NLP-Based Decision Support System for PUV Management: Enhancing Services Through Passenger Feedback Analysis

Abstract

This paper presents the development and evaluation of an NLP-Based Decision Support System for Public Utility Vehicle (PUV) Management, focusing on enhancing services through passenger feedback analysis. The study addresses the need for improved public transportation quality in the Philippines, where PUVs play a vital role in daily commuting. The proposed system aims to digitize the passenger feedback process and utilize Natural Language Processing (NLP) techniques to provide decision support for PUV operators. Methodologically, the study follows a phased approach based on the System Development Life Cycle (SDLC). Developed primarily using PHP as the programming language, with Vanilla JS, Bootstrap, and jQuery for backend development and frontend technologies including HTML5, CSS3, and JavaScript (ES6) for creating an interactive user interface, the system caters to the needs of its different users. The evaluation process incorporates the ISO 25010 standard for evaluating systems, and with the participation of 43 respondents from the province of Iloilo, the evaluation results revealed an overall mean score of 4.34, indicating an "Excellent" level of system functionality, reliability, portability, usability, performance efficiency, security, compatibility, and maintainability. This implies that PUV operators and management can use the developed system.