Article Per Year (5 Year)
p-Index From 2021 - 2026
16.028
P-Index
This Author published in this journals
All Journal International Journal of Electrical and Computer Engineering International Journal of Reconfigurable and Embedded Systems (IJRES) ComEngApp : Computer Engineering and Applications Journal TELKOMNIKA (Telecommunication Computing Electronics and Control) Jurnal Teknologi Informasi dan Ilmu Komputer Register: Jurnal Ilmiah Teknologi Sistem Informasi Journal of Information Technology and Computer Science Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer INTENSIF: Jurnal Ilmiah Penelitian dan Penerapan Teknologi Sistem Informasi Dinamisia: Jurnal Pengabdian Kepada Masyarakat
Dahnial Syauqy
Fakultas Ilmu Komputer, Universitas Brawijaya
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Social Sciences Other

Published : 248 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 248 Documents
Search

 15   16   17   18   19 
Sistem Pemilihan Ikan Lele Siap Panen berbasis Mikrokontroler dengan Metode K-Nearest Neighbors Wisik Dewa Maulana; Dahnial Syauqy; Fitri Utaminingrum
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 6 No 8 (2022): Agustus 2022
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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

Abstract

Catfish is one type of fish that is often consumed by the community, catfish is also one of the fish with high economic value. In addition to high economic value, catfish is also a fish that has a fairly fast growth. Usually catfish with the age of 3.5 - 4 months are ready to be harvested, but even though the age of catfish has entered the harvest period, not all catfish have the same size as one another. That's all caused by the greedy nature of catfish and the imbalance in the number of catfish with the size of the pond. So farmers prefer to do manual sorting to determine which catfish are ready to harvest based on weight and length. Therefore, this study aims to assist catfish farmers in sorting catfish that are ready to harvest with the help of a load cell sensor to measure weight and an ultrasonik sensor to measure length. Then the two values will be classified using the K-Nearest Neighbors method with the help of Arduino as the main system for classifying and also servo as the output of this system. This study tested the load cell and ultrasonik sensors as input for the length and weight while the classification using the K-Nearest Neighbors method got an accuracy value of 81,25% with computing time 33 ms.
Implementasi Algoritma Naive Bayes pada Sistem Monitoring dan Klasifikasi Kualitas Air Akuarium Ikan Mas Koki Agra Firmansyah; Dahnial Syauqy; Barlian Henryranu Prasetio
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 6 No 9 (2022): September 2022
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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

Abstract

In this era of technological development, new innovations are needed that can help humans carry out their activities more efficiently. One of these areas of activity is measuring the water quality of the goldfish aquarium. At this time the measurement of air quality, especially in aquariums, is done manually on each attribute to be measured, while the measuring instrument for measuring the level of the attribute to be measured varies with prices that are relatively affordable to very expensive. In addition, using opinions based on direct observations of aquariums, etc. Therefore, the purpose of this research is to create a system that can help overcome this problem. In this study, the system was designed using a turbidity sensor as a measure of water turbidity levels, mq-135 as a measure of ammonia gas (NH3) and pH as a measure of acid and base levels. As for the display system using a 16x2 LCD to display the output obtained. This system component goes through the Arduino uno as a microcontroller and a laptop to enter code on the Arduino ide so that the system can run and as the main power supply. The classification used in this study is nave Bayes, nave Bayes is an algorithm method to determine the value of each class based on training data and test data, to read numerical attributes using distribution calculations, the attributes used in this Nave Bayes classification are obtained from reading turbidity, ammonia and ph of the sensor. This nave Bayes method has a fairly good accuracy, the higher the accuracy of the method, the more training data with various values.
Pengembangan Sistem Navigasi Robot Beroda menggunakan Lokalisasi berbasis RFID dengan Pathfinding Algoritma A Star pada Simulasi Lingkungan Gudang Farras Nabil; Dahnial Syauqy; Eko Setiawan
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 6 No 11 (2022): November 2022
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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

