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All Journal MANAJEMEN HUTAN TROPIKA Journal of Tropical Forest Management Sodality: Jurnal Sosiologi Pedesaan MANAJEMEN IKM: Jurnal Manajemen Pengembangan Industri Kecil Menengah Jurnal Ilmu dan Teknologi Kelautan Tropis IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Jurnal Ilmu Sosial dan Humaniora Jurnal Kawistara : Jurnal Ilmiah Sosial dan Humaniora Journal of Indonesian Tourism and Development Studies JURNAL ELEKTRO Jurnal Kebijakan dan Administrasi Publik AdBispreneur PAX HUMANA ARISTO JURNAL MEDIA INFORMATIKA BUDIDARMA Jurnal Komunikasi Kritis Humaniora MUWAZAH: Jurnal Kajian Gender Cakrawala Jurnal Penelitian Sosial Building of Informatics, Technology and Science Jurnal Mantik Journal of Information Systems and Informatics Jurnal Studi Sosial dan Politik Jurnal Teknik Informatika C.I.T. Medicom JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) Journal of Computer System and Informatics (JoSYC) EKONOMI, KEUANGAN, INVESTASI DAN SYARIAH (EKUITAS) Jurnal Sistem Komputer dan Informatika (JSON) JOURNAL OF BUSINESS AND ECONOMICS RESEARCH (JBE) Budapest International Research and Critics Institute-Journal (BIRCI-Journal): Humanities and Social Sciences Cita Ekonomika: Jurnal Ilmu Ekonomi ARBITRASE: JOURNAL OF ECONOMICS AND ACCOUNTING International Journal on Social Science, Economics and Art KLIK: Kajian Ilmiah Informatika dan Komputer International Journal of Basic and Applied Science Indonesian Journal of Tourism and Leisure Jurnal InterAct Jurnal Sosiologi Engagement: Jurnal Pengabdian Kepada Masyarakat JKAP (Jurnal Kebijakan dan Administrasi Publik) Jurnal Kawistara
Yerik Afrianto Singgalen
Universitas Katolik Indonesia Atma Jaya
Religion Agriculture, Biological Sciences & Forestry Arts Humanities Biochemistry, Genetics & Molecular Biology Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Physics Public Health Social Sciences Other

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Journal : Journal of Computer System and Informatics (JoSYC)

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Analisis Perilaku Wisatawan Berdasarkan Data Ulasan di Website Tripadvisor Menggunakan CRISP-DM: Wisata Minat Khusus Pendakian Gunung Rinjani dan Gunung Bromo Yerik Afrianto Singgalen
Journal of Computer System and Informatics (JoSYC) Vol 4 No 2 (2023): Februari 2023
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josyc.v4i2.3042

Abstract

Traveller behavior needs to be comprehensively identified and analyzed to determine changes in tourism preference in Indonesia. One relevant approach to identifying traveler behavior is sentiment analysis through review data on the Tripadvisor website by text mining approach. This study aims to recommend a sentiment analysis model that is useful for managers of particular interest climbing tourist destinations on Mount Rinjani and Mount Bromo based on the type of visit alone (solo), with couples (couple), with friends, and with family (family). The research method used is Cross Industry Standard Process for Data Mining (CRISP-DM), with an algorithm adapted to managing tourist destinations for Mount Rinjani and Mount Bromo, namely attractions, roads and modes of transportation (accessibility), and accommodation. To overcome the problem of data balance in datasets, the calculation process of the Decision Tree (DT) algorithm and the Support Vector Machine (SVM) is connected to the Synthetic Minority Over-sampling Technique (SMOTE) operator in the Rapidminer application. The results of this study showed that the SVM algorithm showed better performance with an accuracy value of 97.67%, precision of 100%, recall of 95.34, and f-measure of 97.61% in the classification of 1075 text data of Mount Bromo and 326 review data of Mount Rinjani. In addition, in the context of Mount Rinjani, the top five words that often appear in tourist review data on Mount Rinjani are as follows: summit (272), Rinjani (259), trek (201), hike (170), mountain (159). On the other hand, the top five words that often appear in tourist review data on Mount Bromo are as follows: Bromo (1864), sunrise (1124), view (854), crater (758), and mount (577). Thus, it can be seen that tourists with the type of visit alone (solo), with couples (couple), with friends (friends), and with family (family) have a preference for the types of attractions in the form of summits, craters, natural beauty of mountains, hiking trails, types of transportation modes as well as supporting accommodation that needs to be prepared to keep the sustainability of tourism.
Analisis Sentimen Wisatawan terhadap Taman Nasional Bunaken dan Top 10 Hotel Rekomendasi Tripadvisor Menggunakan Algoritma SVM dan DT berbasis CRISP-DM Yerik Afrianto Singgalen
Journal of Computer System and Informatics (JoSYC) Vol 4 No 2 (2023): Februari 2023
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josyc.v4i2.3092

