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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 Pseudocode 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 RABIT: Jurnal Teknologi dan Sistem Informasi Univrab Jurnal Informatika Jurnal Khatulistiwa Informatika Journal of Information Technology and Computer Science (JOINTECS) Jurnal Ilmiah FIFO INTEGER: Journal of Information Technology INTENSIF: Jurnal Ilmiah Penelitian dan Penerapan Teknologi Sistem Informasi JIKO (Jurnal Informatika dan Komputer) 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 JOURNAL OF APPLIED INFORMATICS AND COMPUTING 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 Jurnal Teknologi Sistem Informasi dan Aplikasi CYBERNETICS Digital Zone: Jurnal Teknologi Informasi dan Komunikasi PHARMACY: Jurnal Farmasi Indonesia (Pharmaceutical Journal of Indonesia) 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) JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Systemic: Information System and Informatics Journal Jurnal Teknologi Terpadu 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, and Controls (AVITEC) Journal of Robotics and Control (JRC) Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) Cyber Security dan Forensik Digital (CSFD) JATI (Jurnal Mahasiswa Teknik Informatika) Jurnal E-Komtek JTIULM (Jurnal Teknologi Informasi Universitas Lambung Mangkurat) International Journal of Advances in Data and Information Systems International Journal of Marine Engineering Innovation and Research Edunesia : jurnal Ilmiah Pendidikan JITU : Journal Informatic Technology And Communication Journal of Innovation Information Technology and Application (JINITA) Tematik : Jurnal Teknologi Informasi Komunikasi Infotech: Journal of Technology Information Jurnal Teknologi Informatika dan Komputer Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) Jurnal Teknik Informatika (JUTIF) Humanism : Jurnal Pengabdian Masyarakat International Journal of Robotics and Control Systems J-SAKTI (Jurnal Sains Komputer dan Informatika) Jurnal Pengabdian Kepada Masyarakat Patikala Jurnal Informatika Teknologi dan Sains (Jinteks) Jurnal Algoritma Techno Wahana Jurnal Pengabdian Informatika (JUPITA) Sinteza Jurnal INFOTEL Jurnal Informatika Polinema (JIP) Jurnal Informatika: Jurnal Pengembangan IT Jurnal Accounting Information System (AIMS) Scientific Journal of Informatics Control Systems and Optimization Letters Journal of Electrical Engineering and Informatics Darma Abdi Karya: Jurnal Pengabdian Kepada Masyarakat Signal and Image Processing Letters Khazanah Informatika : Jurnal Ilmu Komputer dan Informatika SEMINAR TEKNOLOGI MAJALENGKA (STIMA) Edumaspul: Jurnal Pendidikan Methods in Science and Technology Studies JOCHAC Proceeding of Informatics Collaborations and Dessimenation Meeting (Infocoding)
Abdul Fadlil
Ahmad Dahlan University
Religion Aerospace Engineering Agriculture, Biological Sciences & Forestry Arts Humanities Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Immunology & microbiology Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Neuroscience Physics Public Health Social Sciences Transportation Other

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Karakteristik Sosiodemografi dan Klinis Pasien Osteoarthritis pada Berbagai Tingkat Keparahan Berdasarkan Klasifikasi Kellgren-Lawrence Muhammad Nuh; Endang Darmawan; Sugiyarto Surono; Abdul Fadlil; Adnan Adnan
Sinteza Vol. 6 No. 2 (2026): August
Publisher : Universitas Hamzanwadi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29408/sinteza.v6i2.35895

