Article Per Year (5 Year)
p-Index From 2021 - 2026
14.689
P-Index
This Author published in this journals
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 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 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 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) JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) 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 International Journal of Marine Engineering Innovation and Research Edunesia : jurnal Ilmiah Pendidikan 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) 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) Jurnal Algoritma Techno Jurnal Pengabdian Informatika (JUPITA) 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 Signal and Image Processing Letters Scientific Journal of Engineering Research SEMINAR TEKNOLOGI MAJALENGKA (STIMA) Edumaspul: Jurnal Pendidikan Methods in Science and Technology Studies JOCHAC
Abdul Fadlil
Ahmad Dahlan University
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 Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Neuroscience Physics Public Health Social Sciences Transportation Other

Published : 216 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 216 Documents
Search

 18   19   20   21   22 
KERANGKA DASAR JOINT FUSION MULTI-MODAL ARTIFICIAL INTERNET OF THINGS UNTUK PERTANIAN HORTIKULTURA Prasetyo, Tri Ferga; Sunardi; Fadlil, Abdul
SEMINAR TEKNOLOGI MAJALENGKA (STIMA) Vol 9 (2025): Seminar Teknologi Majalengka (STIMA) 9.0 Tahun 2025
Publisher : Universitas Majalengka

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

Abstract

This paper proposes a joint-fusion multi-modal Artificial Intelligence of Things (AIoT) framework for precision horticulture on chili and tomato. We fuse time-series IoT signals (air/leaf temperature, humidity, soil moisture, pH, EC, PAR) with RGB/multispectral images of leaves, fruits, and canopy via an attention-based shared representation. In a 500 m² field trial in Majalengka with >5,000 labeled images and synchronized IoT streams (10-minute interval), our model outperforms single-modal baselines. For chili leaf disease detection, joint fusion reaches 90.0% accuracy (IoT-only 72.0%, vision-only 81.0%). For tomato maturity classification, it achieves 92.0% accuracy (IoT-only 68.0%, vision-only 84.0%). For yield estimation, the multi-modal regressor attains R² = 0.89. We detail data synchronization, train/validation/test splits, baseline configurations (IoT-LSTM, CNN/ViT, early/late fusion), and deployment on an edge-cloud pipeline. The results indicate that modeling cross-modal interactions improves robustness and decision support for irrigation, fertilization, and harvest scheduling. We conclude with ablation analyses and practical implications for Indonesian precision agriculture.
Empowering Teachers in Muhammadiyah Boarding School Yogyakarta toward Safer Digital Behavior through Smartphone Security Education Rakhmadi, Aris; Wintolo, Hero; Putri Silmina, Esi; Soyusiawaty, Dewi; Sunardi; Fadlil, Abdul
JURPIKAT (Jurnal Pengabdian Kepada Masyarakat) Vol. 6 No. 4 (2025)
Publisher : Politeknik Piksi Ganesha Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37339/jurpikat.v6i4.2843

Abstract

Abstract: This community-service program was implemented through the Program Pemberdayaan Umat (PRODAMAT) of Universitas Ahmad Dahlan with the aim of enhancing digital literacy and cybersecurity awareness among teachers at Muhammadiyah Boarding School (MBS) Yogyakarta. The activity focused on smartphone account security education through practical steps such as password management, two-factor authentication (2FA), and phishing awareness. A participatory approach was applied through training involving 15 teachers and staff, combining interactive discussions, demonstrations, and pretest–posttest evaluation. The results showed an increase in the average knowledge score from 4.63 to 4.90, digital awareness from 4.05 to 4.45, and intention and safe digital behavior from 4.35 to 4.73. These improvements reflect positive changes in participants’ understanding, awareness, and behavior toward digital security. The program highlights the importance of integrating technological skills with ethical and religious values to promote sustainable digital empowerment in Islamic educational environments.
Aplikasi Mobile Native untuk Digital Cockpit pada Sistem Human Digital Twin Zein, Wahid Alfaridsi Achmad; Fadlil, Abdul; herman; Kunta Biddinika, Muhammad; Yulianto, Dinan
Jurnal Algoritma Vol 22 No 2 (2025): Jurnal Algoritma
Publisher : Institut Teknologi Garut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33364/algoritma/v.22-2.2206

