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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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Implementasi Metode CRISP-DM dalam Analisis Model Pendukung Keputusan Simple Additive Weighting dan Pengembangan Basis Data Riwayat Pembelian Layanan Akomodasi Hotel Singgalen, Yerik Afrianto
Jurnal Sistem Komputer dan Informatika (JSON) Vol. 5 No. 2 (2023): Desember 2023
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/json.v5i2.7153

Abstract

The development of studies on implementing Simple Additive Weighing (SAW) decision support models in purchasing hotel accommodation services or making stay decisions is limited to hotel recommendations calculated from consumer assessments of criteria with predetermined weights. However, it is necessary to develop a database with interactive visualization of hotel accommodation services and make it easier for consumers to compare and provide ratings. Considering this, this study uses the CRISP-DM method to develop a database based on the purchase history of hotel accommodation services in a business operational area, then uses SAW as a decision support model in the calculation process to produce the best hotel recommendations based on purchase data. The CRISP-DM method consists of business understanding, data understanding, modeling, evaluation, and deployment stages. At the business understanding stage,  the customer's purchase history data is collected in the Agoda website review column. At the data understanding stage, the data collection process is carried out based on the supporting data of the criteria used. At the modeling stage, the SAW algorithm is used in the calculation process to get the best recommendations. In the Evaluation phase, hotels with the best recommendations are analyzed based on the guest's country of origin, guest sentiment, type of guest staying, room type used, length of stay, and month and year. In the Deployment stage, the database is developed using Oracle Apex and visualized interactively so that system users can understand consumer trends and behavior, especially in making overnight decisions based on purchase history data. Based on data obtained from the Agoda platform, it can be seen that A2 ranks first with a value weight of 0.983, then A3 ranks second with a value weight of 0.982, and A1 ranks third with a value weight of 0.946. Meanwhile, based on data obtained from the Booking.com platform, it can be seen that A3 ranks first with a value weight of 0.983, then A2 ranks second with a value weight of 0.974, and A1 ranks third with a value weight of 0.951. Thus, the SAW decision support model implementation output is not limited to the results of calculations and recommendation tables but includes a database with interactive visuals.
Pemilihan Paket Wisata One Day Tour Menggunakan Model Pendukung Keputusan TOPSIS Singgalen, Yerik Afrianto
Jurnal Sistem Komputer dan Informatika (JSON) Vol. 5 No. 2 (2023): Desember 2023
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/json.v5i2.7231

Abstract

The development of Labuan Bajo tourism attracts foreign and domestic tourists to explore various natural beauties through fun activities. Tour agents provide a variety of interesting activities and tourist visits to the islands around Labuan Bajo that can provide new experiences for tourists. The activities are sold through One-day tour packages in Labuan Bajo. Still, depending on the service provider, the itinerary description, admission ticket,  and order of visit to the destination are very complicated. Considering this, this study uses the TOPSIS decision model in choosing One Day Tour tour packages in Labuan Bajo by considering the criteria of price, destination, duration, admission ticket, and service rating. Based on the results of this study, it can be seen that the highest preference value from the ranking results is the Full Day Trip to Explore 6 Destinations in Labuan Bajo and Komodo tour package, with a value of 0.673056111. Furthermore, the tour package that occupies the second position from the ranking results is the 1-day Komodo island Tour hopping around by Speed Boat with a preference value of 0.628303746. Meanwhile, the tour package that occupies the third position from the ranking results is One day Komodo trip with Bintang Komodo Tours with a  preference value of 0.53181476. This shows that the TOPSIS method produces recommendations for One Day Tour packages in Labuan Bajo for tourists by considering the price of tour packages, the number of destinations visited, the length of time or duration of tourist time, admission tickets in tour packages, and ratings The services of the travelers were previously related to the tour package. Thus, the selection of TOPSIS-based One Day Tour tour packages can minimize the risk that causes misunderstandings or tourist dissatisfaction related to the tour packages prepared by each travel agent.
Sentiment Classification of Food Influencer Content Reviews using Support Vector Machine Model through CRISP-DM Framework Singgalen, Yerik Afrianto
Jurnal Sistem Komputer dan Informatika (JSON) Vol. 5 No. 3 (2024): Maret 2024
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/json.v5i3.7509