Abstract

Osteoarthritis (OA) is the most common degenerative joint disease, and its severity is commonly assessed using the Kellgren–Lawrence (KL) classification. Understanding patient characteristics across different severity levels is essential to support clinical evaluation and optimize patient management. This study aimed to analyze the sociodemographic, clinical, and laboratory characteristics of patients with OA according to KL severity. A retrospective analytical observational study was conducted using the medical records of 1,124 patients diagnosed with OA at Sultan Agung Islamic Hospital, Semarang, Indonesia, between January 2020 and January 2025. Sociodemographic, clinical, and laboratory data were collected from electronic medical records. Descriptive statistics were used to summarize patient characteristics, while differences across KL severity levels were analyzed using the Chi-square test with a significance level of p<0.05. Significant differences in OA severity were observed according to age and body mass index (p<0.05), whereas sex was not significantly associated with KL severity (p>0.05). Clinical characteristics, including OA type, comorbidity status, number and type of comorbidities, and pain intensity, differed significantly across KL grades (all p<0.05). Laboratory parameters, including blood pressure, blood glucose, renal function, and lipid profile, also demonstrated significant differences according to OA severity (all p<0.05). These findings indicate that OA severity is associated with distinct sociodemographic, clinical, and laboratory characteristics, providing valuable evidence to support risk stratification, clinical assessment, and individualized management of patients with OA.
Evaluating The Effectiveness of Augmentation and Classifier Algorithms for Fraud Detection: Comparing CGAN and SMOTE with Random Forest and XGBoost Sarmini Sarmini; Sunardi Sunardi; Abdul Fadlil
Applied Information System and Management (AISM) Vol. 8 No. 2 (2025): Applied Information System and Management (AISM)
Publisher : Depart. of Information Systems, FST, UIN Syarif Hidayatullah Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15408/aism.v8i2.46308

Abstract

Fraud detection in imbalanced datasets, where fraudulent transactions represent a small fraction of total data, presents a major challenge for machine learning models. Traditional classifiers often perform poorly in such scenarios due to their bias toward the majority class. This study investigates the effectiveness of two data augmentation techniques, Synthetic Minority Over-sampling Technique (SMOTE) and Conditional Generative Adversarial Networks (CGAN) in improving fraud detection performance. Both methods are applied to balance the dataset, and their impact is evaluated using two classifiers: Random Forest (RF) and XGBoost. The models are tested across three versions of the dataset: the original imbalanced data, the SMOTE-augmented data, and the CGAN-augmented data. Evaluation metrics include accuracy, precision, recall, F1 score, and ROC-AUC. Results indicate that both augmentation techniques enhance the models' ability to detect fraudulent transactions compared to the original dataset. Notably, CGAN outperforms SMOTE in terms of recall and F1 score, suggesting its ability to generate more diverse and realistic synthetic samples. While SMOTE creates new samples through interpolation, CGAN uses an adversarial process involving a generator and a discriminator, resulting in more complex data representations. The study also finds that XGBoost combined with CGAN yields the highest performance, effectively capturing intricate fraud patterns. In contrast, SMOTE, though beneficial, shows limited capacity in improving recall. This research highlights the importance of advanced augmentation techniques like CGAN in addressing class imbalance and improving fraud detection systems. It also opens pathways for future exploration of deep learning-based augmentation and classification methods in fraud detection.
Pola Penggunaan Obat Hipertensi pada Pasien Program Rujuk Balik di Apotek Wilayah Pulau Bangka Sugiyarto Surono; Miftahul Rozak; Endang Darmawan; Nopi Hidayat; Abdul Fadlil
PHARMACY: Jurnal Farmasi Indonesia (Pharmaceutical Journal of Indonesia) Jurnal Pharmacy, Vol. 23 No. 01 Juli 2026
Publisher : Pharmacy Faculty, Universitas Muhammadiyah Purwokerto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30595/pharmacy.v23i1.28368

