Two-Stage Entropy-Topsis Model For Hotel And Ecotourism Destination Selection in Bitung, North Sulawesi, Indonesia

Cyndrika Rany Philipus; Sanriomi Sintaro; Ricardo Gianluigi  Tindi; Bidadari Yuritza Destilasilika

doi:10.58602/chain.v4i2.247

Cyndrika Rany Philipus Universitas Sam Ratulangi
Sanriomi Sintaro Universitas Sam Ratulangi
Ricardo Gianluigi Tindi Universitas Sam Ratulangi
Bidadari Yuritza Destilasilika Universitas Sam Ratulangi

DOI: https://doi.org/10.58602/chain.v4i2.247

Keywords: Decision Support System, Ecotourism, Entropy, Hotel selection, TOPSIS

Abstract

This study develops a Two-Stage Entropy-TOPSIS model for hotel and ecotourism destination selection in Bitung, North Sulawesi, Indonesia. The model reflects a realistic tourist decision process, where tourists first select a hotel from the airport and then choose ecotourism destinations from the selected hotel as the starting point. Data were collected from Google Maps, including rating, number of reviews, distance, travel time, hotel facility score, and ecotourism suitability score. In the first stage, eight hotel alternatives were evaluated based on Google Maps rating, number of reviews, distance from Sam Ratulangi Airport, travel time from the airport, and facility score. The Entropy method was used to determine objective criteria weights, while TOPSIS was applied to rank alternatives. The results showed that favehotel Bitung ranked first with a preference value of 0.9999 and was selected as the origin point for the second stage. In the second stage, ecotourism destinations were evaluated using the selected hotel as the starting point. The main calculation included destinations with complete road-based accessibility data. The results showed that Kebun Binatang Tandurusa ranked first with a preference value of 0.9989, followed by Batuangus Beach, Pantai Tanjung Merah, and Pantai Lilang. These findings indicate that the proposed model can provide structured, sequential, and data-driven recommendations for tourism decision-making based on Google Maps data

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