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All Journal MATICS : Jurnal Ilmu Komputer dan Teknologi Informasi (Journal of Computer Science and Information Technology) Jurnal Buana Informatika Jurnal Teknologi Informasi dan Ilmu Komputer Fountain of Informatics Journal Journal of Information Technology and Computer Science Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Dinamisia: Jurnal Pengabdian Kepada Masyarakat Jurnal Sistem Informasi, Teknologi Informasi, dan Edukasi Sistem Informasi (JUST-SI)
Akbar, Muhammad Aminul
Fakultas Ilmu Komputer, Universitas Brawijaya
Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Engineering Social Sciences Other

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Pengembangan Non-Player Character (NPC) menggunakan Unity ML-Agents pada Karting Microgame Haq, Muhammad Yasir Anshari; Akbar, Muhammad Aminul; Afirianto, Tri
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 5 No 13 (2021)
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Untuk dipublikasikan di Fountain of Informatics Journal (FIJ)
Development of Non-Player Character for 3D Kart Racing Game Using Decision Tree Nashrul Azhar Mas'udi; Eriq Muhammad Adams Jonemaro; Muhammad Aminul Akbar; Tri Afirianto
Fountain of Informatics Journal Vol 6, No 2 (2021): November
Publisher : Universitas Darussalam Gontor

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21111/fij.v6i2.4678

Abstract

Racing game is one of the genre that’s still popular today. Unity is one of many game engines one can use to develop a racing game. At Unity Asset Store, there is a free template called Micro-Game Karting which can only be played alone. In order to play player versus enemy mode, an artificial intelligence (AI) is needed for directing non-player character (NPC) who acts as the opponent. In racing game, the AI requires the use of movement algorithm and decision making system. For this study, the movement algorithm will use pathfinding. The algorithm is used as a guiding path when NPC is moving and avoiding obstacles in the way. Pathfinding will use waypoint system and raycasting to accomplish it. The decision making technique that will be used is decision tree. It functions as decision maker for NPC so it can determine the correct action to be done at certain time. Result of black box and white box testing showed NPC is functional. As for FPS (frame per second) test, performance suffers 0.2-0.3 FPS decrease for every addition of 2 NPCs. According to lap time test, the developed NPC is faster than ML NPC and driving test showed favorable outcome.
NPC Braking Decision for Unity Racing Game Starter Kit Using Naïve Bayes Muhammad Aminul Akbar; Tri Afirianto; Steven Willy Sanjaya; Ratih Kartika Dewi
Fountain of Informatics Journal Vol 4, No 2 (2019): November
Publisher : Universitas Darussalam Gontor

