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Journal : Media Wisata

Override Parade: Isu-Isupariwisata Berkelanjutan pada Destinasi Kepulauan di Indonesia Pitanatri, Putu Diah Sastri
JURNAL MEDIA WISATA: Wahana Informasi Pariwisata Vol 17, No 2 (2019): Media Wisata
Publisher : Sekolah Tinggi Pariwisata AMPTA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36276/mws.v17i2.314

Abstract

Pariwisata saat ini memiliki masalah; relatif kecanduan pertumbuhan, yang tidak sesuai dengan tujuan keberlanjutan.Meskipun selama lebih dari tiga decade pariwisata berkelanjutan terus didengungkan sebagai bentuk ideal dari pariwisata; otoritas pariwisata di seluruh dunia tetap mempromosikan aspek-aspek pertumbuhan meskipun keterbatasan ekologis dan social telah menjadi isu strategis di banyak negara.Selain itu yang menjadi permasalahan kemudian, pariwisata seringkali dikaitkan dengan berbagai isu yang relative memiliki spectrum yang jauh dari pariwisata itu sendiri. Dengan melakukan studi literatur dari 67 artikel baik dari prosiding, jurnal nasional dan internasional, buku, serta laporan dari lembaga nasional dan internasional, artikel ini melihat bagaimana sebenarnya esensi dasar dari permasalahan utama sector ini di Indonesiaadalah overtourismdan tourism leakage.Karena itu tulisan ini berpendapat bahwa pariwisata harus dipahami dan dikelola dengan konteks keberlanjutan yang lebih luas.Rekomendasi dari tulisan ini diantaranya dibutuhkan riset-riset terbarukan seperti sustainable mobilities melalui big data sehingga beragam pendekatan untuk strategi pariwisata dapat dilihat secara real time dan menyasar langsung pada permasalahan pariwisata.
Override Parade: Isu-Isupariwisata Berkelanjutanpada Destinasi Kepulauan di Indonesia Putu Diah Sastri Pitanatri
Media Wisata Vol. 17 No. 2 (2019): Media Wisata
Publisher : Sekolah Tinggi Pariwisata AMPTA Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (442.817 KB) | DOI: 10.36276/mws.v17i2.174

Abstract

Tourism today has a problem. It is addicted to growth, which is incompatible withsustainability goals. Despite three decades of discussing pathways to sustainable tourism,tourism authorities worldwide has continued to promote tourism growth despite the ecologicaland social limits of living on a finite planet. Looking to it’s case to an island destination inIndonesia overtourism and tourism leakage are two major problems the industry arefacing. Therefore this article argues that tourism must be understood and managed with awider context of sustainability. Additionally, strategic approaches to transitioning to asufficiency approach to tourism and leisure is essential if sustainability is to be secured.Recommendations include Sustainable Mobilities, fostering diverse approaches to tourismstrategies for development and regulating and managing tourism. An upgraded reseach insustainable mobility through big data is recommended to further diverse tourism strategiesfrom approach, that be analyzed in real-time and directly targeted at tourism and destinationproblems
Big Data-based Sentiment Analysis on TripAdvisor Reviews Using Naïve Bayes Classification: A Case Study on Luxury Resort in Bali Duta, Putu Krisna Arya; Pitanatri, Putu Diah Sastri; Loanata, Cahyo Purnomo
Media Wisata Vol. 23 No. 1 (2025): Media Wisata
Publisher : Sekolah Tinggi Pariwisata AMPTA Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36276/mws.v23i1.864

Abstract

This research aims to analyze the sentiment of tourist reviews on the TripAdvisor platform towards a luxury resort in Bali by utilizing the Naïve Bayes classification method. The review data is analyzed to identify positive, negative, and neutral sentiments. Three variants of Naïve Bayes algorithm (GaussianNB, MultinomialNB, and BernoulliNB) were implemented and evaluated for performance. The results showed that the GaussianNB model provided the highest classification accuracy of 0.89. Further analysis revealed that the model effectively identified positive sentiments, but had challenges in classifying negative and neutral sentiments. Word cloud visualization confirmed the focus of positive reviews on aspects of accommodation, service and facilities, which can serve as a reference for the hospitality industry. This study concludes that big data-based sentiment analysis is an important tool for understanding customer perceptions, noting the need for further model development to improve the identification of minority sentiments.