Integration Sentiment Analysis and K-Means Clustering in Semeru Pine Forest Management - Solimun; Sumarminingsih, Eni; Mudjiono (Department of Informatics Universitas Islam Indonesia, 2026)
Forest-based tourism management requires integrated institutional and community involvement to ensure sustainability. Semeru Pine Forest in Sumberputih Village, Malang Regency, has significant tourism potential but has experienced a decline in management quality in recent years. This condition is reflected in rising public and visitor complaints about infrastructure, accessibility, and governance. This study aims to empirically examine patterns in public and visitor perceptions of the management of the Semeru Pine Forest. The research employs sentiment analysis of Google review data to extract key perceptual variables, followed by K-Means clustering. Survey data were collected from 200 respondents using a five-point Likert scale. The suitability of the data structure was assessed using Bartlett’s Sphericity Test prior to clustering. The sentiment analysis identified key variables including organizational management, community participation, and tourism sustainability. The K-Means analysis produced two distinct clusters representing different levels of management performance. The first cluster reflects lower perceptions of management quality, while the second cluster indicates relatively better management performance. These findings provide empirical evidence to support data-driven strategies for improving sustainable forest tourism management.