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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 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 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 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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Human Skin Wrinkle Detection Using The Convolutional Neural Network Method Rohmat Ibrahim; Abdul Fadlil; Herman Herman
Jurnal Accounting Information System (AIMS) Vol. 9 No. 1 (2026)
Publisher : Ma'soem University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32627/aims.v9i1.1893

Abstract

Wrinkles are a visual indicator of skin aging and are widely used in dermatological and cosmetic assessments. However, automatic wrinkle detection from facial images remains challenging due to illumination variation, image noise, and subtle skin texture characteristics. This study applies a Convolutional Neural Network (CNN) for human skin wrinkle detection using image preprocessing techniques, including intensity normalization, Contrast Limited Adaptive Histogram Equalization (CLAHE), denoising, and sharpening. Experiments were conducted on 600 facial skin images obtained from publicly available sources and manually categorized into wrinkled and non-wrinkled classes. To ensure result reliability, the dataset was divided into training, validation, and testing sets using a 70:20:10 ratio. The experimental results show that the proposed approach achieved an accuracy of 0.9136, demonstrating consistent performance across validation and test sets.
Efficient Outlier Detection in Energy Analytics Using Isolation Forest and One Class SVM: A Comparative Study for Smart Grid Applications Dheni Apriantsani Budiman; Tole Sutikno; Abdul Fadlil
Jurnal Accounting Information System (AIMS) Vol. 9 No. 1 (2026)
Publisher : Ma'soem University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32627/aims.v9i1.1913

Abstract

Outlier detection is a critical task in informatics, particularly for analyzing large, complex datasets such as electrical energy consumption records. Identifying anomalies enables the recognition of abnormal usage patterns and potential non-technical losses, which are essential for ensuring reliability and efficiency in innovative grid systems. However, conventional supervised learning approaches are often unsuitable due to the unlabeled and imbalanced nature of real-world consumption data. To address the challenge of validating unsupervised models without ground truth, this study utilizes a controlled synthetic dataset with precise anomaly injection. This approach allows for a rigorous comparative evaluation of two widely adopted algorithms, Isolation Forest and One-Class Support Vector Machine (OC-SVM). The analysis examines detection accuracy, F1-score, and computational efficiency under identical experimental conditions. Results demonstrate that Isolation Forest consistently achieves superior performance, attaining a Detection Accuracy of 0.9948 and an F1-Score of 0.9478, significantly outperforming OC-SVM, which yielded an accuracy of 0.9521 and an F1-Score of only 0.5108. Furthermore, Isolation Forest proved to be exceptionally efficient, requiring only 0.9207 seconds for computation approximately 21 times faster than OC-SVM (19.9460 seconds). These advantages highlight its scalability and suitability for large-scale, near-real-time monitoring applications. Overall, the findings provide empirical evidence of Isolation Forest's effectiveness and offer practical guidance on algorithm selection for intelligent grid analytics
PERBANDINGAN CNN UNTUK DETEKSI PENYAKIT DAUN TANAMAN NEW PLANT DISEASES BERBASIS CLOUD COMPUTING Bambang Priambodo; Abdul Fadlil; 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.
Perbandingan Kinerja MobileNetV2 dan VGG16 dalam Klasifikasi Penyakit pada Citra Daun Tanaman Cabai Itsnaini Irvina Khoirunnisa; Abdul Fadlil; Herman Yuliansyah
JISKA (Jurnal Informatika Sunan Kalijaga) Vol. 11 No. 1 (2026): January 2026
Publisher : UIN Sunan Kalijaga Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14421/jiska.5075

Abstract

Chili peppers play a crucial role in the Indonesian economy, serving as a significant source of income for many farmers. Price fluctuations influenced by weather conditions make this crop vulnerable to diseases that can impact productivity. However, leaves are key indicators of plant health, revealing early disease symptoms before they spread. This research focuses on detecting diseases in chili plants using neural network architectures via transfer learning, specifically MobileNetV2 and VGG16, to classify chili leaf images. The study aims to identify three disease classes: begomovirus, leaf spots, and healthy leaves. The dataset comprises 3,150 leaf images, split into 70% for training and 30% for testing. Results show that MobileNetV2 achieved an accuracy of 99.47% and VGG16 98.62%, with evaluation using a confusion matrix indicating good performance in disease identification, where MobileNetV2 offers better computational efficiency. Thus, transfer learning can effectively identify leaf diseases in chili plants.
Penerapan Algoritma Random Forest Dan Support Vector Machine Untuk Deteksi Distributed Denial of Service (DDoS) Asep Ririh Riswaya; Abdul Fadlil; Anton Yudhana
Jurnal Pseudocode Vol 13 No 1 (2026): Volume 13 Nomor 1 Februari 2026
Publisher : UNIB Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33369/pseudocode.13.1.28-35

