Article Per Year (5 Year)
p-Index From 2021 - 2026
24.323
P-Index
This Author published in this journals
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

Published : 235 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 235 Documents
Search

 15   16   17   18   19 
Sentiment Analysis and Trend Mapping of Hotel Reviews Using LSTM and GRU Singgalen, Yerik Afrianto
Journal of Information System and Informatics Vol 6 No 4 (2024): December
Publisher : Universitas Bina Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51519/journalisi.v6i4.926

Abstract

This study explores applying Long Short-Term Memory (LSTM) and Gated Recurrent Unit (GRU) models for sentiment analysis and trend mapping of hotel reviews, specifically focusing on customer feedback from Hotel Vila Ombak in Lombok, Indonesia. The primary objective was to leverage these advanced deep learning models to capture nuanced sentiment patterns in unstructured textual data, enhancing insights into guest satisfaction. The analysis was conducted on a dataset of 326 reviews, achieving an overall model accuracy of 91% (0.91). The results showed that while the models excelled in identifying positive sentiments, with a precision of 0.94, recall of 0.98, and F1-score of 0.96, they struggled with minority classes. Both negative and neutral sentiments exhibited 0% accuracy, primarily due to the dataset’s imbalance, where positive reviews constituted 92.3% of the total entries. The macro average metrics (precision 0.31, recall 0.33, F1-score 0.32) highlighted the model's limitations in classifying sentiments less frequently despite high weighted averages driven by the dominant positive class. This research underscores the need to address data imbalance and suggests that future studies incorporate techniques like data augmentation or hybrid models to improve performance across all sentiment categories. By optimizing sentiment analysis models, hospitality businesses can gain deeper insights into customer feedback, ultimately enhancing service quality and customer satisfaction.
Hotel Guest Length of Stay Prediction Using Random Forest Regressor Singgalen, Yerik Afrianto
Journal of Information System and Informatics Vol 6 No 4 (2024): December
Publisher : Universitas Bina Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51519/journalisi.v6i4.959

Abstract

This research offers a robust framework for integrating predictive analytics into hospitality operations, contributing to sustainable growth and competitive advantage in the industry. This research investigates the application of the Random Forest Regression model to predict the Length of Stay (LoS) of hotel guests, leveraging key features such as country, guest type, room type, and rating. The study addresses the need for precise forecasting to optimize resource allocation, improve operational efficiency, and support data-driven decision-making in the hospitality sector. The methodology involves data collection from a structured dataset of guest reviews, preprocessing through encoding categorical variables, converting target values into numeric forms, and standardizing features to ensure consistency and uniformity. The dataset is split into training (80%) and testing (20%) subsets, with hyperparameters such as n_estimators=100 and random_state=42 set to ensure stability and reproducibility during model training. The Random Forest Regression model demonstrated strong predictive performance, achieving an R-squared value of 0.85 and a Mean Absolute Error (MAE) of 1.06. Feature importance analysis identified "country" as the most significant variable (importance score: 0.5), followed by guest type (0.2), room type (0.15), and rating (0.15). The Predicted vs. Actual Plot and Error Distribution evaluation reveals that most errors cluster near zero, indicating high accuracy with minor deviations in extreme cases. These findings emphasize the model’s potential to enhance marketing strategies, optimize resource allocation, and improve guest satisfaction. This research offers a robust framework for integrating predictive analytics into hospitality operations, contributing to sustainable growth and competitive advantage in the industry.
Exploring the Shariah-Compliant Hotel Market: Meeting the Needs of Muslim Travelers Singgalen, Yerik Afrianto
Ekonomi, Keuangan, Investasi dan Syariah (EKUITAS) Vol 6 No 1 (2024): August 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/ekuitas.v6i1.5525