Abstract

The rise of the use of E-Commerce sites places a huge burden on the logistical side, therefore many E-commerce companies implemented a fulfillment service in the form of warehousing that reduces the burden on the logistical side. The problem with these fulfillment services is the physical burden put on the workers of the warehouse. Therefore a system will be made that will help the worker with the use of a robot that can move from place to place automatically. This system will be in the form of a robot using a differential drive method and equipped with an RFID sensor to know it's location. An RFID will be placed in certain spots and will be named node. The system will use the A* algorithm to find a route starting from 0,0. The accuracy of the whole of the system is 75% for the movement of the robot, and 100% for the algorithm itself with a speed of computation between 34 and 199 microsecond for computing the path using A* in a map of size 4x3.
Sistem Voice Command pada Kursi Roda Pintar menggunakan MFCC dan CNN berbasis Jetson TX2 Tobias Sion Julian; Fitri Utaminingrum; Dahnial Syauqy
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 6 No 11 (2022): November 2022
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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

Abstract

Paralysis is a condition in which the movement of a body part is impaired to the point where it is unable to move partially or completely. People with paralysis often need assistive devices to help with their mobility, such as wheelchairs. Smart wheelchairs that use a voice control system can help people who are unable to use their hands to control a wheelchair. This system uses the MFCC feature extraction method, which is the method that most closely approximates human hearing, and the CNN classification method, which has been proven to work well when trained with features extracted using MFCC. The system is run on a Jetson TX2 device and controls the wheelchair using an Arduino Uno by adjusting the pulse width modulation value according to the classification result of the system's command. The dataset used to train the CNN model is the speech_command v2 dataset created by Tensorflow, which contains over 500,000 data for 36 classes. In this research, however, 15,000 data were used for 4 command classes: "Go," "Right," "Left," and "Stop." The results of the system testing show an accuracy prediction value of 85% with a relatively fast average computation time of only 0.37 seconds to make a prediction.
Klasifikasi Kelayakan Susu Sapi UHT berdasarkan PH, Warna, dan Aroma menggunakan Metode Naive Bayes berbasis Arduino Muhammad Daffa Bintang Nugroho; Dahnial Syauqy; Hurriyatul Fitriyah
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 6 No 11 (2022): November 2022
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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

Abstract

Ultra High Temperature cow's milk is a type of milk that is widely consumed by humans from children to adults because milk has a myriad of health benefits, but if the cleanliness of the processing is not maintained, milk quickly becomes unfit for consumption and can cause various adverse effects for a person who consume it. There are many ways to determine the appropriateness of consuming milk, such as by looking at its color, smelling the aroma, or tasting the milk, but these methods are ineffective and raise doubts about whether milk is still suitable or not suitable for consumption. This study designed a system to determine the feasibility of Ultra High Temperature cow's milk based on pH parameters, ammonia gas content, and color. To determine the value of each parameter, a PH 4502C sensor, MQ135 gas sensor, and TCS3200 color sensor are used to carry out the process of determining the feasibility of milk using the Naive Bayes classification method which is processed with the Arduino Mega 2560 microcontroller. The results of the accuracy of the system test to determine the feasibility of milk Ultra High Temperature cattle based on pH parameters, ammonia gas content, and color with the Naive Bayes classification method using 40 training data and 20 test data is 85% with a computation time of 1,911 seconds.
Sistem Klasifikasi Kualitas Air untuk Budidaya Ikan Nila Hitam (Oreochromis Niloticus) menggunakan Metode Support Vector Machine Dwiki Ilham Bagaskara; Dahnial Syauqy; Barlian Henryranu Prasetio
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 6 No 12 (2022): Desember 2022
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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

