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All Journal Bulletin of Computer Science Research KLIK: Kajian Ilmiah Informatika dan Komputer Bulletin of Information Technology (BIT)
Ismasari Nawangsih
Universitas Pelita Bangsa, Bekasi
Computer Science & IT

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Analisa Penjualan Produk Kosmetik Dengan Metode Algoritma K-Means Di Toko Erremy Ismasari Nawangsih
Bulletin of Information Technology (BIT) Vol 4 No 1: Maret 2023
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bit.v4i1.468

Abstract

Applying data mining to analyze sales patterns of goods using the k-means algorithm method at the Erremy Shop. Availability of goods, stock of goods and completeness of goods in a shop is a very important element. So that the management process to regulate the availability of inventory is needed to avoid the accumulation of the same goods and is less desirable to customers. This research aims to determine buyer interest in a product so that we can ensure the supply and availability of products that are selling well or not selling well. The benefit of this research is to prevent product stockouts and accumulation of unsold products. The method used in product grouping uses the K-Means Clustering method so that the best-selling and less-selling products can be identified. Product data is grouped based on the similarity of the data so that data with the same value will be in one cluster. With the existence of product stock clusters with each level of stock movement owned, this allows it to be used as a reference in predicting the supply of products according to their needs. The tests carried out in this study were using black box testing.
Sistem Pembayaran SPP pada SMK Berbasis Web Menggunakan Metode Waterfall Agung Alfisyakhrin; Ismasari Nawangsih; Ikhsan Romli
KLIK: Kajian Ilmiah Informatika dan Komputer Vol. 4 No. 2 (2023): Oktober 2023
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/klik.v4i2.1315

Abstract

The development of a web-based tuition fee payment system at SMK Global Mulia is relevant for enhancing administrative efficiency and accuracy. The Waterfall method is employed in this development for a structured approach. SMK Global Mulia Vocational High School faces challenges in tuition fee administration. Manual methods are prone to errors and time-consuming. To address these issues, technology is leveraged by developing a web-based Tuition Fee Payment System. The Waterfall method is used for system analysis, design, implementation, testing, and maintenance. This research focuses on implementing a web-based Tuition Fee Payment Information System using the Waterfall method at SMK Global Mulia. The expected outcome is a positive contribution to similar system development in other educational institutions and resolving tuition fee administration issues at SMK Global Mulia. In this development, the system utilizes the Waterfall method with steps including analysis, design, implementation, testing, and maintenance. The system facilitates the finance department in student payment input and processing. The implementation of the Tuition Fee Payment Information System at SMK Global Mulia demonstrates effectiveness and efficiency in the payment process and student data retrieval. This reduces complexity in generating daily and periodical summaries, while expediting services to students
Implementasi Algoritma K-Means Pada Sistem Persediaan Barang Achsyanul Khaliq; Ismasari Nawangsih; Annisa Maulana Majid
Bulletin of Computer Science Research Vol. 6 No. 2 (2026): February 2026
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bulletincsr.v6i2.1017

Abstract

Inventory is an important component in a company's operational activities, especially in the trade sector, because it directly affects the smoothness of sales and the level of customer satisfaction. Unstructured inventory management can lead to stockpiling of goods, stock shortages, and inappropriate decision making. Maisa Building Materials Store located in Semerap, Kerinci Regency, Jambi, currently still records inventory manually, so the shop owner has difficulty in identifying items with high and low sales levels. This study aims to implement the K-Means Clustering algorithm in grouping inventory based on sales levels to support more effective and efficient stock management. The research method used is data mining with the stages of data collection, preprocessing, manual calculation of the K-Means algorithm, and implementation using RapidMiner software. The analyzed data amounted to 507 inventory items that have gone through a data cleaning process so that they are suitable for use in grouping. Grouping is done with two clusters, namely a cluster of goods with a low sales level and a cluster of goods with a high sales level. The results of the study indicate that 494 items, or 97.44 percent, fall into the low-sales cluster, while 13 items, or 2.56 percent, fall into the high-sales cluster. These results indicate that most products have relatively low sales turnover, while only a small proportion contribute significantly to total store sales. The information generated from this clustering process can be used as a basis for decision-making in inventory management, particularly in determining stocking priorities, stock control, and developing appropriate, data-driven marketing strategies.
Analisa Penjualan Produk Kosmetik Dengan Metode Algoritma K-Means Di Toko Erremy Ismasari Nawangsih
Bulletin of Information Technology (BIT) Vol 4 No 1: Maret 2023
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bit.v4i1.468

Abstract

Applying data mining to analyze sales patterns of goods using the k-means algorithm method at the Erremy Shop. Availability of goods, stock of goods and completeness of goods in a shop is a very important element. So that the management process to regulate the availability of inventory is needed to avoid the accumulation of the same goods and is less desirable to customers. This research aims to determine buyer interest in a product so that we can ensure the supply and availability of products that are selling well or not selling well. The benefit of this research is to prevent product stockouts and accumulation of unsold products. The method used in product grouping uses the K-Means Clustering method so that the best-selling and less-selling products can be identified. Product data is grouped based on the similarity of the data so that data with the same value will be in one cluster. With the existence of product stock clusters with each level of stock movement owned, this allows it to be used as a reference in predicting the supply of products according to their needs. The tests carried out in this study were using black box testing.
Co-Authors Achsyanul Khaliq Agung Alfisyakhrin Annisa Maulana Majid Ikhsan Romli