Abstract

It is necessary to analyze traveler sentiment towards Bunaken National Park and Tripadvisor's Top 10 Recommended Hotels to identify traveler satisfaction with the attractions, accommodation services, and transportation used. Considering this, this study uses the Cross-Industry Standard Process for Data Mining (CRISP-DM) framework by testing the performance of the Decision Tree (DT) algorithm and the Support Vector Machine (SVM). CRISP-DM has six stages: business understanding, data understanding, data preparation, modeling, evaluation, and deployment. Based on the processing of 398 Bunaken National Park destination data and 1793 review data on the top 10 hotels recommended by Tripadvisor, the SVM algorithm performed better. In the context of Bunaken National Park destination data, the performance of the SVM algorithm using the SMOTE operator can produce 100% accuracy, precision, recall, f-measure, AUC, and t-Test values. In addition, in processing the top 10 hotel datasets recommended by Tripadvisor, the SVM algorithm using the SMOTE operator provides an accuracy value of 96.42%, a precision value of 100%, a recall value of 92.83%, an f-measure value of 96.27%, an AUC value of 100%, and a t-Test value of 96.4%. The results of identifying the five words that most often appear in tourist reviews for Bunaken Marine Park tourist destinations are 164 words fish, 165 words island, 193-word dive, 230 diving, and 280 words Bunaken. This indicates the driving factor for tourist visits to Bunaken Marine Park is the beauty of underwater nature, including the diversity of marine animal species, the natural beauty of the archipelago, and diving activities. In addition, the results of identifying the five words that most often appear in traveler reviews for Tripadvisor's top 10 recommended hotels are 1170 great words, 1222 bunaken words, 1550 resort words, 1613 diving words, and 1711 dive words. This indicates that the characteristics of tourists who have the motive of traveling to Bunaken National Tourism Park have the intention to use resort accommodations around Bunaken and have mobility and facilities to support diving activities. Thus, the output of this study can be used as a recommendation for accommodation service managers to prepare supporting facilities for tourists who want to visit Bunaken National Park.
Sistem Pendukung Keputusan Pengembangan Ekowisata Mangrove Potensial Menggunakan Simple Additive Weighting (SAW) Yerik Afrianto Singgalen
Journal of Computer System and Informatics (JoSYC) Vol 4 No 3 (2023): May 2023
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josyc.v4i3.3432