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21111/fij.v4i2.3591

Abstract

AbstractRacing video game genre was still being popular today. One way to develop racing games quickly is by using a template or kit that is on the game engine. Racing Game Starter Kit (RGSK) was being the most popular racing game template for Unity game engine. However, there was problem in racing game’s NPC especially in RGSK related to NPC vehicle’s braking decision. The commonly used method is the Brake Zone, but the developers must manually place the zone themselves in the designated locations for braking. The solution that can be applied for that problem is see the angle formed by the vector of the NPC vehicle with the vector from 2 next following waypoint then determine the best configuration angle threshold for NPC braking, but this also has its shortcoming in which to get the best result, a proper threshold configuration is needed in each track. To resolve the problem, researcher proposed the method of machine learning, Naïve Bayes for the braking decision. Naïve Bayes uses two output classes (brake or no brake) in which the data will be obtained from the player. We use data from players who can control racing car games well or have never hit a wall and have fast lap times. The purpose of this study is to provide an alternative braking method to RGSK that can provide fast lap times but does not affect the game's FPS and without the need to determine or change any parameters on each track. The test result using RGSK v1.1.0a in Unity Game Engine showed that the proposed method can be an alternative method in RGSK braking decisions. Our NPC has faster lap time and was able to prevent the vehicle from crashing with the outer wall without dropping the game’s FPS (Frames per Second).Keywords: Braking Decision, Racing Game Starter Kit, Naïve Bayes, Machine learning, Unity engine AbstrakGenre video gim balap masih populer saat ini. Salah satu cara untuk mengembangkan game balap dengan cepat adalah menggunakan template atau kit yang ada di game engine. Racing Game Starter Kit (RGSK) adalah templat game balap paling populer pada Unity Game Engine. Namun, terdapat permasalahan NPC pada gim balapan terutama di RGSK terkait dengan keputusan pengereman kendaraan NPC. Metode yang digunakan untuk eksperimen jenis ini adalah Zona Rem. Namun, pengembang harus secara manual menempatkan zona tersebut di lokasi tertentu pada setiap lintasan. Solusi dari masalah ini yang sudah diterapkan pada RGSK v1.1.0a yaitu dapat menggunakan sudut yang dibentuk oleh vektor kendaraan NPC dengan vektor dari 2 titik arah berikutnya, kemudian menentukan ambang sudut terbaik untuk pengereman NPC, tetapi ini juga memiliki masalah yaitu untuk mendapatkan hasil putaran terbaik atau cepat, perlu menentukan konfigurasi ambang batas yang tepat di setiap trek. Untuk mengatasi masalah tersebut, peneliti mengusulkan metode pembelajaran mesin, Naïve Bayes untuk keputusan pengereman. Naïve Bayes menggunakan dua kelas output (rem atau tidak ada mengerem) di mana data akan diperoleh dari pemain. Kami menggunakan data dari pemain yang dapat mengontrol permainan mobil balap dengan baik atau tidak pernah menabrak tembok dan memiliki waktu putaran yang cepat. Tujuan dari penelitian ini adalah untuk memberikan metode pengereman alternatif untuk RGSK yang dapat memberikan waktu putaran yang cepat namun tidak mempengaruhi FPS game dan tanpa perlu menentukan atau mengubah parameter apa pun di setiap trek. Hasil pengujian menggunakan RGSK v1.1.0a di Unity Game Engine menunjukkan bahwa metode yang diusulkan dapat menjadi metode alternatif dalam keputusan pengereman RGSK. NPC kami mempunyai waktu putaran yang lebih cepat dan mampu mencegah kendaraan agar tidak menabrak dinding luar tanpa menjatuhkan FPS game (Frame per Detik).Kata kunci: Keputusan Pengereman, Racing Game Starter Kit, Naïve Bayes, Pembelajaran Mesin, Unity Engine
Pengembangan Non-Player Character (NPC) Menggunakan Unity ML-Agents Pada Karting Microgame Muhammad Yasir Anshari Haq; Muhammad Aminul Akbar; Tri Afirianto
Fountain of Informatics Journal Vol 7, No 1 (2022): Mei
Publisher : Universitas Darussalam Gontor

