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Integrasi Ekosistem Pariwisata Pesona Semarsaga: Perspektif Demand-Supply melalui Official Statistics dan Big Data

1Badan Pusat Statistik Kota Malang, Malang, Indonesia

2Badan Pusat Statistik Provinsi Jawa Timur, Surabaya, Indonesia

3Badan Pusat Statistik Kota Batu, Batu, Indonesia

Open Access Copyright (c) 2025 Christiayu Natalia, Wahyu Razi Indrawan, FX Gugus Febri Putranto
Creative Commons License This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

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Abstract
Strengthening the tourism sector's contribution to the economy remains a challenge in promoting inclusive and sustainable growth. Moreover, in situations of economic slowdown and uncertainty, tourism as a non-primary commodity tends to be deprioritized by the public in favor of basic needs. This study aims to (1) analyze the demand side of the tourism sector through an analysis of tourists' willingness to pay in Central Java Province; and (2) analyze the supply side through reviews of destinations and supporting facilities in the Pesona Semarsaga area. The methods used are Tobit regression based on microdata from the March 2024 National Socioeconomic Survey (SUSENAS), and sentiment analysis of tourist reviews from Google Review big data. The results indicate that characteristics such as traveler type, gender, generation, regional classification, education, financial inclusion, and employment status significantly influence willingness to pay (WTP). Furthermore, sentiment toward tourist attractions tends to be positive, but positive sentiment toward supporting facilities remains below average. The novelty of this study lies in the integration of microeconomic analysis from national data with online review big data to understand the balance between regional tourism demand and supply. The implication is that these findings reinforce the consumer behavior model in the tourism economy and provide practical guidance for improving facilities and managing sustainable destinations.
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Keywords: Tourism; Official Statistics; Big Data; Tobit Regression; Sentiment Analysis

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Last update: 2026-01-21 17:02:44

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