<![CDATA[Evaluation of oil palm harvesters' performance at PTPN IV Regional 4 Solok Selatan Plantation is still conducted manually, resulting in delays in reporting and calculation errors that affect the accuracy of determining the best harvester. This study aims to design and develop a web-based Decision Support System (DSS) implementing the Simple Additive Weighting (SAW) method to provide efficient, objective, and transparent performance evaluations based on harvest production, attendance level, and harvest quality/loose fruit criteria. This research employed a quantitative approach using a system development method. Data were collected through observations and interviews at the research site. The system was developed using the prototype model with PHP programming language, MySQL database, and Bootstrap 5.3 framework. The SAW method was implemented through value normalization, criteria weighting, and weighted summation processes to generate preference scores for each harvester. The developed system successfully automated the calculation of harvester rankings based on three main criteria in real time. Functional testing showed that all modules operated according to the design, including daily data input, monthly evaluation, SAW calculations, ranking graph visualization, and PDF report export features. The implementation of a web-based DSS using the SAW method effectively replaced the manual process in determining the best harvester, resulting in more accurate, consistent, and accountable evaluations. Future development is recommended to include integration with digital attendance systems and the implementation of automatic weighting methods to improve the objectivity of criteria weight determination.]]>
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