Abstract

This study explores the dynamics of guest preferences and satisfaction within the context of Sharia-compliant hospitality, using data from 445 verified reviews at The Sahira Hotel. Employing a descriptive-analytic methodology, the research utilizes visitor data extracted from Agoda’s review platform, focusing on room preferences, stay duration, and satisfaction ratings. The dataset was systematically filtered, cleaned, and categorized to ensure relevance and accuracy before conducting qualitative and quantitative analyses. Key findings reveal significant trends in visitor demographics and preferences. Families with young children and teenagers strongly preferred spacious accommodations, particularly the Family Deluxe Triple, accounting for over 35% of such bookings. In contrast, solo travelers, representing 20% of the dataset, favored functional and affordable options like the Deluxe Twin. Ratings analysis revealed the Deluxe Twin as the most highly rated room type, receiving over 40% "Exceptional" ratings. Short stays dominated the data, with 60% of guests staying for one night, emphasizing the importance of high-quality service for transient visitors. The study also underscores the significance of cultural and religious considerations, such as Halal-certified amenities and gender-sensitive spaces, in enhancing guest satisfaction. By aligning operational strategies with these insights, the findings provide actionable recommendations for optimizing marketing efforts, improving service delivery, and ensuring consistent guest satisfaction. This research contributes to the broader discourse on integrating cultural sensitivity with modern hospitality practices, offering a pathway for sustainable growth in the competitive halal tourism market.
An Analysis of Visitor Perception Toward Shariah-Compliant Hotels in Contemporary Hospitality Singgalen, Yerik Afrianto
Ekonomi, Keuangan, Investasi dan Syariah (EKUITAS) Vol 6 No 2 (2024): November 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/ekuitas.v6i2.6184

Abstract

This research examines visitor perceptions of Shariah-compliant hotels within the context of contemporary hospitality, focusing on how these establishments meet guest expectations and foster satisfaction in a competitive global market. The study analyzes 445 customer reviews using a descriptive-analytical methodology to explore integrating Islamic principles with modern service standards. Key themes include cleanliness, staff behavior, Halal compliance, and family-oriented facilities. Cleanliness, mentioned in over 30% of reviews, emerges as the most critical factor, reflecting its alignment with Islamic values and universal hospitality standards. Staff behavior, noted in 25% of reviews, highlights the importance of attentiveness and politeness in shaping guest perceptions. Halal compliance, cited in 20% of feedback, underscores the significance of providing prayer facilities and Halal-certified dining options for Muslim travelers. Family-friendly and worship-related amenities, accounting for 15% of mentions, illustrate the need for culturally and spiritually inclusive environments. Sentiment analysis reveals a weak positive correlation (0.165) between ratings and sentiment polarity, while dissatisfaction, noted in 10% of reviews, primarily relates to tranquility, maintenance, and service inconsistencies. The findings emphasize that the success of Shariah-compliant hotels relies on the seamless integration of faith-based principles with operational excellence. Addressing guest concerns and leveraging positive feedback enhances satisfaction and strengthens loyalty and competitiveness. This study contributes to the broader discourse on inclusive hospitality management, offering practical insights for operational improvement and theoretical advancements in understanding niche markets.
Toxicity and topic analysis of travel vlog content in digital era: perspective and multilingual embedding model (voyage-multilingual-2) Singgalen, Yerik Afrianto
Jurnal Teknik Informatika C.I.T Medicom Vol 16 No 3 (2024): July: Intelligent Decision Support System (IDSS)
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/cit.Vol16.2024.844.pp199-210

Abstract

This research investigates the complexities of online discourse by conducting a detailed toxicity and topic analysis of travel vlog content on user-generated platforms. By analyzing 1,503 posts using the Perspective API, the study finds generally low levels of toxicity, with an average toxicity score of 0.06995 and a peak of 0.78207, and similarly low average scores for severe toxicity, identity attack, insult, profanity, and threat (0.00654, 0.01237, 0.03778, 0.06241, and 0.01186, respectively). However, the highest recorded values for these measures—0.45895 for severe toxicity, 0.69287 for identity attack, 0.63084 for insult, 0.81864 for profanity, and 0.51957 for threat—highlight the sporadic presence of harmful content. Advanced clustering techniques, such as HDBScan, k-Means, and Gaussian Mixture models, enable a comprehensive examination of thematic diversity and sentiment distribution within the comments, offering valuable insights into audience engagement and perception. These findings underline the critical need for compelling content moderation and community management strategies to mitigate toxic behaviors and promote a positive digital environment. The study concludes that as digital media evolves, further research into toxicity, thematic content, and user engagement is essential for enhancing theoretical frameworks and practical applications in digital communication.
Toxicity, social network and topic analysis of digital content: Perspective and multilingual embedding model Singgalen, Yerik Afrianto
Jurnal Teknik Informatika C.I.T Medicom Vol 16 No 3 (2024): July: Intelligent Decision Support System (IDSS)
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/cit.Vol16.2024.845.pp115-128

