ADASYN-Based Multiclass Support Vector Machine for Village Development Index Classification in North Maluku Province: Support Vector Machine Multikelas Berbasis ADASYN untuk Klasifikasi Indeks Pembangunan Desa di Provinsi Maluku Utara - Tiani Wahyu Utami; Lea Angelina; Saeful Amri (Department of Sains Data UNIMUS Universitas Muhammadiyah Semarang, 2026)
Class imbalance is a significant constraint that can diminish the performance of classification models. This study implements the integration of Adaptive Synthetic Sampling (ADASYN) and Multiclass Support Vector Machine (SVM) to classify the 2024 Village Development Index (IDM) in North Maluku Province. The dataset comprises 684 villages, utilizing the Social Resilience Index (IKS), Economic Resilience Index (IKE), and Environmental Resilience Index (IKL) as predictor variables. The data was partitioned using a ratio of 80% for training and 20% for testing. An extreme imbalance was identified in the