Abstract

The research problem revolves around the challenges in effectively marketing culinary tourism aligned with tourist preferences in Indonesia, necessitating a substantial exploration of consumer sentiments related to culinary diversity through the lens of food influencer content. Food influencers are crucial in stimulating tourists' interest in gastronomy through culinary tourism in Indonesia. This research reveals challenges in culinary tourism marketing aligned with tourist preferences, necessitating substantial exploration of consumer sentiments related to culinary diversity through food influencer content. The sentiment classification method employed is the Cross-Industry Standard Process for Data Mining (CRISP-DM) using the Support Vector Machine (SVM) algorithm and the SMOTE operator. The data source is derived from a video with the ID PMhfLy_buV8, containing 114,422 comments. This study collects and processes 30,000 comments, resulting in 9,323 data points. The findings highlight the vital performance metrics of SVM models, both with and without SMOTE, showcasing high accuracy, precision, recall, and F-measure values. Specifically, SVM without SMOTE achieves 95.28% accuracy, while SVM with SMOTE achieves 98.67%. Despite some limitations in discerning positive and negative sentiments, indicated by moderate Area Under the Curve (AUC) values (0.608 to 0.658), the overall efficacy of SVM in sentiment analysis for food influencer content is apparent. Drawing from a dataset of 30,000 comments, these insights contribute to advancing sentiment analysis methodologies and offer practical implications for understanding consumer perceptions and behaviors in digital media and influencer marketing. Additionally, the prominence of frequent words such as "bang" (1322), "nonton" (1064), "makan" (921), "yang" (801), "puasa" (711), "tahun" (484), "ngiler" (448), "lagi" (384), "tanboy" (311), and "enak" (315), as extracted from RapidMiner analysis, underscores the significance of language patterns in the realm of food influencer content.
Toxicity Analysis and Sentiment Classification of Wonderland Indonesia by Alffy Rev using Support Vector Machine Singgalen, Yerik Afrianto
Jurnal Sistem Komputer dan Informatika (JSON) Vol. 5 No. 3 (2024): Maret 2024
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/json.v5i3.7563

Abstract

The music industry's increasing reliance on digital platforms like YouTube for dissemination raises concerns about the potential impact of music videos on viewer sentiment and well-being. This study seeks to assess the toxicity and sentiment of the Wonderland Indonesia music video by Alffy Rev through Support Vector Machine analysis, contributing to our understanding of the effects of music content on online audiences. This research addresses the challenge of sentiment classification in digital content by leveraging the Cross-Industry Standard Process for Data Mining (CRISP-DM) framework. The study aims to enhance sentiment classification accuracy by applying a Support Vector Machine (SVM) with a Synthetic Minority Over-sampling Technique (SMOTE) to address class imbalance issues. The research problem revolves around the need for robust sentiment analysis models capable of accurately discerning sentiment polarity within diverse datasets. Through the systematic application of CRISP-DM phases - business understanding, data understanding, data preparation, modeling, evaluation, and deployment - the study examines the efficacy of SVM with SMOTE in sentiment classification tasks. The findings demonstrate notable performance metrics, including accuracy (96.50%), precision (95.75%), recall (99.00%), and F-measure (97.34%). The AUC value substantially increases from 0.642 without SMOTE to 0.997 with SMOTE, highlighting its effectiveness in improving sentiment classification accuracy. In addition, The comparative analysis of toxicity values between the first and second videos demonstrates distinct patterns: the first video showcases a Toxicity score of 0.05290, with notable metrics such as Profanity registering at 0.04815. Conversely, the second video exhibits a slightly lower Toxicity score of 0.04744, with varying metrics such as Severe Toxicity at 0.01386.
Implementation of Global Vectors for Word Representation (GloVe) Model and Social Network Analysis through Wonderland Indonesia Content Reviews Singgalen, Yerik Afrianto
Jurnal Sistem Komputer dan Informatika (JSON) Vol. 5 No. 3 (2024): Maret 2024
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/json.v5i3.7569