Abstract

Black Tilapia or which has the scientific name Oreochromis Niloticus is a type of freshwater fish that is widely consumed throughout the world, especially in Indonesia. Tilapia production continues to increase along with the increasing demands to meet food needs both domestically and abroad. One of the efforts made to achieve this target is cultivating tilapia seeds to improve the quality and production of tilapia. In cultivating tilapia in order to obtain quality fish yields, one of the most important factors influencing this is the quality of the water in the pond where the tilapia is cultivated. In Indonesia there are still many tilapia cultivators who measure and control pond water quality manually or even don't do this at all. For this reason, a water quality classification system will be designed for black tilapia cultivation using the support vector machine method which can carry out classifications to determine water quality in ponds automatically. The system is implemented using 3 sensors, namely the temperature sensor DS18B20, the pH sensor PH-4502c, and the turbidity sensor SEN0189. In the test, 3 features were used in the system to make training and testing data, namely temperature features, pH features, and turbidity features to determine the class of pond water being tested. 60 total training data consisting of 30 pieces of data for the "good" class and 30 pieces of data for the "bad" class were used to conduct training data for the classification system. The support vector machine classification method that is programmed in the system will carry out the classification process by reading the values ​​from the sensors and storing them as features to be processed and compared with the results of the training data. The system will look for the y value as the reference value for class classification results where if the y value ≤ 1 then the water will be declared "good" and if y> 1 then the water is said to be "bad". The test results are obtained by reading the output results on the system LCD for 15 seconds. From the test results, 15 reading were obtained where 12 of the test results were correct readings and 3 were incorrect readings. From the test results it can be concluded that this system can work according to its function and purpose.
Implementasi Metode K-Nearest Neighbor untuk Sistem Deteksi Covid-19 berdasarkan Suhu Tubuh dan Kadar Oksigen Graciella Fiona Br. Panjaitan; Edita Rosana Widasari; Dahnial Syauqy
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 7 No 1 (2023): Januari 2023
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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

Abstract

Covid-19 disease is a contagious disease, so it is necessary to avoid direct contact between humans to minimize exposure to this virus. Examination to the hospital can allow people to be exposed to the Covid-19 virus because direct contact with some people is still carried out in an invasive way. So research is needed to detect the symptoms of Covid-19 non-invasively and does not require a lot of money and time. In this study the detection of body temperature used the MLX90614 sensor by facing the hand towards the front of the sensor so that the body temperature value was obtained. To detect oxygen levels using the MAX30100 sensor by placing your index finger on the sensor then waiting until the oxygen level value is obtained. The two values ​​from the sensor readings will be classified using the K-NN method. The output will be displayed on the LCD in the form of sensor measuring value text and classification results. The test results in this study obtained the accuracy of the sensors used. For measuring body temperature using the MLX90614 sensor, an accuracy of 99.56% was obtained, then for measuring oxygen levels using the MAX30100 sensor, an accuracy of 98.77% was obtained. In the classification test, it is determined by three distances k, namely k=3, k=5, and k=7, where k=3 gets an accuracy of 100%, k=5 gets an accuracy of 90%, and k=7 gets an accuracy of 80%. and from this classification, the average computation time is 2.38 ms.
Sistem Deteksi Hipoksia menggunakan Metode Decision Tree berdasarkan Detak Jantung dan Kadar Oksigen Elisabeth Agustina; Edita Rosana Widasari; Dahnial Syauqy
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 7 No 1 (2023): Januari 2023
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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

Abstract

Hypoxia is a condition where there is a continuous lack of oxygen either in the short or long term according to a period. If hypoxia occurs in the short term, what is caused is acute hypoxia. The symptoms found in hypoxia are very fast heartbeat (tachycardia), rapid breathing, dizziness, weakness. Based on the existing problems, the authors want to conduct research to detect hypoxia. The tool designed for this study can detect hypoxia based on heart rate and oxygen saturation. This detection is very easy to use, just by placing your index finger on the MAX30100 infrared sensor, after that you get the measurement results which will be displayed on the LCD screen. The results of these measurements will be the input data for classification. This classification uses the Decision Tree method where this method is very accurate and fast in carrying out the classification process. Classification results will be displayed on the LCD screen. Testing of this tool was carried out 10 trials in detecting heart rate and oxygen saturation. The accuracy obtained when doing the classification is 100%. The MAX30100 sensor when measuring heart rate obtains an accuracy of 97.66% and an error rate of around 2.34. Then, the accuracy obtained when detecting oxygen levels is 98.75% with an error rate of 1.25%
Klasifikasi Rumah Sehat dengan Metode Jaringan Syaraf Tiruan berbasis ESP32-S Noveriko Noveriko; Dahnial Syauqy; Edita Rosana Widasari
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 7 No 2 (2023): Februari 2023
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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