Abstract

Adjusting resource availability and traveler preferences will allow for an objective assessment of prospective mangrove ecotourism growth. In order to build mangrove ecotourism destinations effectively, it is vital to identify their priority locations. It is required to create the development program as a criterion and the development zone as a prioritized alternative in light of this. This study used the Simple Additive Weighting (SAW) technique, which includes the following stages: deciding on criteria and alternatives; weighing the relative importance of each criterion; creating a matrix of findings; and ranking the alternatives based on the biggest value. The study's findings indicate that five criteria can be categorized based on benefit and cost with varying relative values: attraction (benefit), ancillary (benefit), accommodation (cost), accessibility (cost), and amenities (cost). Attraction has a relative value of 0.3, ancillary has a relative value of 0.2, and amenities (cost) has a relative value of 0.15. The ranking results showed that the amenity criteria came first, followed by accessibility, then attractions, lodging, and ancillary. Attractions were ranked third, while accommodations came in fourth. This demonstrates the necessity for amenities that pique tourist interest and accessibility through accessible modes of transportation, informational resources, and roads to tourist destinations to support the growth of mangrove ecotourism special interest tourism. The management of mangrove ecotourism destinations can be improved by offering lodging options. Following amenities, accessibility, attractions, and lodging, organizations or groups can be established, and infrastructure in tourist sites can be enhanced. As a result, the SAW approach can be used as a system to help decide which initiatives to prioritize
Analisis Perbandingan Nilai SAW dan TOPSIS dalam Menentukan Keputusan Perjalanan Wisata ke Destinasi Wisata Tematik Yerik Afrianto Singgalen
Journal of Computer System and Informatics (JoSYC) Vol 4 No 3 (2023): May 2023
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josyc.v4i3.3504

Abstract

This study aims to process information related to ticket costs, facilities, safety, cleanliness, road access, and mileage using the Simple Additive Weighting (SAW) method and Technique for Other Preferences by Similarity to Ideal Solution (TOPSIS) in the selection of natural tourism destinations, cultural tourism, beach, and marine tourism based on the context of North Halmahera Regency. The weights on each criterion that have been determined in the SAW method are as follows: ticket fee (0.30); facilities (0.30); security (0.30); cleanliness (0.30); access roads (0.30); mileage (0.30). Meanwhile, the weights on each criterion that have been determined according to the degree of importance in the TOPSIS method are as follows: ticket fees (5); facilities (4); security (3); cleanliness (3); access roads (3); mileage (3). Based on the results of the implementation of the SAW method in the selection of thematic tourist destinations, it can be seen that: based on the context of natural and adventure tourism destinations, Telaga Paca (A2) tourist destinations occupy the first position with a value of 0.903333; based on the context of historical and cultural tourist destinations, Hibualamo tourist destinations (B6) observed the first position with a value of 0.975; based on the context of beach and recreation tourism destinations, Pitu Beach tourist destinations (C1) occupy the first position with a value of 0.804167; based on the context of marine tourism destinations in the archipelago, Kumo Island tourist destinations (D2) occupy the first position with a value of 0.946429. Meanwhile, the results of the implementation of the TOPSIS method show that: based on the context of natural and adventure tourism destinations, Telaga Paca (A2) tourist destinations occupy the first position with a value of 0.74523053; based on the context of historical and cultural tourist destinations, Duma Village tourist destinations (B1) observe the first position with a value of 0.86431018; Based on the context of beach and leisure tourism destinations, tourist destinations Tanjung Pilawang (C7) occupies the first position with a value of 0.85054074; based on the context of marine tourism destinations in the archipelago, Magaliho Island tourist destinations (D7) occupy the first position with a value of 0.74142938
Analisis Multi-Objective Optimization on the Basis of Ratio Analysis (MOORA) Terhadap Data Top 10 Best Value Hotel Yerik Afrianto Singgalen
Journal of Computer System and Informatics (JoSYC) Vol 4 No 4 (2023): August 2023
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josyc.v4i4.4053