Abstract

Integrating the Global Vectors for Word Representation (GloVe) Model with Social Network Analysis presents a promising approach for extracting nuanced semantic relationships from Wonderland Indonesia's content reviews. However, the lack of comprehensive studies exploring the effectiveness of this integration, specifically within the context of Wonderland Indonesia's content reviews, necessitates focused research to uncover its potential impact and applications. This study investigates the reception and impact of the "Wonderland Indonesia" video content by Alffy Rev ft. Novia Bachmid (Chapter 1) within the YouTube community using a comprehensive methodology based on CRoss-Industry Standard Process for Data Mining (CRISP-DM), topic analysis, and Social Network Analysis (SNA). Through topic analysis, the content's main themes and narrative elements were identified, shedding light on its storytelling effectiveness. Furthermore, sentiment analysis using Vader was conducted on 2204 out of 24185 posts, revealing that 1369 (92%) exhibited positive sentiment, 427 (31.19%) had neutral sentiment, and 850 (62.09%) contained negative sentiment. Additionally, sentiment analysis using TextBlob was performed on the same subset of posts, with 1369 (40) posts exhibiting positive sentiment, 599 (43.75%) with neutral sentiment, and 730 (53.32%) expressing negative sentiment. Notably, metrics such as toxicity (highest value: 0.90780) and severe toxicity (highest value: 0.95021) exhibited varying prominence within the analyzed content. These findings enable targeted interventions and content moderation strategies to promote healthier online discourse. The SNA uncovered intricate social dynamics and interaction patterns among viewers, emphasizing the video's ability to foster engagement and community interaction. This study underscores the significance of creative storytelling and community engagement strategies in digital content creation, with implications for audience participation and community development within the digital sphere. Future research could explore the longitudinal effects of such content strategies on audience retention and community engagement.
MONITORING MANGROVE MENGGUNAKAN MODEL NORMALIZED DIFFERENCE VEGETATION INDEX (NDVI): STUDI KASUS DI HALMAHERA UTARA, INDONESIA Singgalen, Yerik Afrianto; Gudiato, Candra; Prasetyo, Sri Yulianto Joko; Fibriani, Charitas
Jurnal Ilmu dan Teknologi Kelautan Tropis Vol. 13 No. 2 (2021): Jurnal Ilmu dan Teknologi Kelautan Tropis
Publisher : Department of Marine Science and Technology, Faculty of Fisheries and Marine Science, IPB University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29244/jitkt.v13i2.34771

