KLASIFIKASI PENERIMA BANTUAN DARI KEPEMILIKAN KARTU PELAKU UTAMA SEKTOR KELAUTAN DAN PERIKANAN DENGAN METODE SUPPORT VECTOR MACHINE
DOI:
https://doi.org/10.23960/jitet.v12i3.4507Abstract Views: 228 File Views: 213
Abstract
Cards of Main Actors in the Maritime and Fisheries Sector (KUSUKA) is a card for key players in the marine and fisheries sector, plays a vital role in supporting the industry's growth. To enhance the effectiveness of aid distribution through KUSUKA, this study uses a Support Vector Machine (SVM) method in a web-based application for evaluation, considering factors such as income, ownership status, primary and additional professions, and business experience. Data is divided into training (320 samples) and testing (80 samples) sets with an 80:20 ratio. The developed model shows high classification accuracy: 90.299% for training data and 93.181% for testing data. The application classifies KUSUKA holders into two categories: 80% eligible and 20% not eligible for aid. The confusion matrix records 90.31% for training data and 88.75% for testing data. Precision is 88.65% for training data and 87.67% for testing data, while recall reaches 98.13% for training data and 100% for testing data. Income is the most influential factor in determining aid eligibility, followed by work experience and additional professions as supporting factors in the eligibility assessment process.
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