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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
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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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.
Comparative analysis of k-NN and DT model in sentiment classification of Labuan bajo-wonderful Indonesia content reviews Singgalen, Yerik Afrianto
Jurnal Mantik Vol. 8 No. 1 (2024): May: 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.v8i1.5076

Abstract

This research investigates the efficacy of sentiment classification models, specifically k-NN and DT algorithms, in the context of destination branding, with a focus on Labuan Bajo tourism. Utilizing the CRISP-DM (Cross-Industry Standard Process for Data Mining) framework, the study systematically navigates through all six stages, including business understanding, data understanding, data preparation, modeling, evaluation, and deployment, to analyze textual reviews and gauge public sentiments towards Labuan Bajo. The findings reveal that both k-NN and DT models exhibit high accuracy and precision, with k-NN achieving an average accuracy of 97.79% and DT 97.52%. While k-NN demonstrates commendable performance in recall, DT exhibits superior discriminative power, particularly when integrated with SMOTE, as evidenced by higher AUC values. The research underscores the importance of leveraging advanced machine learning techniques for sentiment analysis to inform destination branding strategies effectively. These insights provide valuable guidance for stakeholders in enhancing the branding and promotion of Labuan Bajo as a premier tourist destination, ultimately contributing to its sustainable development and global recognition
Performance evaluation of SVM with synthetic minority over-sampling technique in sentiment classification Singgalen, Yerik Afrianto
Jurnal Mantik Vol. 8 No. 1 (2024): May: 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.v8i1.5077

Abstract

This study investigates the performance of the Support Vector Machine (SVM) algorithm in sentiment analysis tasks within the context of tourism destination branding, utilizing the Cross-Industry Standard Process for Data Mining (CRISP-DM) framework. Specifically, the research compares SVM performance with and without the Synthetic Minority Over-sampling Technique (SMOTE) across various metrics including accuracy, precision, recall, F-measure, and Area Under the Curve (AUC). The analysis is conducted on a dataset comprising textual data extracted from "Wonderful Indonesia" promotional videos featuring Labuan Bajo. Results indicate that SVM without SMOTE achieves a slightly higher accuracy of 97.79% compared to 96.61% with SMOTE. However, a closer examination reveals that SVM without SMOTE accurately classifies all positive instances, while with SMOTE, one positive instance is misclassified as negative. Precision, recall, and F-measure scores for positive instances are also higher without SMOTE, indicating better performance in classifying positive sentiment
Exploring digital discourse: social network analysis approach to toxicity and interaction patterns Singgalen, Yerik Afrianto
Jurnal Mantik Vol. 8 No. 1 (2024): May: 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.v8i1.5078

Abstract

This study employs Social Network Analysis (SNA) to investigate the structural characteristics, dynamics, and toxicity levels within a digital discourse ecosystem. Using a dataset comprising threaded discussions and chain networks, we analyze the interactions among users and quantify the presence of harmful language. The SNA reveals a network comprising 453 nodes and 330 edges, highlighting the intricate web of connections among users. Additionally, toxicity analysis uncovers nuanced patterns of toxicity, with scores ranging from 0.01129 to 0.05852 across different categories. Further examination of network metrics such as Density, Reciprocity, Centralization, and Modularity provides insights into the network's organization and communication dynamics. Our findings offer valuable insights for content moderation, community management, and promotional strategies in fostering a safer and more inclusive online environment. This research contributes to advancing knowledge in digital communication and provides a foundation for future studies exploring challenges within online communities
Sentiment and Toxicity Analysis in the Narratives of Wamena's Cultural Heritage: Understanding Community Perspectives and External Influences Yan Dirk Wabiser; Yerik Afrianto Singgalen
KLIK: Kajian Ilmiah Informatika dan Komputer Vol. 5 No. 1 (2024): Agustus 2024
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/klik.v5i1.1941

Abstract

This study analyzes digital narratives surrounding Wamena's cultural heritage using the Digital Content Reviews and Analysis Framework, focusing on sentiment, toxicity, and thematic content. The research explores the complex interplay between community perspectives, cultural preservation, modernization, and external influences such as tourism. Toxicity analysis revealed that while most online discourse is supportive, there are instances of harmful language that could disrupt social cohesion, with toxicity scores peaking at 0.50790. These findings highlight the need for continuous moderation to foster a positive digital environment. Sentiment analysis provided a deeper understanding of emotional tones, showing a predominance of positive sentiments and highlighting frustration and dissent related to cultural erosion. The study employed machine learning algorithms for sentiment and toxicity classification, with the Support Vector Machine (SVM) enhanced by Synthetic Minority Over-sampling Technique (SMOTE) demonstrating superior accuracy at 87.29%. Content analysis identified vital themes such as community dynamics, cultural resilience, and the dual impact of tourism as both an economic catalyst and a potential threat to cultural integrity. The findings underscore the importance of maintaining an inclusive digital environment that promotes constructive dialogue and cultural preservation. This framework provides valuable insights for policymakers and community leaders, emphasizing the need for culturally sensitive strategies to manage digital content and support sustainable cultural tourism. Future research should expand this framework to other contexts to enhance the understanding of digital communication dynamics in diverse cultural settings.
Sentiment and Toxicity Score Evaluation of DJI Avata Product Reviews Using Cross-Industry Standard Process for Data Mining Singgalen, Yerik Afrianto
KLIK: Kajian Ilmiah Informatika dan Komputer Vol. 4 No. 6 (2024): Juni 2024
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/klik.v4i6.1946

