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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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Sentiment and Toxicity Analysis of Tourism-Related Video through Vader, Textblob, and Perspective Model in Communalytic Singgalen, Yerik Afrianto
Building of Informatics, Technology and Science (BITS) Vol 6 No 1 (2024): June 2024
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v6i1.5416

Abstract

This study leverages the Tourism and Travel Content Analysis (TTCA) framework to explore user sentiment and behavior in response to digital travel content. Utilizing sentiment analysis models such as VADER and TextBlob, the research analyzed 13,162 posts, revealing that 13.92% were negative, 15.02% neutral, and 71.06% positive, according to VADER. At the same time, TextBlob classified 10.47% as unfavorable, 26.51% as neutral, and 63.02% as positive. Additionally, toxicity scores calculated using Detoxify and Perspective models showed a range from low to high levels of toxic content, highlighting issues like identity attacks, insults, profanity, and threats. The findings underscore the effectiveness of well-crafted narratives in digital content for influencing tourist behavior and visit intentions. However, limitations were noted in the model's ability to fully capture emotional and cultural nuances. Future research should incorporate more advanced analytical tools and diverse datasets to overcome these limitations. Ultimately, the TTCA framework provides valuable insights for enhancing digital marketing strategies and improving user engagement in the tourism secto
The Role of Sentiment and Toxicity in Digital Narratives Surrounding Sulawesi's Wildlife Tourism: A Content Analysis for Enhancing Conservation Strategies Singgalen, Yerik Afrianto
Building of Informatics, Technology and Science (BITS) Vol 6 No 2 (2024): September 2024
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v6i2.5821

Abstract

This research explores the intersection of wildlife tourism and digital narratives, focusing on Sulawesi's endemic species. Utilizing the Digital Content Reviews and Analysis framework, the study combines content analysis, sentiment classification, and toxicity assessment to uncover critical insights. The findings highlight digital narratives' significant role in shaping public perceptions and behaviors toward conservation and ecotourism. Through systematic content analysis, themes such as biodiversity, conservation, and local community involvement emerged as effectively communicated, resonating with audiences and promoting sustainable tourism practices. The framework's structured approach enabled a thorough examination of digital content's impact on wildlife tourism narratives, identifying critical patterns and themes. The study also employed advanced machine learning techniques, specifically the SVM algorithm enhanced by SMOTE, which achieved a sentiment classification accuracy of 88.76% ± 3.11% and an AUC of 0.977, demonstrating its effectiveness. However, toxicity assessment revealed that while most interactions were civil, specific posts contained significant levels of toxicity, with a peak score of 0.64912, underscoring the need for better moderation and engagement strategies. The research emphasizes integrating conservation-focused elements into digital narratives to foster positive engagement and support for wildlife preservation. The study provides practical recommendations for enhancing the positive influence of digital narratives on conservation and sustainable tourism, offering a foundation for future initiatives to optimize digital communication strategies in ecotourism
Exploring Toxicity and Sentiment in Cultural Heritage Documentation: Content Analysis of Sabu Island's Portrayal in KOMPASTV's Expedition Singgalen, Yerik Afrianto
Building of Informatics, Technology and Science (BITS) Vol 6 No 2 (2024): September 2024
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v6i2.5838