Abstract

A home is a place to return to, rest, and take shelter. Most people spend a large portion of their time at home. The amount of time we spend in our homes makes it important for us to pay attention to the health conditions of our home. A home that is not well-maintained can become a breeding ground for diseases. The solution that I propose is to create a system that can determine a home's health score and also measure the criteria in each room. The system that I have created uses a Artificial Neural Network algorithm and an ESP-32 microcontroller as the processor unit. The system will take in features captured by each sensor, including light intensity (BH1750), air temperature (DHT11), air humidity (DHT11), and carbon monoxide levels in the air (MQ-7). The results of the algorithm and measurements will be displayed on a 20x4 LCD screen, showing the measured features, the obtained score, and the confidence of the classification. The training data used in this system consists of a total of 345 data from 4 classes, with each class consisting of approximately 80 data. The testing was carried out in rooms in a volunteer's home, with a total of 20 rooms. The results of the testing show that 18 were correct and 2 were incorrect, resulting in a system accuracy of 90% with an average computation time of 0.148 seconds.
Rancang Bangun Pita Lengan Metronome dengan Koneksi Bluetooth berbasis Mikrokontroler dan Android Jezriel Lukas Lumbantobing; Dahnial Syauqy; Agung Setia Budi
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 7 No 3 (2023): Maret 2023
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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

