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All Journal Journal of Big Data Analytic and Artificial Intelligence
M. Hafid
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Computer Science & IT

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Implementation of Data Mining for Sales Data Clustering Using K-Medoids Algorithm Kamila, Nurul Cahaya; Fitria, Fitria; M. Hafid
Journal of Big Data Analytic and Artificial Intelligence Vol 7 No 1 (2024): JBIDAI Juni 2024
Publisher : STMIK PPKIA Tarakanita Rahmawati

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.71302/jbidai.v7i1.39

Abstract

This study aims to assist a trinket shop in achieving its monthly sales targets by applying data mining techniques using the K-Medoids clustering method. The research was conducted in six main stages: (1) data collection, (2) data cleaning, (3) data mining implementation, (4) evaluation of clustering results using the Davies-Bouldin Index (DBI), (5) determination of the optimal number of clusters (best k), and (6) visualization of clustering results. The data used consists of three selected attributes out of six available attributes. The clustering process with the K-Medoids method produced varying clusters due to the random selection of centroids. Based on the DBI evaluation, the optimal number of clusters was found to be k=3, providing the best clustering results to support the shop's marketing strategies.
Implementasi Logika Fuzzy Mamdani dalam Menentukan Jumlah Pemesanan Produk pada PT Forisa Nusapersada Area Tarakan: Implementation of Mamdani's Fuzzy Logic in Determining the Number of Product Orders at PT Forisa Nusapersada Tarakan Rita Tri Wulandari; Ummi Syafiqoh; M. Hafid
Journal of Big Data Analytic and Artificial Intelligence Vol 6 No 1 (2023): JBIDAI Juni 2023
Publisher : STMIK PPKIA Tarakanita Rahmawati

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.71302/jbidai.v6i1.44

Abstract

PT Forisa Nusapersada, Tarakan is an industrial company engaged in the distribution and marketing of products. When ordering products from the head office, since the customer's product demand sometimes increases or decreases every month, it is sometimes necessary to repeat the order within a month, thus affecting the product inventory in the warehouse. This study applied Fuzzy Mamdani to determine the number of orders based on sales data, goods stock and incoming goods from March to August 2021. This method has 5 stages, fuzzy set formation, rule formation, implication function application, rule composition and defuzzification. The input variables were demand and supply, while the output was orders. The results showed that the determination of the value of the fuzzy set domain can affect the final results differently for each product variant. In this study, the value of the fuzzy set domain was from the minimum and maximum values of sales data, goods stock and incoming goods.
Co-Authors Fitria Fitria Kamila, Nurul Cahaya Rita Tri Wulandari Ummi Syafiqoh