Abstract

This study explores the dual role of media in preserving and potentially distorting cultural heritage, focusing on the portrayal of Sabu Island in KOMPASTV's expedition documentary. Utilizing the Digital Content Reviews and Analysis Framework, the research comprehensively dissection the documentary’s content, uncovering critical insights into the intricate relationship between tourism, cultural preservation, and media representation. By integrating sentiment and toxicity analysis, the study identifies the emotional tone and harmful language present within digital narratives, with the toxicity analysis revealing an average score of 0.09886 and a peak score of 0.83647, indicating the potential influence of negative discourse on cultural heritage. The sentiment classification, conducted through a Support Vector Machine (SVM) model enhanced by SMOTE, demonstrated robust performance metrics, including an accuracy of 66.43%, precision of 60.51%, recall of 94.98%, and an F-measure of 73.90%, with an AUC ranging from 0.728 to 0.904. Additionally, content analysis centered on key themes such as Economic Impact, Sacred Rituals, Tourist Experience, and Weaving Traditions, revealing the complex dynamics where cultural preservation must be balanced with economic development and tourism demands. The findings emphasize the need for responsible and authentic media portrayals to safeguard cultural identities, as media holds the power to uphold or undermine cultural narratives' integrity. This research contributes to the broader discourse on cultural heritage documentation by offering a comprehensive framework for evaluating the impact of digital narratives on the preservation of cultural identities, ensuring the accurate and respectful portrayal of cultural heritage.
An Analysis of User Engagement in the Reviews of The Guardian of Nusantara Official Music Video: Toxicity and Sentiment Analysis Singgalen, Yerik Afrianto
Building of Informatics, Technology and Science (BITS) Vol 6 No 2 (2024): September 2024
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v6i2.5846

Abstract

This study investigates user engagement within digital environments, explicitly focusing on creative content like music videos, and examines how sentiment and toxicity levels in user interactions influence engagement dynamics. Employing the Digital Content Reviews and Analysis Framework, the study reveals that 95.8% of user interactions exhibit positive or neutral sentiments. In comparison, a notable 4.2% are toxic, reflecting underlying societal tensions and potentially perpetuating negative feedback loops. Analysis of 23,112 posts using the Perspective API shows an average toxicity score of 0.03972, with severe cases reaching up to 0.87787. Scores for severe toxicity, identity attacks, insults, profanity, and threats, although generally low, indicate maximum values of concern, highlighting the need for vigilant monitoring. Sentiment classification results using the VADER model and multiple algorithms demonstrate that the Support Vector Machine (SVM) model achieved the highest accuracy (68.74%) and Area Under Curve (AUC) score (0.686), outperforming other models in distinguishing sentiment. The study's discussion on user engagement suggests that high levels of participation, such as comments, likes, and shares, are indicators of user interest and community identity but are susceptible to being undermined by toxic interactions. These findings emphasize the importance of fostering positive engagement through effective moderation strategies and advanced sentiment analysis tools, ensuring digital platforms remain conducive to constructive dialogue and community building. The research underscores the necessity for sophisticated analytical approaches to navigate the complexities of user behavior in digital spaces, providing critical insights into the interplay between sentiment, engagement, and toxicity in shaping online communities.
Pandemi Covid-19 dan Keberlanjutan Bisnis Mikro-Kecil di Kota Sejarah Gastronomi: Pendekatan Penghidupan Berkelanjutan Singgalen, Yerik Afrianto
MANAJEMEN IKM: Jurnal Manajemen Pengembangan Industri Kecil Menengah Vol. 17 No. 1 (2022): Manajemen IKM
Publisher : Institut Pertanian Bogor

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29244/mikm.17.1.33-41

Abstract

The Covid-19 pandemic causes challenges and threats to micro and small businesses' unsustainability. This study aims to describe the dynamics of micro and small business actors in maintaining business continuity based on a sustainable livelihood framework. This research is located in Salatiga City, Central Java Province, Indonesia. The research method used is qualitative, with a case study approach to traditional culinary businesses and coffee shops. These findings indicate that the Covid-19 pandemic urges the government to take a Large-Scale Social Restrictions (PSBB) policy to the Enforcement of Community Activity Restrictions (PPKM) policy. Also, the obligation to implement health protocols to Clean, Health, Safety, and Environment (CHSE) certification for food and beverage businesses. The policy has limited the mobility and access capabilities of traditional culinary business entrepreneurs and coffee shops to social capital and financial capital, as observed by several culinary businesses and coffee shops that showed a quiet condition of visitors during the PPKM in force. To maintain business continuity during the pandemic, coffee shop entrepreneurs innovate products and business processes by utilizing digital platforms for online marketing; some culinary businesses and coffee shops use service on-demand applications to market food and beverages so that they can be accessed by buyers and still earn income during the PPKM applies. Thus, it shows that diversification and intensification are needed to support sustainable businesses and livelihoods during the Covid-19 pandemic.
Pendekatan Komunikasi Interpersonal dalam Pembangunan berdasarkan Perspektif Kultural (Studi Kasus : Pro-Kontra Pengembangan Pariwisata Pulau Meti di Kabupaten Halmahera Utara) Singgalen, Yerik Afrianto
Jurnal InterAct Vol. 9 No. 1 (2020): Jurnal InterAct
Publisher : School of Communication - Atma Jaya Catholic University of Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25170/interact.v9i1.1707

