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All Journal METIK JURNAL TAMIKA: Jurnal Tugas Akhir Manajemen Informatika & Komputerisasi Akuntansi
SA'AD, MUHAMMAD IBNU
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Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Electrical & Electronics Engineering

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Penerapan Data Mining Dalam Menganalisis Pola Belanja Konsumen Menggunakan Market Basket Analysis Sarifmata Purnomo; Heny Pratiwi; Sa'ad, Muhammad Ibnu
METIK JURNAL (AKREDITASI SINTA 3) Vol. 7 No. 2 (2023): METIK Jurnal
Publisher : LPPM Universitas Mulia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47002/metik.v7i2.678

Abstract

Currently, almost every activity is related to data. in the business sector, daily sales transaction data stored in the database system will always increase and accumulate. The existing data is only used as an archive by the shop owner so that it has an impact on sales strategies that are not implemented well, even though the existing data can be processed into information to determine the layout of goods so that it has an impact on increasing the occurrence of impulse buying, increasing or maintaining turnover, and minimizing product waste. accumulate until it expires which can be detrimental to the shop.The aim of this research is to find consumer shopping patterns using Marker Basket Analysis. This research method is called market basket analysis or also called association rules, which is a data mining technique for finding patterns that often appear simultaneously in transaction data, so that it can be used as a method for finding information about what kinds of goods are frequently used. purchased by consumers simultaneously. The results of this research, based on data analysis using the Rapidminer application, found 25 associative relationships or rules with a lift ratio value of more than 1, these rules become a reference in determining the layout of goods. Providing recommendations for layout changes aims to make it easier for consumers to shop, increase the possibility of impulse buying by consumers, and maximize product display, thereby reducing the accumulation of goods in the Purnama Store Warehouse.
Sistem Pakar Berbasis Web untuk Diagnosis Penanganan Pasca Panen Kelapa Sawit Menggunakan Metode Naive Bayes Pratiwi, Heny; Sa'ad, Muhammad Ibnu; Zakaria, Muhammad Alamsyah
TAMIKA: Jurnal Tugas Akhir Manajemen Informatika & Komputerisasi Akuntansi Vol 4 No 2 (2024): TAMIKA: Jurnal Tugas Akhir Manajemen Informatika & Komputerisasi Akuntansi
Publisher : Universitas Methodist Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46880/tamika.Vol4No2.pp259-267

Abstract

This study aims to design a web-based Expert System that is able to diagnose post-harvest handling of oil palm using the Naive Bayes method. In addition, this study also aims to explore optimal harvesting and post-harvest handling management in order to produce high-quality oil yields. This study was conducted at PT Sawit Sukses Sejahtera, the location where the experts work. Data collection was carried out through interviews with experts related to post-harvest handling of oil palm fruit, as well as literature studies to obtain data relevant to the research topic. The Naive Bayes method is used based on the probability found in the post-harvest handling process of oil palm, while system development follows the ESDLC (Expert System Development Life Cycle) methodology, which is the basis for designing and developing expert systems.
Co-Authors Heny Pratiwi Pratiwi, Heny Sarifmata Purnomo Zakaria, Muhammad Alamsyah