Abstract

This research presents a comprehensive approach to analyzing digital content by integrating toxicity analysis, clustering techniques, and Social Network Analysis (SNA) to understand online interactions better. The study finds that, while the average toxicity levels are relatively low, with scores such as 0.06355 for toxicity and 0.00468 for severe toxicity, there are significant spikes, reaching maximum scores of 0.82996 for toxicity and 0.89494 for profanity. These spikes highlight the necessity for continuous monitoring and adaptive moderation strategies to minimize the impact of harmful language. Clustering methods, including K-Means, HDBScan, and Gaussian Mixture models, provide deep insights into the thematic structure of viewer discourse, identifying both prevalent and niche topics. The Gaussian Mixture model identified ten distinct clusters, while HDBScan revealed varying cluster densities, reflecting the diverse range of discussions within the community. In addition, SNA, with 1,716 nodes and 37 edges, offers critical insights into the relational dynamics of the network, pinpointing key influencers and mapping the flow of information between different user groups. By synthesizing these methodologies, the research provides a robust framework for understanding the content and context of digital interactions, facilitating more effective strategies for enhancing community engagement, mitigating toxicity, and promoting a healthier, more inclusive online environment.
Topic modeling using LDA and performance evaluation of classification algorithm: k-NN, SVM, NBC, and DT Singgalen, Yerik Afrianto
Jurnal Teknik Informatika C.I.T Medicom Vol 16 No 3 (2024): July: Intelligent Decision Support System (IDSS)
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/cit.Vol16.2024.846.pp143-157

Abstract

This research investigates the integration of Latent Dirichlet Allocation (LDA) for topic modeling with the performance evaluation of various classification algorithms—specifically, k-nearest Neighbors (k-NN), Support Vector Machines (SVM), Naive Bayes Classifier (NBC), and Decision Trees (DT)—within the Digital Content Reviews and Analysis Framework. The framework systematically processes and analyzes digital content, including data cleaning, extraction, evaluation, and visualization techniques, to enhance machine learning models' interpretability and predictive accuracy. The study demonstrates that combining LDA with these classification algorithms significantly improves data interpretation and model performance, particularly in handling large-scale textual datasets. Notably, the Decision Tree algorithm achieved a 98.86% accuracy post-SMOTE. At the same time, the Support Vector Machine reached a near-perfect AUC of 1.000, highlighting the efficacy of these methods in managing imbalanced datasets. The findings provide valuable insights for optimizing model selection and developing more robust and adaptive machine-learning models across various applications. This research contributes to advancing the field of artificial intelligence by proposing a comprehensive framework that effectively addresses complex data-driven challenges, encouraging further exploration of more flexible and scalable models to accommodate evolving data environments.
Uncovering Service Gaps in Hospitality: A Thematic Analysis of Guest Reviews for Service Quality Improvement Singgalen, Yerik Afrianto
Journal of Business and Economics Research (JBE) Vol 6 No 1 (2025): February 2025
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/jbe.v6i1.6840