Abstract

Hipertensi merupakan salah satu penyakit kronis terbanyak dalam program rujuk balik (PRB) yang membutuhkan terapi jangka panjang serta keberlanjutan layanan di fasilitas kesehatan primer. Informasi tentang pola penggunaan obat di apotek jejaring penting sebagai dasar perencanaan pengadaan dan kebijakan farmasi. Penelitian ini bertujuan untuk menganalisis pola konsumsi dan kombinasi terapi antihipertensi pada pasien PRB di wilayah Pulau Bangka berdasarkan data transaksi tahun 2024. Penelitian ini dilakukan secara kuantitatif deskriptif dengan pendekatan data mining menggunakan algoritma Apriori untuk mengidentifikasi asosiasi antarobat. Data diambil dari transaksi resep PRB selama 1 tahun di beberapa apotek dalam jejaring mitra BPJS Kesehatan. Hasil menunjukkan bahwa kelompok obat Angiotensin II Receptor Blocker (ARB), Calcium Channel Blocker (CCB) dihidropiridin, dan beta blocker selektif merupakan golongan yang paling banyak digunakan. Amlodipine 10 mg, Candesartan 8 mg dan 16 mg, serta Bisoprolol menjadi item obat yang paling sering diresepkan. Pola kombinasi dua obat yang paling menonjol adalah Candesartan dan Amlodipine, sementara kombinasi tiga obat yang dominan mencakup Candesartan, Amlodipine, Bisoprolol, Spironolactone, dan Furosemide. Nilai lift yang tinggi mengindikasikan kekuatan asosiasi yang relevan secara klinis. Temuan ini mencerminkan pola terapi yang rasional dan konsisten dengan pedoman hipertensi, serta dapat digunakan untuk menyusun strategi pengadaan obat dan optimalisasi kesinambungan terapi bagi pasien PRB.
Implementasi CNN berbasis Autoencoder pada Klasifikasi Pola Batik Muhammad Faqih Dzulqarnain; Abdul Fadlil; Imam Riadi
Proceeding of Informatics Collaborations and Dessimenation Meeting Vol. 1 No. 1 (2025)
Publisher : Universitas Muhammadiyah Surakarta

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

Abstract

Batik sebagai warisan budaya Indonesia memiliki keragaman motif yang perlu dilestarikan. Batik yang menjadi warisan budaya, memiliki tantangan untuk pengenalan pola yang ditujukan untuk melestarikan motif sesuai identifikasi ciri khas wilayahnya. Penelitian ini bertujuan untuk mengeksplorasi potensi alternatif autoencoder dalam identifikasi pola batik. Pemanfaatan teknologi kecerdasan buatan, khususnya autoencoder, diharapkan dapat dilakukan sebagai identifikasi motif batik secara akurat. Autoencoder dipilih karena kemampuannya dalam belajar representasi dengan mereduksi dimensi data secara otomatis tanpa memerlukan rekayasa fitur yang kompleks. Hasil penelitian menunjukkan bahwa autoencoder mampu mencapai akurasi 95,4% untuk data training, dan akurasi 93,7% untuk data testing. Penelitian ini memberikan kontribusi dalam pengembangan metode klasifikasi pola batik berbasis deep learning. Hasil yang diperoleh menunjukkan potensi autoencoder sebagai alat untuk pelestarian dan dokumentasi identifikasi motif batik.
Literasi Digital Penggunaan Blogspot Sebagai Media Portofolio Karya Siswa Smk Muhammadiyah 2 Tangerang Selatan Rosalina; Halim, Zuhri; Lelisa Army, Widya; Fadlil, Abdul; Yuliansyah, Herman
Jurnal Pengabdian Kepada Masyarakat Patikala Vol. 6 No. 1 (2026): Jurnal PkM PATIKALA
Publisher : Pusat Pengembangan Pendidikan dan Bakat Indonesia/Education and Talent Development Center of Indonesia (ETDC Indonesia)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51574/patikala.v6i1.5815

Abstract

Advancements in digital technology across various aspects of life including education, the workforce, and youth career development are driving a major shift toward the "Society 5.0" transformation. Students in the Computer and Network Engineering (TKJ) program at SMK Muhammadiyah 2 South Tangerang currently lack established proficiency in using digital tools productively. Blogspot can serve not only as a platform for communication and entertainment but also as a medium for documenting and publishing creative work. This *Prodamat* (Community Empowerment Program) initiative aims to enhance the digital literacy of SMK Muhammadiyah 2 South Tangerang students by utilizing Blogspot as a platform for digital portfolios showcasing their work. The implementation process comprises several stages: preparation, delivery of digital literacy material, a demonstration of Blogspot usage, hands-on practice in creating and managing blogs, guidance on portfolio development, and evaluation via a post-test. The participants were students from SMK Muhammadiyah 2 South Tangerang who underwent both theoretical and practical training. The results indicate an improvement in the students' understanding and skills regarding the use of Blogspot specifically in creating blogs, customizing layouts, uploading work, and adding descriptions to their projects. Post-test results showed an average score of 80.82 across the 24 participants. This performance is considered excellent, as the students progressed from having no prior knowledge of the application to achieving a strong understanding; only two or three participants received low scores. Ultimately, this activity aims to enable students to use Blogspot as a simple digital portfolio platform, thereby fostering digital literacy and preparing the students of SMK Muhammadiyah 2 South Tangerang for the workforce.
Klasifikasi Pola Sidik Jari Arch, Loop, dan Whorl Menggunakan Kombinasi Fitur Histogram of Oriented Gradients (HOG) dan Local Binary Pattern (LBP) dengan Support Vector Machine (SVM) Rizal Parghani; Abdul Fadlil; Tole Sutikno
INTEGER: Journal of Information Technology Vol 11, No 2 (2026): September
Publisher : Fakultas Teknologi Informasi Institut Teknologi Adhi Tama Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31284/j.integer.2026.v11i2.9286

