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All Journal International Journal of Electrical and Computer Engineering IJCCS (Indonesian Journal of Computing and Cybernetics Systems) JURNAL SISTEM INFORMASI BISNIS Proceedings of KNASTIK Techno.Com: Jurnal Teknologi Informasi TELKOMNIKA (Telecommunication Computing Electronics and Control) Bulletin of Electrical Engineering and Informatics Jurnal Informatika SPEKTRUM INDUSTRI Jurnal Sarjana Teknik Informatika Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI) Jurnal Teknik Elektro Bulletin of Electrical Engineering and Informatics Jurnal Teknologi Jurnal Teknologi Informasi dan Ilmu Komputer Telematika Jurnal Edukasi dan Penelitian Informatika (JEPIN) JUITA : Jurnal Informatika Scientific Journal of Informatics Seminar Nasional Informatika (SEMNASIF) Jurnas Nasional Teknologi dan Sistem Informasi JURNAL PENGABDIAN KEPADA MASYARAKAT Jurnal Teknologi Elektro INFORMAL: Informatics Journal Proceeding SENDI_U Khazanah Informatika: Jurnal Ilmu Komputer dan Informatika KLIK (Kumpulan jurnaL Ilmu Komputer) (e-Journal) Bulletin of Electrical Engineering and Informatics JOIN (Jurnal Online Informatika) Edu Komputika Journal Jurnal Teknologi dan Sistem Komputer JOIV : International Journal on Informatics Visualization Sinkron : Jurnal dan Penelitian Teknik Informatika Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) International Journal of Artificial Intelligence Research Jurnal Informatika Jurnal Khatulistiwa Informatika Journal of Information Technology and Computer Science (JOINTECS) Jurnal Ilmiah FIFO INTENSIF: Jurnal Ilmiah Penelitian dan Penerapan Teknologi Sistem Informasi AKSIOLOGIYA : Jurnal Pengabdian Kepada Masyarakat JURNAL MEDIA INFORMATIKA BUDIDARMA Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control CogITo Smart Journal IT JOURNAL RESEARCH AND DEVELOPMENT InComTech: Jurnal Telekomunikasi dan Komputer Insect (Informatics and Security) : Jurnal Teknik Informatika JURNAL REKAYASA TEKNOLOGI INFORMASI PROCESSOR Jurnal Ilmiah Sistem Informasi, Teknologi Informasi dan Sistem Komputer Applied Information System and Management ILKOM Jurnal Ilmiah Compiler MATRIK : Jurnal Manajemen, Teknik Informatika, dan Rekayasa Komputer CYBERNETICS Digital Zone: Jurnal Teknologi Informasi dan Komunikasi J-SAKTI (Jurnal Sains Komputer dan Informatika) JUMANJI (Jurnal Masyarakat Informatika Unjani) JURTEKSI RESISTOR (Elektronika Kendali Telekomunikasi Tenaga Listrik Komputer) Komputasi: Jurnal Ilmiah Ilmu Komputer dan Matematika Informatika : Jurnal Informatika, Manajemen dan Komputer Jurnal Ilmiah Mandala Education (JIME) Systemic: Information System and Informatics Journal EDUMATIC: Jurnal Pendidikan Informatika Building of Informatics, Technology and Science Jurnal Mantik Jutisi: Jurnal Ilmiah Teknik Informatika dan Sistem Informasi JISKa (Jurnal Informatika Sunan Kalijaga) Buletin Ilmiah Sarjana Teknik Elektro Mobile and Forensics Aviation Electronics, Information Technology, Telecommunications, Electricals, Controls (AVITEC) Journal of Robotics and Control (JRC) Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) Cyber Security dan Forensik Digital (CSFD) JTIULM (Jurnal Teknologi Informasi Universitas Lambung Mangkurat) International Journal of Advances in Data and Information Systems Edunesia : jurnal Ilmiah Pendidikan Journal of Innovation Information Technology and Application (JINITA) Infotech: Journal of Technology Information Jurnal Teknologi Informatika dan Komputer Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) Jurnal Teknik Informatika (JUTIF) JURPIKAT (Jurnal Pengabdian Kepada Masyarakat) Humanism : Jurnal Pengabdian Masyarakat International Journal of Robotics and Control Systems J-SAKTI (Jurnal Sains Komputer dan Informatika) Jurnal Informatika Teknologi dan Sains (Jinteks) Techno Jurnal Pengabdian Informatika (JUPITA) Jurnal INFOTEL Jurnal Informatika: Jurnal Pengembangan IT Scientific Journal of Informatics Jurnal Karya untuk Masyarakat (JKuM) Control Systems and Optimization Letters Signal and Image Processing Letters Scientific Journal of Engineering Research SEMINAR TEKNOLOGI MAJALENGKA (STIMA) Edumaspul: Jurnal Pendidikan Methods in Science and Technology Studies