Abstract

This study employs thematic analysis methodology to examine service quality dimensions through systematic investigation of 1,284 verified guest reviews at Katamaran Hotel & Resort Lombok, Indonesia. The research utilizes Atlas.ti software for rigorous coding and theme development, implementing a five-phase analytical framework encompassing data collection, preparation, coding analysis, theme development, and reporting. The findings reveal that guest satisfaction is predominantly influenced by three key factors: physical facility quality (9.4/10), staff performance (9.3/10), and service delivery mechanisms (9.2/10). Analysis identified specific service gaps requiring strategic intervention, particularly in response time optimization and interdepartmental coordination. The study establishes that successful service enhancement necessitates integration of standardized protocols across operational touchpoints, complemented by comprehensive staff development initiatives. Theoretical contributions include advancing understanding of service quality dynamics through sophisticated thematic analysis methodologies, establishing novel frameworks for service gap identification, and demonstrating effectiveness of integrated approaches to service quality enhancement. Practical implications provide hospitality managers with actionable insights for maintaining balanced focus across physical facility maintenance, staff training programs, and service delivery protocols. Future research directions suggest exploring artificial intelligence integration in service monitoring systems, developing predictive models for guest needs, and conducting cross-cultural analysis of service quality expectations in diverse hospitality contexts.
The Economic Impact of Halal Tourism Development on Local Communities Singgalen, Yerik Afrianto
Ekonomi, Keuangan, Investasi dan Syariah (EKUITAS) Vol 6 No 3 (2025): February 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/ekuitas.v6i3.7010

Abstract

This research examines the economic dynamics of halal tourism development in Setanggor Village, a traditional craft village in Lombok, Indonesia, focusing on the interrelationship between cultural preservation and sustainable economic growth. Digital ethnographic methodology facilitates comprehensive analysis by systematically observing online interactions, digital footprints, and virtual community engagements across social media platforms, e-commerce activities, and digital marketing strategies of Setanggor's artisanal enterprises. Data collection encompasses news articles, and TripAdvisor reviews specific to Setanggor Village, processed through Atlas.ti software for rigorous content categorization and thematic analysis. Pattern identification and cross-source validation enhance analytical depth, ensuring methodological coherence in deriving robust conclusions. The findings reveal significant correlations between community cooperative structures, artisan empowerment, and equitable distribution of economic benefits within Setanggor's traditional weaving industry. Market expansion through halal-certified products demonstrates the substantial potential for income generation, while Setanggor's traditional weaving practices exemplify the successful integration of cultural heritage with contemporary market demands. However, the research identifies critical challenges in maintaining an equilibrium between commercialization pressures and cultural authenticity. Implementing strategic policy frameworks and fair trade mechanisms emerges as essential for fostering sustainable economic development while preserving traditional craftsmanship. This investigation contributes to the academic discourse by establishing innovative approaches for evaluating tourism-driven economic impacts within traditional craft villages, offering valuable insights for policymakers and stakeholders in developing sustainable halal tourism initiatives that benefit local artisanal communities in Setanggor and similar cultural destinations.
Digital Ethnographic Exploration of Media Narratives: Shaping Investment Decisions in Halal Tourism Ecosystems Singgalen, Yerik Afrianto
Ekonomi, Keuangan, Investasi dan Syariah (EKUITAS) Vol 6 No 3 (2025): February 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/ekuitas.v6i3.7051

Abstract

This research investigates the influence of digital media narratives on investment decision frameworks within halal tourism ecosystems through digital ethnographic methodology. The study employs a comprehensive methodological approach incorporating systematic data collection across multiple digital platforms, including specialized forums, social media environments, and digital financial communities. Using mixed-methods analysis combining qualitative narrative assessment with quantitative lexicometric evaluation, the research reveals significant patterns in terminology frequency, with tourism-related terms dominating the discourse at 17,181 instances, followed by growth indicators (5,587), value measurements (4,678), and impact assessments (4,524). The business environment analysis identifies "tourism" as the predominant term (174 occurrences), followed by "muslim" (127) and "halal" (93), demonstrating fundamental market dynamics. Digital ethnographic analysis illuminates distinctive patterns in investment behavior through three interconnected phases: initial digital immersion, targeted observation of investor-content interactions, and in-depth narrative reception analysis. The findings demonstrate that digital media narratives fundamentally influence investment decisions through sophisticated platform interactions, with distinctive patterns emerging at intersections of Islamic principles and economic considerations. This research contributes to understanding investment dynamics within halal tourism markets while establishing robust parameters for culturally sensitive market development.
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