Abstract

Teknologi Human Digital Twin telah membuka peluang baru dalamoptimalisasi sistem Digital Cockpit, terutama dalam pemantauankesehatan pengguna. Urgensi penelitian ini didorong oleh tingginyaangka kematian akibat penyakit kardiovaskular di Asia Tenggara,khususnya di Indonesia, yang menempati posisi kedua. Penelitian inibertujuan untuk mengembangkan dan mengintegrasikan teknologiHuman Digital Twin ke dalam Digital Cockpit, memungkinkanpemantauan kondisi kesehatan secara real-time melalui sensor yangtertanam dalam perangkat wearable. Data kesehatan yang diperoleh,diproses dan divisualisasikan dalam antarmuka interaktif yangdirancang dengan pendekatan low-fidelity wireframe menggunakanFigma, sehingga memudahkan pengguna dalam memahamiinformasi yang disajikan. Aplikasi diuji menggunakan metode BlackBox Testing untuk memastikan bahwa setiap fitur berfungsi sesuaidengan yang diharapkan tanpa memerlukan akses langsung ke kodeprogram. Selain itu, pengujian dilakukan dalam lingkungan simulasiuntuk mengevaluasi pengalaman pengguna serta efektivitas sistemdalam menyajikan informasi kesehatan. Hasil pengujianmenunjukkan bahwa sistem dapat beroperasi dengan baik sesuaidengan skenario yang dirancang, dengan antarmuka yang intuitif danresponsif terhadap interaksi pengguna. Penelitian ini berkontribusidalam bidang Teknologi Informasi dan Rekayasa Perangkat Lunakdengan menghadirkan solusi berbasis Human Digital Twin untukDigital Cockpit. Untuk pengembangan lebih lanjut, disarankaneksplorasi fitur prediktif berbasis kecerdasan buatan sertaoptimalisasi sistem agar dapat beradaptasi dengan berbagaiperangkat dan kebutuhan pengguna yang lebih luas.
Baseline Evaluation of Backpropagation Artificial Neural Network for Visual Image-Based Vehicle Type Classification Harman, Rika; Riadi, Imam; Fadlil, Abdul
Compiler Vol 14, No 2 (2025): November
Publisher : Institut Teknologi Dirgantara Adisutjipto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28989/compiler.v14i2.3210

Abstract

The increasing number of vehicles in urban areas requires technology-based solutions for efficient transportation management. This study proposes a vehicle classification model using Artificial Neural Networks (ANN) with the backpropagation algorithm, based on digital image data. The model is a feedforward neural network comprising an input layer, a hidden layer with 64 sigmoid-activated neurons, and an output layer with 7 softmax-activated neurons. The dataset, sourced from Roboflow Inc., consists of 16,185 images across eight vehicle classes: Hummer, Toyota Innova, Hyundai Creta, Suzuki Swift, Audi, Mahindra Scorpio, Rolls Royce, and Tata Safari. The data is split 80:20 for training and testing. Input features include vehicle dimensions, dominant RGB color, number of axles, and license plate detection. The model is trained using gradient descent and categorical crossentropy loss. Evaluation results show 85% validation accuracy at epoch 28 and 100% test accuracy. Precision, recall, and F1-score indicate strong performance, though minor errors occur in visually similar classes. These findings demonstrate that backpropagation-based ANN is effective for vehicle classification and can be applied in systems such as automatic parking and traffic monitoring
Developing a Delphi Validated Instrument for Assessing Digital Forensics Readiness Based on COBIT 2019 Rochmadi, Tri; Fadlil, Abdul; Riadi, Imam
International Journal of Advances in Data and Information Systems Vol. 6 No. 3 (2025): December 2025 - International Journal of Advances in Data and Information Syste
Publisher : Indonesian Scientific Journal

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59395/ijadis.v6i3.1453

Abstract

The increasing complexcity of cyber threats has reinforced the need for robust digital forensic readiness in higher education institutions. However, existing frameworks often lack integration between forensic capabilities and IT governance practices. Objective: This study aims to develop and validate a new instrument to assess digital forensic readiness based on the COBIT 2019 framework. Methods: A three-round Delphi process was conducted with seven digital forensics and IT governance experts to develop and validate a new instrument comprising forty proposed indicators across six domains. Result : The instrument achieved full context, with  I-CVI values increasing from 0.60 to 0.99 and IQR values reaching  1.00 across all items. Implications: The validated instrument integrates governance and forensic principles, providing a standardized tool for institutional self-assessment and policy development, while contributing methodologically through the use of a structured Delphi validation process.
PERBANDINGAN CNN UNTUK DETEKSI PENYAKIT DAUN TANAMAN NEW PLANT DISEASES BERBASIS CLOUD COMPUTING Priambodo, Bambang; Fadlil, Abdul; Sunardi
Jurnal Informatika Teknologi dan Sains (Jinteks) Vol 7 No 4 (2025): EDISI 26
Publisher : Program Studi Informatika Universitas Teknologi Sumbawa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51401/jinteks.v7i4.6782

