Analisis Akar Permasalahan Kepuasan Tamu Hotel Savana Berdasarkan Sentimen Negatif
Kata Kunci:
analisis sentimen, Root Cause Analysis (RCA), hotel savana, IndoBERTAbstrak
Industri perhotelan di Indonesia termasuk di Kota Malang menghadapi persaingan ketat sehingga penting bagi hotel-hotel untuk memanfaatkan ulasan online agar bisa menjaga kualitas layanannya, salah satunya Hotel Savana. Ulasan online yang diberikan oleh para pengunjung sangat bermanfaat bagi calon pengunjung dan pihak hotel sendiri. Ulasan online berguna bagi pihak hotel karena pihak hotel dapat memanfaatkannya sebagai bahan pertimbangan pembuatan kebijakan, peraturan, dan keputusan. Penelitian ini menganalisis sentimen ulasan tamu menggunakan algoritma IndoBERT untuk mengetahui persepsi publik terhadap Hotel Savana. Pengujian model IndoBERT mendapatkan nilai akurasi sebesar 98,3%, precision sebesar 97%, recall sebesar 96,3%, dan f1-score sebesar 96,7%. Ulasan bersentimen negatif 1 tahun terakhir (September 2023 – September 2024) selanjutnya dianalisis lebih lanjut untuk dicari akar masalahnya. Hasil analisis mengungkap tiga isu utama yang sering dikeluhkan oleh pengunjung Hotel Savana, yaitu aspek fasilitas, aspek pelayanan, dan aspek kamar. Ishikawa diagram dan five whys analysis diterapkan untuk menganalisis akar permasalahan dari setiap aspek.
Referensi
Al-Zwainy, F.M.S., Mohammed, I.A. & Varouqa, I.F., 2018. Diagnosing the Causes of Failure in the Construction Sector Using Root Cause Analysis Technique. Journal of Engineering, 2018, pp.1–12. doi:https://doi.org/10.1155/2018/1804053.
Badan Pusat Statistik (n.d.). Statistik Hotel dan Akomodasi Lainnya di Indonesia. [online] Badan Pusat Statistik. Tersedia di: https://webapi.bps.go.id/download.php?f=gen+J6tdEgmfX9UCwOKq3FJlSGFHRUd2WFNuaXlFc3hiaWd4TlJSZndyODZxTzdZLzVvMzUvQnBXaUw1ZlBidnljaUl6V3FsaDhJRGJIQnloRTNyVGtBWUpmV3ZuQyt3d2twMVIxTXl6cnNHeEtrczdROVlpQ1ZHaW9CSUxWaUJrbUplU2szM0FaZWpqSmxRRjZlaFNibjRqejhZYkZOVjhBTzQvRndrVXNEUHBscmJJSDlwcFRMUXJYbSs4V0ZIS3NQQm93bUw2U0V5cFZkWEQ1VWRxVUxIU3h5emRqbGdqUjA5UWFYZWQvMGZSTW5lMzFxbXY5ZVBBbUIweEluWWtVTjVFRTBBWG9WK2tDK2J2a3FTYzIzWFRQRE1OVXNWMkt6M1RHR2JDWWJtRUFyYlNnQ3RlVTBLZitVPQ==[Diakses 26 Agustus 2024].
Bricken, A., 2021. Does BERT Need Clean Data? Part 2: Classification. [online] Medium. Tersedia di: https://towardsdatascience.com/does-bert-need-clean-data-part-2-classification-d29adf9f745a [Diakses 16 Oktober 2024].
Devlin, J., Chang, M.W., Lee, K. & Toutanova, K., 2019. BERT: Pre-training of deep bidirectional transformers for language understanding. In Proceedings of the North American Chapter of the Association for Computational Linguistics.
Hanif, M.F., Wijoyo, S.H. & Putra, N. 2024. Klasifikasi Sentimen Ulasan Aplikasi Threads Berbasis Algoritma Naive Byaes dan Metode Root Cause Analysis. Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer, [online] 8(6). Tersedia di: https://j-ptiik.ub.ac.id/index.php/j-ptiik/article/view/13786 [Diakses 25 September 2024].
Hidayat, M. & Pramudita, R., 2024. Analisis Sentimen Terhadap Pembelajaran Secara Daring Pasca Pandemi Covid-19 Menggunakan Metode IndoBERT. INFORMATION MANAGEMENT FOR EDUCATORS AND PROFESSIONALS : Journal Of Information Management
Hotelsavana.com., 2024. Hotel Savana. [online] Tersedia di: https://www.hotelsavana.com/ [Diakses 29 Agustus 2024].
Imaduddin, H., A’la, F.Y. & Nugroho, Y.S., 2023. Sentiment Analysis in Indonesian Healthcare Applications using IndoBERT Approach. International journal of advanced computer science and applications/International journal of advanced computer science & applications, 14(8). doi:https://doi.org/10.14569/ijacsa.2023.0140813.
Koto, F., Lau, J.H., Baldwin, T. & Lete, H., 2020. IndoLEM and IndoBERT: A benchmark dataset and pre-trained language model for Indonesian NLP. arXiv preprint arXiv:2011.00677.
Nasukawa, T. & Yi, J., 2003. Sentiment Analysis: Capturing Favorability Using Natural Language Processing. In Proceedings of the 2nd International Conference on Knowledge Capture, pp.70-77.
Paget, S., 2024. Local Consumer Review Survey 2024: Trends, Behaviors, and Platforms Explored. [online] BrightLocal. Tersedia di: https://www.brightlocal.com/research/local-consumer-review-survey/#the-most-important-review-factors.
