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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

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Klasifikasi Sumber Nektar Madu berdasarkan Kecerahan dan Warna dengan Metode Naive Bayes berbasis Embedded System Syarief Taufik Hidayatullah; Dahnial Syauqy; Hurriyatul Fitriyah
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 5 No 8 (2021): Agustus 2021
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Honey is a liquid has many benefits for humans and also as a food reserve for bees, honey stored by bees undergoing chemical processes and fermentation through evaporation, air exchange and changes in increasing heat temperatures. The bees job is divided into three kind, female bees lay eggs, male bees to mate with female bees and the worker bees looking for nectar which is stored in the bee hive as food reserves. Honey from different nectars produces different colors and tastes, so it have different benefits. Honey can be used as a sugar substitute and has many contain beneficial. This design system with naive bayes classification uses acacia honey, eucalyptus honey, coffee honey longan honey, Sengon multiflora honey and mango honey with Arduino Uno microcontroller, TCS3200 sensor and LDR sensor. The classification process is carried out by pouring honey into a 50ml beaker glass then placing it above the LDR sensor and under the TCS3200 sensor according to the prototype design of the calcification tool. The LDR sensor gets light from the color sensor and then will give output red, green, blue, and honey clarity then the data is processed by the naive bayes method so the result will be a classification of honey. Classifications are displayed on the LCD so that users can see the classification results. Naive Bayes classification was chosen because it is effective and requires a bit of training data, in this study using 10 samples of training data per honey. From the test results with 67 honey samples, the results obtained 94% accuracy with an average computation time of 1007.28ms, an average LCD accuracy 100%, an average LDR sensor accuracy 98.9% and an average error on the color sensor 5.69%. This means that the results can be said it's good
Implementasi Over the Air Update menggunakan Protokol SSDP untuk Pencarian Perangkat Ahmad Wildan; Mochammad Hannats Hanafi Ichsan; Dahnial Syauqy
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 5 No 9 (2021): September 2021
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

With the Over the Air (OTA) update method, firmware updates on IoT device can be done without having to visit the IoT device. IoT device that installed at home or in the building and using local network the firmware can be easily updated and discovered with SSDP protocol (Simple Service Discovery Protocol). SSDP protocol usage in this research is for IP identification from each node that connect with the local network so that each node's web server can be accessed using IP address. The web server of each node is used to update the firmware of the accessed node. From the tests carried out 60 times with different distances in 1 meter, 3 meters, 5 meters, 10 meters, 15 meters, and 20 meters, it can be seen from the three nodes, the smallest average delay for device discovery using SSDP is at 1 meter that is 520.6 - 521 ms and the largest average delay is at 15 meters which is 682.23 - 785 ms. Then for firmware updates for the 3 tested nodes, the smallest average delay is at 1 meter, which is 8309 - 9801.5 ms and the largest average delay is at 15 meters, which is 15911 - 28687.8 ms.
Implementasi Sistem Pendeteksi Myocardial Ischemia menggunakan Metode Support Vector Machine (SVM) Ezra Maherian; Rizal Maulana; Dahnial Syauqy
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 5 No 9 (2021): September 2021
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Myocardial Ischemia is a condition occurs when the blood flow to the heart is reduced, making the heart muscle lack of oxygen supply. The reduced blood flow occurs due to blockage inside the coronary arteries which could be the build-up of cholesterol or the clotting of the blood. The blockage could build-up even more from time to time, blocking the blood flow entirely and making the person with the condition more prone to a heart attack. Commonly, diagnosing Myocardial Ischemia is done by medical professionals at the hospital. AD8232 sensor kit and Arduino Uno Microcontroller are used to detect Myocardial Ischemia. The detection of heart condition is based on the slope of ST-segment and the peak of T wave that will be classified by Support Vector Machine classifier into either Myocardial Ischemia or Normal class. As many as 40 data were used to train the system and as many as 20 data were used to test the system. Sensor accuracy test shows sensor's accuracy of 95.56%. Test of SVM computation time gives a result of 3912.30 ms for average training time and 0.061 ms for average testing time. The accuracy of SVM classification tested on 20 data gives an accuracy rate of 85%.
