A Utilization of Convolutional Neural Network (CNN) Method with MobileNetV2 Architecture for Home Feasibility Assessment

Indonesia

Abstract

In the era of digitalization, efforts to improve efficiency and accuracy in the process of assessing home eligibility for social assistance are becoming increasingly important. We plan to develop a convolutional neural network home eligibility assessment system to address this issue. Our system uses artificial intelligence technology to automatically analyze uploaded photos of houses and provide an eligibility assessment based on predefined criteria. The goal is to automate the assessment process, improve efficiency and accuracy, ensure social assistance is well-targeted, and reduce administrative workload. Through the implementation of this system, we hope to positively contribute to improving the effectiveness of social assistance programs and community development. The result of this research is a home eligibility assessment program that is expected to be implemented in the field in the future.

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