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All Journal Jurnal Masyarakat Informatika Bulletin of Electrical Engineering and Informatics JUTI: Jurnal Ilmiah Teknologi Informasi Format : Jurnal Imiah Teknik Informatika JOIV : International Journal on Informatics Visualization Tech-E Jurnal Ilmiah FIFO Jurnal CoreIT BAREKENG: Jurnal Ilmu Matematika dan Terapan JITK (Jurnal Ilmu Pengetahuan dan Komputer) Technomedia Journal Riau Journal of Empowerment The IJICS (International Journal of Informatics and Computer Science) JURIKOM (Jurnal Riset Komputer) KOMPUTIKA - Jurnal Sistem Komputer Jurnal Manajemen Informatika Komputasi: Jurnal Ilmiah Ilmu Komputer dan Matematika Jurnal Tekno Kompak Building of Informatics, Technology and Science Jurnal Ilmiah Betrik : Besemah Teknologi Informasi dan Komputer IJAIT (International Journal of Applied Information Technology) Jurnal Tata Kelola dan Kerangka Kerja Teknologi Informasi Indonesian Journal of Electrical Engineering and Computer Science Jurnal Sisfotek Global Journal of Computer System and Informatics (JoSYC) Community Development Journal: Jurnal Pengabdian Masyarakat TIN: TERAPAN INFORMATIKA NUSANTARA Journal of Computer Science, Information Technology and Telecommunication Engineering (JCoSITTE) Jurnal Teknik Informatika (JUTIF) JiTEKH (Jurnal Ilmiah Teknologi Harapan) Jurnal Informatika dan Rekayasa Perangkat Lunak Jurnal Ilmiah Infrastruktur Teknologi Informasi Jurnal Teknologi dan Sistem Informasi Journal Social Science And Technology For Community Service Jurnal Pendidikan dan Teknologi Indonesia Bulletin of Computer Science Research Journal of Informatics Management and Information Technology KLIK: Kajian Ilmiah Informatika dan Komputer Reputasi: Jurnal Rekayasa Perangkat Lunak EXPLORER J-Intech (Journal of Information and Technology) BEES: Bulletin of Electrical and Electronics Engineering Jurnal Sisfotek Global Jurnal Telematics and Information Technology (TELEFORTECH) Bulletin of Data Science Jurnal Ilmiah Sistem Informasi Akuntansi (JIMASIA) Jurnal Pengabdian Masyarakat Inovasi Paradigma Journal of Engineering and Information Technology for Community Service Journal of Computing and Informatics Research JEECS (Journal of Electrical Engineering and Computer Sciences) Jurnal Ilmiah Informatika dan Ilmu Komputer Journal of Informatics, Electrical and Electronics Engineering TEKNOSIA Jurnal INFOTEL Bulletin of Informatics and Data Science Jurnal Ilmiah Computer Science CHAIN: Journal of Computer Technology, Computer Engineering and Informatics Journal of Data Science and Information System Journal of Artificial Intelligence and Technology Information Journal of Information Technology, Software Engineering and Computer Science Jurnal Media Jawadwipa Bulletin of Artificial Intelligence International Journal of Informatics and Data Science Journal of Decision Support System Research Journal of Information Technology
Setiawansyah Setiawansyah
(Scopus ID : 57446859700), Universitas Teknokrat Indonesia
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Modification of the Grey Relational Analysis Method in Determining the Best Mechanic Arshad, Muhammad Waqas; Sulistiani, Heni; Maryana, Sufiatul; Palupiningsih, Pritasari; Rahmanto, Yuri; Setiawansyah, Setiawansyah
Building of Informatics, Technology and Science (BITS) Vol 6 No 3 (2024): December 2024
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v6i3.5678

