DESIGNING A WEB-BASED INFORMATION SYSTEM FOR MEASURING SUSTAINABLE TOURISM PERFORMANCE IN KARST CAVE GEOTOURISM OF INDONESIA

Abstract

Karst cave geotourism in Indonesia faces serious threats due to uncontrolled tourism pressure on vulnerable ecosystems. The lack of a data-driven management system leads to environmental degradation, tourist safety risks, and a decline in destination quality. This research aims to design a digital information system to measure tourism performance sustainably, with a case study of Jomblang Cave in Yogyakarta, Indonesia. Its contribution is to present a digital solution to monitor aspects of safety, enjoyment, and support decision-making in sustainable tourism governance. This research uses mixed methods with quantitative and qualitative approaches, and develops an information system based on the Waterfall-type System Development Life Cycle (SDLC) model through the stages of analysis, design, and implementation. Analysis was conducted using Use Case Diagram (UCD), Entity Relationship Diagram (ERD), and Data Flow Diagram (DFD) to design a system that meets the needs. The system can automatically calculate geosite performance values using the Modified Geosite Assessment Model (M-GAM) method, including two additional variables, namely safety and enjoyment. The web-based Jomblang Cave tourist attraction performance measurement information system consists of a home page, a questionnaire, and an assessment matrix that allows users to provide assessments, while the admin and owner monitor the results based on automatically processed inputs. The implementation phase maps the data of 32 tourists and six experts into the M-GAM Matrix, and calculates the MV and AV values to determine the Z-index position. The system automatically generates evaluative recommendations based on the lowest scores and has performed as expected as an evaluation and decision-making tool in tourism management. This research presents a real-time and easily accessible system for measuring tourist attraction performance. The system generates MV 6.37 and AV 16.09, placing the Z-index at a medium level (Z22). The automated system detected major weaknesses in the Education (VSE = 1.82) and functionality (VFn = 2.87) factors, especially regarding cave protection and tourist safety. Automated recommendations allow managers to focus on improving critical areas and support strategic decisions for geotourism development.