Abstract

To determine the tempo in a song, Metronome is needed to help as a tool, because the metronome will produce sound on every beat of the song. However, the metronome used on the market is less effective in terms of helping the tempo during live shows and can also interfere with hearing when using earphones if the volume of the metronome should be increased. A metronome arm band can be a solution because it produces a vibration that can be felt in the hands. Users can also set the desired number of beats per minute (BPM) via a smartphone application that is connected via bluetooth. There are 3 elements to be used, which are; Smartphone as input, ESP32 as processor and Vibration Motor as an output. Because metronomes must have high accuracy in keeping the tempo, RTOS is needed to help avoid interruptions when the user sends other commands during vibration. There are 3 tests carried out to determine the accuracy of the Metronome Bracelet. The first test to see whether 60 bpm on the metronome produces an output of exactly 60 beats per minute. The second and third tests are also the same but at different tempo numbers, which are 90 and 120. The expected output of the metronome should be exactly like the number shown in the bpm value on the Metronome Bracelet, where 60 produces a vibration accuracy of 60 bpm, 90 produces 90 bpm, and 120 produces 120 bpm.
Co-Authors A. Ashar Ashari A. Baihaqi Mubarok Abdul Aziz, Muhammad Rafi Abdul Rahman Halim Abdussalam, Ghifarie Sa'id Achmad Basuki Achmad Fanani Kurniawan Saputra Achmad Rizal Zakaria Addin Miftachul Firdaus Adharul Muttaqin Adhisuwignjo, Supriatna Adhitya Bhawiyuga, Adhitya Adi Setiyawan Adinugroho, Sigit Adit Ilmawan Adryan Chiko Pratama Afdy Clinton Afflatuslloh Adi Salung Agastya Bramanta Sanjaya Aghnadiin, Radifan Muhammad Agi Putra Kharisma Agra Firmansyah Agung Bachtiar Sukmaarta Agung Leona Suparlin Agung Prasetyo Agung Setia Budi Agung Setia Budi, Agung Setia Agung Widya Gumelar Agung Wismawan Rochmatullah Ahmad Mustafidul Ibad Ahmad Rizqi Pratama Ahmad Wildan Ahmad Yazid Bastomi AJI, IBRAHIM Akbar, Muhammad Daffa Pradipta Akbar, Muhammad Faithur Adel Patria Alfian Reza Pahlevi Alrynto Alrynto Althaf Banafsaj Yudhistira Andhika Nino Pratama Anggi Diatma Styandi Angsar, Mohamad Rinaldi Anisa Awalia Rizky Anjasmoro, Reza Ardiansyah Ardiansyah Arief Kurniawan Arief Wahyu Wicaksono Aulady, Fadhli Aulia Zhafran Barlian Henryranu Prasetio Bayu Rahayudi Bayu Santoso Belsazar Elgiborado Giovani Djoedir Billy Gusparentaqi Bima Muridianto, Muhammad Bimo Dimas Nugraraga Buce Trias Hanggara Bukhori Darmawan Bunga Boru Hasian Siahaan Cahyanita Qolby Rahmarta Rizaputri Cipto Bagus Jati Kusumo Constantius Leonardo Pratama Dading Firwandhi Sukma Daffa, Ali Zhafran Dedi Siswanto Defri Alif Raihan Denis Reza Ramdani Devo Harwan Pradiansyah Dimas Rizqi Firmansyah Dini Eka Ristanti Dini Ismawati Duwi Hariyanto Dwi Arini, Talitha Dwi Firmansyah Dwiki Ilham Bagaskara Dyas Restu Palupi Edita Edita Rosana Widasari Edita Rosana Widasari, Edita Rosana Eka Nanda Sugianto Eko Ardiansyah Eko Hilmi Firmansyah Eko Setiawan Eko Setiawan Elisabeth Agustina Era Imanningtyas Ezra Maherian Fachry Ananta Fahmi Gymnastiar Gozali, Muhammad Faizal Ardiansyah FAQIH, ABDULLAH Farras Nabil Fatur Rahman, Mohammad Fauzi Ali Farhi Fauzi Rivani Fikri Fauzan Firdy Yantama Firmanda, Dwi Ady Firza Zamzani, Muhammad Fitriyah, Hurriyatul Fungki Pandu Fantara Ganda Wibawa Putra Gembong Edhi Setyawan Ghazy Timor Prihanda Govinda Dwi Kurnia Sandi Graciella Fiona Br. Panjaitan Grafidi, Alif Akbar Gunawan Wahyu Andreanto Hafidz Abdillah Masruri Hafiz Nul Hakim Hamdan Bagus Firmansyah Hamzah Attamimi Hanggara, Buce Trias Hannats Hanafi Ichsan Haqiqi, Farih Akmal Harahap, Syazwandy Hazal Kurniawan Putra Hazbiy Shaffan, Nur Henryranu Prasetio, Barlian Herenda Madi, Matius Herwin Yurianda Hurriyatul Fitriyah Hurriyatul