Abstract

Determining the best mechanics in the industry has an important role to ensure the quality and reliability of the products and services offered. Competent and experienced mechanics are able to diagnose and repair accurately and efficiently, thereby minimizing operational downtime and increasing productivity. Without a structured system, mechanical performance appraisals tend to be subjective and inconsistent, which can lead to dissatisfaction among employees and customers. Mechanics may not get clear and constructive feedback on their performance, thus hindering skill development and professionalism. The purpose of the research of the modified Grey Relational Analysis (GRA) using standard deviation is to improve the accuracy and reliability of the decision-making process in situations where the data has a high degree of variability or significant uncertainty. By integrating standard deviations into the GRA, the study aims to account for variations and fluctuations in the data, which allows for more accurate and representative assessment of the criteria. This modification is expected to overcome the weaknesses of traditional GRAs that may not adequately consider data uncertainty, as well as produce more robust and realistic alternative rankings. The results of the best ranking of mechanics, Mechanic FR ranks first with a value of 0.11, followed by Mechanic HS with a value of 0.104. The third place was occupied by Mechanic AY with a score of 0.099.
Modifikasi Metode Simple Additive Weighting Dalam Rekomendasi Restoran Terbaik Berdasarkan Ulasan Pengunjung Prastowo, Kukuh Adi; Sulistiani, Heni; Setiawansyah, Setiawansyah
Building of Informatics, Technology and Science (BITS) Vol 6 No 3 (2024): December 2024
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v6i3.5679

Abstract

Simple Additive Weighting (SAW) is a method in DSS that is used to solve multi-criteria problems by adding up the value weights of each alternative. The weakness of SAW is its sensitivity to weight determination and value which can significantly affect the final result. If the weight or value of the criteria is not determined correctly or does not reflect reality well, the results of the decision can be less accurate. The purpose of this study is to modify the SAW method with the name SAW-C to be more effective in providing the best restaurant recommendations based on visitor reviews. SAW modification using a change driven approach not only improves accuracy in decision-making, but also improves adaptability and responsiveness to dynamic and complex environments. The SAW-C method not only improves decision-making accuracy, but also improves adaptability and responsiveness to dynamic and complex environments. SAW-C integrates flexibility and adaptability in managing changes in visitor preferences or the weighting of relevant criteria, which often change over time. With this approach, the recommendation system can dynamically update restaurant ratings based on recent reviews and changing visitor preferences, providing more personalized and relevant recommendations. The results of the ranking of the best restaurants using the SAW-C method show that the results of rank 1 with a final score of 0.92135 are obtained by Flamboyant Restaurant, rank 2 with a final score of 0.70548 obtained by Zozo Garden, and rank 3 with a final score of 0.70312 obtained by Square Restaurant.
Combination of PIPRECIA and Multi-Attributive Ideal-Real Comparative Analysis for the Determination of Scholarship Students Hadad, Sitna Hajar; Chandra, Iryanto; Maryana, Sufiatul; Setiawansyah, Setiawansyah
Building of Informatics, Technology and Science (BITS) Vol 6 No 3 (2024): December 2024
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v6i3.6313

Abstract

Scholarships are a form of financial assistance given to individuals to support their education. Criteria considered in the determination of scholarship recipients may include academic achievement, special talents, financial need, participation in extracurricular activities, and potential contributions to the community. The combination of weighting using PIPRECIA and MAIRCA can be a powerful approach in determining scholarship recipients. With PIPRECIA, scholarship providers can gather preferences from various relevant parties to determine the relative weight of each evaluation criterion. Furthermore, by applying MAIRCA, scholarship recipients can be evaluated based on these criteria by comparing between ideal attributes that reflect expected standards with real attributes that reflect the actual conditions of each recipient. By integrating these two methods, the process of determining scholarship recipients becomes more structured, transparent, and takes into account diverse preferences and priorities, ensuring that aid is distributed to the most deserving and needy individuals. The results of alternative rankings in determining scholarship recipients are 1st place with a final score of 0.071 obtained on behalf of Yusuf Maqdis, 2nd place with a final score of 0.068 obtained on behalf of Kurniawansyah, and 3rd place with a final score of 0.062 obtained on behalf of Ketut Purwanti.
Decision Support System for Platform Selection in E-Commerce Using the OWH-TOPSIS Method Wang, Junhai; Isnain, Auliya Rahman; Suryono, Ryan Randy; Rahmanto, Yuri; Mesran, Mesran; Setiawansyah, Setiawansyah
Journal of Computer System and Informatics (JoSYC) Vol 6 No 1 (2024): November 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josyc.v6i1.5990

