Published: 2025-07-01

Penerapan Data Mining Menggunakan Algoritma Single Moving Average pada Penjualan Mobil Honda

DOI: 10.35870/jtik.v9i3.3847

Tundo, Marcia Rizky Hamdala, Andi Saidah, Muhammad Nurdin
  • Tundo: , Sekolah Tinggi Ilmu Komputer Cipta Karya Informatika
  • Marcia Rizky Hamdala: Universitas 17 Agustus 1945 Jakarta image/svg+xml
  • Andi Saidah: Universitas 17 Agustus 1945 Jakarta image/svg+xml
  • Muhammad Nurdin: , Sekolah Tinggi Ilmu Pelayaran, Kota Jakarta Utara

Abstract

Data mining is a branch of artificial intelligence that is used to find patterns and information hidden in data. One of the common algorithms used in data mining is the Single Moving Average (SMA). The SMA algorithm can be used to analyze and predict trend data, such as sales, stocks, production, and so on. In this study, SMA will be used to provide forecasts on Honda car sales and find hidden patterns in them with the aim of finding out the dominant patterns in Honda car sales and preparing for all possible risks that will be obtained due to this forecasting system. The data used in this study is Honda car sales data from official Honda dealers, where data was collected as much as 90 data as a dataset, and 8 data as data to be tested from 2017 to 2023. The results of the study show that the SMA algorithm can be used to analyze Honda car sales data where the right order in this case is order 2 with a value obtained above 90% based on the results of calculations from MAPE and MSE. These results can be used by the Honda company to improve sales strategies and improve product quality in terms of inventory management.

Keywords

Data mining ; Single Moving Average Algorithm ; Forcast ; Honda car sales

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Article Information

This article has been peer-reviewed and published in the Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi). The content is available under the terms of the Creative Commons Attribution 4.0 International License.

  • Issue: Vol. 9 No. 3 (2025)

  • Section: Computer & Communication Science

  • Published: July 1, 2025

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