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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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Sistem Kontrol Kecepatan Motor Exhaust Fan Pada Cooking Hood Menggunakan Metode Fuzzy Devo Harwan Pradiansyah; Wijaya Kurniawan; Dahnial Syauqy
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 8 (2019): Agustus 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

In cooking activities, smoke has a risk to health. This is often underestimated by the community, especially women who are more often at kitchen. If the kitchen is a minimalist type where there is no air hole which causes air circulation in kitchen can not change and it is difficult to smoke to get out. Although it looks trivial, smoke actually has a bad impact on the health of the skin until breathing, it is caused by incomplete combustion smoke in the kitchen containing carbon monoxide (CO), SO2, and NO2 gas which if inhaled excessively can cause pneumonia and cancer. based on these problems there needs to be a system that is able to detect smoke and take action to remove it. In previous studies, there are studies on how to monitor levels of cigarette smoke in the room and regulate the flame on the fan. In this study, there are two kinds of inputs, namely MQ 2 sensor and MQ 7 sensor values ​​obtained from these sensors will be processed using fuzzy logic method whose results will be used as a consideration to run the output in the form of an accelerator on the fan according to the requirements needed based on the smoke conditions and CO gas contained in the air. This system also equipped with LCD which is useful for displaying the concentration of smoke and CO gas contained in the air and the required motor speed based on calculations on the fuzzy logic method. From the results of tests that have been carried out the system can run well in accordance with the design that has been done. Motor speed in this system change responsively according to changes of the concentration of smoke and CO gas.
Sistem Embedded untuk Pengaturan Pakan lkan Mas Koki berdasarkan Banyaknya JumIah lkan dan Ketinggian Air Arief Wahyu Wicaksono; Dahnial Syauqy; Mochammad Hannats Hanafi Ichsan
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 8 (2019): Agustus 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Feeding is one of the important things for fish farming and hobbyist businesses. Currently feeding is generally still dependent on human resources that are manual. Therefore designed tools to feed fish that can work automatically based on the time or schedule of feeding and the amount or amount of feed. Nowadays wireless technology is becoming very popular because of its ability to distribute and disseminate data wirelessly. An important factor in keeping fish in an aquarium is the timeliness of fish feeding. Based on this in this final project project is designed and made a fish feed tool based on the number of fish and water level. Then designed a tool that makes it easy to feed fish based on the number of fish that is automatically in accordance with specified. The components of fish feed scheduling support include making the minimum circuit Arduino Uno system as the brain of this tool which will later be filled with programs using the Java language, RTC (Real Time Clock) as a timer, DC Motor to rotate the spiral wire connected to the place of fish feed . Then the ultrasonic sensor readings are processed using an Arduino uno microcontroller. Tests carried out ultrasonic sensor testing, processing time testing, automatic fish feeding testing and the suitability of the serial data monitor and LCD. In this study it was found that the tool worked well, the functional suitability of the feeding equipment was 90% and the results were successful and smooth.
Klasifikasi Umur Padi berdasarkan Data Sensor Warna dengan menggunakan Metode K-NN Anggi Diatma Styandi; Dahnial Syauqy; Wijaya Kurniawan
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 9 (2019): September 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Indonesian country is one of the rice producers. Most of Indonesian people work in agriculture. However, it is unfortunately that Indonesia cannot meet the national rice needs so that supposes Indonesia to import rice from other countries. The cultivating time of farmers in Indonesia is still one of the causes lack of rice quality and quantity that is less than optimal, so that the quality of rice products is still said to be deficient. Rice that is cropped too late has very bad impacts. Therefore, farmers should be smart in choosing the right time to crop rice. Weather factors and large fields make it increasingly difficult for farmers to check the age of their whole rice regularly. Based on these problems, farmers now need a system to help observing the age of rice by seeing on changes in the color of rice plant so that the study entitled "Rice Plant Age Classification Based on TCS3200 Color Sensor Data Using the Knn Method" is proposed. This research utilizes TCS320 Integrated Circuit (IC) Color Sensor, Arduino Integrated Development Enviroenment (IDE) software and LED as an indicator to be arranged into a system. I hope the system that I create will help farmers to improve the quality and quantity of rice yields. So that the Indonesian government does not need to import rice from other countries.After testing several times of test, it is known that this system can detect colors precisely in 20 times the experiment by attaching objects. From the results of the KNN test the highest accuracy was found at K = 5, where the accuracy value obtained was 80%. While the lowest accuracy is at k = 9, where the accuracy value obtained is only 10%
Klasifikasi Tingkat Kematangan Susu Kefir dengan Metode K-Nearest Neighbor (KNN) menggunakan Sensor Cahaya dan Sensor Warna Faizal Ardiansyah; Dahnial Syauqy; Gembong Edhi Setyawan
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 9 (2019): September 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Milk is a product that is classified as rare in Indonesian society and also the age of milk that is classified as short, making it difficult for the community to consume milk every day. Therefore, the prototype of the kefir milk fermentation process is designed using the K-nearest neighbor method. Starting from fresh cow's milk mixed with kefir seeds, after that the freshly mixed kefir milk will be inserted into the dark box in the box, there are color sensors and light sensors that are used to monitor color changes and the light intensity that occurs when fermentation is in progress. The readings obtained by the next two sensors will be determined using the K-nearest neighbor method. The test results obtained to determine the accuracy of the reading of the light sensor is worth 5.12% while the color sensor is worth 8.64% from the results of testing the two sensors, it can be concluded that the readings of the two sensors can be said to be quite good. The test results on the Kefir milk maturity level classification system using the K-nearest neighbor method with 10 times testing found an accuracy rate of 80%. And the average value of system computing time obtained after the calculation of the value of K obtained 353.3ms in 10 times the test.