Abdul Fadlil

Ahmad Dahlan University

Author-ID : 262682

Religion Aerospace Engineering Arts Humanities Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Neuroscience Public Health Social Sciences Transportation Other

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Sistem Pengenalan Botol Plastik Berdasarkan Label Merek Menggunakan Faster-RCNN Arief Setyo Nugroho; Rusydi Umar; Abdul Fadlil
Techno (Jurnal Fakultas Teknik, Universitas Muhammadiyah Purwokerto) Vol 21, No 2 (2020): Techno Volume 21 No.2 Oktober 2020
Publisher : Universitas Muhammadiyah Purwokerto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30595/techno.v21i2.8635

Penumpukan botol plastik saat ini sudah tidak terkendali sehingga mengakibatkan polusi pada lingkungan. Sampah botol plastik saat ini dapat ditukar dengan imbalan yang beragam. Sehingga proses sortir botol plastik dapat dilakukan untuk memilih sampah botol plastik. Pada penelitian isi dibuat sistem yang dapat menganali dan mengklasifikasi botol pastik berdasarkan label merek dengan 5 kelas berukuran sedang atau 600ml. Metode yang akan digunakan adalah teknik pengolahan citra dengan menggunakan Convolutional Neural Network dengan Tensorflow dan model data Faster-RCNN. Penelitian dibagi menjadi 3 bagain yaitu pre-processing, training, dan testing. Pengujian dilakukan dengan menampilkan hasil dari proses bagian yang akan dilakukan serta menampilkan hasil akurasi. Berdasarkan dari hasil pengujian sistem dapat mengenali objek dengan baik dengan akurasi sebesar 87,12%

K Nearest Neighbor Imputation Performance on Missing Value Data Graduate User Satisfaction Abdul Fadlil; Herman; Dikky Praseptian M
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 6 No 4 (2022): Agustus 2022
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

A missing value is a common problem of most data processing in scientific research, which results in a lack of accuracy of research results. Several methods have been applied as a missing value solution, such as deleting all data that have a missing value, or replacing missing values with statistical estimates using one calculated value such as, mean, median, min, max, and most frequent methods. Maximum likelihood and expectancy maximization, and machine learning methods such as K Nearest Neighbor (KNN). This research uses KNN Imputation to predict the missing value. The data used is data from a questionnaire survey of graduate user satisfaction levels with seven assessment criteria, namely ethics, expertise in the field of science (main competence), foreign language skills, foreign language skills, use of information technology, communication skills, cooperation, and self-development. The results of testing imputation predictions using KNNI on user satisfaction level data for STMIK PPKIA Tarakanita Rahmawati graduates from 2018 to 2021. Where using the five k closest neighbors, namely 1, 5, 10, 15, and 20, the error value of the k nearest neighbors is 5 in RMSE is 0, 316 while the error value using MAPE is 3,33 %, both values are smaller than the value of k other nearest neighbors. K nearest neighbor 5 is the best imputation prediction result, both calculated by RMSE and MAPE, even in MAPE the error value is below 10%, which means it is very good.

MASK DETECTION ANALYSIS USING HAAR CASCADE AND NAÏVE BAYES Imam Riadi; Abdul Fadlil; Izzan Julda D.E Purwadi Putra
Jurnal Teknologi Informasi Universitas Lambung Mangkurat (JTIULM) Vol. 7 No. 2 (2022)
Publisher : Fakultas Teknik Universitas Lambung Mangkurat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20527/jtiulm.v7i2.135

Coronavirus Disease (COVID-19) is a new virus variant that emerged in 2019. The World Health Organization (WHO) states that 394,381,395 people have been infected with COVID-19, and 5,735,178 have died. This epidemic has been found in Indonesia since March 2020. New cases in Indonesia are still increasing every day as a whole. The Government as a policy has imposed a policy on anyone who will be required to wear a mask and also carry out physical distancing so that they can work without the maker being exposed to the virus. In the midst of a pandemic, the use of masks has increased to prevent transmission. Various types of masks are easy to find, but not all masks are recommended to avoid transmission. Among them are the N-95 masks, which are recommended to prevent transmission. This application uses the haar cascade and naive bayes methods. The pycharm edition 2021.2 tools and python 3.8 are the detection systems used in this mask. The haar cascade method is also used in detecting objects with masks or not and naive Bayes, which is used as an accuracy calculation. This study uses a dataset of 1092, which is divided into 192 positive images and 900 negative images. Accuracy results using the haar cascade method are 100% more accurate, while the nave Bayes method is 76.6% less accurate.

