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All Journal MANAJEMEN HUTAN TROPIKA Journal of Tropical Forest Management Sodality: Jurnal Sosiologi Pedesaan MANAJEMEN IKM: Jurnal Manajemen Pengembangan Industri Kecil Menengah Jurnal Ilmu dan Teknologi Kelautan Tropis IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Jurnal Ilmu Sosial dan Humaniora Jurnal Kawistara : Jurnal Ilmiah Sosial dan Humaniora Journal of Indonesian Tourism and Development Studies JURNAL ELEKTRO Jurnal Perkotaan Jurnal Kebijakan dan Administrasi Publik AdBispreneur PAX HUMANA ARISTO JURNAL MEDIA INFORMATIKA BUDIDARMA Jurnal Komunikasi Kritis Humaniora MUWAZAH: Jurnal Kajian Gender Cakrawala Jurnal Penelitian Sosial Building of Informatics, Technology and Science Jurnal Mantik Journal of Information Systems and Informatics Jurnal Studi Sosial dan Politik Jurnal Teknik Informatika C.I.T. Medicom JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) Journal of Computer System and Informatics (JoSYC) EKONOMI, KEUANGAN, INVESTASI DAN SYARIAH (EKUITAS) Jurnal Sistem Komputer dan Informatika (JSON) JOURNAL OF BUSINESS AND ECONOMICS RESEARCH (JBE) Budapest International Research and Critics Institute-Journal (BIRCI-Journal): Humanities and Social Sciences Cita Ekonomika: Jurnal Ilmu Ekonomi ARBITRASE: JOURNAL OF ECONOMICS AND ACCOUNTING International Journal on Social Science, Economics and Art KLIK: Kajian Ilmiah Informatika dan Komputer International Journal of Basic and Applied Science Indonesian Journal of Tourism and Leisure Jurnal InterAct Jurnal Sosiologi Engagement: Jurnal Pengabdian Kepada Masyarakat JKAP (Jurnal Kebijakan dan Administrasi Publik) Jurnal Kawistara Muwazah: Jurnal Kajian Gender
Yerik Afrianto Singgalen
Universitas Katolik Indonesia Atma Jaya
Religion Agriculture, Biological Sciences & Forestry Arts Humanities Biochemistry, Genetics & Molecular Biology Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Physics Public Health Social Sciences Other

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SOCIAL CAPITAL AND LIVELIHOOD DIVERSIFICATION: TOURISM ENTREPRENEURSHIP IN A REMOTE AREA OF NORTH HALMAHERA, INDONESIA Yerik Afrianto Singgalen; Gatot Sasongko; Pamerdi Giri Wiloso
Jurnal Kawistara Vol 9, No 3 (2019)
Publisher : Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/kawistara.34627

Abstract

This article aims to describe the capability of public access to social capital as a form of livelihood diversification through tourism entrepreneurship. This idea was originated from the optimization of the tourism sector and the creative economy by the local government since 2017, aiming to encourage creative entrepreneurship in tourism, creative multimedia, and coffee shop businesses. This study was conducted in a qualitative approach; thus, primary and secondary data sources were used to analyze the data. The primary data was obtained through in-depth interviews and observations, while the secondary data was obtained from document studies. In this case, the in-depth interviews were conducted with the entrepreneurs. The participants involved as key informants had various backgrounds in tourism entrepreneurship such as travel agent and tour guide service, creative multimedia service, and coffee shop business. Furthermore, field observations were done based on activities or events, aiming to observe the process of involvement of these entrepreneurs in regional tourism activities during the events of “Torang Angkat Sampah” in 2017, “Tanjung Bongo Festival” in 2017, “North Galela Festival” in 2018, “Wonderful North Halmahera” in 2018, and “O Molulu Ma Akere” in 2019. The secondary data used was the Medium Term Program Plan of the Local Government Agencies of the Regional Tourism Department of North Halmahera Regency after there was a policy of creative economy development elaborated in the bureaucratic structure changes at the Regional Tourism Department. The results show that the availability of infrastructure, accessibility of information and transportation, and the capability of access to social capital were such a stimulus for the diversification of people’s livelihoods to run tourism, creative multimedia, and coffee shop businesses. Through social capital, entrepreneurs were strengthened by their social relations with various communities to have more consumers while also maintaining the business sustainability.
Actor-Network Theory and Sentiment Analysis on Regional Development Issues and Politics in Social Media Yerik Afrianto Singgalen
Jurnal Komunikasi Vol. 13 No. 1 (2021): Jurnal Komunikasi
Publisher : Fakultas Ilmu Komunikasi Universitas Tarumanagara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24912/jk.v13i1.9627

