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All Journal Jurnal Pengabdian pada Masyarakat Ilmu Pengetahuan dan Teknologi Terintegrasi Jurnal Akuntansi dan Ekonomi Bisnis Information Technology Education Journal
Dion Yanuarmawan
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Automotive Engineering Computer Science & IT Economics, Econometrics & Finance Education Electrical & Electronics Engineering

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FORCAS: A Least Squares-Based Forecasting Application for Business Sales Budgeting Bakhtiar, Yohan; Abidatul Izzah; Ahmad Saifi Athoillah; Dion Yanuarmawan; Wiwik Mukholafatul Farida; Dwi Rahma Fitriani
Information Technology Education Journal Vol. 5, No. 1, February (2026)
Publisher : Jurusan Teknik Informatika dan Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59562/intec.v5i1.266

Abstract

Purpose – This study aims to develop FORCAS (Forecasting Comprehensive Application for Sales), a universal forecasting application based on the Least Squares method to support business sales budgeting.  Design – The research employed a system development approach consisting of problem analysis, system design, algorithm implementation, and application testing. The Least Squares method was used to generate sales forecasts, while system validation was conducted through black box testing. User experience and usability were evaluated using the System Usability Scale (SUS) and User Experience Questionnaire (UEQ).  Findings – The results show that FORCAS successfully generates accurate sales forecasts consistent with manual Least Squares calculations. Black box testing confirmed that all system functions operated correctly. Usability evaluation yielded a SUS score of 71, indicating a Grade C (acceptable usability), while UEQ results showed an Excellent rating across pragmatic and hedonic dimensions. Research implications – In conclusion, FORCAS provides a practical and replicable forecasting tool that can be applied across various business contexts. The application is particularly beneficial for small and medium enterprises (SMEs) and accounting education, offering an accessible solution for systematic sales budgeting. Future development may include the integration of advanced forecasting models such as ARIMA and machine learning-based methods.  Originality – However, most existing forecasting systems are designed for specific cases and lack flexibility for broader business applications. This study develops FORCAS as a universal forecasting application to address this limitation.
Co-Authors Abidatul Izzah Ahmad Saifi Athoillah Auliya Dewi Oktari Dwi Rahma Fitriani Mochamad Alfan Yoga Ardian MUHAMMAD RAHARDYAN Wiwik Mukholafatul Farida Yohan Bakhtiar