Sistem Deteksi Titik Kebakaran dengan Algoritme K-Nearest Neighbor (KNN) menggunakan Sensor Suhu dan Sensor Api Addin Miftachul Firdaus; Dahnial Syauqy; Rizal Maulana
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 9 (2019): September 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Fires often occur in the area of housing, Office space or in the Woods. The emergence of the fires themselves often leave casualties is not a little. Fire occurrence process itself can develop quickly or slowly depending on various factors such as the typically temperature, wind direction or weather based on material to burn. The issue was made of various fire alarm systems that are usually placed on building large and function gives a warning if the fire is large enough or usually the alarm will also be activated manually but the system does not tell you the location of the occurrence of fires. Based on the problems researchers make fire with point detection system sensor LM35 and flame sensor using algorithms K-Nearest Neighbor and a microcontroller, Arduino Mega as data processing. The workings of this system with sensor LM35 temperature detected on duty around the room and the sensor detects flame flame candles. If there is a fire then the system will process the calculation by the method of classification results obtained so KNN are used as the end result of this system. After the research is done, the results obtained from testing system has the accuracy of 80.55% and for process calculation of classification are obtained for 1428.83 ms.
Sistem Otomatisasi Lampu Rumah Dengan Algoritme Naive Bayes Berdasarkan Kebiasaan Penghuni Rumah Ahmad Yazid Bastomi; Dahnial Syauqy; Issa Arwani
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 9 (2019): September 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

In the house function development there is term called Smart Home where the automatic system is applied to ensure the resident activities can be arrange in certain ways. One of the electronics device is automatic lamp that decrease human error and increased the efficiency use of the lamp to resident in that house. With that purpose, needed research where an automatic lamp system taking the habit data of the resident while using lamp to turn it on or off and apply that to the lamp for next day. There are three main input of the system that controlled using switch that consist of training switch that control the system mode, lamp 1 switch as input habit for lamp 1 and lamp 2 switch as input habit for lamp 2. The user habit data will recorded into Arduino UNO EEPROM in minutes then processed using Naive Bayes Algorithm to determine the output of relay module that control the lamp condition. The result of system for EEPROM accuracy data from 5 times test is 100% for switch 1 and 100% for switch 2 while main system accuracy for 12 test data is 91,6% for switch 1 and 83,3% for switch 2.
Sistem Deteksi dan Klasifikasi Pergerakan Kepala Menggunakan K-Nearest Neighbor Nikmatus Soleha; Dahnial Syauqy; Eko Setiawan
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 10 (2019): Oktober 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

The development of technology by utilizing the movement of the human body is developing very rapidly. One of them is an artificial intelligence system that utilizes head movements to control wheelchairs based on embedded systems. In that study, the head moved as a control to move a wheelchair. Previous similar research have raised several obstacles, one of which is the system is inflexible so that not all users can use it. To overcome these problems, researchers conducted a system design by calibrating the system so that it could classify the direction of head movement according to its class using the K-Nearest Neighbor (K-NN) method. With this, it is hoped that the system can be used more flexibly by users. The system uses MPU6050 sensor and ESP32 microcontroller which are arranged in the form of a headband. The results obtained from the system classification calibration are displayed on the serial monitor in the form of head movement class. The system testing was carried out with four experiments in each head movement class, there were five head movement classes tested. Based on the test results on this system, obtained an accuracy rate of 95% of the K-Nearest Neighbor classification.