Abstract

During the Covid-19 pandemic, North Halmahera Regency's political activity became intense in virtual spaces, especially on the Facebook group Quovadis North Halmahera. The things discussed in the virtual space have an impact on the community in the real world. Hate Speech and provocative issues generate negative responses in the real world, marked by conflicts in several social spaces.This article aims to discuss regional development issues and politics in social media based on sentiment analysis and actor-network theory. This article also identifies the vulnerability aspect by mapping and classifying netizen's argument in the virtual space to various regional development issues based on economic, social, cultural, political, tourism, and environmental aspects. This research uses qualitative methods. The process of collecting data uses in-depth interview techniques, observation, and document study. Data processing uses triangulation techniques. Also, research instruments used are QGIS 2.18.4 and Nvivo 12 Plus applications for mapping research sites and mapping development issues in virtual space, namely Quo Vadis Halmahera Utara Facebook group. This study indicates that social capital (Norm, Trust, Network) becomes an aspect of vulnerability based on mapping and content analysis in virtual space according to netizens' response to development issues in the North Halmahera Regency. Furthermore, the contents containing hate speech elements, invalid information (hoax), sarcasm, bullying, and privacy attacks are the potential actors to cause social capital degradation based on the Actor-Network-Theory. Selama Pandemi Covid-19, kondisi perpolitikan di Kabupaten Halmahera Utara menjadi intensif di ruang virtual, khususnya grup facebook QuoVadis Halmahera Utara. Pelbagai isu pembangunan dan politik di ruang virtual tersebut berdampak terhadap kondisi sosial masyarakat di kehidupan sehari-hari. Ujaran kebencian, isu profokatif hingga sentimen negatif memantik konflik di ruang sosial. Artikel ini bertujuan untuk mendiskusikan masalah pembangunan dan politik di media sosial berdasarkan analisis sentimen dan teori jejaring aktor. Artikel ini juga mengidentifikasi aspek kerentanan, dengan memetakan dan mengklasifikasikan argumen netizen di ruang virtual, menanggapi pelbagai persoalan sosial, budaya, politik, pariwisata dan lingkungan. Penelitian ini menggunakan metode kualitatif. Proses pengolahan data menggunakan teknik wawancara mendalam, observasi dan studi dokumen. Proses pengolahan data menggunakan trianggulasi. Instrumen penelitian yang digunakan ialah QGIS 2.18.4  untuk pemetaan lokasi atau wilayah penelitian dan Nvivo 12 Plus untuk pemetaan isu pembangunan dan politik yang didiskusikan dalam grup facebook Quovadis Halmahera Utara.  Hasil penelitian ini menunjukkan bahwa modal sosial (norma, kepercayaan, jejaring) menjadi aspek kerentanan. Selain itu, konten yang teridentifikasi dari hasil analisis sentimen ialah ujaran kebencian, informasi yang tidak valid, sarkasme, perundungan dan penyerangan privasi, sebagai penyebab degradasi modal sosial berdasarkan teori jejaring aktor.
Optimizing website development with rad for the center of digital transformation and tourism development Singgalen, Yerik Afrianto
Jurnal Mantik Vol. 8 No. 3 (2024): November: Manajemen, Teknologi Informatika dan Komunikasi (Mantik)
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/mantik.v8i3.5758

Abstract

This study explores the implementation of Rapid Application Development (RAD) frameworks in the design and optimization of websites for academic institutions, particularly focusing on enhancing the functionality of digital platforms used by study centers. By leveraging agile methodologies, this research aims to streamline the development process, ensuring that digital resources remain responsive to user needs and institutional objectives. The findings underscore the effectiveness of iterative prototyping and feedback integration in creating a user-centered design that significantly improves engagement and information accessibility. Furthermore, the study reveals how optimizing website content not only elevates the digital presence of study centers but also supports broader educational goals, such as fostering collaboration and expanding academic outreach. The analysis highlights the critical role of digital transformation in aligning technological advancements with strategic institutional missions. As a result, this research provides valuable insights into the practical application of RAD in optimizing digital infrastructures, ultimately contributing to the sustainable growth and innovation of academic environments
Feedback analysis of service quality through data mining approach Singgalen, Yerik Afrianto
Jurnal Mantik Vol. 8 No. 3 (2024): November: Manajemen, Teknologi Informatika dan Komunikasi (Mantik)
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/mantik.v8i3.5761