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21111/fij.v7i1.5487

Abstract

AbstrakPerkembangan teknologi di bidang gim sekarang sudah sangat pesat terutama pada gim balapan. Gim balapan memiliki tujuan untuk memberikan pemain sebuah pengalaman yang menantang dan menyenangkan dalam sebuah balapan melawan mobil yang dikendalikan oleh gim tersebut atau biasa disebut dengan Non-Player Character (NPC). Pengembangan gim balapan tentunya tidak dapat lepas dari pengembangan NPC sebagai lawan main dari pemain. Pada umumnya NPC dikembangkan menggunakan metode waypoint untuk navigasi dalam melintasi trek balapan. Kekurangan dalam metode waypoint adalah harus diatur secara manual untuk setiap trek dan memakan waktu yang lama untuk mengatur waypoint pada setiap trek. Begitu juga untuk membuat NPC balap yang kompetitif dibutuhkan desain rule base yang kompleks. Peneliti mengusulkan menggunakan metode machine learning untuk mengatasi permasalahan tersebut. Unity3D menyediakan sebuah open-source API bernama Unity ML-Agents yang dapat digunakan untuk melatih NPC. NPC dilatih menggunakan metode reinforcement learning dengan Unity ML-Agents yang bertujuan untuk melatih NPC dengan cara memberikan reward agar mencapai hasil yang optimal. Hasil yang didapatkan dengan memanfaatkan Unity ML-Agents adalah NPC yang dapat melintasi berbagai macam trek dan dapat menghindari tabrakan. NPC yang telah dikembangkan dengan Unity ML-Agents juga mendapatkan waktu total yang lebih sedikit dibandingkan dengan waktu total yang diperlukan pemain untuk menempuh 3 lap putaran pada suatu trek yaitu 55,9 detik dibandingkan dengan 59,4 detik.Kata kunci: gim balapan, non-player character, unity ml-agents, reinforcement learning.Abstract[Non-Player Character (NPC) Development Using Unity ML-Agents in Karting Microgame] Nowadays, the development of game technology is very fast, especially in racing games. The racing game aims to provide players with a challenging and fun experience in a race against cars controlled by the game or commonly known as the Non-Player Character (NPC). Of course, the development of a racing game cannot be separated from the development of NPCs as opponents of the players. In general, NPCs were developed using the waypoint method for navigation across racetrack. The disadvantage of the waypoint method is that it must be set manually for each track, and it takes a long time to set the waypoint for each track. Likewise, making a competitive racing NPC requires a complex rule base design. Researchers suggest using machine learning methods to overcome these problems. Unity3D provides an open-source API called Unity ML-Agents which can be used to train NPCs. NPCs are trained using the reinforcement learning method with Unity ML-Agents which aims to train NPCs by providing rewards to achieve optimal results. The results obtained by utilizing Unity ML-Agents are NPCs that can traverse various kinds of tracks and can avoid collisions. NPCs that have been developed with Unity ML-Agents also get less total time compared to the total time required for a player to take 3 laps on a track, which is 55.9 seconds compared to 59.4 seconds.Keywords: racing game, non-player character, unity ml-agents, reinforcement learning.
Peningkatan Kompetensi Keilmuan IOT Melalui Pelatihan Pengontrolan Perangkat IOT dengan Menggunakan Smartphone untuk Siswa SMK dan SMA di Kota Malang Dahnial Syauqy; Yuita Arum Sari; Putra Pandu Adikara; Muhammad Aminul Akbar; Hurriyatul Fitriyah
Dinamisia : Jurnal Pengabdian Kepada Masyarakat Vol. 4 No. 3 (2020): Dinamisia: Jurnal Pengabdian Kepada Masyarakat
Publisher : Universitas Lancang Kuning

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31849/dinamisia.v4i3.3785

Abstract

The internet has encouraged the emergence of a new paradigm in the use of computing, marked by the emergence of devices that are connected to each other or known as the Internet of Things (IoT). One of the factors that contributed to the rapid emergence of "things" in the IoT network was the rapid development of chip technology and also increasingly varied wireless communication technology. With the emergence of the phenomenon of the development of IoT, especially those involving entrepreneurial opportunities in related fields, it is considered important to be introduced early on to students of vocational-high school equivalents in Indonesia. The activity was held in September 2019 at Filkom UB involving 41 participants from 6 schools of vocational-high school or equivalent. The activity succeeded in increasing the participant's understanding of the theory and also the practice of IoT where the participants' pre-test and post-test scores increased from an average of 61.6 to 92.9. The implementation of the activity was also declared successful from the results of the questionnaire. From a total of 425 answers, there were 17 STS answers, 39 TS answers, 205 S answers and 164 SS answers. Taking into account the positive and negative components, a recapitulation of 415 answers (98%) was found to be satisfied with the implementation of the activities.
Penerapan Algoritma Hybrid Pathfinding A* dan Boids untuk Game Pesawat Tempur Firdaus Rahmat Prasetyo; Eriq M. Adams Jonemaro; Muhammad Aminul Akbar
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 1 No 12 (2017): Desember 2017
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

