Forecast of Muslimah fashion trends in Caca's company / Muhammad Saifullah Mohd Taip

Mohd Taip, Muhammad Saifullah (2023) Forecast of Muslimah fashion trends in Caca's company / Muhammad Saifullah Mohd Taip. [Student Project] (Submitted)

Abstract

Alhamdulillah, thanks to Allah, nearly all businesses now require business intelligence technologies in the quickly expanding globalisation era. The development of the best practical strategy by a corporation depends on business intelligence. caca company that provides different types of Muslim clothes. This store is facing some problems due to lack of methods predict their sales, so stores can overstock certain products leading to loss to the company, problems like this occur when the management cannot make a budget exact amount. This predictive analysis is carried out to learn future predictions about the classification of each outfit, its colour, and its size, and the project begins with the study's first data collection and exploration before putting data mining activities into practise. In this study, researchers measured weekly sales pattern performance accuracy findings using two different methodologies. There are roughly 2068 data collected from May to September 2022. In this scenario, it will lower expenses, particularly for product production, utilities, and maintenance. By putting the approach into practise, it will assist the management team in making the fundamental decision to develop the product in order to avoid losses. Researchers are using CRISP-DM as their method for finishing the current project. These findings will be displayed on the execution dashboard. The results showed that the decision tree algorithm had a higher accuracy of 100% for category prediction, 47% for colour prediction, and 65% for size prediction, while the random forest algorithm had a higher accuracy of 100% for category prediction, 85% for colour prediction, and 91% for size prediction. The dashboard was created to make it simple for people to understand
trends. In conclusion, BI may assist businesses in locating and fixing issues.

Metadata

Item Type: Student Project
Creators:
Creators
Email / ID Num.
Mohd Taip, Muhammad Saifullah
2020973575
Contributors:
Contribution
Name
Email / ID Num.
Thesis advisor
Ghazali, Ahmad Faiz
UNSPECIFIED
Subjects: Q Science > QA Mathematics > Evolutionary programming (Computer science). Genetic algorithms
Q Science > QA Mathematics > Instruments and machines > Electronic Computers. Computer Science > Data mining
Divisions: Universiti Teknologi MARA, Terengganu > Kuala Terengganu Campus > Faculty of Computer and Mathematical Sciences
Programme: Bachelor of Information Technology (Hons.) Business Computing
Keywords: Business Intelligence Technologies ; Muslimah Fashion
Date: 2023
URI: https://ir.uitm.edu.my/id/eprint/82325
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