Multi-layer fuzzy logic for welfare disbursement

• Main Authors: Zakaria, Noor Hidayah, Hassan, Rohayanti, Othman, Muhamad Razib, Asmuni @ Hasmuni, Hishammuddin
• Format: Conference or Workshop Item
• Published: 2015
• Subjects: TJ Mechanical engineering and machinery
• Online Access: http://eprints.utm.my/id/eprint/61719/; http://ieeemy.org/mysection/?p=2406
• Institution: Universiti Teknologi Malaysia

This study focus on the implementation of datadriven multi-layer fuzzy in welfare disbursement based on the only data source available which human expert knowledge. The proposed study is designed to determine the welfare candidate eligibility. This study highlights on welfare distribution to the new urban poor household which is categorized into three multidimensional classes namely, the needy, poor and non-poor. Firstly this study highlights on the establishment of the data-driven expert system which is the human expert knowledge in welfare and the experts’ analytical steps. The welfare data collected from households is analysed using descriptive statistics. The study demonstrates the accuracy of the analysis for welfare eligibility of new urban poor using data-driven multi-layer fuzzy inference system compared to the domain human experts.