The A* and Boids hybrid pathfinding algorithms can be used as a way of tracking the flying paths of aircraft games. In hybrid pathfinding, A* algorithm is used as the shortest path finding and avoid static obstacles while the Boids algorithm is used as a flyweeker in groups and avoids dynamic obstacles .Grid used for path search using A* algorithm is driven according to A* agent position that it does not increase number of nodes because in aircraft game the map size is so large. Pathfinding using A* algorithm will only be call when grid touch static obstacle, so pathfinding doesn't take a long time. This is proven when the agent uses an A* algorithm, the average of execution time increase by 4.24% and the average of FPS decreases by 11.59% compared with not using the A * algorithm. While the use of Boids algorithm is continuously on the aircraft so that the aircraft does not collide with each other. This algorithm is chosen because it has a time complexity that is not too high. This is also proven when there is dynamic obstacles in map, the average of execution time increase is only 6.21%.The average FPS on all maps is 75.91 which is above of the FPS limit that can trick the eye by 20. The average execution time of all maps is 102.79 ms. The average path length of all maps is 445.56. The average number of actors destroyed from all maps is 107.
Pengembangan Permainan Edukasi Berbasis Kinect bagi Penderita Asperger Syndrome untuk Menangani Empathy Disorder Dessy Amri Raykhamna; Tri Afirianto; Muhammad Aminul Akbar
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 1 (2018): Januari 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

In Indonesia, the handling of empathy disorder in asperger syndrome sufferers was not welcomed by parents due to cost and transportation factors. In addition, treatment of empathy disorder in asperger syndrome sufferers is given the same treatment with other Autism Spectrum Disorder (ASD) classification. This research aims to develop Kinect-based educational game that can help a person with asperger syndrome in understanding feelings of the others, so that empathy toward each other can grow. At the end of 2013 until 2014, Kinect considered feasible for dealing with therapy and rehabilitation in people with neurological disease and Traumatic Brain Injury (TBI). In this research, Kinect applied in educational game that relies on the movement of the right hand. This research was tested on 5 asperger syndrome sufferers with empathy disorder. The results of this research achieved after asperger syndrome sufferers using Kinect-based educational game, that resulted increased score on each level and emotion, as well as descreased total Toronto Empathy Questionnaire (TEQ) of 12.8% from average of total TEQ before asperger syndrome sufferers using Kinect-based educational game.
Implementasi Adaptive AI Pada Game Turn-Based RPG Dengan Menggunakan Metode Hierarchial Dynamic Scripting Intishar Fadi Abdillah; Eriq Muh. Adams Jonemaro; Muhammad Aminul Akbar
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 2 (2018): Februari 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

