IMAGE CLASSIFICATION OF HOUSEHOLD BENEFICIARIES OF DIRECT CASH ASSISTANCE USING EFFICIENTNET IN DKI JAKARTA PROVINCE - Adam, Dzikri; Santoso, Hadi (Informatika, Universitas Jenderal Soedirman, 2024)
This study investigates the application of the EfficientNet architecture for image classification to determine eligible recipients of direct cash assistance among households in Jakarta Province. As government efforts to provide aid to citizens increase, it becomes essential to have a system that can accurately recognize and classify eligible populations. Misallocation of aid remains a prevalent issue, often leading to undeserving individuals receiving assistance, which has detrimental consequences. The primary focus is on leveraging deep learning, specifically EfficientNet, to address these challenges. The dataset used consists of house images categorized into two classes: