DECISION SUPPORT SYSTEMS CERDAS UNTUK PEMILIHAN BIBIT CENGKEH UNGGUL DALAM KONSEP SMART AGRICULTURE

The recent development of artificial intelligence (AI) technology has encouraged the use of intelligent systems in various sectors, including agriculture. One of the challenges faced by clove farmers is determining superior seeds with optimal growth potential. Selecting appropriate seeds is crucial because it directly impacts productivity and plant resilience to environmental conditions. Based on this, this research focuses on developing an intelligent Decision Support System (DSS) to assist in the selection of superior clove seeds by implementing the Simple Additive Weighting (SAW) method integrated into the Smart Agriculture concept. In this system, the decision-making process is based on several key criteria: pest infestation, growing medium moisture, seedling age, leaf color, leaf number, stem diameter, and seedling height. Each criterion is assigned a specific weight according to its influence on seedling quality. The SAW method is used to obtain preference scores for each seedling through data normalization and calculation of total weights. From these results, seedling number 10 obtained the highest score of 0.96, thus it is recommended as the best superior clove seedling (ranked 1). Furthermore, seedling number 13 with a score of 0.89 is ranked second, and seedling number 11 with a score of 0.88 is ranked third.