Abstract

This article aims to describe the interpersonal communication approach for development based on the perspective of the Hibualamo culture forthe people of Meti Village in the case of the pros and cons of tourism development on Meti Island in North Halmahera Regency. The researchmethod used is qualitative with a case study approach. Meanwhile, the data collection technique used in-depth interviews, observation anddocument study. The results of this study indicate that the existence of the Tourism Industry in this case Meti Cottage on Meti Island canincrease regional investment and maintain environmental sustainability, but it has not been able to provide economic and social benefits for localcommunities because of the pros and cons. Culturally, the interpersonal communication approach plays an important role in the level of publicacceptance of increasing investment in the tourism industry. However, the conflict between the manager of the tourist attraction and thecommunity related to empowerment and resource use has resulted in a disintegration of interests for sustainable tourism.
Implementation of SVM, k-NN, and DT for Toxicity and Sentiment Classification of AWA Vlog Content in Wasur National Park Singgalen, Yerik Afrianto
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 8, No 2 (2024): April 2024
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v8i2.7434

Abstract

This study delves into the response of viewers to video content focusing on Wasur National Park in Papua, Indonesia, with a particular emphasis on its implications for livelihood and ecology. The increasing popularity of online platforms such as YouTube has provided a medium for content creators to showcase natural landscapes and cultural heritage, potentially influencing viewers' perceptions and behaviors toward conservation efforts. Employing the CRISP-DM (Cross-Industry Standard Process for Data Mining) framework, this research systematically analyzes a specific video from the AWA channel, known for its documentaries on environmental and cultural topics. The methodology involves sentiment analysis to gauge viewers' emotional responses, toxicity assessment to identify harmful content, and thematic coding to categorize comments based on recurring themes. The analysis reveals that viewers engage with the content positively, expressing appreciation for the video's educational and visually compelling nature. Moreover, the study identifies various dimensions of toxicity within the dataset, including Toxicity (0.05364), Severe Toxicity (0.00629), Identity Attack (0.02250), Insult (0.03534), Profanity (0.03589), and Threat (0.01280). Furthermore, the performance of the Support Vector Machine (SVM) with Synthetic Minority Over-sampling Technique (SMOTE) is highlighted, demonstrating its effectiveness in classifying sentiment with an accuracy of 93.86%, precision of 100.00%, recall of 87.73%, f-measure of 93.44%, and an Area Under the Curve (AUC) value of 1.000. This research underscores the significance of balanced media portrayals in fostering positive attitudes toward environmental conservation and cultural preservation.
Sentiment Classification of The Capsule Hotel Guest Reviews using Cross-Industry Standard Process for Data Mining (CRISP-DM) Singgalen, Yerik Afrianto
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 8, No 1 (2024): Januari 2024
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v8i1.7329