Abstract

Klasifikasi pola sidik jari ke dalam kategori struktural sebelum pencocokan minutiae membantu menyederhanakan sistem verifikasi identitas. Meskipun model deep learning seperti Convolutional Neural Network mampu mencapai akurasi tinggi, pendekatan tersebut umumnya memerlukan dataset besar dan sumber daya komputasi besar, sehingga mendorong eksplorasi alternatif berbasis fitur handcrafted yang lebih ringan. Penelitian ini mengusulkan model klasifikasi pola sidik jari yang menggabungkan deskriptor Histogram of Oriented Gradients (HOG) dan Local Binary Pattern (LBP), diklasifikasikan menggunakan Support Vector Machine (SVM) berkernel Radial Basis Function (RBF). Sebanyak 2.401 citra sidik jari dari repositori publik Kaggle digunakan, mencakup tiga kelas pola: Arch, Loop, dan Whorl. Setelah konversi grayscale, resize ke 128×128 piksel, dan peningkatan kontras CLAHE, citra dibagi menjadi 1.679 data latih, 479 data validasi, dan 243 data uji. Vektor fitur gabungan HOG-LBP berdimensi 8.110 distandardisasi sebelum melatih SVM, dengan hyperparameter dioptimalkan melalui grid search pada data validasi. Konfigurasi terbaik (C = 1, gamma = 0,001, kernel RBF) selanjutnya digunakan untuk menghasilkan akurasi uji sebesar 89,71% dan weighted average F1-score sebesar 89,75%. Whorl mencatatkan F1-score tertinggi (91,82%), sedangkan Arch mencatatkan recall terendah (88,89%), terutama akibat kesalahan klasifikasi dengan kelas Loop. Hasil ini menunjukkan bahwa kombinasi HOG-LBP-SVM merupakan solusi yang efisien secara komputasi dan kompetitif untuk klasifikasi pola sidik jari, meskipun penyempurnaan lebih lanjut seperti reduksi dimensi dan validasi silang k-fold masih berpotensi meningkatkan kemampuan diskriminasi model pada kelas dengan kemiripan struktural.
Klasifikasi Multi Penyakit Tanaman Pepaya Berdasarkan Citra Daun Berbasis Deep Learning Menggunakan Convolutional Neural Network (CNN) Heri Wahyudi; Abdul Fadlil; Herman Herman
INTEGER: Journal of Information Technology Vol 11, No 2 (2026): September
Publisher : Fakultas Teknologi Informasi Institut Teknologi Adhi Tama Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31284/j.integer.2026.v11i2.9158