Abstract

Ekowisata berbasis masyarakat menjadi salah satu pendekatan yang efektif dalam menjaga kelestarian hutan mangrove. Strategi untuk menetapkan prioritas pengembangan kawasan mangrove, dapat dilakukan dengan menganalisis kerapatan hutan mangrove. Kawasan mangrove dengan nilai kerapatan paling rendah perlu diprioritaskan sebagai strategi preservasi dan konservasi melalui konsep ekowisata berbasis masyarakat. Artikel ini bertujuan mengidentifikasi sebaran mangrove menggunakan model normalized difference vegetation index (NDVI) di Kabupaten Halmahera Utara, Indonesia. Perspektif penghidupan berkelanjutan digunakan untuk mendiskusikan konteks sosio-kultural masyarakat lokal. Penelitian ini mengadopsi metode campuran. Pengolahan data terbagi menjadi dua tahap yakni: tahap pertama, pemetaan sebaran hutan mangrove berdasarkan tingkat kerapatan; tahap kedua, trianggulasi. Pemetaan sebaran hutan mangrove menggunakan citra satelit Landsat 8 operational land imager (OLI) tahun 2013 dan 2021 serta model NDVI di Tanjung Pilawang, Pulau Kumo, Pulau Kakara, Pulau Maiti, dan Pulau Tagalaya. Hasil penelitian ini menunjukkan bahwa Tanjung Pilawang pada zona 1 dan 2 memiliki Nilai NDVI paling rendah di tahun 2021 yakni 0,22 dengan kategori jarang, sehingga perlu diprioritaskan dalam pengembangan ekowisata mangrove berbasis komunitas sebagai strategi perlindungan kawasan hutan mangrove.
MONITORING KAWASAN EKOWISATA MANGROVE MENGGUNAKAN NDVI, NDWI, DAN CMRI DI PULAU DODOLA, KABUPATEN PULAU MOROTAI, INDONESIA Singgalen, Yerik Afrianto; Manongga, Danny
Jurnal Ilmu dan Teknologi Kelautan Tropis Vol. 14 No. 1 (2022): Jurnal Ilmu dan Teknologi Kelautan Tropis
Publisher : Department of Marine Science and Technology, Faculty of Fisheries and Marine Science, IPB University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29244/jitkt.v14i1.37605

Abstract

Pembangunan infrastruktur pariwisata menyebabkan alih fungsi lahan atau konversi lahan dari ruang terbuka hijau menjadi kawasan ekonomi pariwisata. Pemanfaatan kawasan mangrove sebagai daya tarik ekowisata perlu dimonitoring secara berkala agar pembangunan sarana dan prasarana tidak mengancam keberlanjutan vegetasi mangrove. Artikel ini bertujuan mengidentifikasi sebaran mangrove menggunakan model normalized difference vegetation index (NDVI), normalized difference water index (NDWI), combined mangrove recognize index (CMRI) di Kabupaten Pulau Morotai, Provinsi Maluku Utara, Indonesia. Perspektif ekowisata berkelanjutan digunakan untuk mendiskusikan konteks sosio-kultural masyarakat Morotai khususnya masyarakat Pulau Kolorai. Penelitian ini mengadopsi metode campuran. Pengolahan data terbagi menjadi dua tahap yakni: tahap pertama, pemetaan sebaran mangrove Pulau Dodola menggunakan citra satelit Landsat 8 Operational Land Imager (OLI) dari tahun 2013-2021 berdasarkan kalkulasi NDVI, NDWI, dan CMRI; tahap kedua, trianggulasi. Hasil penelitian ini menunjukkan bahwa pada tahun 2017, terjadi penurunan nilai NDVI dan CMRI di Zona 1, Zona, 2, dan Zona 3 sebagai kawasan ekowisata mangrove Pulau Dodola.. Hal ini menunjukkan adanya ancaman ekosistem mangrove apabila pembangunan infrastruktur menyebabkan penurunan nilai indeks vegetasi secara signifikan dari tahun ke tahun. Dengan demikian, diperlukan program pengendalian terhadap program pembangunan infrastruktur dengan melibatkan masyarakat lokal dalam pemeliharaan ekosistem mangrove.
Livelihood Transformation through the Existence of Mining and Tourism Industries: Case of North Halmahera District, North Maluku, Indonesia Singgalen, Yerik Afrianto
ARISTO Vol 10 No 2 (2022): July
Publisher : Universitas Muhammadiyah Ponorogo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24269/ars.v10i2.4674