Abstract

Penyakit tanaman merupakan ancaman serius bagi ketahanan pangan global, sehingga deteksi dini yang akurat penting untuk meminimalkan kerugian panen. Perkembangan Convolutional Neural Networks (CNN) memungkinkan klasifikasi penyakit daun dengan akurasi tinggi, namun keterbatasan komputasi sering menghambat, terutama di negara berkembang. Untuk itu, dibutuhkan arsitektur CNN ringan namun andal yang dapat diimplementasikan pada cloud platform (CP) dengan sumber daya terbatas. Penelitian ini membandingkan tiga arsitektur CNN—MobileNetV3-Small, EfficientNetB0, dan ResNet-50—dengan pendekatan transfer learning dua tahap menggunakan teknik unfreeze-layer. Dataset yang digunakan adalah New Plant Diseases yang mencakup 85.486 citra dari 38 kelas dan 14 spesies dengan rasio 82:13:5. Eksperimen dilakukan pada cloud platform menggunakan pipeline replikatif dengan konfigurasi hyperparameter dan callback seragam. Hasil menunjukkan ResNet-50 meraih akurasi uji tertinggi (99,34%), MobileNetV3-Small sesuai untuk keterbatasan ekstrem (97,16%) namun memilik  9 kelas dengan performa di bawah 95%, sedangkan EfficientNetB0 menawarkan keseimbangan (98,92%) dengan hanya satu kelas bermasalah. Ini konsisten dengan studi sebelumnya yang mengadaptasi EfficientNetB0 (98,4%) serta variannya dengan Focal Loss (99,72%) dan ResNet-50 (95,1%) dengan subset New Plant Diseases 10 kelas dengan rasio 80:20. Temuan ini menegaskan trade-off akurasi–efisiensi lebih nyata, sekaligus memberi rekomendasi praktis pemilihan arsitektur CNN untuk sistem deteksi penyakit tanaman berbasis komputasi terbatas di negara berkembang.
Identification of Learning Javanese Script Handwriting Using Histogram Chain Code Arif Budiman; Abdul Fadlil; Rusydi Umar
Edumaspul: Jurnal Pendidikan Vol 7 No 1 (2023): Edumaspul: Jurnal Pendidikan
Publisher : Universitas Muhammadiyah Enrekang

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

Abstract

One of the wealth of the Indonesian nation is the many tribes with their own languages and scripts. One of the scripts that has existed since long before the independence of the State of Indonesia is the Javanese script, with the use of Latin script used by almost every aspect of life, both official official activities and daily use, the use of traditional scripts, especially Javanese script, is increasingly scarce. To facilitate learning the Javanese script, learning media is needed with the ability to recognize Javanese characters. In this study, pre-processing was used, especially feature extraction using the Histogram Chain Code (HCC) method and classification using artificial neural networks using the Multi Layer Perceptron method. This study compares four research models by setting the number of HCC feature extraction parameters obtained from one intact image and 3 divided images of 4, 9 and 16 parts respectively so that the total parameters of each HCC model are 8, 32, 72 and 128 parameters characteristic. The training and testing process using the Multi Layer Perceptron method uses 2000 handwritten Javanese script image data which is divided into 80%, namely 1600 images for the training process and 400 images for the testing process. This research resulted in different accuracies, namely 57%, 78%, 83% and 76%. The best accuracy is obtained from the HCC model with 72 parameters and the image is divided into 9 sections.
Integration of Zachman Framework and TOGAF ADM on Academic Information Systems Modeling Fadlil, Abdul; Riadi, Imam; Basir, Azhar
INTENSIF: Jurnal Ilmiah Penelitian dan Penerapan Teknologi Sistem Informasi Vol 5 No 1 (2021): February 2021
Publisher : Universitas Nusantara PGRI Kediri

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1952.179 KB) | DOI: 10.29407/intensif.v5i1.14678

Abstract

Zachman Framework (ZF) and The Open Group Architecture Framework (TOGAF) are Architecture Frameworks often used in Architecture Enterprise's implementation. Each side of the two architecture Frameworks has advantages and disadvantages. Sekolah Tinggi Manajemen Informatika dan Komputer Muhammadiyah Paguyangan Brebes (STMIK MPB) is a new university established on April 28, 2017; STMIK MPB as a new university has no plans in building an information system. The research will select the parts that exist in the ZF and TOGAF methodologies. The two methods will be combined and compiled to be applied to the Academic Information System modeling or blended methods. These research results are architectural blueprints that can be used as a reference in the development of academic information systems.
Similarity Identification Based on Word Trigrams Using Exact String Matching Algorithms Fadlil, Abdul; Sunardi, Sunardi; Ramdhani, Rezki
INTENSIF: Jurnal Ilmiah Penelitian dan Penerapan Teknologi Sistem Informasi Vol 6 No 2 (2022): August 2022
Publisher : Universitas Nusantara PGRI Kediri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29407/intensif.v6i2.18141

