Artificial Neural Networks for RTW Outcome Prediction in Malaysia’s Socso Program: A Semma-Based Predictive Analytics Study
by E. N. I. Hashim, I. L. Ismail, M. Z. A. Chek, Muhammad Syakir Asrulsani, Rinda Nariswari, Z. H. Zulkifli
Published: March 23, 2026 • DOI: 10.47772/IJRISS.2026.10200611
Abstract
Return-to-Work (RTW) programmes administered by the Social Security Organization of Malaysia (SOCSO) are critical in facilitating the reintegration of injured or ill employees into productive employment. However, accurately predicting rehabilitation outcomes remains challenging due to the complex and nonlinear interactions among demographic and employment-related factors. This study develops a predictive modelling framework using Artificial Neural Networks (ANN) to enhance outcome forecasting within SOCSO’s RTW programme.