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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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Penerapan Metode Evaluation based on Distance from Average Solution (EDAS) dalam Optimalisasi Layanan dan Pemasaran Coffeeshop Yerik Afrianto Singgalen
Journal of Computer System and Informatics (JoSYC) Vol 5 No 1 (2023): November 2023
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josyc.v5i1.4460

Abstract

Business owners of coffee shops that fall under the Micro, Small, and Medium Enterprises (MSMEs) employ marketing methods to attract more clients to satisfy the demands and preferences of coffee enthusiasts. However, consumer purchasing behavior demonstrates the difficulty in evaluating marketing performance. In light of this, this study employs the Distance from Average Solution Evaluation Method (EDAS). Meanwhile, coffee shop business brands observed and used as alternatives in this study are Coffee Tanem, 1915 Koffie-Huis, Friends of Coffee Salatiga, Dusk Koffie Salatiga, and Street Side Coffee Salatiga. The results of this study show that the EDAS method can be used to optimize coffee shop business services and marketing as a strategic step in strengthening and improving the performance of the coffee shop business or business. In the context of testing the EDAS decision model, each alternative is assigned a random code (A1-A5). Coffee varieties (C1), aroma and roasted level (C2), serving technique variants (C3), beverage prices (C4), and coffeeshop locations (C5) are often employed as criteria, with categories C1–C3 representing advantages, and C4–C5 representing expenses. Based on the EDAS method's calculation results, it can be seen that the top-ranking coffee shops are those that offer a variety of coffee bean varieties (robusta and arabica), various aromas, and roasted levels (light, medium, dark), various serving methods using espresso machines and manual brew, affordable drink prices, and strategically located coffee shops with enough parking. Thus, it is advised that coffee shop business experts assist in improving capital capabilities and business performance and optimize marketing mix components in STP (Segmenting, Targeting, Positioning) marketing strategies to increase trust, sales volume, consumer satisfaction, and loyalty.
Penerapan Metode Additive Ratio Assessment (ARAS) dan Ranking of Centroid (ROC) dalam Pemilihan Layanan Akomodasi dan Local Cuisine Yerik Afrianto Singgalen
Journal of Computer System and Informatics (JoSYC) Vol 5 No 1 (2023): November 2023
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josyc.v5i1.4569

Abstract

Salatiga is a gastronomic city with various types of traditional food and drinks and is a recreational tourism city with exciting and crowded mountain natural scenery. The availability of accommodation services and local cuisine adds to visitors' preferences to enjoy local culinary dishes. This study offers an initiative to use the Additive Ratio Assessment (ARAS) method in selecting the best accommodation and restaurant services in Salatiga based on Tripadvisor data. The stages in the calculation process based on the ARAS method are as follows: the stage of determining the value of criteria, weights, alternatives, and optimal values; the stage of converting the value of the criterion into a decision matrix; the stage of normalization of the decision matrix for all criteria; stage of calculating the value of utility; Ranking stage. The calculation results show that in the context of accommodation services, A5 occupies the first position with a Ki value of 0.887, A4 occupies the second position with a Ki value of 0.870, and A1 occupies the third position with a Ki value of 0.849. Meanwhile, in the context of local cuisine, A2 occupies the first position with a Ki value of 0.951, A5 occupies the second position with a Ki value of 0.914, and A4 occupies the third position with a Ki value of 0.854. This shows that ARAS and ROC methods can produce the best recommendations for tourists who want to use accommodation services and enjoy local cuisine in Salatiga City.
Perbandingan Metode ARAS dan EDAS dalam Menghasilkan Rekomendasi Layanan Akomodasi Hotel Yerik Afrianto Singgalen
Journal of Computer System and Informatics (JoSYC) Vol 5 No 1 (2023): November 2023
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josyc.v5i1.4574