Abstract

Labuan bajo sebagai destinasi wisata super prioritas memiliki daya tarik wisata alam, budaya, pantai dan bahari. Wisatawan mancanegara dan nusantara yang berkunjung ke destinasi wisata premium Labuan Bajo, dapat menggunakan layanan akomodasi dan amenitas hotel, hingga bisnis layanan akomodasi lainnya. Penelitian ini bertujuan untuk menerapkan metode Multi-Objective Optimization on the Basis of Ratio Analysis (MOORA) terhadap 10 best value hotel di Labuan Bajo, berdasarkan website Tripadvisor. Hasil penelitian ini menunjukkan bahwa wisatawan dapat memilih mengambil keputusan menginap di top 10 best value hotel Labuan Bajo dengan mempertimbangkan ketersediaan ruangan dan amenitas hotel, maupun penilaian tamu yang memiliki pengalaman menginap di hotel tersebut. Berdasarkan hasil penerapan metode MOORA, hasil pengolahan data berdasarkan ketersediaan ruangan dan amenitas hotel menunjukakn bahwa Meruorah Komodo Labuan Bajo memiliki total nilai paling tinggi dengan jumlah 0,57 sehingga menempati urutan pertama, sedangkan Zasgo Hotel memiliki total nilai 0,49 sehingga menempati urutan kedua. Adapun, Ayana Komodor Resort, Waecicu Beach memiliki total nilai 0,38 sehingga menempati urutan ketiga. Adapun, berdasarkan penilaian tamu yang memiliki pengalaman menginap di top 10 best value hotel Labuan Bajo, dapat diketahui bahwa Zasgo Hotel memperoleh nilai sebesar 0,248 dan menempati urutan pertama. Selanjutnya, Parlezo Hotel memperoleh nilai sebesar 0,237 dan menempati urutan kedua. Meskipun demikian, Zasgo Hotel dan Parlezo Hotel tidak dapat direkomendasikan karena tidak memilik nilai pada kriteria value. Oleh sebab itu, Hotel yang direkomendasikan ialah Ayana Komodo Resort, Waecicu Beach dengan total nilai sebesar 0,157 serta Sudamala Resort, Seraya dengan total nilai 0,153. Dengan demikian, penerapan metode MOORA dapat menghasilkan rekomendasi yang sesuai dengan preferensi tamu hotel.
Analisis Perbandingan Top 10 Best-Value dan Top 10 Traveler-Ranked Hotel di Kota Ternate Menggunakan MOORA Yerik Afrianto Singgalen
Journal of Computer System and Informatics (JoSYC) Vol 4 No 4 (2023): August 2023
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josyc.v4i4.4070

Abstract

There are a variety of factors that influence hotel visitors' decisions. The first consideration pertains to the room and amenities, while the second comprises prior guest ratings. Tripadvisor is frequently used to propose lodging and amenity services in different places. Using the MOORA decision support model, this study compares the top 10 best-value hotels in Ternate City to the top 10 most-recommended hotels by travelers. This research consists of four phases: the data gathering phase, the data analysis phase, the data interpretation phase, and the reporting phase. The data processing results utilizing the MOORA decision support model on the top 10 best-value hotels in Ternate City revealed a considerable disparity with the Tripadvisor rankings based on room and amenity criteria and guest reviews. Muara Hotel Ternate has a total scale of 0.491% based on parameters related to its rooms and amenities. Additionally, the order is dynamic and dependent on guest rating criteria. The Bela International Hotel ranks #1 if review data is considered because its reviews exceed 100. The same conclusion was drawn from the data processing findings of the top 10 traveler-ranked hotels in Ternate City, where the ranking results based on room and amenities criteria refer to the Ternate City Hotel with a total yi value of 0.79. The ranking results are also dynamic and dependent on guest rating criteria. If the number of reviews is considered, the Bela International Hotel will be ranked #1 because its number of studies is more significant than 100. This implies that information about rooms and hotel amenities and the number of guest evaluations on the Tripadvisor website can be crucial in influencing hotel guests' decisions regarding their stay.
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.
Sentiment Classification of Over-Tourism Issues in Responsible Tourism Content using Naïve Bayes Classifier Yerik Afrianto Singgalen
Journal of Computer System and Informatics (JoSYC) Vol 5 No 2 (2024): February 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josyc.v5i2.4904