Abstract

Development has changed indigenous people's cultural structure and function, which is identical to a traditional lifestyle to the modern one, encouraging livelihood diversification or transformation. The development approach is vulnerable to socio-cultural, economic, and environmental changes, including in the mining and tourism sector. This article aims to describe the development process that has caused changes in the structure and function of indigenous culture and rural livelihoods in Northern Maluku, Indonesia. This study was done qualitatively using a case study approach to describe the livelihood strategies of indigenous people to cope with the existence of the mining and tourism industry’s activity in the North Halmahera Regency. The key informants involved in this research are traditional leaders, community leaders, and youth. Data collection is adjusted to the context of the research location, both around tourist destinations and mining areas. Data processing uses a triangulation approach. These findings indicate that the traditional community of Hibualamo had cultural structures and functions that mobilised access to social and natural capital. Furthermore, The challenges of globalisation cause a livelihood transformation and influence the capability of local communities to access financial capital, human capital, and physical capital.
Sentiment, toxicity, and social network analysis of virtual reality product content reviews Singgalen, Yerik Afrianto
Jurnal Teknik Informatika C.I.T Medicom Vol 16 No 1 (2024): March: 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.Vol16.2024.716.pp24-34

Abstract

Virtual Reality (VR) technology has garnered significant attention in recent years due to its potential to revolutionize various industries. This study aims to investigate consumer sentiments toward VR products, mainly focusing on Meta Quest 3 in the context of the AI era. The background section outlines the rising popularity of VR products and their impact on consumer behavior, emphasizing the need for a comprehensive understanding of consumer sentiments to inform marketing strategies effectively. Methodologically, the study adopts the Cross-Industry Standard Process for Data Mining (CRISP-DM) framework to guide the analytical approach, which includes sentiment classification, toxicity scoring, and social network analysis (SNA). A dataset comprising 2,115 consumer interactions and evaluations was utilized, with 1,302 interactions for the ALINE tech video and 813 interactions for The Tech Chap video, to derive insights into sentiment patterns and interaction dynamics. The findings reveal a positive reception towards VR products, with Meta Quest 3 particularly well-received. The sentiment classification algorithm achieved an accuracy of 77.92% without SMOTE and 85.66% with SMOTE, demonstrating competency in sentiment prediction. The precision, recall, and f-measure for SVM without SMOTE were 85.78%, 99.83%, and 92.27%, respectively, while with SMOTE, they were 100%, 55.82%, and 71.50%, respectively. Toxicity scoring yielded an average toxicity score of 0.05. Social network analysis (SNA) identified a network diameter of 6, modularity of 0.6072, and a density of 0.002815, highlighting the intricate dynamics of consumer interaction within the VR domain.
Enhancing accommodation selection: an analysis of simple additive weighting and rank order centroid Singgalen, Yerik Afrianto
Jurnal Teknik Informatika C.I.T Medicom Vol 16 No 1 (2024): March: 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.Vol16.2024.726.pp35-44

Abstract

This study deploys Simple Additive Weighting (SAW) and Rank Order Centroid (ROC) in selecting accommodations. The research problem investigates the efficacy and applicability of these methods in aiding decision-makers, mainly tourists, in choosing accommodations based on diverse criteria. To address this issue, a comprehensive comparative analysis was conducted utilizing both SAW and ROC methodologies to evaluate a range of accommodations in the vibrant tourism destination of Raja Ampat, Indonesia. The SAW method involved the assignment of weights to various criteria and the subsequent calculation of overall scores for each accommodation. In contrast, the ROC method utilized a centroid-based approach to rank the accommodations. The findings underscore notable distinctions between the two methodologies, with SAW providing a detailed assessment of accommodations based on weighted criteria, whereas ROC offers a simplified ranking system. Additionally, the research identified Nyande Raja Ampat as the top-ranked accommodation with a score of 0.95859128, followed by Raja Ampat Sandy Guest House (score: 0.924445677) and Mambetron Homestay Raja Ampat (score: 0.861666825). Warahnus Dive Homestay and Hamueco Raja Ampat Resort secured the fourth and fifth ranks, with scores of 0.831961086 and 0.827113234, respectively. These findings offer valuable insights for tourists seeking accommodations in Raja Ampat and contribute to the broader understanding of decision-making methodologies in the tourism industry.
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