There are many methods used by game developers in applying Artificial Intelligence (AI) into Non Playable Character (NPC) which aims to inhibit gamers in achieving their goals or mission. Scripting method is one of the most used method of game developers in designing AI in NPC because of its simple, flexible (easy to modify), and powerful process. Scripting method is a way to design behavior NPC through a combination of rules that are modeled with if-then sentences. The combination of these rules is explicitly written on source code or other external files (commonly referred to as hard coded) which is not possible to change the NPC behavior when the game has been released. This causes the NPC is often easily exploited by gamers who have understood the pattern of the NPC behavior. To overcome these problems, we need a method capable of producing an adaptive NPC behavior while still providing the nature of Scripting method that is simple, flexible, and powerful. Therefore, Hierarchial Dynamic Scripting method tries to answer the problem in this research. Hierarchial Dynamic Scripting method is an advanced development of the Dynamic Scripting method by adding Hierarchial Task Network architecture in it. The main principle of the Dynamic Scripting method is to assign specific weights to the set of rules and combine them into a dynamic script. Adaptive test results conducted in the game with the genre of Turn-Based Role Playing Game based on three parameters of the test of effectiveness, efficiency, and variation shows that the NPC using Hierarchial Dynamic Scripting method has a high effectiveness with the average fitness value of 0.73 and High efficiency by achieving an average turn-point value of 6 against all scenario tactics in this study. In addition, testing the value of break even point yields the best value of 0.5 to get a good level of NPC adaptability.
Penerapan Adaptive AI pada Game Turn Based RPG Dengan Menggunakan Metode Monte Carlo Tree Search Yuka Bimatara Putra; Eriq M. Adams Jonemaro; Muhammad Aminul Akbar
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 7 (2018): Juli 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Many methods can be used by game developers to be implemented into Artificial Intelligence (AI) in enemy agents or commonly called Non Playable Character (NPC) which aims to make players become more challenged in completing the game they play. One of the usual algorithms is Monte Carlo Tree Search (MCTS). The MCTS algorithm has been successfully constructed for turn-based gaming board games, the GO game. In the experiment, AI agents using MCTS scored higher than previous studies, so when tested, AIs using the MCTS algorithm can beat international GO champions. Given the success of the MCTS implementation, this study will discuss the application of MCTS to enemy agents in turn-based RPG games. The test is performed to validate the decision making of the selected agent and the effect of the MCTS process loop on the skill to be selected. For validation of decision making, testing will be done by looking at the effectiveness level and for testing the effect of MCTS process loop on effectiveness is done by simulation with several scenarios using different MCTS loops. The level of effectiveness is tested by looking at the win ratio of the agent team.
Evaluasi User Experience pada Game Left 4 Dead 2 Menggunakan Cognitive Walkthrough Muchtar Prawira Sholikhin; Eriq Muh. Adams Jonemaro; Muhammad Aminul Akbar
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 7 (2018): Juli 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Each product has a user experience aspect which is a science to make the users convenient of using the product. It is aimed to optimize the interaction between the users and the product. In order to concretely find out the User Experience, it requires mathematic calculation. Cognitive Walkthrough is one of analytic evaluation method. This method will evaluate each step in a product, to find out the main problem which make the users inconvenient. This method is cheap, fast and efficient so that it is suitable to be applied to new users. Game Left 4 Dead 2 which was awarded as IGN's Best Multiplayer Game in 2009, is suitable to be an object of evaluation by using Cognitive Walkthrough method. The result shows that the average of error is 7 times for each respondent, with type of User Error (U) and Hidden error (H).