Abstract

The research problem addressed in this study is the analysis of public sentiment regarding over-tourism issues. Utilizing the Cross Industry Standard Process for Data Mining (CRISP-DM) methodology and the Naive Bayes Classifier (NBC) algorithm, the study navigates through stages of business understanding, data processing, modeling, evaluation, and deployment. The central focus lies in understanding and classifying public sentiments surrounding the challenges associated with over-tourism. The findings reveal that the NBC algorithm, particularly when augmented with Synthetic Minority Over-sampling Technique (SMOTE), demonstrates superior performance metrics, showcasing an accuracy of 84.82%, precision of 91.69%, recall of 76.75%, f-measure of 83.47%, and AUC of 0.838. The comparison with NBC without SMOTE, which registers an accuracy of 78.16%, precision of 87.61%, recall of 74.56%, f-measure of 80.51%, and AUC of 0.745, underscores the significance of addressing class imbalance for improved predictive performance. Integrating CRISP-DM with the NBC algorithm and SMOTE proves instrumental in advancing sentiment analysis methodologies, providing nuanced insights into public perceptions and attitudes concerning the critical issue of over-tourism.
Co-Authors A.Y. Agung Nugroho Abigail Rosandrine Kayla Putri Rahadi Agnes Harnadi Agnes Harnadi Agung Mulyadi Purba Alfonso Harrison Aloisius Gita Nathaniel Aprius Sutresno, Stephen Astuti Kusumawicitra Astuti Kusumawicitra Laturiuw Astuti Kusumawicitra Laturiuw Bernardus Alvin Rig Bernardus Alvin Rig Biafra Daffa Farabi Biafra Daffa Farabi Billy Macarius Sidhunata Brito, Manuel Charitas Fibriani Christanto, Henoch Juli Christine Dewi Danny Manongga Dasra, Muhamad Nur Agus Eko Sediyono Eko Widodo Elfin Saputra Elfin Saputra Elly Esra Kudubun Eugenius Kau Suni Fang, Liem Shiao Faskalis Halomoan Lichkman Manurung Gatot Sasongko Gilberto Dennis G E Sidabutar Gintu, Agung Rimayanto Gudiato, Candra Henoch Juli Christanto Henoch Juli Christanto Henoch Juli Christanto Heru Prasadja Hindriyanto Dwi Purnomo Hironimus Cornelius Royke Irene Sonbay Irwan Sembiring Jesslyn Alvina Seah Jonathan Tristan Santoso Juli Christanto, Henoch Kartikawangi, Dorien Kusumawicitra, Astuti Manuel Brito Marthen Timisela Mavish, Steven Michael Kenang Gabbatha Nantingkaseh, Alfonso Harrison Nicolas Arya Nanda Susilo Nugroho, A. Y. Agung Octa Hutapea Octa Hutapea Pamerdi Giri Wiloso Pamerdi Giri Wiloso Pamerdi Giri Wiloso, Pamerdi Giri Pedro Manuel Lamberto Buu Sada Pinia, Nyoman Agus Perdanaputra Pontolawokang, Theresya Ellen Pristiana Widyastuti Pristiana Widyastuti Purwoko, Agus Puspitarini, Titis Radyan Rahmananta Radyan Rahmananta Rafael Christian Rahadi, Abigail Rosandrine Kayla Putri Rahmadini, Asyifa Catur Richard Emmanuel Adrian Sinaga Rosdiana Sijabat Ruben William Setiawan Samuel Piolo Seingo, Martha Maraka Setiawan, Ruben William Siemens Benyamin Tjhang Sri Yulianto Joko Prasetyo Stephen Aprius Sutresno Suharsono SUHARSONO Tabuni, Gasper Tharsini, Priya Titi Susilowati Prabawa Titis Puspitarini Widodo, Eko Winayu, Birgitta Narindri Rara Yan Dirk Wabiser Yoel Kristian Zsarin Astri Puji Insani