Implementasi Deteksi Dini dan Klasifikasi Jenis Urine dengan Metode K-Nearest Neighbor (KNN) pada Pasien Operasi Althaf Banafsaj Yudhistira; Rizal Maulana; Dahnial Syauqy
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 5 No 9 (2021): September 2021
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Urine produced by each person may vary based on its physiological. It was happened by some reason like daily diet, gender, condition of exrectory system, and so on. These factor may lead physiological change of urine like color and turibidity. That is why urin often used to determine a person's health condition. In other side doing traditional urine analysis error often occurs because it only rely on analyzer sight. Analysis of a person's condition through urine physical conditions is also very much needed in the operation process and it is not possible if periodic analysis is carried out continuously during the operation. Therefore we need a tool that can perform automatic analysis to minimize errors in analysis and taking patient handling actions. This study uses the TCS3200 sensor to extract features in the form of color and an IR Proximity sensor for urine fluid turbidity. The two features will be processed by Arduino Uno to carry out the classification process. The urine will be divided into three classes, namely: Normal Urine, Blood Urine, Pus Urine. The classification process will use the K-Nearest Neighbor method with varying K values ​​starting from K = 3, K = 5, and K = 7. The system was able to recognize urine with an accuracy of 86.7% then 86.7% and 80% respectively
Alas Kaki Penimbang Berat Badan Dengan Berjalan berbasis Sensor Load Cell dan Metode Regresi Linier Afflatuslloh Adi Salung; Hurriyatul Fitriyah; Dahnial Syauqy
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 5 No 9 (2021): September 2021
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

The ideal body is everyone's dream. From teenagers to old people, both male and female, definitely want the ideal body. The ideal body can be obtained from sufficient exercise, a healthy diet, and adequate sleep. We can find out whether our bodies are ideal or not by measuring their body height and body weight, which are adjusted from the person's age. Monitoring weight is one of the needs to maintain a healthy body. We should always check our weight, so we can control the body's healthy patterns. Sometimes measuring weight takes time, for busy people it may not be important. In fact it is very necessary to always know the weight. It will be very helpful if there is a weight meter that can be used at any time and is not required to stand still on a regular weight scale. Therefore we need a tool that can make it easier for us to monitor our weight at any time. We can check our weight when sleeping, running, eating, and all daily activities. In this study, we will create a wearable device that adds the function of sandals to a weight monitoring tool. By using several Load Cell sensors on the sandal, these sensors function to get the value of the Load Cell sensor which will be processed with the Wemos D1 microcontroller. The results of the process will come out on android devices that are commonly used every day. We can use this tool like an ordinary scale, when standing upright we can get a weight value, and this tool can also be used when walking conditions. In this study, we will focus on examining the device while walking. With this tool, we can make it easier for users to monitor their weight during daily activities without using ordinary scales.
Pengembangan Sistem Pemilah Telur Ayam Negeri dan Ayam Kampung berdasarkan Berat dan Warna Cangkang Telur menggunakan metode K-Nearest Neighbor (K-NN) Johannes Archika Waysaka; Dahnial Syauqy; Mochammad Hannats Hanafi Ichsan
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 5 No 10 (2021): Oktober 2021
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Eggs are one of the nutritious foods that contain animal protein that is good for the body. Eggs themselves are popular in Indonesia, which can be seen from the demand for eggs that increases every year. From BPS information from 2015 around 13 tons, 2016 rise to 303 tons, and in 2017 it increased by around 386 tons it can be concluded that from 2015 to 2017 it increased by 2824%. In Indonesia, there are 2 types of chicken eggs, namely native chicken eggs and domestic chicken eggs. The difference between these two eggs is in their weight and color. Native chicken eggs have a lighter weight than domestic chicken eggs and the color of native chicken eggs is brighter than domestic chicken eggs. From the difference in parameters, some ordinary people have difficulty distinguishing them. Based on these problems, it is necessary to create a system capable of sorting chicken eggs automatically. The system is made using a loadcell sensor to measure the weight of the egg, and use the TSC3200 sensor to get the value of eggs based on red, green, and blue. The data taken from the two sensors is then processed using the K-Nearest Neighbor method with the output in the form of a servo that moves towards the egg, all systems are processed using Arduino mega. Testing is focused on the functionality, accuracy, and performance of the system. From the functional testing that has been done the system gets 100% correct results. So it can be said that this system is successful. For the K test, the system was tested using a K value of 3,5,7 with 20 training data and 20 test data, which obtained accuracy of 100%, 99%, and 98.57% respectively. And the system performance test obtained a processing time speed of 568.8 ms when using K3.
