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All Journal IJID (International Journal on Informatics for Development) Jurnal Teknologi Terapan Jurnal Abdi Insani Syntax: Journal of Software Engineering, Computer Science and Information Technology Media Jurnal Informatika Jurnal Pengabdian Masyarakat IPTEK Industrial Research Workshop and National Seminar Journal Of Artificial Intelligence And Software Engineering
Hayati, Hashri
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Journal : Media Jurnal Informatika

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DEVELOPMENT OF A SALES FORECASTING APPLICATION USING THE AUTOREGRESSIVE INTEGRATED MOVING AVERAGE METHOD WITH EXTERNAL INPUT (ARIMAX) Fauziyyah, Aulia Aziizah; Brahmana, Jonanda Pantas Agitha; Simatupang, Paulina Lestari; Soewono, Eddy Bambang; Hayati, Hashri
Media Jurnal Informatika Vol 17, No 2 (2025): Media Jurnal Informatika
Publisher : Teknik Informatika Universitas Suryakancana Cianjur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35194/mji.v17i2.5693

Abstract

that also operates in the culinary industry through the Pempek Duo brand. In the operational business of the culinary sector, PT Selada has developed the Mireta Point of Sale (POS) system as a transactional and reporting tool. However, the existing system has not been equipped with a transaction history data analysis feature to predict sales trends. This condition makes it difficult for the company to identify which products are best-selling and which ones are less popular. This development aims to create a sales forecasting feature based on the Autoregressive Integrated Moving Average with Exogenous Input (ARIMAX) method in the Mireta POS system. The ARIMAX model was chosen because it can incorporate external variables into the prediction calculations, in this case, holiday factors. The development was carried out using a waterfall approach which includes the stages of requirements analysis, system design, model implementation, and accuracy testing. The data used consists of the sales transaction history of Pempek Duo products from January 2022 to February 2023, which has been grouped by week, as well as holiday data as an external variable. The model evaluation results show that the best parameter combination is ARIMAX(1,0,2) with a Mean Absolute Error (MAE) value of 4.3333. This value indicates an average prediction error of 4 sales packages per week. With this feature, Mireta POS can provide more accurate sales predictions, making it easier for the company to identify the best-selling and least popular products.
Co-Authors Ade Hodijah Asri Maspupah Brahmana, Jonanda Pantas Agitha Djoko Cahyo Utomo Lieharyani Eddy Bambang Soewono Fauziyyah, Aulia Aziizah Firdaus, Lukmannul Hakim Gelar, Trisna Iwan Awaludin Muhammad Riza Alifi Muhammad Rizqi Sholahuddin Mulia, Syelvie Ira Ratna Putriadhinia, Salma Syawalan Sari, Aprianti Nanda Setijohatmo, Urip Teguh Simatupang, Paulina Lestari Syakrani, Nurjannah Transmissia Semiawan Wonoseto, Muhammad Galih Wulan, Sri Ratna