Abstract

This study compares the decision support model Additive Ratio Assessment (ARAS) and Evaluation based on Distance from Average Solution (EDAS) in selecting hotels in Semarang City. Meanwhile, the criterion-setting method adopts the Ranking of Centroid (ROC) to set criteria, determine the priority of criteria, and determine the weight of the criteria values. Comparison of the two algorithms needs to be done to compare the results and test the performance of the two algorithms, when developed into a decision support application to generate hotel service recommendations. Meanwhile, the stages in this research are as follows: data collection stage, using TripAdvisor; data processing stage, using ARAS and EDAS models; and data analysis stage. The results of this study show that the ranking results based on the EDAS method show that A1 occupies the first position with an NSP value of 1,000 and an NSN of 0,983. Furthermore, A3 occupies the second position with an NSP value of 0.707 and an NSN of 0.983. Meanwhile, A2 occupies the third position with an NSP value of 0.311 and an NSN of 0.983. Furthermore, the ARAS method ranking results show that A1 occupies the first position with a Si value of 0.171 and a Ki value of 0.994. Furthermore, A3 occupies the second position with a Si value of 0.169 and a Ki value of 0.984. Meanwhile, A2 occupies the third position with a Si value of 0.167 and a Ki value of 0.970. Based on the comparison of EDAS and ARAS methods, it can be seen that both produce the same alternative ranking where Padma Hotel Semarang ranks first, Aruss Hotel Semarang ranks second, and Tentrem Hotel Semarang ranks third. Thus, it can be seen that EDAS and ARAS methods can produce the best hotel recommendations for travelers by considering ratings and reviews on the TripAdvisor platform.
Toxicity and Social Network Analysis of Green Marketing Content for Electric Cars through Digital Media Yerik Afrianto Singgalen
International Journal on Social Science, Economics and Art Vol. 13 No. 4 (2024): February: Social Science, Economics
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

This study aims to investigate the effectiveness of green marketing strategies in influencing consumer interest and purchasing behavior towards electric cars, focusing on media coverage, as exemplified by BBC News. Specifically, it seeks to understand how media portrayals of electric cars through green marketing narratives impact consumer perceptions and preferences in the context of sustainability. The research adopts the Cross Industry Standard Process for Data Mining (CRISP-DM) methodology. The study culminates in noteworthy findings obtained through Toxicity Analysis and Social Network Analysis (SNA). Toxicity Analysis yielded specific numerical values across categories: Toxicity (0.05645, 0.99613), Severe Toxicity (0.00002, 0.00333), Identity Attack (0.00211, 0.35185), Insult (0.03630, 0.99520), Profanity (0.01584, 0.93590), and Threat (0.00279, 0.43515). These metrics signify varying levels of negative sentiment and potentially harmful language within the examined dataset. Concurrently, SNA provided structural insights with a diameter of 6, low density (0.009484), negligible reciprocity (0.000000), modest centralization (0.038160), and high modularity (0.872000). While the network exhibits centralized influence and limited reciprocity, the high modularity suggests distinct communities or clusters. These findings underscore the importance of considering sentiment dynamics and network structure, emphasizing the need for targeted interventions to mitigate toxicity and cultivate healthier communication environments.
Social network and sentiment analysis of product reviews (case of smartwatch product content) Yerik Afrianto Singgalen
International Journal on Social Science, Economics and Art Vol. 13 No. 4 (2024): February: Social Science, Economics
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

This study addresses the need to understand the dynamics of sentiment and social network analysis (SNA) in the context of smartwatch product reviews. Leveraging the CRoss-Industry Standard Process for Data Mining (CRISP-DM) methodology, the research aims to analyze sentiments and social networks to glean insights into consumer behavior and interaction patterns. The CRISP-DM framework guides the research through structured phases of business understanding, data understanding, data preparation, modeling, evaluation, and deployment. Through sentiment analysis using Support Vector Machine (SVM) with Synthetic Minority Over-sampling Technique (SMOTE) and SNA, the study examines accuracy (91.41% +/- 1.66%), precision (100.00% +/- 0.00%), recall (82.80% +/- 3.36%), f-measure (90.56% +/- 2.01%), Area Under the Curve (AUC), as well as network metrics such as diameter (4), density (0.001036), reciprocity (0.000000), centralization (0.004920), and modularity (0.994200). Findings reveal a robust performance of the SVM algorithm coupled with SMOTE, showcasing high accuracy and effective discrimination between sentiments. Additionally, SNA uncovers valuable insights into network structures, communication patterns, and sentiment propagation dynamics within the online community. These findings contribute to a deeper understanding of consumer sentiments and interactions, guiding strategic marketing, product development, and reputation management decisions.
Selling vegetables through live streaming: sentiment and network analysis Yerik Afrianto Singgalen
International Journal on Social Science, Economics and Art Vol. 13 No. 4 (2024): February: Social Science, Economics
Publisher : Institute of Computer Science (IOCS)

