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This Author published in this journals
All Journal International Journal of Management Science and Information Technology (IJMSIT)
Dwi Latifah Intan Ahadani
Institut Teknologi Sawit Indonesia
Decision Sciences, Operations Research & Management Economics, Econometrics & Finance

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Design and Build a Decision Support System for Assessing the Feasibility of Weather Conditions to Support the Implementation of Oil Palm Harvesting Using the Simple Additive Weighting (SAW) Method Dwi Latifah Intan Ahadani; Ritna Wahyuni; Raden Aris Sugianto
International Journal of Management Science and Information Technology Vol. 6 No. 2 (2026): July - December 2026
Publisher : Lembaga Komunitas Informasi Teknologi Aceh (KITA), Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijmsit.v6i2.8348

Abstract

Weather conditions play an important role in supporting the effectiveness and safety of oil palm harvesting activities. However, weather feasibility assessment is often conducted manually and subjectively, which may result in inconsistent decision-making. This study aims to design and develop a web-based Decision Support System (DSS) for assessing weather conditions to support oil palm harvesting using the Simple Additive Weighting (SAW) method. The research employed field research and a Prototype development model. Weather data were obtained from the Meteorology, Climatology, and Geophysical Agency (BMKG), while system requirements were identified through observation and literature studies. The assessment involved four criteria: rainfall, average temperature, humidity, and solar radiation intensity. Each criterion was converted into a rating scale and processed through the SAW stages, including decision matrix formation, normalization, weighting, preference value calculation, and ranking. The results indicate that the developed system can generate a structured ranking of weather conditions based on their feasibility for harvesting activities. The system also provides weather data management, criteria management, automated SAW calculations, recommendations, and ranking results. Black-box testing showed that the main system functions operated according to the specified requirements. Therefore, the proposed DSS can support faster, more objective, and systematic decision-making in oil palm harvesting activities.
Co-Authors Ritna Wahyuni