Abstract

This study explores the application of data mining techniques to analyze customer feedback for improving service quality at Tanjung Lesung Beach Hotel. Utilizing the Knowledge Discovery in Databases (KDD) framework, the research systematically collected, cleaned, and analyzed 1,239 customer reviews from the Agoda platform. Through a thorough data cleaning process, 642 verified reviews were identified as authentic, providing a robust dataset for in-depth analysis. Sentiment analysis was employed to extract key insights, revealing both positive aspects of the hotel experience, such as staff friendliness and beach amenities, as well as areas requiring improvement, particularly related to room conditions and breakfast offerings. Trend analysis indicated an upward trend in customer satisfaction from 2018 to 2023, with a minor decline observed in 2024, suggesting the need for ongoing service enhancements. The findings emphasize the critical role of leveraging verified customer feedback to inform strategic improvements, ultimately aiming to enhance guest satisfaction and maintain a competitive edge in the hospitality industry. This research contributes to the field by demonstrating how data-driven approaches can optimize service quality and align organizational strategies with evolving customer expectations
A Hybrid CNN-LSTM Model with SMOTE for Enhanced Sentiment Analysis of Hotel Reviews Singgalen, Yerik Afrianto
Building of Informatics, Technology and Science (BITS) Vol 6 No 3 (2024): December 2024
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v6i3.6301

Abstract

The growing reliance on online reviews as a critical decision-making tool in the hospitality industry underscores the need for robust sentiment analysis methodologies. Understanding customer feedback is essential for hotels to enhance service quality and maintain a competitive edge in an increasingly digital marketplace. However, traditional sentiment analysis models often encounter difficulties processing unstructured textual data, particularly when faced with class imbalances where positive reviews dominate, overshadowing critical negative feedback. To address these challenges, this study investigates integrating a hybrid Convolutional Neural Network and Long Short-Term Memory (CNN-LSTM) model with the Synthetic Minority Over-sampling Technique (SMOTE) to improve sentiment classification accuracy. Utilizing a dataset of 665 reviews from THE 1O1 Bandung Dago Hotel, the model leverages CNN’s capability to capture local features and LSTM’s strength in handling sequential dependencies, resulting in a more nuanced analysis of customer sentiments. The application of SMOTE effectively balances the dataset, addressing the class imbalance issue, which often skews sentiment classification. This approach improves predictive accuracy and provides actionable insights to enhance customer satisfaction strategies. The study achieved an overall classification accuracy of 77%, with precision at 78%, recall at 77%, an F1 score of 77.5%, and an AUC score of 0.81, reflecting discriminatory solid capability. Future research could focus on model optimization, multilingual sentiment analysis, aspect-based sentiment insights, and real-time sentiment monitoring to further refine customer feedback analysis and support strategic decision-making in the hospitality sector.
Sentiment Classification Using BERT-CNN and SMOTE: A Case Study on Hotel Reviews Dataset Singgalen, Yerik Afrianto
Building of Informatics, Technology and Science (BITS) Vol 6 No 3 (2024): December 2024
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v6i3.6309

Abstract

The increasing importance of user-generated content in the hospitality industry necessitates advanced sentiment analysis tools to derive actionable insights from customer reviews. Traditional methods often struggle with the complexities of natural language, such as contextual dependencies and nuanced emotional expressions. This research leverages the BERT-CNN hybrid model, which combines BERT’s contextual language understanding with CNN’s feature extraction capabilities, to address these challenges and improve sentiment classification accuracy. Using a dataset of 1,828 hotel reviews from Eastparc Hotel Yogyakarta, the model achieved an impressive accuracy of 99.59%, with precision and recall exceeding 0.99. The application of SMOTE effectively resolved class imbalance, enhancing the model’s ability to generalize across diverse sentiment classes. Training and validation loss curves exhibited steady convergence, indicating robust learning and minimal overfitting. These results provided actionable insights into customer satisfaction, offering targeted recommendations for enhancing service quality and operational strategies. This study demonstrates the practicality of integrating advanced machine learning architectures in sentiment analysis, enabling the hospitality sector to transform unstructured feedback into meaningful insights. The findings contribute to academic advancements in natural language processing and practical innovations in customer experience management. Future research may expand this framework to other domains, further underscoring its adaptability and impact.
Understanding Hotel Customer Experience through User-Generated Reviews using Knowledge Discovery in Databases (KDD) Singgalen, Yerik Afrianto
Journal of Computer System and Informatics (JoSYC) Vol 6 No 1 (2024): November 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josyc.v6i1.6014