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Abstract

This study addresses the research problem of understanding digital interactions and dynamics in online environments, mainly focusing on sentiment analysis and Social Network Analysis (SNA). The methodology integrates sentiment analysis techniques to discern prevailing attitudes and emotions within digital content, coupled with SNA to unveil intricate network structures and user relationships. Concurrently, SNA unveils intricate network structures and relationships among users, illuminated by numerical metrics such as Diameter (2), Density (0.003982), Reciprocity (0.000000), Centralization (0.027240), and Modularity (0.978600). Additionally, the performance vector further enhances the evaluation with metrics including accuracy (97.68% +/- 2.44%), AUC (0.429 +/- 0.477), precision (97.68% +/- 2.44%), recall (100.00% +/- 0.00%), and f-measure (98.81% +/- 1.25%). The study utilizes a dataset of digital content and user interactions, applying sentiment analysis to quantify sentiments and SNA to map network connections. Findings reveal nuanced insights into audience perceptions, engagement patterns, and network dynamics within digital ecosystems. Moreover, the study employs numerical metrics to evaluate the performance of sentiment analysis and SNA methodologies. The results underscore the importance of integrating sentiment analysis and SNA in comprehensively understanding online behavior and communication dynamics, offering valuable insights for content creation, engagement optimization, and community management strategies in digital environments.
Digital marketing of smartphone manufacturing product: toxicity, social network, and sentiment classification Yerik Afrianto Singgalen
International Journal on Social Science, Economics and Art Vol. 14 No. 1 (2024): May: Social Science, Economics
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/ijosea.v14i1.442

Abstract

This research explores digital interactions, analyzing toxicity, sentiment, and network dynamics using the Cross-Industry Standard Process for Data Mining (CRISP-DM) methodology. Understanding and managing these elements are crucial for effective digital strategies with the rise of user-generated content. Leveraging machine learning, including Support Vector Machines (SVM) and Synthetic Minority Over-sampling Technique (SMOTE), toxicity analysis and sentiment classification are conducted. Data preprocessing involves text cleaning and feature engineering, aligning with the CRISP-DM data preparation phase. Toxicity levels are measured using various toxicity metrics, including Toxicity, Severe Toxicity, Identity Attack, Insult, Profanity, and Threat. Sentiment analysis employs SVM to classify sentiment polarity, while SMOTE addresses class imbalance as part of the CRISP-DM modeling phase. Social Network Analysis (SNA) techniques are also applied to study network structures following the CRISP-DM modeling phase. Network data are processed to compute key SNA metrics such as Diameter, Density, Reciprocity, Centralization, and Modularity. Findings reveal a toxicity level of 0.06194 and severe toxicity at 0.00730. Identity Attack stands at 0.01107, while insults and profanity are at 0.03803 and 0.04905, respectively. The threat is observed at 0.01359. The sentiment analysis indicates an accuracy of 97.94%, with a precision and recall of 98.07% and 99.86%, respectively, for the positive class. The f-measure for the positive class is 98.96%. The SNA metrics show a diameter of 4, a density of 0.000266, and a reciprocity of 0.000000. Centralization is calculated at 0.001468, while modularity stands at 0.999400.
Comprehensive analysis of tempel hamlet digital content reviews: Toxicity, sentiment, and social network Yerik Afrianto Singgalen
International Journal on Social Science, Economics and Art Vol. 14 No. 1 (2024): May: Social Science, Economics
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/ijosea.v14i1.468

