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Journal : MEANS (Media Informasi Analisa dan Sistem)

Penerapan Algoritma Decision Tree Dalam Penentuan Karyawan Kontrak Aziz Alibasyah; Abdul Ajiz; Gifthera Dwilestari; Kaslani; Edi Wahyudin
MEANS (Media Informasi Analisa dan Sistem) Volume 7 Nomor 1
Publisher : LPPM UNIKA Santo Thomas Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (736.756 KB) | DOI: 10.54367/means.v7i1.1844

Abstract

The problem that arises at this time is a complicated evaluation (assessment) process, meaning that what often happens now is that contract employees who get promoted to permanent employees are only seen on one criterion, but the employee is not necessarily superior on several other criteria. but still get promotions for permanent employees. And there are several problems that exist today, namely the process of evaluating contract employees which is still subjective. Data mining using the decision tree method is widely used to deal with problems with large amounts of data. This decision tree method is a classification method that is widely used because its construction is relatively fast, the results of the model built are easy to understand and the prediction results are very strong so that they can assist in decision making. This study uses 4 criteria, namely Achievement, Ability, Personality and Results. Prediction results accuracy obtained is 91.54% with the following details. Prediction results are accepted and it turns out to be true, 72 data are accepted. Prediction Result Accepted and it turns out True Not Accepted for 14 Data. Prediction Results Not Accepted and it turns out True Accepted 1 Data. Prediction Results Not Accepted and in fact True Not Accepted Amounting to 91 Data.
Pada minimarket, produk merupakan bahan pokok yang akan dijual belikan. Produk di minimarket ini akan menentukan pengelompokkan data stok barang di Toko Toba. Dengan adanya masalah ini, perlu untuk menciptakan sistem baru menggunakan Rapidminer yang dapat Irfa Mulhimah Fauziah; Dita Rizki Amalia; Edi Wahyudin; Mulyawan; Kaslani
MEANS (Media Informasi Analisa dan Sistem) Volume 7 Nomor 2
Publisher : LPPM UNIKA Santo Thomas Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

In minimarkets, the product is a staple that will be sold and bought. The products in this minimarket will determine the grouping of stock data at the Toba Store. Given this problem, it is necessary to create a new system using Rapidminer that can group stock data at Toko Toba, which was carried out at the Toko Toba Sedong minimarket and carried out in November 2021-January 2022. This k-means algorithm will not be affected by the order of objects which has been used.  In stock management that is carried out inaccurately and carelessly will cause very high and uneconomical storage costs, because there can be vacancies or excess goods and certain types of items. This study aims to group stock data using Rapidminer at Toba Stores into 2 clusters. The method that will be used in this research is using the K-Means Clustering method. This research is also strongly supported by 1 data mining tool, namely Rapidminer. Data mining on Rapidminer tools for cluster 0 there are 15 items and the data contained in it, for cluster 1 there are 9 data contained in it.