Article Per Year (5 Year)
p-Index From 2020 - 2025
0.23
P-Index
This Author published in this journals
All Journal Journal of Informatics and Information Security
Imam Zaenuddin
Unknown Affiliation
Computer Science & IT

Published : 1 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search

 1 
Prediksi Barang Sering dan Jarang Terjual Dengan Menggunakan Algorithma K-Mean Clustering (Studi Kasus Toko Bina Mulia) Muhammad khaerudin; Imam Zaenuddin; Tukino
Journal of Informatic and Information Security Vol. 3 No. 1 (2022): Juni 2022
Publisher : Program Studi Teknik Informatika, Fakultas Teknik Universitas Bhayangkara Jakarta Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31599/72dwrc41

Abstract

The rapid increase in the population in the buffer zone of the capital city has an effect on the lifestyle of the people in the area, including in the Bekasi district. Likewise, the growth of small and medium community businesses, one of which is the Bina Mulia cooperative shop. This study was made to determine which types of goods are often sold and which types of goods arerarely sold. The algorithm used is K-Means Clustering, where data grouped based on the same characteristics will be included in the same group and the data sets entered into the groups do not overlap. The information displayed is in the form of groups of product names and the amount sold in one week for two months, namely April and May as a sample. The results of this study will help the store in analyzing which types of goods are often sold and which are rarely sold. The software used to help this grouping is Rapid Miner.
Co-Authors Muhammad Khaerudin tukino, tukino