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All Journal RISTEC : Research in Information Systems and Technology Jurnal Teknologi dan Informatika (JEDA) Jurnal Alih Teknologi Komputer (ALTEK) Jurnal Alih Teknologi Sistem Informasi (JATSI) Jurnal Pengabdian UMKM PENGAMATAN: Jurnal Pengabdian Masyarakat untuk Ilmu MIPA dan Terapannya
Sukri, Hamdan
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Agriculture, Biological Sciences & Forestry Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Languange, Linguistic, Communication & Media Mathematics

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Pelatihan Python untuk Sistem Prediksi Hasil Tangkapan Ikan di Pulau Pasaran, Bandarlampung Pramono, Doni Eko Hendro; Sukri, Hamdan; Purnomo, Rosyana Fitria; Hartanto, M Budi
PENGAMATAN: Jurnal Pengabdian Masyarakat untuk Ilmu MIPA dan Terapannya Vol 3 No 1 (2025): PENGAMATAN: Jurnal Pengabdian Masyarakat untuk Ilmu MIPA dan Terapannya
Publisher : Jurusan Matematika FMIPA Universitas Pattimura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/pengamatanv3i1p27-36

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.
Co-Authors Afriansyah, Dodi Arie Setya Putra Azahra, Nurfitriyana Brojonoto, Destroprani Budi Hartanto Fawa'ati, Teuku Muhammad Hartanto, M Budi Hendri, Romi Hendro Pramono, Doni Eko ikhwan, Ahmad Rosyana Fitria Purnomo Sugara, Fernando Aria Yodhi Yuniarthe