Co-Authors Abdulloh, Roihan Abdurrahman Prawira Purmiaji Abi Firmandhani Adam Hendra Brata Ade Suluh Novriananda Aditya Luthfi Alvari Ramadhan Aditya Rachmadi Aditya Rachmadi, Aditya Agi Putra Kharisma Agi Putra Kharisma, Agi Putra Agung Dwi Budiarto Ahmad Afif Supianto Ahmad Afif Supianto Ahmad Fadli Naharu Ahmad Fathoni Akbar Ramadhan Akhmad Dinan Jatnika, Aditya Aldo Rizky Saputra Alfi Nur Rusydi Allen Nazario Istalaksana Amzi, Dzakwan Mufid Anderson Manurung Andhi Indra Lestya Wicaksono Andri Alfian Arief Alamsyah Arito Jalu Priyangga, Dionisius Arya Bhanuartha, Putu Gde Aryo Pinandito Aryo Seto Dwisaputra Auliya, Meida Dela Risyafa Azhim Kustiwa, Alwan Fauzul Azizah Febyanti, Hilda Ayu Azzaky, Mohammad Rafi Buce Trias Hanggara Bugi Pradana Nugroho Cahyani, Luvita Intan Cahyono Hadi Kurniawan Carlista Naba Christian Doxa Hamasiah Chrysler Imanuel Chyntia Savrila Putri Dahnial Syauqy David Hosea Sipahutar Davin Benaya Dessy Amri Raykhamna Dheanisa Putri Rahayu Ditya Enandini Palupi Djoko Pramono Djoko Pramono Dwi Rama Malawat Edy Santoso Eriq M. Adams Jonemaro Eriq Muh. Adams Jonemaro Eriq Muhammad Adams Jonemaro Eriq Muhammad Adams Jonemaro Eriq Muhmmad Adams Jonemaro Fajar Pradana Farisi, Hariz Fathony Teguh Irawan Fathurrahman Annafabi Fernando, Samuel Fikri Ihsan Ahmad Firadi Surya Pramana Firdaus Rahmat Prasetyo Fitraldy Soefana Fitrantika Diashafira Gunawan, Alexander Hamdany, Mohammad Naufal Adib Hamidah, Nazwa Ambar Hanifah Muslimah Az-Zahra Hanifah Muslimah Az-Zahra, Hanifah Muslimah Haq, Muhammad Yasir Anshari Hariz Farisi Hendro Dwi Prasetyo Herawan, Almaas Rozikin Herlambang Yudha Prasetya Herlando, Muhammad Raafi Herman Tolle Hermawan, Renaldy Hilmi Derian, Ivan Hilmi Ilyas Rizaldi Hurriyatul Fitriyah I Made Wira Satya Dharma Ian Setyo Aji Ilham Akbar Ahmadi Ilham Gibran, Muhammad Ilmam Achmadiarsyi Ilman Naafian Firmansyah Indi Rachmah Winona Intan Sartika Eris Maghfiroh Intishar Fadi Abdillah Iqbal Firmansyah Iqbal Putra Santosa Ismiarta Aknuranda Ismiarta Aknuranda Issa Arwani Issa Arwani Isthofi Aslim Sofyan Javas Marchad, Radithya Jermias Kristian Jonemaro, Eriq Muhammad Adams Kaeksi, Racana Ayu Komang Candra Brata Kusuma, I Made Yudi Anantha Lailatussaadah M Nur, Lailatussaadah Lutfi Fanani Lutfi Fanani Luthfi Fawwaz Putranto Mas'udi, Nashrul Azhar Mayovio Ahmad Mahendrata Mochamad Chandra Saputra, Mochamad Chandra Mochamad Halim Mohamad Ilham Ridho Mohammad Alauddin Mohammad Chaliffilardhy Syaifuddin Muadz Askarul Muslim Muchtar Prawira Sholikhin Muhamad Arifin Ramadhan Muhammad Adams Jonemaro , Eriq Muhammad Arif Nabil Lesmana Muhammad Aufa Athallah Muhammad Azmi Muhammad Azzam Al-Ghifari Habiburrahman Muhammad Reza Pahlevi Muhammad Salman, Raditya Muhammad Satrio Bayu Pamungkas Muhammad Yasir Anshari Haq Muhtadin Ziqi Maulana Mujahid Bariz Hilmi Musavi Ardabilly Taufik Naba, Carlista Najibudin, Mochamad Asrof Nashir, Idham Ahmad Nashrul Azhar Mas'udi Nashrul Azhar Mas'udi Niken Hendrakusma Nugroho, Bramantyo Raka Adi Nur Efendi, Akhmad Farid Nur Muhammad Rashid Oktafianto, Mukhammad Afan Pamesthi, Radya Farrel Panji Yodantara Pardede, Natanael Isaac Pardamean Pelealu, Billawal Nadipa Prakoso, Bondan Sapta Pramudya Vizkal Arfianto Purnomo, Welly Putra Pandu Adikara PW, M. Qodarul Amar Rahadian Fernandika Ramadhan Rizki Arga Putra Ramdani, Aditasha Fadhila Ratih Kartika Dewi Retno Indah Rokhmawati Retno Indah Rokhmawati, Retno Indah Reza Saputra Richard Hans Octavian Riswan Septriayadi Sianturi Robertus Dwi Ari Utomo Ryan Aristo Salman, Raditya Muhammad Sandhi Wistara Sativandi Putra Satrio Hadi Wijoyo Setiawan, Muhammad Syahrul Setyowidodo, Fauzan Athallah Shandya Fajar Widyono Shena Star Sarwodi Silitonga, Erico Steven Willy Sanjaya Steven Willy Sanjaya Sudjianto, Aulia Heppy Cahya Susanto, Stefanus Rangga Ananta Syahputra, Andira Mahendra Syarief Noor Permadi TABAYUNI, RAHIMI ILLONG Tjandra, Jahzeiah Paskah Togan Jagat Raya Tri Afirianto Tri Afirianto Tri Afirianto Tri Afirianto Tri Afirianto, Tri Trias Hanggara, Buce Utomo, Ibnu Najah Barlian Hadi Viqi Hanada Wibisono Sukmo Wardhono Wibisono Sukmo Wardhono, Wibisono Sukmo Widhy Hayuhardhika Nugraha Putra Wijaya, Aldy Imam Winny Ardhian Septiko Wiranata, Danuar Wong, Vinncent Wong, Vinncent Alexander Yolanda Saputri Yoshua Aditya Kurnia Yosua Yosua Yudha Hadi Pratama Yudistira, Faisal Ariawan Yuita Arum Sari Yuka Bimatara Putra Yuki Pradana Yung, Clara Clarita Yusi Tyroni Mursityo Zulfikar Fahmi Falakh Zulkahfi, Muhammad Razzaaq