Abstract

Platforms in e-commerce are digital systems that allow online transactions to buy and sell products or services. E-commerce platforms also provide benefits for business actors because they are able to reach a wider market without geographical restrictions, while offering efficiency in business operations. The main problem in choosing a platform for e-commerce is often related to the sheer number of options available and the variety of criteria that must be considered. Criteria such as fees, platform popularity, transaction security, ease of use, features provided, as well as customer service support are important factors in determining the most suitable platform. The implementation of a decision support system to help select the optimal e-commerce platform by applying the OWH-TOPSIS method shows that this system can provide accurate and effective recommendations, so that it can be used as a reference for users in determining the e-commerce platform that suits their needs. The decision support system using the OWH-TOPSIS method provides an efficient and objective solution in the selection of e-commerce platforms. The results of the ranking of the best e-commerce platforms show that Platform D occupies the top position with the highest score value, which is 0.882. In second place is Platform E which obtained a score of 0.8599, followed by Platform A with a score of 0.8341.
Implementation of MABAC Method and Entropy Weighting in Determining the Best E-Commerce Platform for Online Business Wang, Junhai; Darwis, Dedi; Setiawansyah, Setiawansyah; Rahmanto, Yuri
JiTEKH Vol. 12 No. 2 (2024): September 2024
Publisher : Universitas Harapan Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35447/jitekh.v12i2.1000

Abstract

The main problem in choosing an e-commerce platform for an online business is finding the one that best suits the specific needs of the business. Each platform has its advantages and disadvantages, such as ease of use, cost, features offered, as well as support for inventory management, shipping, and payments. Other challenges include ensuring that the platform can support future business growth, offer good scalability, and provide flexibility in terms of customization and integration with digital marketing tools. In addition, data security and a good user experience are also important considerations for long-term success. The purpose of this study is to implement the MABAC method and Entropy weighting in determining the best e-commerce platform for online businesses, so that this research can provide clear and data-driven recommendations to stakeholders regarding the most effective e-commerce platform. The application of the MABAC method combined with Entropy weighting in determining the best e-commerce platform for online business people offers a comprehensive and objective approach in decision-making. This combination not only improves decision-making accuracy, but also ensures that the most important criteria are weighted accordingly, resulting in more reliable results in choosing the best platform for business needs. The final result of the MABAC Platform A score is the first choice, considering the highest score of 0.82, which indicates its optimal performance in meeting the criteria that have been set. In addition, Platforms B and C, with scores of 0.78 and 0.75, respectively.
Combination of LOPCOW and MOORA in Restaurant Recommendation Decision Support System Based on User Reviews Setiawansyah, Setiawansyah
Journal of Information Technology, Software Engineering and Computer Science (ITSECS) Vol. 2 No. 3 (2024): Volume 2 Number 3 July 2024
Publisher : PT. Tech Cart Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58602/itsecs.v2i3.153

Abstract

A restaurant is a place of business that provides various types of food and beverages to be consumed on the spot or taken home. Restaurants are also often the venue of choice for various events, such as family gatherings, birthday celebrations, or business meetings. Restaurant recommendations based on user reviews are becoming an increasingly popular approach in helping individuals find the best places to eat according to their preferences. The purpose of the research is to develop an effective and objective decision support system in providing the best restaurant recommendations based on user reviews. This research makes a significant contribution to improving the quality of the user review-based recommendation system, by combining the advantages of objective data analysis (LOPCOW) and multi-criteria optimization (MOORA). The results of the combined ranking of the LOPCOW and MOORA methods show that Kedai Kita is ranked the highest with a score of 0.2897, followed by De'leuit Restaurant with a score of 0.284. Lemongrass Restaurant is in third place with a score of 0.2485, while Kluwih Sunda Authentic and Gurih 7 Bogor obtained a score of 0.2223 and 0.1981, respectively. The last position was occupied by RM Bumi Aki Puncak with the lowest score, which was 0.0396. These results show differences in performance or quality levels based on criteria analyzed using a combination of the two methods.
Decision Support System for Choosing the Best Shipping Service for E-Commerce Using the SAW and CRITIC Methods Wang, Junhai; Setiawansyah, Setiawansyah; Rahmanto, Yuri; Asistyasari, Ayuni
Jurnal Ilmiah Informatika dan Ilmu Komputer (JIMA-ILKOM) Vol. 3 No. 2 (2024): Volume 3 Number 2 September 2024
Publisher : PT. SNN MEDIA TECH PRESS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58602/jima-ilkom.v3i2.32