Abstract

This research explores the analysis of 388 hotel customer reviews to understand guest experiences, employing advanced analytical methodologies to uncover valuable insights for service quality enhancement. Utilizing the Knowledge Discovery in Databases (KDD) framework, the study applies Latent Dirichlet Allocation (LDA) for topic clustering and k-nearest Neighbors (k-NN), enhanced by the Synthetic Minority Over-sampling Technique (SMOTE) for sentiment classification. The integration of these techniques allows for the extraction of coherent thematic patterns and the accurate differentiation of sentiment categories within the reviews. The findings reveal that LDA, evaluated through metrics such as log-likelihood (-54,886.092) and coherence scores (-14.949), effectively captures the underlying themes discussed by guests, providing a clear representation of customer priorities and concerns. Additionally, applying SMOTE significantly improves the k-NN model's performance, achieving an accuracy of 91.43% and a precision of 97.26% by balancing class distributions and enhancing classification accuracy. This approach demonstrates the potential of combining topic modeling and sentiment analysis to derive actionable insights, which can be strategically utilized to optimize service delivery and elevate the overall customer experience in the hospitality industry. The study concludes that leveraging such data-driven methodologies facilitates a deeper understanding of customer feedback, ultimately supporting informed decision-making and continuous service improvement.
Utilizing Knowledge Discovery in Databases (KDD) for Hotel Guest Feedback Analysis Singgalen, Yerik Afrianto
Journal of Computer System and Informatics (JoSYC) Vol 6 No 1 (2024): November 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josyc.v6i1.6094

Abstract

This research explores the application of Knowledge Discovery in Databases (KDD) to analyze hotel guest feedback and improve service quality at Bintang Flores Hotel in Labuan Bajo. Utilizing KDD methodologies, the study processed 589 guest reviews to identify key factors influencing customer satisfaction, including cleanliness (1.00), location (0.82), and staff service (0.71). The analysis also highlighted issues such as limited breakfast variety (0.59) and inconsistent Wi-Fi connectivity (0.41) as recurring concerns, especially for long-term guests and business travelers. The data revealed that guests staying in the Deluxe Double or Twin Room frequently rated their experience as "Excellent" or "Very Good," with couples and families expressing high satisfaction levels. In contrast, suite categories received fewer and more varied ratings, signaling areas for targeted improvement. Through KDD, the study effectively combined structured numerical ratings and unstructured written feedback to pinpoint areas needing operational enhancement. Addressing challenges related to service consistency during peak periods, infrastructure maintenance, and food variety is essential for boosting guest satisfaction. The findings support implementing targeted strategies to ensure that Bintang Flores Hotel maintains a competitive edge and meets evolving customer expectations in the hospitality market.
Analyzing Hotel Customer Satisfaction Using Review Dataset: Insights and Implications for Service Improvement Singgalen, Yerik Afrianto
Journal of Business and Economics Research (JBE) Vol 5 No 3 (2024): October 2024
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/jbe.v5i3.6015

Abstract

This research investigates customer satisfaction at Meruorah Komodo Labuan Bajo through a comprehensive analysis of review data extracted from the Agoda platform. By examining 1,340 reviews, including 527 verified accounts, the study identifies key factors influencing guest experiences, such as service quality, room features, and location. The methodology comprised four stages: hotel selection, data scraping, data processing, and data interpretation. Findings indicate that premium room types, such as “The Signature Sea View Room,” consistently receive high satisfaction ratings, with 414 mentions (2.99%), highlighting the value placed on scenic views and superior amenities. Seasonal fluctuations and guest origins also impact satisfaction, with Indonesian guests strongly preferring familiarity, while international travelers prioritize diverse amenities. The data shows that 37 out of 203 accounts were domestic, while 17 were from the United States and Australia combined. The study reveals that 89% of domestic guests reported satisfaction, compared to varied expectations among international visitors. These insights suggest that tailored service strategies and enhancements in service consistency can further improve overall guest satisfaction. The research underscores the necessity of aligning service offerings with guest expectations to maintain a competitive edge in the dynamic hospitality industry.
Hotel Customer Satisfaction: A Comprehensive Analysis of Perceived Cleanliness, Location, Service, and Value Singgalen, Yerik Afrianto
Journal of Business and Economics Research (JBE) Vol 5 No 3 (2024): October 2024
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/jbe.v5i3.6016