Desain Sistem Monitoring dan Penyiraman Tanaman Tomat Berbasis Internet of Things (IoT) Zulhijayanto -; Abdul Fadlil
Buletin Ilmiah Sarjana Teknik Elektro Vol. 4 No. 2 (2022): Agustus
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/biste.v4i2.5884

Air temperature and soil moisture are things that need to be considered in caring for tomato plants. Watering is also important because tomatoes are plants that do not tolerate dry soil. This study aims to monitor air temperature, air humidity and soil moisture as well as watering plants when the soil moisture value is dry. The research method used is IoT-based watering automation with Node MCU components ESP8266, DHT11 sensor, V1.2 SEN0193 capacitive soil moisture sensor, 1 channel relay module, DC water pump, and 20x4 LCD. The test results of the DHT11 sensor on air temperature have an error of 3.09% with an accuracy of 96.91%. The error value for air humidity is 12.34% with an accuracy of 87.61%. The V1.2 SEN0193 capacitive soil moisture sensor has an error of 6.82% with an accuracy of 93.18%. This research has succeeded in watering plants based on the specified value, which is below 60% and stops watering before 80%. Suhu udara dan kelembaban tanah adalah hal yang perlu diperhatikan dalam merawat tanaman tomat. Penyiraman juga penting karena tomat adalah tanaman yang tidak tahan terhadap tanah yang kering. Penelitian ini bertujuan untuk memantau suhu udara, kelembaban udara dan kelembaban tanah serta menyiram tanaman pada saat nilai kelembaban tanah kering. Metode penelitian yang digunakan adalah otomasi penyiraman berbasis IoT dengan komponen Node MCU ESP8266, sensor DHT11, sensor kelembaban tanah kapasitif V1.2 SEN0193, modul relay 1 channel, pompa air DC, dan LCD 20x4. Hasil pengujian sensor DHT11 terhadap suhu udara memiliki error sebesar 3,09 % dengan akurasi 96,91%. Nilai error terhadap kelembaban udara sebesar 12,34 % dengan akurasi 87,61%. Pada sensor kelembaban tanah kapasitif V1.2 SEN0193 memiliki error sebesar 6.82 % dengan akurasi 93,18%. Penelitian ini telah berhasil menyiram tanaman berdasarkan nilai yang ditentukan yaitu di bawah 60% dan berhenti menyiram sebelum 80%.

Penerapan Algoritma K-Means pada Pengelompokan Data Pendaftar Bantuan Biaya Pendidikan Abdul Fadlil; Imam Riadi; Yana Mulyana
Jurnal Teknologi Informatika dan Komputer Vol 8, No 2 (2022): Jurnal Teknologi Informatika dan Komputer
Publisher : Universitas Mohammad Husni Thamrin

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37012/jtik.v8i2.1261

Universitas Muhammadiyah Tasikmalaya merupakan salah satu perguruan tinggi yang mendapatkan bantuan biaya pendidikan untuk mahasiswa penerima program Kartu Indonesia Pintar Kuliah (KIP-Kuliah) disetiap tahunnya. Program ini diperuntukan bagi lulusan SMA/SMK/sederajat dari keluarga miskin/rentan miskin/afirmasi yang memiliki keinginan untuk melanjutkan belajar ke jenjang yang lebih tinggi. Hasil dari evaluasi pelaksanaan dalam penetapan data penerimaannya terdapat masalah karena data pendaftar masih banyak yang berasal dari keluarga mampu, disamping itu jumlah kuota yang diberikan oleh pemerintah sebanyak 30 kuota, jauh lebih sedikit daripada jumlah pendaftar yang berjumlah 191, sehingga harus ada metode yang dapat mengoptimalkan pengelompokan data pendaftar terlebih dahulu agar penetapan penerima bantuan biaya pendidikan KIP-Kuliah tepat sasaran. dalam penelitian ini penulis menggunakan metode Kmeans untuk pengelompokan data pendaftar dengan jumlah klaster sebanyak 3 (K=3). Hasil dari penelitian ini yaitu klaster C0 sebanyak 109 data (57,1%), klaster C1 sebanyak 52 data (27,2%), dan klaster C2 sebanyak 30 data (15,7%). Hasil dari sebaran data pada masing-masing kelompok, penulis merekomendasikan klaster C0 sebagai data kelompok yang dipertimbangkan, klaster C1 sebagai kelompok yang tidak layak dan klaster C2 sebagai kelompok yang layak mendapatkan bantuan biaya pendidikan / KIP-Kuliah.

