Low-Cost Digital Decision Tools for Improving Traditional Rice Farming Practices in Indonesia Using a Simple Additive Weighting (SAW) Approach

Fransiska Elly Renni Susanti; Heni Ermewaningsih

doi:10.35568/abdimas.v9i2.7764

Authors

Fransiska Elly Renni Susanti Institut Teknologi Keling Kumang, Sekadau, Indonesia
Heni Ermewaningsih Institut Teknologi Keling Kumang, Sekadau, Indonesia

DOI:

https://doi.org/10.35568/abdimas.v9i2.7764

Keywords:

Decision Support System, Simple Additive Weighting (SAW), Digital Agriculture, Rice Cultivation

Abstract

Smallholder rice farming in Indonesia is still largely characterized by experience-based decision-making, often leading to inconsistencies in cultivation practices. This study aims to develop and evaluate a low-cost digital decision support tool based on Microsoft Excel using the Simple Additive Weighting (SAW) method. The study employed a Research and Development approach with a quasi-experimental pre–post design involving 30 rice farmers in Entabuk Village, West Kalimantan. The system integrates five key variables that is land size, crop age, growth stage, weather conditions, and rice variety, into a weighted scoring model that generates risk classifications and cultivation recommendations. Decision quality before and after system implementation was analyzed using a paired t-test. The results indicate a statistically significant improvement in decision consistency and quality (p < 0.05) after system use. The mean decision score increased substantially, accompanied by reduced variability among farmers. Usability evaluation also demonstrated high user acceptance, with an average score of 4.21 (84.3%). These findings demonstrate that integrating the SAW method into an accessible Excel-based platform provides a practical and affordable approach to supporting structured decision-making in smallholder rice farming.

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