Abstract

Several studies regarding excellent exact string matching algorithms can be used to identify similarity, including the Rabin-Karp, Winnowing, and Horspool Boyer-Moore algorithms. In determining similarities, the Rabin-Karp and Winnowing algorithms use fingerprints, while the Horspool Boyer-Moore algorithm uses a bad-character table. However, previous research focused on identifying similarities using these algorithms based on character n-gram. In contrast, identification based on the word n-gram to determine the similarity based on its linguistic meaning, especially for longer strings, had not been covered yet. Therefore, a word-level trigram was proposed to identify similarities based on the word trigrams using the three algorithms and compare each performance. Based on precision, recall, and running time comparison, the Rabin-Karp algorithm results were 100%, 100%, and 0.19 ms, respectively; the Winnowing algorithm results with the smallest window were 100%, 56%, and 0.18 ms, respectively; and the Horspool algorithm results were 100%, 100%, and 0.06 ms. From these results, it can be concluded that the performance of the Horspool Boyer-Moore algorithm is better in terms of precision, recall, and running time.
Comparing Data Mining Classification for Online Fraud Victim Profile in Indonesia Sunardi, Sunardi; Fadlil, Abdul; Kusuma, Nur Makkie Perdana
INTENSIF: Jurnal Ilmiah Penelitian dan Penerapan Teknologi Sistem Informasi Vol 7 No 1 (2023): February 2023
Publisher : Universitas Nusantara PGRI Kediri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29407/intensif.v7i1.18283

Abstract

Classification is one of the most often employed data mining techniques. It focuses on developing a classification model or function, also known as a classifier, and predicting the class of objects whose class label is unknown. Categorizing applications include pattern recognition, medical diagnosis, identifying weaknesses in organizational systems, and classifying changes in the financial markets. The objectives of this study are to develop a profile of a victim of online fraud and to contrast the approaches frequently used in data mining for classification based on Accuracy, Classification Error, Precision, and Recall. The survey was conducted using Google Forms, which is an online platform. Naive Bayes, Decision Tree, and Random Forest algorithms are popular models for classification in data mining. Based on the sociodemographics of Indonesia's online crime victims, these models are used to classify and predict. The result shows that Naïve Bayes and Decision Tree are slightly superior to the Random Forest Model. Naive Bayes and Decision Tree have an accuracy value of 77.3%, while Random Forest values 76.8%.
Co-Authors Aang Anwarudin Abdul Azis Achmad Nugrahantoro Aditiya Dwi Candra Ahmad Naufal, Ahmad Ahmat Taufik Aji Pamungkas Akrom, Akrom Alfiansyah Imanda Putra Alfiansyah Imanda Putra Alfian Amiruddin, Nanda Fahmi Andrianto, Fiki Anggit Pamungkas Annisa, Putri Anton Yudhana Anwar Siswanto ANWAR, FAHMI ardi, Ardi Pujiyanta Arief Setyo Nugroho Arief Setyo Nugroho Arif Budi Setianto Arif Budiman Arif Budiman Arif Wirawan Muhammad Aris Rakhmadi Asep Ririh Riswaya Asno Azzawagama Firdaus Atmojo, Dimas Murtia Aulia, Aulia Az-Zahra, Rifqi Rahmatika Aznar Abdillah, Muhamad Bagus Primantoro Bashor Fauzan Muthohirin Basir, Azhar Budiman, Dheni Apriantsani Candra, Aditiya Dwi Darajat, Muhammad Nashiruddin Davito Rasendriya Rizqullah Putra Dewi Soyusiawaty 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 Budi Cahyono 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 Haksono, Muhammad Rizky 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 Ibrahim, Rohmat 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 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 Mukti, Sindhu Hari Muntiari, Novita Ranti Murinto Murinto - Murinto Murinto Murni Murni Musliman, Anwar Siswanto Mustofa Mustofa Muthorihin, Bashor Fauzan Mutiara Titani Muwardi, Fitri Nasution, Dewi Sahara Nasution, Musri Iskandar Nilam Tri Astuti Nurwijayanti Pahlevi, Ryan Fitrian Ponco Sukaswanto Poni Wijayanti Prabowo Soetadji 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 Siswahyudianto Siti Helmiyah Sri Winiarti 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 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 Yuantoro, Jody Yulianto, Dinan Yulianto, Muhammad Anas Yuminah yuminah yuminah, Yuminah Yuminah, Yuminah Yuwono Fitri Widodo Zein, Wahid Alfaridsi Achmad Zulhijayanto -