Abstract

This research employs the CRISP-DM framework to analyze consumer sentiment and preferences regarding DJI Avata drone products, aiming to provide data-driven strategic recommendations for marketing and product development. By systematically exploring business objectives, preparing and cleaning data, and modeling sentiment, the study reveals high consumer engagement and predominantly positive sentiment (51.91% positive, 31.16% neutral, 16.93% negative) towards the DJI Avata. The Support Vector Machine (SVM) algorithm demonstrated superior performance in sentiment classification, achieving an accuracy of 74.69%, with an AUC of 0.839, precision of 77.57%, recall of 69.68%, and F-measure of 73.23%. A comparative analysis between the VADER and TextBlob models, showing a moderate agreement (Cohen’s kappa statistic = 0.413) on 64.84% of the posts, highlighted the value of using multiple sentiment analysis tools. Furthermore, toxicity scores calculated via the Perspective API identified critical areas for improvement in user engagement. Subsequently, the toxicity results reveal the following scores: Toxicity with an average of 0.09461 and a peak of 0.90451, Severe Toxicity with an average of 0.00817 and a peak of 0.45895, Identity Attack with an average of 0.01139 and a peak of 0.58743, Insult with an average of 0.04543 and a peak of 0.70658, Profanity with an average of 0.06133 and a peak of 0.89080, and Threat with an average of 0.02063 and a peak of 0.69437. These detailed metrics provide a comprehensive understanding of the dataset's different dimensions and intensities of negative sentiments. The significant variation between average and peak values indicates the presence of highly negative interactions, which necessitates targeted intervention. Consequently, these findings inform the development of specific strategies to mitigate toxicity and enhance the overall user experience in digital communities. These insights informed strategic recommendations to enhance digital marketing efforts and product features, underscoring the CRISP-DM framework's efficacy in guiding comprehensive consumer sentiment analysis and fostering informed decision-making in the aerial photography and videography market.
Understanding Digital Engagement through Sentiment Analysis of Tourism Destination through Travel Vlog Reviews Singgalen, Yerik Afrianto
KLIK: Kajian Ilmiah Informatika dan Komputer Vol. 4 No. 6 (2024): Juni 2024
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/klik.v4i6.1947

Abstract

This research employs the CRISP-DM framework to analyze digital engagement through travel vlog content, explicitly focusing on vlogs about Gili Trawangan. The study systematically follows the CRISP-DM phases: business understanding, data understanding, data preparation, modeling, evaluation, and deployment. Utilizing the VADER sentiment analysis model and the SVM algorithm with SMOTE, the research achieves a high level of accuracy in sentiment classification, with the SVM model demonstrating an accuracy of 88.57% +/- 5.11% and a precision of 90.95% +/- 5.09%. Analysis of 442 cleaned and labeled data points reveals a strong dominance of positive sentiments, with 62.61% in the first video and 84.25% in the second video. These findings underscore the effectiveness of travel vlogs in engaging viewers and generating positive interactions as powerful tools for tourism marketing. The study concludes that the CRISP-DM framework is highly effective in facilitating comprehensive sentiment analysis and enhancing strategic tourism marketing initiatives.
Understanding Tourism Destination through Music: Digital Engagement Discourse Based on Sentiment Analysis Approach Singgalen, Yerik Afrianto
KLIK: Kajian Ilmiah Informatika dan Komputer Vol. 4 No. 6 (2024): Juni 2024
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/klik.v4i6.1950