Rancang Bangun Sistem Klasifikasi Tingkat Kematangan Pisang berdasarkan Warna Kulit dan Berat menggunakan Metode K-Nearest Neighbor berbasis Arduino Pramandha Saputra; Dahnial Syauqy; Hurriyatul Fitriyah
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 5 No 10 (2021): Oktober 2021
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Currently, bananas are one of the favorite fruits that have good nutrition and taste that is liked by most people, because bananas have good nutritional content for the body. Banana is a fruit that is very beneficial for human life, which can be consumed at any time and at all ages. Constraints on the community in distinguishing ripe bananas that are suitable for management are sometimes experienced by ordinary people who do not know about the characteristics of ripe bananas and are good to manage. To make processed products, bananas with the right maturity are needed, for that a study was made on the ripeness of bananas based on the weight and color of banana peels that classify them using the K-Nearest Neighbor method. In this system there are several components, namely: Arduino Mega 2560 microcontroller to process k-nearest neighbor calculation data, TCS3200 sensor whichs is use to detect skin color on bananas, loadcell sensor as a weight gauge on bananas. The system in distinguishing the ripeness of bananas using the k-nearest neighbor method got an accuracy of 86.6%. Perform testing on the value of K = 3 and then the results of the changed K value are compared to see a more accurate K value in the k-nearest neighbour method applied to the system.
Pengembangan Sistem Penghitung Takaran Air untuk menentukan Tingkat Kematangan Nasi menggunakan Regresi Linier berbasis Embeded System Anisa Awalia Rizky; Dahnial Syauqy; Agung Setia Budi
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 5 No 11 (2021): November 2021
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

One of the principal food suppliers in some countries is rice, not limited to Indonesia. The need for rice is predicted to continue to increase annually as rice consumers increase. Rice treatment should be used properly. But not all refined rice will be consumed. It's because of the ill-fitting measures which tend to become food waste. In order to alleviate the problem, it required a tool that calculated the precise ratio of rice and water and could predict the quality of rice maturity. On the study, the weight of rice and the volume of water became the key sharer in the classification of rice maturity levels. Thus, loadcell sensors and hx711 modules will be required as weight stabilizers and linear regression as a as a calculation method for making predictions. There are 30 training data and 15 testing data in the testing process. The result was 90% accuracy in weighing rice and water volume with an average computing time was 20,46 seconds.
Rancang Bangun Sistem Klasifikasi Ukuran Baju berdasarkan Ukuran Tubuh dengan Metode K-Nearest Neighbor berbasis Arduino Xavierro Lawrenza; Hurriyatul Fitriyah; Dahnial Syauqy
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 6 No 1 (2022): Januari 2022
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Technological developments that are currently growing rapidly indicate the emergence of several new innovations that make work activities more practical and efficient because at this time time efficiency is an added value in the success factor in work, one of the fields of work is clothing measurement activities. Currently, the activity of measuring clothing sizes in order to get clothes of the right size requires an innovation to create efficiency and comfort. The purpose of this research is to create a system that can overcome the problems of efficiency and convenience. In this thesis research, the system was created using two ultrasonic sensors HC-SR04 as a measuring tool for body height and width as a parameter for determining the size of clothes and pants and a 16X2 LCD as the output of the size results obtained so that they are more efficient in terms of measurement and speed of time. Arduino Uno is used as a microcontroller in this study because it is hoped that its smaller size can overcome efficiency problems. The sizes that will be included as a classification include sizes S, M, L and XL. Parameters for determining the size include body height and body width. K-nearest neighbor is a classification calculation method by determining the closest distance from the test data to the training data, the number of training data for the nearest neighbor or referred to as K has been determined previously by the researcher. The calculation speed of each test data is about 10 seconds at the latest. Determination of the size using the k-nearest neighbor method because after testing and analysis this method has a high level of accuracy where the calculation results on average almost all get 100% accuracy results.
Sistem Klasifikasi Saus Cabai mengandung Formalin dengan Sensor TCS3200 dan Sensor Groove-HCHO menggunakan Metode K-Nearest Neighbor berbasis Arduino Hamzah Attamimi; Dahnial Syauqy; Hurriyatul Fitriyah
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 6 No 1 (2022): Januari 2022
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Chili sauce is a sauce made using the main ingredient chili, which is processed by adding spices and permitted food ingredients, or without the addition of other foods. However, in Indonesia, the term fake sauce is often used to define sauces that contain ingredients that are harmful to the health of the body, one of the dangerous ingredients used is formalin. In checking chili sauce containing formalin carried out by experts by mixing a sample of sauce into a test tube and mixing it with a special formalin reagent, the results of the examination also require a long time. Based on these needs, it is necessary to design a system that can facilitate the checking of chili sauce containing formalin, and does not take much time in the inspection process. In this study, the detection system for chili sauce containing formalin used color parameters and formaldehyde gas content in the sauce sample. Arduino Mega microcontroller is used as a data processor on the system. The system will classify the Non-formalin and Contain Formalin data with the K-Nearest Neighbor method. In this study, 20 test data were applied in 60 training data used to determine the level of classification accuracy from the use of the K-Nearest Neighbor method with a value of K=3 of 85%, K=5 of 85%, and K=7 of 80%. Meanwhile, the average computation time obtained from 10 tests is 1807.3ms.
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