Pradhisa, K. & Fajriyah, R., 2024 “Analisis Sentimen Ulasan Pengguna E-commerce di Google Play Store Menggunakan Metode IndoBERT”, Building of Informatics, Technology and Science (BITS), 6(1), p. 92−104. doi: 10.47065/bits.v6i1.5247
Rohaeni, H. & Marwa, N., 2018. Kualitas pelayanan terhadap kepuasan pelanggan. Jurnal Ecodemica, 2(2), pp.312-318.
Sharma, H., Tandon, A., Kapur, P.K. & Aggarwal, A.G., 2019. Ranking hotels using aspect ratings based sentiment classification and interval-valued neutrosophic TOPSIS. International Journal of System Assurance Engineering and Management, 10(5), pp.973–983. doi:https://doi.org/10.1007/s13198-019-00827-4.
Vorley, G., 2008. Mini guide to root cause analysis. London: Quality Management & Training Limited.
Al-Zwainy, F.M.S., Mohammed, I.A. & Varouqa, I.F., 2018. Diagnosing the Causes of Failure in the Construction Sector Using Root Cause Analysis Technique. Journal of Engineering, 2018, pp.1–12. doi:https://doi.org/10.1155/2018/1804053.
Badan Pusat Statistik (n.d.). Statistik Hotel dan Akomodasi Lainnya di Indonesia. [online] Badan Pusat Statistik. Tersedia di: https://webapi.bps.go.id/download.php?f=gen+J6tdEgmfX9UCwOKq3FJlSGFHRUd2WFNuaXlFc3hiaWd4TlJSZndyODZxTzdZLzVvMzUvQnBXaUw1ZlBidnljaUl6V3FsaDhJRGJIQnloRTNyVGtBWUpmV3ZuQyt3d2twMVIxTXl6cnNHeEtrczdROVlpQ1ZHaW9CSUxWaUJrbUplU2szM0FaZWpqSmxRRjZlaFNibjRqejhZYkZOVjhBTzQvRndrVXNEUHBscmJJSDlwcFRMUXJYbSs4V0ZIS3NQQm93bUw2U0V5cFZkWEQ1VWRxVUxIU3h5emRqbGdqUjA5UWFYZWQvMGZSTW5lMzFxbXY5ZVBBbUIweEluWWtVTjVFRTBBWG9WK2tDK2J2a3FTYzIzWFRQRE1OVXNWMkt6M1RHR2JDWWJtRUFyYlNnQ3RlVTBLZitVPQ==[Diakses 26 Agustus 2024].
Bricken, A., 2021. Does BERT Need Clean Data? Part 2: Classification. [online] Medium. Tersedia di: https://towardsdatascience.com/does-bert-need-clean-data-part-2-classification-d29adf9f745a [Diakses 16 Oktober 2024].
Devlin, J., Chang, M.W., Lee, K. & Toutanova, K., 2019. BERT: Pre-training of deep bidirectional transformers for language understanding. In Proceedings of the North American Chapter of the Association for Computational Linguistics.
Hanif, M.F., Wijoyo, S.H. & Putra, N. 2024. Klasifikasi Sentimen Ulasan Aplikasi Threads Berbasis Algoritma Naive Byaes dan Metode Root Cause Analysis. Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer, [online] 8(6). Tersedia di: https://j-ptiik.ub.ac.id/index.php/j-ptiik/article/view/13786 [Diakses 25 September 2024].
Hidayat, M. & Pramudita, R., 2024. Analisis Sentimen Terhadap Pembelajaran Secara Daring Pasca Pandemi Covid-19 Menggunakan Metode IndoBERT. INFORMATION MANAGEMENT FOR EDUCATORS AND PROFESSIONALS : Journal Of Information Management
Hotelsavana.com., 2024. Hotel Savana. [online] Tersedia di: https://www.hotelsavana.com/ [Diakses 29 Agustus 2024].
Imaduddin, H., A’la, F.Y. & Nugroho, Y.S., 2023. Sentiment Analysis in Indonesian Healthcare Applications using IndoBERT Approach. International journal of advanced computer science and applications/International journal of advanced computer science & applications, 14(8). doi:https://doi.org/10.14569/ijacsa.2023.0140813.
Koto, F., Lau, J.H., Baldwin, T. & Lete, H., 2020. IndoLEM and IndoBERT: A benchmark dataset and pre-trained language model for Indonesian NLP. arXiv preprint arXiv:2011.00677.
Nasukawa, T. & Yi, J., 2003. Sentiment Analysis: Capturing Favorability Using Natural Language Processing. In Proceedings of the 2nd International Conference on Knowledge Capture, pp.70-77.
Paget, S., 2024. Local Consumer Review Survey 2024: Trends, Behaviors, and Platforms Explored. [online] BrightLocal. Tersedia di: https://www.brightlocal.com/research/local-consumer-review-survey/#the-most-important-review-factors.
Pradhisa, K. & Fajriyah, R., 2024 “Analisis Sentimen Ulasan Pengguna E-commerce di Google Play Store Menggunakan Metode IndoBERT”, Building of Informatics, Technology and Science (BITS), 6(1), p. 92−104. doi: 10.47065/bits.v6i1.5247
Rohaeni, H. & Marwa, N., 2018. Kualitas pelayanan terhadap kepuasan pelanggan. Jurnal Ecodemica, 2(2), pp.312-318.
Sharma, H., Tandon, A., Kapur, P.K. & Aggarwal, A.G., 2019. Ranking hotels using aspect ratings based sentiment classification and interval-valued neutrosophic TOPSIS. International Journal of System Assurance Engineering and Management, 10(5), pp.973–983. doi:https://doi.org/10.1007/s13198-019-00827-4.
Vorley, G., 2008. Mini guide to root cause analysis. London: Quality Management & Training Limited.
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