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All Journal Jurnal Ilmiah Ilmu Komputer Banthayo Lo Komputer (BALOK)
Iftinan Inayah Mohamad
Universitas Ichsan Gorontalo
Computer Science & IT

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Penerapan Metode K-Means Untuk Clustering Penjualan Suku Cadang Kendaraan Viar (Studi Kasus: CV. Gotama Viar Gorontalo) Iftinan Inayah Mohamad; Irvan Abraham Salihi; Kartika Chandra Pelangi
Jurnal Ilmiah Ilmu Komputer Banthayo Lo Komputer Vol 2 No 1 (2023): Edisi Mei 2023
Publisher : Teknik Informatika Fakultas Ilmu Komputer Universitas Ichsan Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37195/balok.v1i2.399

Abstract

Until now motorcycles are still one of the most widely used means of transportation by Indonesian people. One of the authorized VIAR dealers in Sulawesi is CV Gotama VIAR Gorontalo. The company sells several VIAR-branded motorcycles and some genuine spare parts. There are stock-outs in several types of VIAR vehicle spare parts that are sold because many consumers buy them. There is a stacking of stock of other types of VIAR vehicle spare parts in the warehouse because they are not well sold. It is caused by the company experiencing confusion in determining what types of spare parts are more and less in-demand. The purpose of this study is to group several types of vehicle spare parts that are more and less in demand. The K-Means method is one of the methods in partitional clustering which works in grouping large data by dividing the data into one or more clusters. Based on the results of this study, it can be concluded that the results obtained explain that there are 373 types of goods categorized as more in-demand and 7 types of goods categorized as less in-demand. The system created can obtain a system that can classify spare parts sales data using the K-Means method which is reliable when applied.
Co-Authors Irvan A. Salihi Kartika Chandra Pelangi