This study aims to develop a web-based decision support system using the Multi-Attribute Utility Theory (MAUT) algorithm to assess land suitability for porang cultivation. The system is designed to assist farmers and land developers in selecting optimal planting sites. The research methodology includes problem identification, primary data collection through field surveys, determination of criteria and weights based on land characteristics, and the implementation of the MAUT algorithm to generate land recommendations. The five main criteria considered are soil texture, altitude, temperature, soil pH, and shading level. The results indicate that the three tested land alternatives achieved suitability levels of 86.67%, 75.57%, and 73.33%, respectively. Based on the suitability threshold of ≥70%, all land alternatives are deemed suitable for porang cultivation. These findings demonstrate the effectiveness of MAUT in supporting data-driven decision-making in the agricultural sector. Furthermore, this approach can be replicated for other commodities and further enhanced through the integration of spatial mapping and financial benefit analysis.
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