Pelatihan Python untuk Sistem Prediksi Hasil Tangkapan Ikan di Pulau Pasaran, Bandarlampung

Abstract

The Python training program for a fish catch prediction system in Pasaran Island, Bandarlampung, aims to enhance the efficiency and accuracy of fishery forecasts for local fishermen. Utilizing machine learning algorithms, the system processes environmental data such as sea surface temperature, chlorophyll levels, and weather conditions. This training introduces participants to Python basics, data processing, and the implementation of predictive algorithms like linear regression and artificial neural networks. Results from the training indicate an improvement in participants' understanding of predictive technology, directly supporting decision-making in fisheries activities. Furthermore, the application of this technology is expected to reduce reliance on less precise traditional methods. By integrating spatial and temporal data, this program delivers a prediction system that adapts to changing marine ecosystems, supporting sustainable fishery resource management. The study contributes to the coastal community's capacity to address challenges posed by climate change and marine economic dynamics.