Design an Internet of Things-Based LPG Gas Leak Detection System Mustofa Mustofa; Abdul Fadlil
Buletin Ilmiah Sarjana Teknik Elektro Vol. 4 No. 3 (2022): December
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/biste.v4i3.5572

LPG currently plays a big role in human life, both in industry and households. However, since the existence of LPG, there have been many cases of fires caused by LPG gas leaks. Undetected LPG gas leaks can cause sparks and can trigger fires. Therefore, currently an LPG gas detection device is needed. The system designed in this study uses an MQ-6 sensor to detect LPG gas, and NodeMCU as a microcontroller. This system not only detects leaking gas, but can also provide alerts and information to the Blynk application on smartphones by utilizing the Internet of Things (IoT). System testing resulted in an error value in detecting gas of 9.52% and the distance between the system and the smartphone was 500 meters. The sensor can detect gas well when the distance between the gas and the sensor is no more than 10 cm. The system can provide information to the smartphone if a gas leak is detected and can provide alerts by turning on the buzzer and LEDs.

The Application of The Manhattan Method to Human Face Recognition Sunardi; Abdul Fadlil; Novi Tristanti
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 6 No 6 (2022): Desember 2022
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v6i6.4265

In face recognition, the input image used will be converted into a simple image, which will then be analyzed. The analysis was carried out by calculating the distance of data similarity. In the process of measuring data similarity distances, they often experience problems implementing complex algorithm formulas. This research will solve this problem by implementing the Manhattan method as a method of measuring data similarity distances. In this study, it is hoped that the Manhattan method can be used properly in the process of matching test images and training images by calculating the proximity distance between the two variables. The distance sought is the shortest distance; the smaller the distance obtained, the higher the level of data compatibility. The image used in this study was converted into grayscale to facilitate the facial recognition process by thresholding, namely the process of converting a grayscale image into a binary image. The binary image of the test data is compared with the binary image of the training data. The image used in this study is in the Joint Photographic Experts Group (JPEG) format. Testing was carried out with 20 respondents, with each having two training images and two test images. The research was conducted by conducting experiments as many as 20 times. Facial recognition research using the Manhattan method obtains an accuracy of 70%. The image lighting used as the dataset influenced the accuracy results obtained in this study. Based on the results of this study, it can be concluded that the Manhattan method is not good for use in facial recognition research with poor lighting.

Improving The Results of Learning Nglegena Javanese Handwriting Using Backpropagation Artificial Neural Network Arif Budiman; Abdul Fadlil; Rusydi Umar
Edunesia: Jurnal Ilmiah Pendidikan Vol. 4 No. 1 (2023)
Publisher : research, training and philanthropy institution Natural Aceh

The Nglagena Javanese script is one of the cultural assets of the Indonesian nation that needs to be preserved. Various efforts have been made to preserve this script, one of which is using information technology as a learning medium for the Nglagena Javanese script. Information Technology allows the Javanese script to be introduced interactively to students. To support this need, one of which is the ability of information technology to classify Javanese script. Classification of Javanese script is carried out using the Backpropagation Artificial Neural Network (BANN) method. Twenty primary Javanese characters are classified as classes using the Backpropagation Artificial Neural Network (BANN) method. The stages of this research are initial processing, feature extraction, model training, and model testing. Initial processing is carried out to prepare image data so that it is ready for the feature extraction process. The feature extraction method is the Histogram Chain Code (HCC) to obtain the main characteristics of each data class or character of the Nglegena Javanese script. This study compares three research models by adjusting the ratio between the training image data and the test image so that the model that produces the highest accuracy value is produced. The model training and testing process uses 2000 image data, with the percentage distribution of training image data and test images, namely 20%, 80%, second 50%, 50%, and third 80%, 20%, resulting in different levels of accuracy. The results are to produce successive accuracy of 66%, 72%, and 88%.

