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All Journal Journal of Big Data Analytic and Artificial Intelligence
Risma Sakila
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Computer Science & IT

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Penerapan Algoritma Hash Based untuk Analisa Pola Penjualan Obat pada Apotek Permata Tarakan Sahira Reggina Putri; Fitria, Fitria; Risma Sakila
Journal of Big Data Analytic and Artificial Intelligence Vol 8 No 1 (2025): JBIDAI Juni 2025
Publisher : STMIK PPKIA Tarakanita Rahmawati

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.71302/jbidai.v8i1.68

Abstract

In an era of increasingly intense business competition, entrepreneurs in the healthcare sector, such as pharmacies, are required to optimize the use of transaction data. Apotek Permata Sejahtera has experienced a daily increase in sales transaction volume, resulting in an accumulation of data without further analysis. Therefore, a method is needed to identify associations between pharmaceutical products that are frequently purchased together by customers to support sales strategies and product arrangement. This study applies the Hash-Based algorithm to discover association patterns from drug sales transaction data between February and September 2024. The research stages include tabular data construction, determination of minimum support, hash address computation, calculation of minimum confidence, confidence evaluation, and formulation of association rules. The results show that the maximum itemset combination meeting the minimum support threshold of 40% reaches only up to the 5-itemset level, with a single final combination. From the 41 combinations that met the support criteria, 37 rules were identified with a minimum confidence of 80%, indicating strong relationships among pharmaceutical products. These findings offer practical contributions to sales strategy planning, inventory management, and product layout optimization in pharmacies to enhance operational efficiency and customer satisfaction
Implementasi Association Rule Mining pada Penentuan Pola Tata Letak Barang Menggunakan Metode Frequent Pattern Growth Virra Ayu Andira; Fitria, Fitria; Lies Hartono; Risma Sakila
Journal of Big Data Analytic and Artificial Intelligence Vol 8 No 2 (2025): JBIDAI Desember 2025
Publisher : STMIK PPKIA Tarakanita Rahmawati

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.71302/jbidai.v8i2.72

Abstract

CV. HKA (CV. Harapan Kaltim Abadi) is a distributor that sells several skin care, hair care, perfume, deodorant and baby care products, which will be distributed to customers. CV. HKA does not yet have a layout pattern for goods in the warehouse so that the storage of goods in the warehouse is irregular. Arranging the layout pattern of goods is needed to speed up the helper's performance so that it can shorten time and make it easier to pick up goods. Therefore, we need a system that can help determine item layout patterns by applying data mining. Association rules are used to search and find relationships between items in a dataset. The application of data mining with association rules aims to find information on items that are related to each other in the form of rules. Frequent Pattern-Growth (FP-Growth) is a method that can be used to determine the data set that appears most frequently (frequent item set) in a data set. This method aims to determine the layout decisions often taken by the helper. The results of the application using the FP-Growth method are rules that explain the helper's tendency to take goods simultaneously. These rules will determine the placement of goods in the warehouse. Based on the analysis system that has been created, it produces 10 rules from a combination of 2 items with the highest confidence value of 0.63, namely the Caplang brand item MKP and the Mandom brand item MR so that the two brands can be recommended to be placed close together. Apart from that, the resulting lift ratio value is more than 1, namely 1.21, the higher the lift ratio value, the stronger the resulting association rule.
Co-Authors Fitria Fitria Lies Hartono Sahira Reggina Putri Virra Ayu Andira