Forecasting Honda Car Retail Sales Using the Seasonal Autoregressive Integrated Moving Average Method

This article discusses the forecasting of Honda car retail sales using the Seasonal Autoregressive Integrated Moving Average (SARIMA) method. The study aims to forecast Honda car retail sales for the upcoming year. Various SARIMA models have been tested to determine the best model, and the results show that the SARIMA (1,1,0)(1,1,1)¹² model provides the lowest Mean Absolute Percentage Error (MAPE) among all tested models, which is 17,74%. Therefore, this model was chosen for forecasting sales over the next 12 months. The forecast results are expected to assist management in making optimal decisions regarding stock and marketing, as well as significantly enhancing operational efficiency and customer satisfaction in the future.

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Publication Details

Journal
Journal Of Data Insights
Published
2025-06-30
DOI
https://doi.org/10.26714/jodi.v3i1.416
Primary Topic
Forecasting Techniques and Applications
Type
article
Field-Weighted Citation Impact
0.00
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article

Forecasting Honda Car Retail Sales Using the Seasonal Autoregressive Integrated Moving Average Method

Muhammad Haris, Ihsan Fathoni Amri, Lea Angelina, Alia Permata et al.
Journal Of Data Insights
Forecasting Techniques and Applications
article

Forecasting Honda Car Retail Sales Using the Seasonal Autoregressive Integrated Moving Average Method

Muhammad Haris, Ihsan Fathoni Amri, Lea Angelina, Alia Permata, Jesicha Arsusma, Firochul Masichah
article en

Abstract

This article discusses the forecasting of Honda car retail sales using the Seasonal Autoregressive Integrated Moving Average (SARIMA) method. The study aims to forecast Honda car retail sales for the upcoming year. Various SARIMA models have been tested to determine the best model, and the results show that the SARIMA (1,1,0)(1,1,1)¹² model provides the lowest Mean Absolute Percentage Error (MAPE) among all tested models, which is 17,74%. Therefore, this model was chosen for forecasting sales over the next 12 months. The forecast results are expected to assist management in making optimal decisions regarding stock and marketing, as well as significantly enhancing operational efficiency and customer satisfaction in the future.

Journal Of Data InsightsVol. 3(1)
Openalex Percentile: Top 82%
Forecasting Techniques and Applications
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