Abstract

This research investigates the effectiveness of music-video content as a tool for tourism destination marketing, employing the CRISP-DM framework to approach data collection, analysis, and interpretation systematically. Focusing on the music video "Welcome to Sumba Island" by Marapu Reggae Official, the study analyzes public sentiment and toxicity scores to gauge audience engagement. The findings reveal a predominance of positive sentiments and minimal toxicity, with scores such as 0.02117 for general toxicity and 0.00189 for severe toxicity, indicating a respectful and appreciative audience. The Decision Tree (DT) algorithm, enhanced by the SMOTE operator, demonstrated superior performance in sentiment classification, achieving an accuracy of 95.50% and an AUC of 0.979. While the study's focus on a single music genre and location limits generalizability, it highlights the potential of music videos in tourism marketing. Future research should expand to diverse music genres and destinations and integrate mixed-method approaches for deeper insights. The CRISP-DM framework's effectiveness in this study underscores its value in guiding sentiment analysis and developing impactful tourism marketing strategies
Integrating Remote Sensing and Spatial Data for Ecological Sustainability through Spatio-temporal Analysis Singgalen, Yerik Afrianto
KLIK: Kajian Ilmiah Informatika dan Komputer Vol. 5 No. 1 (2024): Agustus 2024
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/klik.v5i1.2082

Abstract

This research underscores the pivotal role of integrating spatial data and remote sensing technologies within a spatio-temporal analysis framework for regional development planning. Analyzing NDVI, NDBI, and SAVI values from 2013, 2018, and 2024 provided significant insights into vegetation health, urbanization, and soil conditions on Kumo Island. The NDVI values exhibited changes from a minimum of -0.0549, a mid-value of 0.1782, and a maximum of 0.4690 in 2013 to a minimum of 0.2456, a mid-value of 0.8296, and a maximum of 0.9416 in 2024. Similarly, the NDBI values shifted from a minimum of -0.8734, a mid-value of -0.5779, and a maximum of 0.0009 in 2013 to a minimum of -0.6561, a mid-value of -0.4304, and a maximum of 0.0247 in 2024. The SAVI values showed notable changes from a minimum of -0.0365, a mid-value of 0.1245, and a maximum of 0.3814 in 2013 to a minimum of 0.1138, a mid-value of 0.4953, and a maximum of 0.6160 in 2024. These findings highlight the importance of ecological sustainability in decision-making processes, demonstrating how advanced spatial analysis within a spatio-temporal framework can effectively monitor and manage land use changes. The urgency of this research lies in addressing rapid environmental changes and escalating human activities, necessitating timely and accurate monitoring techniques. The study reveals the utility of the NDVI, NDBI, and SAVI indices in assessing vegetation health, urbanization, and soil conditions, which are instrumental in identifying trends and informing sustainable development strategies. The research advocates for the continued use of remote sensing and spatial data to ensure balanced and informed regional development, emphasizing the necessity of sustainable practices to preserve ecological integrity while supporting socio-economic growth. Integrating remote sensing into the decision-making process enhances the accuracy and reliability of spatial data, leading to more effective and responsible regional development
Comparative Spatio-temporal Analysis Using NDVI, NDBI, and SAVI based on Landsat 8/9 OLI (2013, 2018 and 2024) Singgalen, Yerik Afrianto
KLIK: Kajian Ilmiah Informatika dan Komputer Vol. 5 No. 1 (2024): Agustus 2024
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/klik.v5i1.2088

Abstract

The research on the comparative spatio-temporal analysis of NDVI, NDBI, and SAVI values for Kumo Island, Kakara Island, and Tagalaya Island from 2013, 2018, and 2024 offers insights into environmental dynamics influenced by human activities, particularly tourism. Key findings indicate that NDVI values, reflecting vegetation health, improved across all three islands, with Kumo Island showing the most significant increase from -0.0549 in 2013 to 0.2456 in 2024. NDBI values, indicative of urban development, also rose on all islands. Kumo Island's NDBI increased from -0.8734 in 2013 to -0.6561 in 2024, and Kakara Island's NDBI rose from -0.8838 in 2013 to -0.7183 in 2024. Tagalaya Island saw a more moderate rise in NDBI values from -0.8818 in 2013 to -0.7118 in 2024, suggesting controlled urban expansion. SAVI values, reflecting soil and vegetation conditions, also improved. Kumo Island's SAVI increased from -0.0365 in 2013 to 0.1138 in 2024, Kakara Island's from -0.1161 to -0.0319, and Tagalaya Island's from -0.1652 to -0.0732. These trends indicate effective soil conservation and sustainable land use practices. The findings highlight the dual impact of urbanization and environmental conservation, suggesting that while urbanization progresses, vegetation health and soil conditions are concurrently improving. This underscores the potential for balancing development with ecological sustainability through targeted conservation efforts. Future research should identify specific practices and policies contributing to these positive trends, ensuring economic development and environmental preservation can continue to coexist harmoniously on these islands
Co-Authors A.Y. Agung Nugroho Agnes Harnadi Agnes Harnadi Agung Mulyadi Purba Alfonso Harrison Aloisius Gita Nathaniel 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 Titi Susilowati Prabawa Titis Puspitarini Widodo, Eko Winayu, Birgitta Narindri Rara Yan Dirk Wabiser Yoel Kristian Zsarin Astri Puji Insani