Abstract

Choosing the best delivery service for e-commerce is a crucial step that can affect customer satisfaction and overall business success. In today's digital era, consumers expect fast, secure, and affordable delivery. The main problem in choosing the best shipping service for e-commerce is often related to several interrelated factors, which can affect the customer experience and business sustainability. One of the biggest challenges is ensuring that products reach customers within the promised time. Delays in delivery can lead to customer dissatisfaction and potentially damage a business's reputation. The combination of SAW and CRITIC methods provides a powerful approach to multi-criteria decision-making. By leveraging the advantages of each method, users can objectively determine the weight of the criteria and evaluate alternatives in a systematic and transparent way. This approach not only improves the accuracy of decisions but also increases decision-makers confidence in the results obtained. Based on the results of the ranking using the method that has been applied, the alternative with the highest score is Pos Indonesia (A6) with a final score of 0.82506, followed by JNE (A1) with a score of 0.76181, and Tiki (A2) with a score of 0.72127. Based on these values, Pos Indonesia ranks first as the best service provider.
G2M weighting: a new approach based on multi-objective assessment data (case study of MOORA method in determining supplier performance evaluation) Hendrastuty, Nirwana; Setiawansyah, Setiawansyah; An’ars, M. Ghufroni; Rahmadianti, Fitrah Amalia; Saputra, Very Hendra; Rahman, Miftahur
Indonesian Journal of Electrical Engineering and Computer Science Vol 38, No 1: April 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v38.i1.pp403-416

Abstract

Criteria weighting methods in decision support system (DSS) face various challenges and limitations that can affect their accuracy and reliability. One of the main challenges is subjectivity, this subjective assessment can reduce the objectivity and consistency of results. The main objective of the new weighting method grey geometric mean (G2M) weighting is to provide more objective and robust criteria weights under conditions of uncertainty and incomplete data. The new G2M weighting approach has a significant potential impact on the DSS field, it has the potential to generate more effective and efficient decisions, which can improve organizational performance, reduce risk and optimize outcomes. Pearson correlation test results of two sets of rankings generated by DSS methods namely grey relational analysis (GRA), simple additive weighting (SAW), multi-attributive ideal-real comparative analysis (MAIRCA), weighted product (WP), combined compromise solution (COCOSO), vlsekriterijumska optimizacija i kompromisno resenje (VIKOR), and a new additive ratio assessment (ARAS) that there is a strong positive correlation between the two methods using G2M weighting criteria. The high correlation value indicates that the rankings of the methods used tend to move together, giving confidence in the consistency and validity of the resulting ranking results. This gives confidence that both methods can be used simultaneously or interchangeably with consistent results. The use of G2M weighting in the DSS method used can support better decision-making by providing consistent information and validity of ranking results.
Development of a Decision Support System Based on New Approach Respond to Criteria Weighting Method and Grey Relational Analysis: Case Study of Employee Recruitment Selection Megawaty, Dyah Ayu; Damayanti, Damayanti; Sumanto, Sumanto; Permata, Permata; Setiawan, Dandi; Setiawansyah, Setiawansyah
JOIV : International Journal on Informatics Visualization Vol 9, No 1 (2025)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/joiv.9.1.2744

