Pemanfaatan Metode Convolutional Neural Network (CNN) Dengan Arsitektur MobileNetV2 Untuk Penilaian Kelayakan Rumah
In the digitalization era, efforts to enhance efficiency and accuracy in assessing household eligibility for social assistance have become important. We plan to develop a household eligibility assessment system using convolutional neural network methods. Our system uses artificial intelligence to analyze uploaded house photos and provide eligibility assessments based on predefined criteria. The goal is to automate the assessment process, increase efficiency and accuracy, ensure social assistance is well-targeted, and reduce administrative workload. Through the implementation of this system, we hope to improve the effectiveness of social assistance and community development. The result of this research is a household eligibility assessment program that can be implemented in the future.
Authors
- Anggraini Puspita Sari (ORCID: https://orcid.org/0009-0008-4343-7882)
- Muhammad Rahman
- Ahmad Zidan
Institutions
- University of Pembangunan Nasional Veteran Jawa Timur (ID)
Publication Details
- Journal
- ALINIER Journal of Artificial Intelligence & Applications
- Published
- 2024-11-04
- DOI
- https://doi.org/10.36040/alinier.v5i2.11061
- Primary Topic
- Computer Science and Engineering
- Type
- article
- Field-Weighted Citation Impact
- 0.00