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All Journal Journal of Information Systems and Business Technology Journal of Information Technology and Informatics Engineering
Daviqia Fadel
Universitas Pamulang
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Engineering Library & Information Science

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Analisis Sistem Informasi Inventory Menggunakan Metode Waterfall Berbasis Web Daviqia Fadel; Deryl Iman Condro Baskoro
Journal of Information Systems and Business Technology Vol 1 No 1 (2025): Journal of Information Systems and Business Technology
Publisher : PT Jurnal Cendekia Indonesia

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Abstract

This research aims to develop a web-based inventory information system using the Waterfall method. This system is designed to overcome problems in stock management, such as inaccurate recording, late information, and lack of operational efficiency. The Waterfall method is used because of its systematic and structured development flow, starting from needs analysis to the maintenance stage. This system includes main features such as registration, login, management of goods data, categories, stocks, and creation of printable reports. Testing shows that all features run according to user needs and are free from bugs. With an easy-to-use interface and real-time access capabilities, this system is expected to improve the efficiency and accuracy of inventory management in the organization.
Implementasi Algoritma K-means Clustering Data Penjualan Pada Warung Sembako Isan Menggunakan Rapidminer Muhammad Azriel; Daviqia Fadel; Fajri Maulana Azzam Harahap; Irsad Fauzan; Muhammad Fadlan Jabbar; Maulana Fansyuri
Journal of Information Technology and Informatics Engineering Vol 1 No 1 (2025): Journal of Information Technology and Informatics Engineering (JITIE)
Publisher : PT Jurnal Cendekia Indonesi

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Abstract

This study aims to apply the K-Means Clustering algorithm with the help of RapidMiner software on sales data at Warung Sembako Isan. In managing small businesses such as grocery stores, processing sales data manually often faces various challenges, such as errors in recording and difficulties in identifying sales trends. Therefore, data mining techniques, especially clustering methods, are used to categorize products based on their sales capabilities. This process is carried out using RapidMiner, which allows analysis without the need for programming through a visual interface. The data were analyzed using the K-Means algorithm with parameter k = 3, which produces three categories: products with high potential, medium potential, and low potential. The results of this clustering make it easier for shop owners to understand product performance, develop storage strategies, and plan more efficient promotions. This study shows that the use of simple technology can improve operational efficiency and assist MSMEs in data-based decision making.
Co-Authors Deryl Iman Condro Baskoro Fajri Maulana Azzam Harahap Irsad Fauzan Maulana Fansyuri Muhammad Azriel Muhammad Fadlan Jabbar