Sistem Monitoring pH dan Kekeruhan Kolam ikan Koi Berbasis Internet of Things Menggunakan Aplikasi Blynk Ahmat Taufik; Abdul Fadlil
Jurnal Teknologi Elektro Vol 14, No 1 (2023)
Publisher : Electrical Engineering, Universitas Mercu Buana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/jte.2023.v14i1.010

Ikan koi termasuk salah satu jenis ikan yang banyak digemari oleh masyarakat karena harganya yang mahal dan warnanya yang unik. Hal tersebut juga didukung dengan proses perawatan ikan koi yang tidaklah mudah. Salah satunya adalah kualitas air dan pakan yang baik sehingga ikan dapat tumbuh dengan sehat. Namun permasalahannya untuk menciptakan kualitas air yang baik membutuhkan pengorbanan waktu dan tenaga yang lebih banyak. Oleh sebab itu, dengan adanya perkembangan teknologi maka pengecekan kualitas air utamanya pH dan kekeruhan dapat dilakukan dengan bantuan teknologi. Salah satunya dengan menggunakan bantuan Internet of Things (IoT). Dimana metode ini mempercepat pengguna dalam memperoleh data. Hal tersebut dikarenakan hasilnya akan terkirim secara otomatis melalui sebuah aplikasi Blynk yang terinstal pada smartphone. Hasil akhir dari penelitian yang telah dilakukan menunjukan bahwa alat tersebut berhasil dalam memantau kekeruhan dan pH air kolam ikan koi secara otomatis dan tepat. Pnegujian menggunakan jaringan yang berbeda dengan hasil nilai yang didapatkan dari sensor pH berada pada rentang nilai pH 7,23 – 7,74 dan untuk kekeruhan air berada pada rentang nilai dengan rentang nilai 5–37 NTU.

Penentuan Penerimaan Karyawan Menggunakan Metode Simple Additive Weighting dan Weight Product Ermin Al Munawar; Sunardi Sunardi; Abdul Fadlil
JSINBIS (Jurnal Sistem Informasi Bisnis) Vol 11, No 2 (2021): Volume 11 Nomor 2 Tahun 2021
Publisher : Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21456/vol11iss2pp117-124

Recruitment errors influence in a decrease of quality, performance, and company revenue. One of the causes is the absence of a method that is applied as a systematically of information system in determining the acceptance of the best prospective employees. This study uses the Simple Additive Weighting (SAW) and Weight Product (WP) methods to build an objective, fast, and accurate of Decision Support System (DSS) in determining employee acceptance. This research case study was applied to the Indonesian Market Traders Cooperative (KOPPI) Sorong City, West Papua Province by involving a number of 10 alternative applicants. This study aims to produce an objective information system and provide convenience in determining the best employees, referring to the determination of 9 criteria obtained from interviews, namely education, work experience, motivation, intrapersonal ability, achievement orientation, sales ability, self-confidence, trustworthy, and work ethic by weighting each. SAW and WP methods are both used to determine the best ranking of all alternative applicants and get the best prospective employees. The information system was built using the Waterfall development method with the PHP programming language and Mysql database. Based on the results of research that has been carried out, it is found that the information system built has 100% conformity of functionality and compatibility between manual and application system. Both methods provide the same highest alternative to be used as the determination of the best employee acceptance, however it is found that the WP method provides better accuracy and validity than SAW.