Abstract

The purpose of this research is to propose a new approach in the criteria weighting method using the RECA method, the RECA method can help provide a systematic and structured framework for determining criteria weights in multi-criteria decision making. The determination of weights using the RECA method is to increase objectivity and accuracy in the candidate assessment and selection process by determining the appropriate weight for each criterion based on responses and assessments from experts or stakeholders. Testing the RECA Method with Multi Attribute Decision Making (MADM) techniques is an important step in measuring the effectiveness of the RECA Method in the context of multi-criteria decision making. Ranking tests using Spearman correlation between the RECA method and other methods such as SAW with a correlation value of 1, MOORA with a correlation value of 0.9636, MAUT with a correlation value of 0.9515, WP with a correlation value of 0.891, SMART with a correlation value of 0.9636, and TOPSIS with a correlation value of 0.8788 show a high level of rank consistency between the RECA method and these methods. This indicates that the RECA Method has a strong ability to generate similar candidate rankings with other methods, validating its reliability and consistency in the context of multi-criteria decision making. Implications for further research include exploring the application of the RECA method in different decision-making contexts other than recruitment, such as performance evaluation, project selection, or supplier selection. Further research could investigate the integration of the RECA method with other decision-making methods or algorithms to improve its performance and applicability in complex decision environments. Comparative studies with larger sample sizes and diverse datasets can provide deeper insights into the effectiveness and reliability of the RECA method compared to other methods.
DYNAMIC WEIGHT ALLOCATION IN MODIFIED MULTI-ATRIBUTIVE IDEAL-REAL COMPARATIVE ANALYSIS WITH SYMMETRY POINT FOR REAL-TIME DECISION SUPPORT Hadad, Sitna Hajar; Chandra, Iryanto; Wang, Junhai; Megawaty, Dyah Ayu; Setiawansyah, Setiawansyah; Yudhistira, Aditia
Jurnal Teknik Informatika (Jutif) Vol. 6 No. 1 (2025): JUTIF Volume 6, Number 1, February 2025
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2025.6.1.4170