Abstract

Penyakit pada tanaman pepaya seperti Anthracnose, Bacterial Spot, Curl, dan Ring Spot dapat menurunkan produktivitas dan kualitas hasil panen secara signifikan. Keterbatasan metode konvensional yang mengandalkan pengamatan visual secara manual menyebabkan proses identifikasi penyakit menjadi tidak konsisten, memakan waktu lama, dan sulit diterapkan pada skala lahan pertanian yang luas. Penelitian ini bertujuan untuk mengembangkan model deep learning berbasis Convolutional Neural Network (CNN) guna mengklasifikasikan lima kategori kondisi daun pepaya secara akurat. Metodologi yang digunakan meliputi pemanfaatan dataset BDPapayaLeaf yang berisi 2.159 citra asli, yang kemudian diekspansi menjadi 6.477 citra menggunakan teknik augmentasi data. Model dilatih menggunakan pembagian data 70:15:15 (latih, validasi, uji) dengan memanfaatkan metode transfer learning, optimizer Adam, dan mekanisme early stopping. Hasil pengujian menunjukkan bahwa model PapayaLeafCNN yang diusulkan berhasil mencapai akurasi keseluruhan sebesar 84,66% dan weighted average F1-score sebesar 84,82% pada data uji. Analisis per kelas menunjukkan performa tertinggi pada kelas daun sehat (Healthy) dengan F1-score 94,29%, sementara kelas Bacterial Spot mencatatkan performa terendah (76,54%) akibat tingginya tingkat kesalahan prediksi yang tumpang tindih dengan kelas Curl. Secara keseluruhan, model CNN yang diusulkan mampu melakukan klasifikasi multi-penyakit daun pepaya dengan baik, meski ke depannya tetap diperlukan strategi khusus untuk mengklasifikasikan penyakit dengan kemiripan visual yang tinggi. 
Development of an Integrated IoT-based Monitoring System for a Three-Phase Induction Motor Using ESP32 and Industrial Power Meter Nandar Nandar; Abdul Fadlil; Tole Sutikno
Journal of Electrical Engineering and Informatics Vol. 4 No. 1 (2026): Journal of Electrical Engineering and Informatics
Publisher : Fakultas Teknik Universitas Negeri Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59562/jeeni.v4i1.13327

