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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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Rancang Bangun Sistem Portabel untuk Klasifikasi Cendol Merah Mengandung Rhodamin B menggunakan Metode Jaringan Syaraf Tiruan Muhammad Fadhil Sadeli; Dahnial Syauqy; Edita Rosana Widasari
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 6 No 6 (2022): Juni 2022
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Cendol is a traditional West Javanese drink made from hunkwe flour or mung bean flour. Cendol that is often found is green cendol. However, there are also cendol sellers who use red cendol derived from food coloring or agar powder. However, there are still cendol sellers who add synthetic dyes containing Rhodamin B to cendol as a dye. Because the price is relatively cheap and makes the color more striking so that buyers become interested in buying the cendol. Rhodamine B is a synthetic dye in the form of a crystalline powder, green in color, odorless, and fluoresces in a bright red solution. Rhodamine B is very dangerous if consumed and inhaled which can cause liver function disorders, cancer, irritation of the respiratory tract, skin, and eyes. The misuse of these dyes occurs due to a lack of public knowledge about how to distinguish food coloring from Rhodamine B dye and the dangers of its use. Therefore, the researchers designed a system that can classify cendol containing Rhodamine B based on color. The system is built with a portable design for efficiency and portability. This system uses a power bank as a resource, then uses a TCS3200 sensor to determine the RGB value of the cendol color, a 16x2 LCD with I2C to display the output and classification results of the system, Arduino uno as a microcontroller to process data and calculate classifications, and an Artificial Neural Network (ANN). as a classification method. This system utilizes 50 sets of training data, 25 sets of test data for the ANN method, and 15 sets of test data for the whole system. Based on the results of the tests carried out, the accuracy of the Artificial Neural Network method was 96.08% with an average computation time of 58 ms and an overall system accuracy of 93.34%.
Klasifikasi Frekuensi Penggunaan Minyak Goreng Ikan dan Tahu menggunakan Metode Jaringan Syaraf Tiruan berbasis Arduino Aulia Zhafran; Dahnial Syauqy; Edita Rosana Widasari
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 6 No 6 (2022): Juni 2022
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Palm cooking oil which belongs to the basic food category (SEMBAKO) is a food element made from triglycerides derived from palm oil. Yellow to orange is the normal color found in palm cooking oil. Using the same cooking oil continuously can reduce the quality of the cooking oil and can be dangerous for the health of consumers. Frequency classfication system is needed to find the accurate amount of used cooking oil. The parameters used in the classification process are color and turbidity which are tested using a TCS3200 sensor to process and measure color and an LDR sensor to process and measure the level of turbidity of cooking oil connected to Arduino Uno and use the Artificial Neural Network (ANN) classification method. The classification results are divided into 7 classes, namely pure oil, 1 time fish frying, 2 fish frying, 3 fish frying, 1 times tofu frying, 2 times tofu frying, and 3 times tofu frying. The classification results will be displayed on a 20x4 I2C lCD. Based on the test results, the accuracy of the color sensor is 98.827% and the LDR sensor can see the difference in the level of turbidity of a cooking oil so that the system can have an accuracy rate of 80% in computation time for 5,114 seconds after processing 70 training data and 20 test data.
Klasifikasi Kualitas Beras berdasarkan Nilai Data Larik Sensor Gas MQ menggunakan Metode Jaringan Syaraf Tiruan berbasis Arduino Defri Alif Raihan; Dahnial Syauqy; Barlian Henryranu Prasetio
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 6 No 6 (2022): Juni 2022
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Rice is the result of the rice plant which is separated from the husks, every year the need of rice for indonesian people continues to increase, the abundant rice yields make rice have different types and qualities, in general the components that make up the smell of rice consist of several compounds it will produce a different smell of rice. Indonesian people still use conventional methods to classify quality in terms of taste and aroma, this makes the quality classification inaccurate and produces inappropriate quality, that makes many people commit fraud by circulating unsuitable types of rice and make bad quality which causes losses to various parties due to inappropriate prices and quality. With the development of technology, a tool that can classify based on quality is made using input from the array of MQ gas sensor by utilizing the Arduino UNO R3 microcontroller as a data processor from the gas sensor and utilizing a computational time code which make the system can classify quickly, the classification process uses the artificial neural network method and the classification results will be displayed on a 16x2 I2C LCD. the system is able to classify the quality with an average execution time of 54 milliseconds. From 11 test, the system is able to complete 9 times the output according to the detected sample which makes the accuracy of the system more than 80% and in accordance with which is expected.