Co-Authors Aang Anwarudin Abdul Azis Achmad Nugrahantoro Aditiya Dwi Candra Ahmat Taufik Aji Pamungkas Alfiansyah Imanda Putra Alfiansyah Imanda Putra Alfian Amiruddin, Nanda Fahmi Andrianto, Fiki Anggit Pamungkas Annisa, Putri Anton Yudhana Anwar Siswanto ANWAR, FAHMI Arief Setyo Nugroho Arief Setyo Nugroho Arif Budi Setianto Arif Budiman Arif Budiman Arif Wirawan Muhammad Aris Rakhmadi Asno Azzawagama Firdaus Atmojo, Dimas Murtia Aulia, Aulia Az-Zahra, Rifqi Rahmatika Aznar Abdillah, Muhamad Bagus Primantoro Basir, Azhar Candra, Aditiya Dwi Darajat, Muhammad Nashiruddin Davito Rasendriya Rizqullah Putra Dewi Soyusiawaty Dhimas Dwiki Sanjaya Dian Permata Sari Dianda Rifaldi Dikky Praseptian M Dimas Murtia Atmojo Doddy Teguh Yuwono Dwi Susanto Dwi Susanto Edy Fathurrozaq Egi Dio Bagus Sudewo Eko Prianto Eko Prianto Elvina, Ade Ermin Al Munawar Ermin Ermin Esthi Dyah Rikhiana Fahmi Anwar Fahmi Auliya Tsani Fahmi Auliya Tsani Fahmi Fachri Fanani, Galih Faqihuddin Al-anshori Faqihuddin Al-Anshori, Faqihuddin Fathurrahman, Haris Imam Karim Fauzi Hermawan Fiki Andrianto Firmansyah Firmansyah Firmansyah Firmansyah Firmansyah Yasin Fitri Muwardi Furizal Gusrin, Muhaimin Gustina, Sapriani Hafizh, Muhammad Nasir Hanif, Abdullah Hanif, Kharis Hudaiby Harman, Rika Helmiyah, Siti Hendril Satrian Purnama Herdiyanto, Erik Herman Herman Herman Yuliansyah, Herman Herman, - Ibnu Rifajar Ibrahim Mohd Alsofyani Ihyak Ulumuddin Ikhsan hidayat Ilhamsyah Muhammad Nurdin Imam Riadi Imam Riadi Imam Riadi Imam Riadi Imam Riadi Imam Riadi Imam Riadi Irjayana, Rizky Caesar Irwansyah Irwansyah Izzan Julda D.E Purwadi Putra januari audrey Jayawarsa, A.A. Ketut Jogo Samodro, Maulana Muhamammad Joko Supriyanto Joko Supriyanto Kamilah, Farhah Kartika Firdausy Khoirunnisa, Itsnaini Irvina Kusuma, Nur Makkie Perdana Laura Sari Lestari, Yuniarti Lestari, Yuniarti Lin, Yu-Hao Luh Putu Ratna Sundari M. Nasir Hafizh Maftukhah, Ainin Maulana Muhammad Jogo Samudro Mini, Ros Mohd Hatta Jopri Muammar Mudinillah, Adam Mufaddal Al Baqir Muh. Fadli Hasa Muhaimin Gusrin Muhajir Yunus Muhamad Daffa Al Fitra Muhamad Rosidin Muhammad Faqih Dzulqarnain, Muhammad Faqih Muhammad Johan Wahyudi Muhammad Kunta Biddinika Muhammad Ma’ruf Muhammad Nasir Hafizh Muhammad Nur Faiz Muhammad Nurdin, Ilhamsyah Muhammad Rizki Setyawan Muntiari, Novita Ranti Murinto Murinto - Murinto Murinto Murni Murni Musliman, Anwar Siswanto Mustofa Mustofa Muwardi, Fitri Nasution, Dewi Sahara Nasution, Musri Iskandar Nurwijayanti Pahlevi, Ryan Fitrian Ponco Sukaswanto Poni Wijayanti Prabowo, Basit Adhi Prayogi, Denis Priambodo, Bambang Putra, Fajar R. B Putri Annisa Putri Annisa Putri Purnamasari Putri Silmina, Esi Ramadhani, Muhammad Ramdhani, Rezki Razak, Farhan Radhiansyah Rezki Rezki Rifqi Rahmatika Az-Zahra Rizky Andhika Surya Rochmadi, Tri Roni Anggara Putra Rusydi Umar Rusydi Umar S Sunardi S, Sunardi Saad, Saleh Khalifah Safiq Rosad Saifudin Saifudin Saifullah, Shoffan Saleh khalifa saad Santi Purwaningrum Sarmini Sarmini Septa, Frandika Setyaputri, Khairina Eka Setyaputri, Khairina Eka Setyaputri, Khairina Eka Shinta Nur Desmia Sari Siti Helmiyah Subandi, Rio Sukaswanto, Ponco Sukma Aji Sulis Triyanto Sunardi Sunardi Sunardi Sunardi, Sunardi Surya Yeki Surya Yeki Syamsiar, Syamsiar Syarifudin, Arma Tole Sutikno Tresna Yudha Prawira Tresna Yudha Prawira Tri Ferga Prasetyo Tristanti, Novi Tuswanto Tuswanto Virdiana Sriviana Fatmawaty Wahju Tjahjo Saputro Wahyusari, Retno Winoto, Sakti Wintolo, Hero Wulandari, Cisi Fitri Yana Mulyana Yana Mulyana Yasidah Nur Istiqomah Yeki, Surya Yohanni Syahra Yossi Octavina Yulianto, Dinan Yulianto, Muhammad Anas Yuminah yuminah Yuminah, Yuminah yuminah, Yuminah Yuwono Fitri Widodo Zein, Wahid Alfaridsi Achmad Zulhijayanto -

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