Sistem Deteksi Tingkat Kematangan Pada Tapai Singkong Berdasarkan Data Sensor pH dan Kadar Alkohol Berbasis Embedded System Nurul Ikhsan; Dahnial Syauqy; Agung Setia Budi
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 10 (2019): Oktober 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Tapai cassava is one of the traditional processed food products in Indonesia. Tapai cassava changes the fermentation process that turns cassava into tapai with the help of tapai yeast, We can say about people who would like cassava which has sweet taste, soft texture and a little alcohol content. Yeast will then produce tapai which has high water content, high acidity, very high texture and becomes acidic which contains a very sharp and alcoholic aroma. By knowing to the level or alcohol in cassava tapai, we can find out the future level of cassava tapai, whether tapai is not yet ripe, ripe, or too ripe for consumption. From this explanation, the researchers made a Maturity Level System in Cassava Based on Ph Sensor and the Embedded Alcohol Based Alcohol Level Data that can help the public or connoisseurs to achieve what has reached, which has been produced, which has been produced or that has been produced. In this system several components are used, namely the Arduino Uno microcontroller for data processing and for classification using the k-Nearest Neighbor method, the SEN0161 pH meter sensor and the MQ-3 sensor used to measure alcohol content and levels of cassava. In this system after testing the value of K, k9 is obtained as the best K with a percentage of 100% and for testing the accuracy of the test is 86.66% and the average rat error in the system is 13.34%, the tests produced at produce from the nearest k-neighbor classification.Keywords: cassava tapai, mq3 sensor, ph sensor, k-nearest neighbor
Rancang Bangun Sistem Klasifikasi Kemurnian Susu Sapi dengan menggunakan Metode Naive Bayes Dimas Rizqi Firmansyah; Dahnial Syauqy; Fitri Utaminingrum
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 10 (2019): Oktober 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Cow's milk is a popular food and beverage consumed by the public. The benefits generated from cow's milk are numerous, because they contain protein, vitamins, and minerals needed in the body. Sales of cow's milk are often found in rural, urban, tourist attractions, roadside, to restaurants. Because there are so many people who need cow's milk, there are often bad sellers or sellers selling impure cow's milk. Because by falsifying cow's milk, naughty sellers benefit very much. From the falsification of the purity of cow's milk, there are a lot of losses felt by consumers, including consumers being a loss, so that the worse is consumers can be hospitalized because falsified milk is included ingredients that are not suitable for food. Therefore, to help the public not to get caught buying cow's milk which has been mixed with water by an individual, tools are needed that are able to test the purity of cow's milk directly and quickly. Because of this problem, a research was carried out to build a tool that could detect cow's milk, mixed milk or pure milk. This research requires a TCS3200 color sensor which is used to detect color in cow's milk, and also a pH sensor to obtain the acidity value in cow's milk. For the classification results using the Naive Bayes method calculation. The choice of using the Naive Bayes classification is because the method can be used to process biased data and accurate calculation results. Based on the test results, obtained an accuracy of Naive Bayes calculation of 90% taken from 20 times the test, and the test there are 2 results that are not appropriate. While the speed of calculating the device starts from the taking of the value by the sensor until the tool can issue an average classification result of 6932 ms.
Penerapan Filter Mahony Pada Tracking System Pergerakan Orientasi dan Posisi Kepala Berskala Ruang Muhammad Kholash Fadhilah; Dahnial Syauqy; Eko Setiawan
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 10 (2019): Oktober 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Virtual Reality (VR) is a term in a 3D environment generated by a computer and has the ability to make users to be able to interact with alternative realities. To interact with virtual reality, users need devices that accommodate user interaction with the VR environment. A room scale VR device is capable of allowing users to interact more freely. VR devices that currently available in the market still require supporting external devices, resulting in a lack of device portability. Based on these problems, researchers developed a device based on head orientation and head position on a room scale. In the development of devices, testing is done to determine the performance of the device system. Testing of device systems involves the application of Mahony Filters as orientation filters. Tests are based on orientation data and position of user's head in a room. The testing of the device system obtains detection accuracy of head position data acquisition in a room area of ​​3.33m2 with an average deviation of 4.9cm from the range of actual space size and for the accuracy detection of orientation data by system, the average degree deviation is 2.59 degrees from the actual degree angle. In the classification of determining the heading by the system, that obtained success rate by 73.5%.
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