Klasifikasi Kandungan Boraks pada Gendar menggunakan Sensor Warna dengan Metode Jaringan Syaraf Tiruan berbabsis Arduino Andhika Nino Pratama; Dahnial Syauqy; Edita Rosana Widasari
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 6 No 6 (2022): Juni 2022
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Gendar is one of the traditional foods typical of Central Java that can be found until now. The texture of the gendar itself is like rice cake or ketupat but is more chewy and has a more savory taste. In ancient times, the use of bleng salt or what is now called borax was commonly used in the process of making gendar because it can provide a savory taste of food and provide a legit and chewy texture as well as a preservative for gendar. Borax is a dangerous chemical compound which if consumed by the body does not cause an immediate reaction. The safe limit for the use of borax itself is 1 gram in 1 kg of food and the fatal dose when consumed and enters the body for children is 3 - 6gr and for adults is 15 - 20gr. The rampant ignorance of the public regarding the safe limits of borax that enters the body has prompted researchers to design a system that can classify the borax content in gendar based on 3 classes, namely no borax, light borax, and heavy borax. The system utilizes Arduino Uno as a data processor and classification calculation, a color sensor that is used as a color detector for the gendar object being tested, and a 16x2 LCD to display the classification results. The classification process itself uses the backpropagation artificial neural network classification method. Based on the system testing process, of the 30 samples tested, 90% accuracy was obtained with the average computation time required by the backpropagation Neural Network in the classification process is 3057ms or 3 seconds and 0.057 seconds.
Klasifikasi Mutu Biji Kakao berbasis Data Electronic Nose menggunakan Metode Jaringan Syaraf Tiruan Ghazy Timor Prihanda; Dahnial Syauqy; Mochammad Hannats Hanafi Ichsan
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 6 No 6 (2022): Juni 2022
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Cocoa (Theobroma cacao Linn) is one of the leading export commodities of plantations in Indonesia. To maintain the quality of cocoa commodities, the government enforces the rules of SNI 2323-2008 regarding the quality standards of cocoa beans. The special requirements in the regulation divide cocoa bean into 3 classes, namely: Kelas Mutu I, Kelas Mutu II, and Kelas Mutu III. The aroma quality of cocoa beans is one of the standards contained in the regulation. So far, the quality of cocoa bean aroma has been identified using a human tester, which has the weakness of being unstable and subjective. With the development of technology, an electronic nose consisting of a series of gas sensors can analyze and recognize the characteristics of complex gas samples. So this research was carried out by making a classification system for the quality of cocoa beans based on their aroma using an electronic nose. The classification system used to measure quality of cocoa beans uses the Artificial Neural Network (ANN) method, to identify patterns in identifying the type of quality of cocoa beans based on their aroma. The electronic nose system was built using 3 gas sensors, namely: MQ 2, MQ 3, and MQ 135. The data processing and classification of ANN implementation were carried out using Arduino MEGA 2560. The results showed that the ANN method was able to identify the type of quality of cocoa beans with a success rate of 77.78 % and the average computation time required is 1.1317244 seconds.
Implementasi Low Power pada Sistem Notifikasi Kantuk pada Pengemudi menggunakan Finite-State Machine berbasis Arduino Muhammad Irvine Fidellio Maiza; Agung Setia Budi; Dahnial Syauqy
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 6 No 7 (2022): Juli 2022
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Every year, the death rate caused by traffic accidents increases sharply. One of the biggest causes of traffic accidents is drowsiness experienced by vehicle drivers. Therefore, researchers are interested in developing a drowsiness detection system using low power in the hope of reducing the rate of traffic accidents caused by drowsiness. The system is designed using the FC-51 Infrared sensor embedded in the glasses as a detection of the driver's eyelid position. The system is built with a threshold parameter that can be reconfigured such as the duration of closed eyelids. This system is also built using a finite-state machine algorithm, where this algorithm will create several states with different operational modes. One of these states is the Low Power On state to save power. This is necessary because the system will work continuously. In the Low Power On state, the method used to save power usage is to make the 800L SIM module enter sleep mode by slowing down the clock its used. The system will send a notification in the form of a buzzer and an SMS message containing the driver's coordinates to relatives when sleepiness is detected. From the results of the tests that have been carried out, it is concluded that the system can carry out each of its functionalities and succeeded in reducing the use of current consumption by 30% when in the Low Power On state.
