
title_fullStr Prediction System for stock ordering by using Naïve Bayes technique / Muhammad Hafizuddin Rozi
title_full_unstemmed Prediction System for stock ordering by using Naïve Bayes technique / Muhammad Hafizuddin Rozi
title_sort prediction system for stock ordering by using naïve bayes technique / muhammad hafizuddin rozi
granting_institution Universiti Teknologi MARA, Cawangan Melaka
granting_department Faculty of Computer and Mathematical Sciences
publishDate 2015
url https://ir.uitm.edu.my/id/eprint/41570/1/41570.pdf
_version_ 1804889635762995200