Abstract

Three-phase induction motors are essential in industrial systems and require continuous condition monitoring to improve operational reliability and reduce unexpected downtime. However, many Internets of Things (IoT)-based monitoring systems focus on data acquisition without quantitatively validating communication performance and data integrity. This study develops and validates an IoT-based monitoring system for real-time acquisition, transmission, visualization, and storage of electrical parameters. The proposed system integrates an ESP32 microcontroller, an industrial multifunction power meter, Modbus RTU communication, a Flask web server, an SQLite database, and a Streamlit dashboard. Voltage, current, active power, power factor, and frequency were monitored under no-load and loaded conditions. System validation used 621 valid monitoring samples, while communication performance was evaluated through three independent trials comprising 300 transmission attempts. The system achieved an HTTP success rate of 99.33% with an average latency of 655.47 ms (minimum 100 ms, maximum 3952 ms). Database verification confirmed 100% sequence completeness, with no missing sequence IDs among the records validated in the database. These results demonstrate consistent near-real-time monitoring, high HTTP transmission success, and complete sequence integrity within the validated database records. This study introduces an IoT-based monitoring platform validated through quantitative evaluation of HTTP success rate, communication latency, and database sequence completeness using sequence IDs. The validated platform provides a foundation for future LSTM-based predictive-maintenance research on three-phase induction motors.
Co-Authors Aang Anwarudin Abdul Azis Abdul Azis Achmad Nugrahantoro Aditiya Dwi Candra Adnan, Adnan Ahmad Naufal Ahmat Taufik Aji Pamungkas Akrom, Akrom Alfiansyah Imanda Putra Alfiansyah Imanda Putra Alfian Amiruddin, Nanda Fahmi Andi Zulherry Anggit Pamungkas Annisa, Putri Anton Yudhana Anton Yudhana Anwar Siswanto ANWAR, FAHMI Anwarudin, Aang Aqid Fahri Hafin ardi, Ardi Pujiyanta Arief Setyo Nugroho Arief Setyo Nugroho Arif Budi Setianto Arif Budiman Arif Budiman Arif Wirawan Muhammad Asep Ririh Riswaya Asno Azzawagama Firdaus Atmojo, Dimas Murtia Aulia, Aulia Az-Zahra, Rifqi Rahmatika Aznar Abdillah, Muhamad Bagus Primantoro Bambang Priambodo Bashor Fauzan Muthohirin Basir, Azhar Candra, Aditiya Dwi Darajat, Muhammad Nashiruddin Davito Rasendriya Rizqullah Putra Dedy Sumarhadi Dewi Soyusiawaty Dewi Soyusiawaty Dheni Apriantsani Budiman Dhimas Dwiki Sanjaya Dian Novianti 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 Budi Cahyono Eko Prianto Eko Prianto, Eko Elvina, Ade Endang Darmawan Endang Darmawan 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 Fiki Andrianto Firmansyah Firmansyah Firmansyah Firmansyah Firmansyah Yasin Fitri Muwardi Furizal Gusrin, Muhaimin Gustina, Sapriani Hafizh, Muhammad Nasir Haksono, Muhammad Rizky Hanif, Abdullah Hanif, Kharis Hudaiby Harman, Rika Helmiyah, Siti Hendril Satrian Purnama Herdiyanto, Erik Heri Wahyudi Herman Herman Herman Herman Herman Herman Herman Yuliansyah 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 Imroatul Khuluqi Izzah Indah Purnama Sari Irjayana, Rizky Caesar Irwansyah Irwansyah Itsnaini Irvina Khoirunnisa Izzan Julda D.E Purwadi Putra januari audrey Jayawarsa, A.A. Ketut Jody Yuantoro Jogo Samodro, Maulana Muhamammad Joko Supriyanto Joko Supriyanto Kamilah, Farhah Kartika Firdausy Khairul Nisa Panilestari Khoirunnisa, Itsnaini Irvina Kusuma, Nur Makkie Perdana Laura Sari Lelisa Army, Widya Lestari, Yuniarti Lin, Yu-Hao Luh Putu Ratna Sundari M. Nasir Hafizh Maftukhah, Ainin Maulana Muhammad Jogo Samudro Mhd. Basri Miftahul Rozak 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 Arief Sutisna Muhammad Faqih Dzulqarnain Muhammad Faqih Dzulqarnain, Muhammad Faqih Muhammad Johan Wahyudi Muhammad Kunta Biddinika Muhammad Ma’ruf Muhammad Nasir Hafizh Muhammad Noko Darpito Muhammad Nuh Muhammad Nur Faiz Muhammad Nurdin, Ilhamsyah Muhammad Rizki Setyawan Mukti, Sindhu Hari Munawaroh Munawaroh Muntiari, Novita Ranti Murinto Murinto - Murinto Murinto Murni Musliman, Anwar Siswanto Mustofa Mustofa Muthorihin, Bashor Fauzan Mutiara Titani Mutiara Titani Muwardi, Fitri Nandar Nandar Nasution, Dewi Sahara Nasution, Musri Iskandar Nilam Tri Astuti Nopi Hidayat Nurwijayanti Nuryasin, Ilyas Pahlevi, Ryan Fitrian Ponco Sukaswanto Poni Wijayanti Prabowo Soetadji Prabowo, Basit Adhi Prayogi, Denis Putra, Fajar R. B Putri Annisa Putri Annisa Putri Purnamasari Ramadhani, Muhammad Ramdhani, Rezki Razak, Farhan Radhiansyah Rezki Rezki Rifqi Rahmatika Az-Zahra Rizal Parghani Rizky Andhika Surya Rochmadi, Tri Rohmat Ibrahim Roni Anggara Putra Rosalina Rusydi Umar Rusydi Umar S Sunardi S, Sunardi Saad, Saleh Khalifah Safiq Rosad Saifudin Saifudin Saifullah, Shoffan Saleh khalifa saad Santi Purwaningrum Sarmini Sarmini Sarmini Sarmini Septa, Frandika Setyaputri, Khairina Eka Setyaputri, Khairina Eka Setyaputri, Khairina Eka Shinta Nur Desmia Sari Sri Winiarti Sri Winiarti Subandi, Rio Sugiyarto Surono Sugiyarto Surono Sukaswanto, Ponco Sukma Aji Sulis Triyanto Sunardi Sunardi Sunardi Sunardi Sunardi, Sunardi Surya Yeki Surya Yeki Syamsiar, Syamsiar Syarifudin, Arma Tole Sutikno Tresna Yudha Prawira Tri Ferga Prasetyo Tri Ferga Prasetyo Tri Rochmadi Tristanti, Novi Tuswanto Tuswanto Virdiana Sriviana Fatmawaty Wahju Tjahjo Saputro Wahyusari, Retno Winoto, Sakti Wulandari, Cisi Fitri Yana Mulyana Yana Mulyana Yanuar Wicaksono 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 Zuhri Halim Zulhijayanto -