Fitriyah Hurriyatul Fitriyah, Hurriyatul Idang Wahyuddin Septiawan Ihsanurrahim Ihsanurrahim Ikhwan Zulfy Imam Cholissodin Irfan Pratomo Putra Irvan Ramadan Issa Arwani Ivan Kasogi Izaaz Waskito Widyarto Izza Febria Nurhayati Jeffry Atur Firdaus Jevandika Jezriel Lukas Lumbantobing Johannes Archika Waysaka Khairul Anwar Khairul Anwar Kresna Wiska Kafila Kurnia, Yudisthira Dwi Kurniawan, Rizaldy Ariobimo Kurwniawan, Wijaya La Ode Muh. Fadlun Akbar Lase, Nicolash Jeremy Onoma Latief Nurrohman Alfansuri Lavanna Indanus Ramadhan Lb Novendita Ariadana Lutfi Anang Makruf M Nuzulul Marofi M. Adib Fauzi Rahmana M. Ali Fauzi Mahendra, I Gusti Putu Krisna Suaba Malik, Hifdzul Megananda, Muhammad Rifqi Mela Tri Audina Merry Hassani, Fadila Muqtadaro Mhd. Idham Khalif Moch. Alfian Zainullah Moch. Alvin Yasyfa Salsabil Mochamad Iswandaru Mochammad Hannats Hanafi Mochammad Hannats Hanafi Ichsan Moh. Saifud Daulah Moh. Zainur Rodhi Mohammad Ali Muhsin Mohammad Faizal Ajizi Muchamad Rafi Dharmawan Muchammad Cholilulloh Muh. Syifau Mubarok Muhajir Ikhsanushabri Muhammad Alif Alfajra, Andi Muhammad Aminul Akbar Muhammad Daffa Bintang Nugroho Muhammad Eraz Zarkasih Muhammad Fadhil Sadeli Muhammad Fajaruddin Akbar Muhammad Habib Jufah Alhamdani Muhammad Hanif Haikal Muhammad Hannats Hanafi Ichsan Muhammad Irvine Fidellio Maiza Muhammad Jibriel Bachtiar Muhammad Kholash Fadhilah Muhammad Naufal Muhammad Nazrenda Ramadhan Muhammad Rizqi Zamzami Muhammad Wingga Woggiasworo Muhammad Yusuf Ramadan Mukhamad Angga Setiawan Mukhamad Roni Mukmin Mukmin Munif Cleveriandy, Ahmad Musharrif, Mohammad Faiz Mustajib Furqon Haqiqi Mutiara Pramesti Utami Muzayyin, Asep Nabila Eka Putri, Alisya Nadhifa, Nadaa Nanda Epriliana Asmara Putri Navayo, Bagja Nicho Ferdiansyah Kusna Nikmatus Soleha Niko Aji Nugroho Noveriko Noveriko Nur Aini Afifah Isbindra Nur Fuady, Muhammad Sholahuddin Nurul Ikhsan Nyoman Wira Prasetya Oggy Setiawan Parja, Mujianto Anda Perkasa, Septiyo Budi Prakoso, Aldo Hani Pramandha Saputra Prasetya, Nyoman Wira Prasetyo, Budi Eko Prasojo, Satya Haryo Pricillia, Lidya Ruth Purnomo, Welly Putra Pandu Adikara Putra Pandu Adikara Putra, Brylliano Maza Raga Jiwanda Raharja, Kahfi May Rahayu, Vina Trisnawati Rahman, Edy Raka Bagas Perdana Rakhamadhany Primananda Rakhmadhany Primananda Rakhmadhany Primananda, Rakhmadhany Randy Cahya Wihandika Rekyan Regasari Mardi Putri, Rekyan Regasari Mardi Renal Prahardis Reza Budi Pratikto Rezak Andri Purnomo Rifqi Anshari Ringga Aulia Primahayu Rint Zata Amani Rioadam Sayyid Abidin Riza Irfan, Muhammad Rizal Maulana Rizal Maulana, Rizal Rizal Setya Perdana Rizka Ayudya Pratiwi Rizky Putra Wijaya Rizqi Muh. Muqoffi Ashshidiqi Ronilaya, Ferdian Rudy Agus Santoso Sabrian Rizqika Akbar Sabriansyah Rizkiqa Akbar Sabriansyah Rizqika Akbar Sabriansyah Rizqika Akbar Sabriansyah Rizqika Akbar Safirurrasul Santoso, Mush'ab Safrudin Bendang, Dehleezto Lawanangkara Salman Farizy Nur Samuel Lamhot Ladd Palmer Simarmata Santoso, Bayu Saputro, Mauna Mohammad Wahyu Sari, Sylvia Sentosa, Azy Dwi Putra Septino, Fernando Setiawan , Eko Shaffan, Nur Hazbiy Shelsa Faiqotul Himmah Sigi Syah Wibowo Siradjuddin, Indrazno Sulaiman, Ihsan Susilo, Faizal Andy Sutikno Sutikno Syarief Taufik Hidayatullah Syauqi, Mohd Alfitra Syazwana, Selvia Tibyani Tibyani Tio Haryanto Adi Putra Toar, Mikhael Ryan Tobias Sion Julian Utaminingrum, Fitri Utomo, Satria Wahyudi Vira Muda Tantriburhan Mubarak Virza Audy Ervanda Wahyu Adi Prayitno Welly Purnomo Widasari, Edita Rosana Widhy Hayuhardhika Nugraha Putra Wijaya Kurniawan Wijaya Kurniawan Wijaya Kurniawan Wijaya, Jason Wildo Satrio Wirafadil Nugraha Wisik Dewa Maulana Wisnu Mahendra Xavierro Lawrenza Yanottama Oktabrian Yudhistira, Gevan Putra Yuita Arum Sari Yunan Alamsyah Nasution Yunus, Ahmad Haykal Yurliansyah Hirma Fajar Yusriansyah Shohibul Hamzah Zahra, Inez Bedwina Zakaria, Akhmad Nizar