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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 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
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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Journal : Journal of Information Systems and Informatics

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Exploring the Digital Narratives in Tourism and Culture through The Case of Rambu Solo: Sentiment, Toxicity, and Content Analysis Singgalen, Yerik Afrianto
Journal of Information System and Informatics Vol 6 No 3 (2024): September
Publisher : Universitas Bina Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51519/journalisi.v6i3.836

Abstract

This research urgently addresses the need to understand and manage viewer interactions with culturally significant video content, particularly the Rambu Solo ritual. By integrating the Digital Content Reviews and Analysis Framework with sentiment classification performance, toxicity score evaluation, and content analysis, the study systematically analyzed 21,562 posts across four videos, revealing critical themes related to cultural preservation and tourism impact that shaped viewer perceptions. Sentiment and toxicity evaluations of 15,762 posts showed an average toxicity score of 0.068, with a peak of 0.85174. Sentiment classification, using algorithms like SVM, k-NN, NBC, and DT, highlighted the superior performance of SVM enhanced by SMOTE, with an accuracy of 81.97%. However, the study identified limitations in automated sentiment analysis tools, noting that they may not fully capture the complexities of human expression. This research recommends incorporating advanced natural language processing techniques and multimodal analysis within the framework. This comprehensive methodology offers essential insights into the intersection of culture, tourism, and digital media, emphasizing the importance of creating and managing content that respects and promotes cultural heritage in the digital age. The findings are crucial for developing more effective strategies for digital content creation and community engagement, ensuring that cultural narratives are presented thoughtfully and respectfully to global audiences.
Unveiling Indonesia's New Capital: A Digital Content Analysis of Tourism Narratives Tabuni, Gasper; Singgalen, Yerik Afrianto
Journal of Information System and Informatics Vol 6 No 3 (2024): September
Publisher : Universitas Bina Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51519/journalisi.v6i3.837

Abstract

This research investigates the role of digital narratives in promoting emerging destinations, with a focus on Indonesia's new capital (IKN). Utilizing the Digital Content Reviews and Analysis Framework, this study analyzed 248 digital posts, including social media posts and videos, to evaluate the effectiveness of tourism strategies that emphasize authentic cultural elements and unique regional attractions. The findings demonstrate that strategically crafted digital content significantly increases public awareness and interest in IKN. The analysis of 194 posts, through sentiment classification and toxicity scoring, reveals a predominantly positive public discourse, with an average toxicity score of 0.05541 and a maximum score of 0.90611. The sentiment classification model exhibited high accuracy (97.46% ± 3.00%) and precision (96.78% ± 4.17%), with a micro-average accuracy of 97.48%, and a notable AUC score of up to 0.999, indicating robust differentiation between positive and negative sentiments. These results underscore the practical implications of leveraging digital media to enhance tourism promotion strategies, suggesting that effective digital narratives, supported by comprehensive analytical frameworks and minimal toxicity, are crucial for converting interest into actual tourism activity. This approach positions IKN as a competitive entity in the global tourism market, emphasizing the importance of digital narratives in shaping international perceptions of new destinations.
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.
Social Media Management System for Educational Promotion Singgalen, Yerik Afrianto; Kartikawangi, Dorien; Winayu, Birgitta Narindri Rara
Journal of Information System and Informatics Vol 7 No 1 (2025): March
Publisher : Universitas Bina Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51519/journalisi.v7i1.1052

Abstract

Educational institutions, particularly tourism study programs, face significant challenges in managing fragmented and inefficient social media promotion strategies that hinder student recruitment and weaken institutional visibility. These problems arise from inconsistent content delivery, lack of stakeholder coordination, and limited performance monitoring and analytics capacity. To address these challenges, this research employs the Rapid Application Development (RAD) methodology through four stages: Requirements Planning, User Design, Construction, and Cutover. The requirement planning phase involved gathering aspirations from all stakeholders within the study program to ensure alignment in designing creative and effective promotional content. The resulting system integrates automated content workflows, scheduling algorithms, demographic-based audience targeting, and real-time performance analytics. The findings indicate substantial improvements in resource efficiency, precision of outreach, enrollment conversion rates, and institutional branding consistency. This research provides a comprehensive framework for transforming academic promotional practices through digital system integration, specifically tailored to the operational needs of educational institutions.
Digital Mapping of Fermented Foods for the Advancement of Gastronomy Tourism in Indonesia Singgalen, Yerik Afrianto; Kartikawangi, Dorien; Winayu, Birgitta Narindri Rara
Journal of Information System and Informatics Vol 7 No 2 (2025): June
Publisher : Universitas Bina Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51519/journalisi.v7i2.1055

Abstract

This research introduces a pioneering digital mapping framework for Indonesian fermented foods that integrates geospatial technologies with traditional gastronomic knowledge systems. Employing Rapid Application Development methodology on the Oracle APEX platform, the study establishes a comprehensive documentation infrastructure capturing the geographical distribution, production methodologies, and cultural significance of diverse fermentation practices across Indonesia's archipelagic landscape. The resulting prototype offers multifunctional capabilities through an intuitive interface design that serves preservation imperatives and tourism development objectives. Findings demonstrate that systematic digital documentation of fermented food traditions creates measurable economic opportunities through enhanced destination competitiveness, specialized culinary tourism routes, and improved market visibility for artisanal producers. The community-driven documentation protocols position local knowledge-holders as primary content contributors, while the system architecture establishes essential connections between geographical contexts and traditional fermentation techniques. This research addresses critical documentation gaps while establishing standardized protocols applicable beyond Indonesia to other regions with significant fermentation heritage. The digital mapping system ultimately functions as both a cultural preservation mechanism and a strategic asset for sustainable gastronomy tourism development, offering a replicable model for transforming endangered culinary knowledge into economically viable digital assets that benefit traditional food-producing communities.
Co-Authors A.Y. Agung Nugroho Abigail Rosandrine Kayla Putri Rahadi Agnes Harnadi Agnes Harnadi Agung Mulyadi Purba Alfonso Harrison Aloisius Gita Nathaniel Aprius Sutresno, Stephen 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 Eugenius Kau Suni 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 Henoch Juli Christanto Heru Prasadja 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 Ruben William Setiawan Samuel Piolo Seingo, Martha Maraka Setiawan, Ruben William Siemens Benyamin Tjhang Sri Yulianto Joko Prasetyo Stephen Aprius Sutresno Suharsono SUHARSONO Tabuni, Gasper Tharsini, Priya Titi Susilowati Prabawa Titis Puspitarini Widodo, Eko Winayu, Birgitta Narindri Rara Yan Dirk Wabiser Yoel Kristian Zsarin Astri Puji Insani