Abstract

This research investigates the key determinants of customer satisfaction in the hospitality industry, focusing on cleanliness, service quality, location, and value. Analyzing guest reviews, the study reveals that 85% of guests consider cleanliness a primary factor influencing their overall experience, while 78% highlight service quality, particularly staff responsiveness and professionalism, as crucial components. Location is identified as a significant contributor by 65% of guests, emphasizing convenience and accessibility to local attractions, and 72% of guests evaluate their satisfaction based on the perceived value of the stay, which balances price and service quality. Additionally, digital engagement, health and safety perceptions, and sustainability practices play an increasing role in shaping guest satisfaction. Specifically, 60% of guests appreciate digital features such as contactless check-in and personalized communication. Meanwhile, 70% note that visible health and safety measures, including enhanced cleaning protocols, positively impact their comfort and trust. Furthermore, 58% of guests prefer hotels adopting sustainability practices, such as reducing plastic use and promoting eco-friendly amenities. The study concludes that 90% of guests rated cleanliness, service quality, and value highly were more likely to recommend the property and return in the future. In contrast, properties lacking in these areas saw a 45% decline in repeat visit intentions. These findings underscore hospitality providers' need to prioritize these factors and integrate digital, health, and sustainability considerations to optimize service delivery, enhance guest satisfaction, and establish a sustainable competitive advantage.
Co-Authors A.Y. Agung Nugroho Agnes Harnadi Agnes Harnadi Agung Mulyadi Purba Alfonso Harrison Aloisius Gita Nathaniel Astuti Kusumawicitra Astuti Kusumawicitra Astuti Kusumawicitra Laturiuw Astuti Kusumawicitra Laturiuw Bernardus Alvin Rig Bernardus Alvin Rig Biafra Daffa Farabi Biafra Daffa Farabi Billy Macarius Sidhunata Brito, Manuel Charitas Fibriani Christanto, Henoch Juli Christine Dewi Danny Manongga Dasra, Muhamad Nur Agus Eko Sediyono Eko Widodo Elfin Saputra Elfin Saputra Elly Esra Kudubun Fang, Liem Shiao Faskalis Halomoan Lichkman Manurung Gatot Sasongko Gilberto Dennis G E Sidabutar Gintu, Agung Rimayanto Gudiato, Candra Henoch Juli Christanto Henoch Juli Christanto Heru Prasadja Heru Prasadja, Heru Hindriyanto Dwi Purnomo Hironimus Cornelius Royke Irene Sonbay Irwan Sembiring Jesslyn Alvina Seah Jonathan Tristan Santoso Juli Christanto, Henoch Kartikawangi, Dorien Kusumawicitra, Astuti Manuel Brito Marthen Timisela Mavish, Steven Michael Kenang Gabbatha Nantingkaseh, Alfonso Harrison Nicolas Arya Nanda Susilo Nugroho, A. Y. Agung Octa Hutapea Octa Hutapea Pamerdi Giri Wiloso Pamerdi Giri Wiloso Pamerdi Giri Wiloso, Pamerdi Giri Pedro Manuel Lamberto Buu Sada Pinia, Nyoman Agus Perdanaputra Pontolawokang, Theresya Ellen Pristiana Widyastuti Pristiana Widyastuti Purwoko, Agus Puspitarini, Titis Radyan Rahmananta Radyan Rahmananta Rafael Christian Rahadi, Abigail Rosandrine Kayla Putri Rahmadini, Asyifa Catur Richard Emmanuel Adrian Sinaga Rosdiana Sijabat Samuel Piolo Seingo, Martha Maraka Setiawan, Ruben William Siemens Benyamin Tjhang Sri Yulianto Joko Prasetyo Stephen Aprius Sutresno, Stephen Aprius Suharsono SUHARSONO Suni, Eugenius Kau Tabuni, Gasper Tharsini, Priya Timisela, Marthen Titi Susilowati Prabawa Titis Puspitarini Widodo, Eko Winayu, Birgitta Narindri Rara Yan Dirk Wabiser Yoel Kristian Zsarin Astri Puji Insani