Biofarmaka (medicinal plants) in Indonesia play a crucial role in the pharmaceutical industry's development, providing natural resources for drug research, and supporting the utilization of traditional herbal remedies for public health. This research aims to analyze the development of biofarmaka plant production in Indonesia through predictions. This is essential for strategic planning, resource management, and future pharmaceutical industry development, ensuring an adequate supply of raw materials and supporting sustainable growth in the bio-pharmaceutical sector. The research dataset comprises biofarmaka plant production data in Indonesia by plant type, from 2018 to 2022, obtained from the Indonesian Central Statistics Agency. The research employs the Resilient algorithm, a machine learning technique. Architectural models used include 3-5-1, 3-10-1, 3-15-1, and 3-20-1. Among the four models, the 3-5-1 model is selected as the best due to its higher accuracy of 100%, and a lower Mean Squared Error (MSE) of 0.0023021, indicating the successful application of the Resilient algorithm in predicting the development of biofarmaka plant production in Indonesia.
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