Abstract

This research addresses the complexities of digital content analysis, focusing on toxicity, sentiment, and social network dynamics, employing the CRISP-DM (Cross-Industry Standard Process for Data Mining) as the overarching framework. The research problem centers on understanding the prevalence of toxicity, discerning sentiment nuances, and unraveling viewer interactions within social networks. Comprehensive toxicity analysis was conducted, revealing specific scores for toxicity attributes and a prevalence of positive sentiment (72.5%). Sentiment classification utilizing the k-NN algorithm achieved exceptional accuracy (98.06%), showcasing its efficacy in sentiment discernment. Social network dynamics were examined, uncovering key metrics such as Diameter (3), Density (0.002140), Reciprocity (0.000000), Centralization (0.393200), and Modularity (0.552200), shedding light on network structures and interactions. Findings underscore the need for nuanced content moderation strategies and highlight the importance of fostering positive interactions in digital spaces. Recommendations include implementing targeted moderation policies, leveraging sentiment analysis for audience engagement, and fostering community-building initiatives to promote healthier online environments.
Land Use, Built-Up, and Vegetation Index in North Halmahera Regency through Spatio-Temporal Analysis Singgalen, Yerik Afrianto
Jurnal Manajemen Hutan Tropika Vol. 30 No. 1 (2024)
Publisher : Institut Pertanian Bogor (IPB University)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.7226/jtfm.30.1.70

Abstract

Monitoring land use, buildings, and vegetation index of ecotourism areas in North Halmahera can support planning space utilization in urban areas for tourist areas as the concept of land use management and urban planning. This study offers ideas for analyzing the distribution of buildings, vegetation index, and land use in the mangrove ecotourism area of North Halmahera Regency using the spatio-temporal analysis method. The spatio-temporal analysis method comprises several stages: data selection, preprocessing, data integration, spatial analysis, temporal analysis, spatio-temporal analysis, data visualization, interpretation and understanding, and data visualization. The results of this study show that changes in the livelihood strategy of local people, from farmers and fishermen to traders, also affect land use patterns, from agricultural activities to economic activities, which triggers an increase in the number of buildings for production activities to product distribution. The implications of these findings on ecotourism development programs and policies and infrastructure development in the North Halmahera Regency are to consider community livelihoods and space or land use behavior in ecotourism areas based on vegetation, soil, and building index values. Thus, the intensification of building distribution and changes in vegetation index values from 2013-2023 reflect changes in people's livelihood strategies from agrarian activities to trade and from fishermen's activities to tourism transportation service providers.
Prediksi Ekspor Migas Indonesia Dengan Double Exponential Smoothing Juli Christanto, Henoch; Aprius Sutresno, Stephen; Mavish, Steven; Afrianto Singgalen, Yerik; Dewi, Christine
Jurnal Elektro Vol 15 No 1 (2022): Vol.15 No.1 April 2022: Jurnal Elektro
Publisher : Prodi Teknik Elektro, Fakultas Teknik Unika Atma Jaya Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25170/jurnalelektro.v15i1.5123

Abstract

In Indonesia, there are several forms of exports, one of which is oil and gas exports. The Double Exponential Smoothing method is a forecasting method that can be used to forecast oil and gas export data. This method uses two smoothing parameters, namely the average smoothing parameter alpha (α), the trend smoothing parameter beta (β). In this study, the population used is data on oil and gas exports in Indonesia. And the sample used is Indonesia's oil and gas export data from January 2020 to October 2021, we get 22 data sourced from the Central Statistics Agency (BPS). The Double Exponential Smoothing method is used because the data to be processed has a trend, both an up and a down trend and gas exports in Indonesia have an up and down pattern. The Double Exponential Smoothing method can also predict the prediction of oil and gas exports in Indonesia in the next months, November 2021 to February 2022. To process the data, the researcher used the Holt Double Exponential Smoothing method .
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