Rancang Bangun Sistem Deteksi Dini Status Gizi dan Risiko Stunting pada Balita berdasarkan Tinggi dan Berat Badan menggunakan Metode JST Backpropagation Mukhamad Roni; Dahnial Syauqy; Rakhmadhany Primananda
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 6 No 7 (2022): Juli 2022
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Nutrition is a health status based on a balance between needs and nutrients. Toddlers can be said undernourished if the measurement of the W/A z-score <-2SD, and stunting if the measurement of the H/A z-score <-2SD. Currently, the determination of nutritional status and stunting is still using conventional measurements and matched with the standard book table of children's nutritional status from the Ministry of Health. Therefore, a system developed can detect weight and height as well as nutritional status and risk of stunting in toddlers. This system uses ultrasonic sensor HC-SR04 to measure height, load cell and HX711 module to measure weight and backpropagation NN to predict nutritional status in toddlers. The implementation of nutritional status with the backpropagation NN method is divided into 2, namely nutritional status with poor and good classes, and stunting risk with low and high classes. The system has a height of 125 cm and a square footing with a width of 30cm x 30cm. Using MLP Topology Workbench for data panning using 3 input layers, 12 hidden layers, and 1 output layer for each backpropagation NN implementation. The ultrasonic sensor test got an accuracy of 98.5%, the load cell sensor test got an accuracy of 94.7%, the test on the method got 100% accuracy, and the overall system test got an accuracy of 96.6%.
Rancang Bangun Sistem Klasifikasi Padi Siap Dipanen dengan Parameter Warna Padi dan Warna Daun menggunakan Metode Random Forest Adi Setiyawan; Dahnial Syauqy; Sabriansyah Rizqika Akbar
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 6 No 7 (2022): Juli 2022
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Indonesia is an agricultural country, where the agricultural sector has a very important role in improving the national economy. One type of food crop in Indonesia is rice, which currently Indonesian people still use rice as a staple food. The process for planting and caring for rice in Indonesia is currently still less effective and efficient, this has an impact on harvest and post-harvest yields including farmers will lose as much as 20.51% of rice when the harvest time is not right, rice that falls by 9, 52%, rice lost during drying time was 2.13% and the loss during milling was 2.19%. Currently, farmers are still routinely checking the rice fields to see if the rice is ready to be harvested, but farmers have problems checking the paddy fields because erratic weather factors can affect the growth of rice plants. Based on this problem, the authors developed a pre-existing tool using the TCS3200 color sensor to detect the value of leaf color and rice panicle color using the Random Forest method to see whether the rice classification results are ready to be harvested which will be displayed on the 16x2 LCD output and the sound on the buzzer. , so that farmers do not lose their crops due to loss and can get maximum yields. After testing 20 times by inserting the object into the hole on the tool that has been made, the system can detect RGB color values with a low percentage of error. From the results of testing the Random Forest method, the results of the test accuracy are 95% with an average computation time of 38.95ms.
Sistem Klasifikasi Kualitas Keju Mozzarella berdasarkan Warna dan pH menggunakan Metode Naive Bayes Izaaz Waskito Widyarto; Dahnial Syauqy; Rakhmadhany Primananda
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 6 No 7 (2022): Juli 2022
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Mozzarella cheese is one type of cheese that is favored by the people of Indonesia, because it has elastic and melting texture properties that are different from other cheeses. Currently, in determining the quality of Mozzarella cheese, it is usually seen from the color and level of moisture, one example in determining the quality of Mozzarella cheese which is easy to see with the eye must be shiny and white like porcelain. The microcontroller used by Arduino Uno is because the method of use is not too difficult and very easy to use. This system uses a TCS3200 color sensor to measure the color of Mozzarella cheese, a pH sensor to measure acidity and Naive Bayes to predict the quality of Mozzarella cheese. The position of the TCS3200 color sensor is placed at the base facing up, for the measuring cup it is on top of the TCS3200 sensor. The point of placing the TCS3200 sensor is in a solid black acrylic due to reducing the entry of light from outside. While the pH sensor is placed above the measuring cup which is useful for taking the acidity value of Mozzarella cheese. Naive Bayes classification is used because it is very effective and requires quite a bit of training data, from the test results obtained 94% accuracy, the average accuracy of the color sensor TCS3200 is 98.07%, and the average accuracy of the pH sensor is 98.83%.
Rancang Bangun Sistem Tracking Matahari berdasarkan Cahaya dan Arus pada Sel Surya menggunakan Logika Fuzzy Model Sugeno Yunan Alamsyah Nasution; Dahnial Syauqy; Barlian Henryranu Prasetio
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 6 No 7 (2022): Juli 2022
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Electricity is one of the most demand energy nowadays, demand for electricity has come greater year by year. With the increasing demand for electrical energy, the need for fulfillment of enviromentally friendly energy. One way is to use solar panels. However, the effectiveness of solar panels will be reduced if their position is not perpendicular to the direction of the sun's rays. Based on the problem, writer want to make a system that can increase solar panels effectivity with detecting where sun ray come with LDR sensors, and the system can move the solar panel in the direction of sun ray comes with servo motor. Data gathered from each sensors will be processed in the Arduino Uno with Fuzzy Logic and then Arduino Uno will send a signal to servo motor to move according to calculations that has been done before. Based on testing, after solar fuzzy system installed on the solar panel, the effectiveness of solar panels increased by 13,427%.
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