Abstract

Decision Support Systems (DSS) have a crucial role in real-time decision-making, especially in the digital era that demands high speed and accuracy. Managing criterion weights in a dynamic environment presents significant challenges due to rapid and unpredictable changes in conditions. However, determining an accurate weight becomes difficult due to uncertainty, incomplete data, and subjective factors from decision-makers. In addition, changes in the external environment, such as market trends, regulations, or customer preferences, can affect the relevance of each criterion, thus requiring a real-time weight adjustment mechanism. The purpose of this study is to develop and explore the dynamic weight allocation method in symmetry point- multi-attributive ideal-real comparative analysis (S-MAIRCA) to support more accurate and responsive real-time decision-making in a dynamic environment. This research contributes to the understanding of how the weights of criteria can be adjusted automatically and responsively to changing conditions or new data, which increases the relevance and accuracy of decisions in a dynamic environment. The urgency of S-MAIRCA research is important because it often involves real-time, dynamic, and complex data. This development not only improves the adaptability of the S-MAIRCA method, but also contributes significantly to creating computer science-based applications that are more intelligent, flexible, and relevant to the evolving needs of the system. The results of the alternative ranking comparison using the CRITIC-MAIRCA, LOPCOW-MAIRCA, ROC-MAIRCA, and S-MAIRCA methods showed variations in the ranking order generated for each alternative using spearman correlation. The results of the correlation value of CRITIC-MAIRCA and LOPCOW-MAIRCA have a very high correlation of 0.993, which shows that these two methods provide almost identical rankings in alternative evaluation. Likewise, CRITIC-MAIRCA and S-MAIRCA had a high correlation of 0.979, signaling a strong similarity in ranking results despite slight differences in the approaches used by the two methods. The results of the application of the MAIRCA-S method in the development of DSS based on real-time data have a significant impact on improving the speed, accuracy, and adaptability of decisions. MAIRCA-S strengthens the validity of decision results by considering a variety of attributes on a more comprehensive scale, providing added value in the development of DSS for various industrial sectors.
Co-Authors Abhishek R Mehta Ade Dwi Putra Ade Surahman Adi Sucipto, Adi Aditia Yudhistira Agus Perdana Windarto Agus Wantoro Agustina, Intan Ahdan, Syaiful Ahmad Ari Aldino Ahmad Ari Aldino Ahmad Ari Aldino Ahmad Ari Aldino Ahmadfauzy Alfry Aristo Jansen Sinlae Alita, Debby Amalia, Zahrina Andi Nurkholis Andika, Rio Aniyanti Tafonao An’ars, M. Ghufroni Arfinia Rahma Ari Sulistiyawati Ari Sulistiyawati Ari Sulistiyawati Ari Sulistiyawati Ariany, Fenty Arie Qur’ania Arief Budiman Arshad, Muhammad Waqas Arsi Hajizah Asistyasari, Ayuni Ayu Megawaty, Dyah Bustanul Ulum Chandra, Iryanto Damayanti Damayanti Damayanti, Damayanti Daniarti, Yeni Daniel Prasetyo Tarigan Deas Andrian Dwijaya Debby Alita Dedi Darwis Dedi Triyanto Desyanti Dinda Titian Lestari Dodi Siregar Dodi Siregar Dwi Satria, M. Najib Dyah Aminatun Dyah Ayu Megawaty Eko Bagus Fahrizqi Erlin Windia Ambarsari Erliyan Redy Susanto Fadila Shely Amalia Fajar Irvansyah Faruk Ulum Febrianus Gea Ferico Octaviansyah Pasaribu, Ahmad Fernando, Yusra Fikri Hamidy Gibtha Fitri Laxmi Hamdan Sobirin, Muhammad Heni Sulistiani Heni Sulistiani Ida Mayanju Pandiangan Imam Ahmad Imam Ahmad Iryanto Chandra Isnain, Auliya Rahman Jeperson Hutahaean Jumaryadi, Yuwan Junhai Wang Junhai Wang Junhai Wang Junhai Wang Kiki Septiani Kurniawan, Arsy Laurent Nababan Mahendra, Ferdian Jerry Mahesa Raihan Rifqi Mandasari, Berlinda Marzuki, Dwiki Hafizh Megawaty, Dyah Ayu Merlin Puspita Sari Mesran Mesran Mesran, Mesran Mohammad Taufan Asri Zaen Muhaqiqin muhaqiqin Ni Komang Ratih Kumala Nirwana Hendrastuty Nuari, Reflan Nuralia Nuralia Nurman Fadhlullah nurnaningsih, Desi Nuzuliarini Nuris Octaviansyah, A. Ferico Oprasto, Raditya Rimbawan Palupiningsih, Pritasari Parjito Parjito Pasaribu, A. Ferico Octaviansyah Pasha, Donaya Permata, Permata Pramuditya, Andri Prastowo, Kukuh Adi Priandika, Adhie Thyo Pritasari Palupiningsih Purbha Irwansyah, Irsyad Pustika, Reza Putra, Ade Dwi Putra, Rulyansyah Permata Putri Sukma Dewi Putri Sukma Dewi Qadhli Jafar Adrian R Metha, Abhishek Rahmadianti, Fitrah Amalia Rahman, Miftahur Rasli, Roznim Mohamad Reflan Revife Purba Rilo Nur Devija Rini Nuraini Riska Aryanti Rohmat Indra Borman Romadhoni, Randi Roswita Daeli Roznim, Roznim Ruziana binti Mohamad Rasli Ryan Randy Suryono S. Samsugi Safi, Mudar Sanriomi Sintaro Saputra, Alvin Setiawan, Dandi Setyani, Tria Sinta, Ratna Sari Roma Siti Mahmuda Sitna Hajar Hadad Sofiansyah Fadli Sri Agustiani Br Siburian Subhan Subhan Sufiatul Maryana Sufiatul Maryana Sumanto Sumanto Sumanto Sumanto Surahman, Ade Susanto, Erliyan Redy Sussolaikah, Kelik Syaiful Ahdan Temi Ardiansah Trisnawati, Fika Ulum, Faruk Untoro Adji Very Hendra Saputra Very Hendra Saputra Wahyudi, Agung Deni Wang, Junhai Waqas Arshad, Muhammad Widiyanti, Adella yasin, ikbal Yohanes Eka Wibawa Yuliani, Asri Yuri Rahmanto Yusra Fernando