Abstract

Technology advancements empower hotel accommodation service managers to undertake innovative initiatives to enhance guest appeal and ensure safety and comfort. One manifestation of such innovation is exemplified by The Capsule Hotel, which offers novel experiences to both domestic and international tourists. This research seeks to assess the sentiments of guests at The Capsule Malioboro, employing the Cross-Industry Standard Process for Data Mining (CRISP-DM) methodology and the Support Vector Machine (SVM) technique with Synthetic Minority Over-sampling Technique (SMOTE) operators. The findings demonstrate that when operated without SMOTE, the SVM algorithm yields a confusion matrix displaying an accuracy of 99.01%, precision of 99.00%, recall of 100%, AUC of 0.944, and an f-measure of 99.49%. With the integration of SMOTE, there is a notable enhancement across all metrics, with accuracy, precision, recall, AUC, and f-measure, all achieving perfect scores of 100%. In addition, an analysis of the top 10 frequently used words in guest reviews, such as "solo," "good," "place," "staff," "comfortable," "room," "clean," "hotel," "capsule," and "Malioboro," provides additional insights. Examining guest profiles within the dataset uncovers a strong inclination among Indonesian individuals to opt for The Capsule Malioboro's services, with solo travelers being the predominant guest type and most stays lasting only a single day. The capsule accommodations cater to various gender preferences, and an examination of overnight data indicates a rising trend, particularly in December 2022 and 2023. These insights enable the hotel to discern guest preferences, offering valuable information for enhancing service ratings and addressing specific needs.
Toxicity, Sentiment, and Social Network Analysis (SNA) of Borneo Death Blow Video Documentary Reviews Singgalen, Yerik Afrianto
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 8, No 2 (2024): April 2024
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v8i2.7633

Abstract

The study aimed to evaluate sentiment classification models using toxicity scores and to conduct Social Network Analysis (SNA) to understand network dynamics. The research used CRISP-DM methodology to comprehensively analyze sentiment classification models and toxicity scores. It utilized various machine learning algorithms, including Decision Tree (DT), Support Vector Machine (SVM), and Naive Bayes Classifier (NBC), with Synthetic Minority Over-sampling Technique (SMOTE) to address class imbalance. In addition, Social Network Analysis (SNA) was conducted to examine network properties and dynamics. The findings revealed varying toxicity scores, ranging from 0.12409 to 0.98808, across different categories, such as general toxicity, severe toxicity, identity attacks, insults, profanity, and threats. Evaluation of sentiment classification models indicated that the SVM model with SMOTE achieved the highest accuracy of 92.57% +/- 1.17% (micro average: 92.57%), followed by the NBC model with an accuracy of 78.24% +/- 1.30% (micro average: 78.24%), and the DT model with an accuracy of 61.16% +/- 1.20% (micro average: 61.16%). Despite variations in model performance, the SVM model consistently demonstrated robust performance across various evaluation metrics. Furthermore, the SNA findings provided insights into network structural characteristics, including Average Degree, Average Weighted Degree, Diameter, Radius, and Average Path Length, facilitating a comprehensive understanding of network organization and behavior. These findings contribute to advancing the understanding of sentiment analysis models and network dynamics in digital environments.
Enhancing Sentiment Analysis of Garden by the Bay Reviews on TripAdvisor Platform Using CRISP-DM through DT and SVM with SMOTE Singgalen, Yerik Afrianto
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 8, No 2 (2024): April 2024
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v8i2.7485

Abstract

This research aims to improve sentiment analysis of reviews related to Garden by the Bay, a prominent tourist destination in Singapore, by leveraging the CRISP-DM methodology and Synthetic Minority Over-sampling Technique (SMOTE). The study employs a comprehensive approach, integrating CRISP-DM phases to systematically collect, clean, and analyze data from online reviews. The dataset comprises a substantial number of reviews, reflecting diverse visitor experiences. Using SMOTE, class imbalance issues within the dataset are addressed, leading to enhanced performance of sentiment analysis algorithms. The evaluation of Decision Tree (DT) and Support Vector Machine (SVM) algorithms, both with and without SMOTE, reveals significant improvements in accuracy, precision, recall, and F-measure metrics when SMOTE is applied. These findings underscore the efficacy of SMOTE in optimizing sentiment analysis algorithms for the Garden by the Bay dataset, thereby facilitating a deeper understanding of visitor sentiments and experiences, which inform strategies for enhancing the tourism experience at Garden by the Bay.
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