Abstract

Distributed Denial of Service (DDoS) attacks significantly threaten the availability of modern network services by overwhelming resources with malicious traffic. The increasing complexity of these attacks, including multi-vector and low-rate variants, reduces the effectiveness of traditional detection methods based on signatures and static rules. This study explores the effectiveness of Random Forest (RF) and Support Vector Machine (SVM) algorithms in detecting DDoS attacks using the CICDDoS2019 dataset, focusing on the impact of various decision threshold values on performance. The CICDDoS2019 dataset consists of 431,371 network traffic flows with 80 numerical features. Preprocessing involves eliminating null values, standardizing numerical attributes, and encoding labels into binary classifications of normal and DDoS traffic. The dataset is then divided into training and testing sets at a 70:30 ratio. Performance evaluation is done using a confusion matrix to calculate accuracy, precision, recall, and F1-score. Results show that both algorithms perform well, but Random Forest offers greater consistency, with a threshold of 0.5 achieving the best balance in metrics.
Perancangan Electronic Nose (E-Nose) untuk Analisis dan Klasifikasi Aroma Daging Menggunakan PCA dan LDA Muhammad Rizki Setyawan; Abdul Fadlil; Anton Yudhana
JITU Vol 10 No 1 (2026)
Publisher : Universitas Boyolali

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36596/jitu.v10i1.2254

Abstract

Meat is a vital food commodity prone to adulteration through species mixing or chemical contamination such as formalin and borax. This study aimed to design and test an Electronic Nose (E-Nose) system for aroma pattern analysis and meat classification using Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA). Samples included pure meat (beef, chicken, pork), mixed meat, and chemically contaminated meat. Aroma data were captured using an array of gas sensors sensitive to Volatile Organic Compounds (VOCs) and standardized prior to analysis. PCA reduced eight sensor features into three principal components explaining a total variance of 79.63%. PC1, PC2, and PC3 accounted for 46.10%, 20.58%, and 12.96% of variance, respectively, showing clustering patterns among samples with minor overlap. LDA provided clearer class separation with three discriminant components LD1, LD2, and LD3 explaining 77.13%, 16.63%, and 4.59% of between-class variance, totaling 98.34%. LD1 separated pure, mixed, and contaminated meat, LD2 distinguished variations due to contaminant type and species, and LD3 refined separation of similar classes. Classification evaluation achieved an overall accuracy of 82%. Most classes were well classified, while classes 1 and 10 experienced misclassification due to similar aroma patterns. The findings confirm that E-Nose combined with PCA and LDA is a rapid, non-destructive, and efficient method for detecting meat authenticity and adulteration, showing strong potential for food quality monitoring in the field
USER ACCEPTANCE TESTING MELALUI EVALUASI BLACKBOX DAN ISO 9241-11 TERHADAP APLIKASI KESEHATAN MOBILE: MAHATI Ahmad Naufal; Ilyas Nuryasin; Bashor Fauzan Muthohirin; Mutiara Titani; Akrom Akrom; Abdul Fadlil
JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Vol 10, No 4 (2025)
Publisher : STKIP PGRI Tulungagung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29100/jipi.v10i4.7377

Abstract

Penelitian ini bertujuan untuk mengevaluasi kualitas dan tingkat penerimaan pengguna terhadap aplikasi kesehatan mobile MAHATI, yang dirancang untuk mendukung pengelolaan hipertensi melalui fitur pemantauan tekanan darah, pengingat obat, dan edukasi kesehatan. Evaluasi dilakukan dengan metode Blackbox Testing menggunakan pendekatan State Transition Testing untuk memverifikasi fungsionalitas aplikasi, serta User Acceptance Testing (UAT) berdasarkan standar ISO 9241-11 untuk menilai efektivitas, efisiensi, dan kepuasan pengguna. Hasil pengujian Blackbox Testing menunjukkan 91% fungsi aplikasi berjalan dengan baik, dengan 73 dari 80 test case dinyatakan berhasil. UAT yang melibatkan 62 responden menghasilkan penilaian sangat baik, dengan efektivitas sebesar 84,90%, efisiensi 88,12%, dan kepuasan pengguna 85,80%. Meskipun aplikasi secara umum telah memenuhi kebutuhan fungsional dan aspek usability, perbaikan tetap diperlukan untuk meningkatkan pengalaman pengguna dan menangani skenario pengujian yang gagal. Penelitian ini memberikan kontribusi penting dalam meningkatkan kualitas aplikasi kesehatan digital melalui pendekatan evaluasi yang komprehensif.
PENGEMBANGAN APLIKASI MOBILE MAHATI MENGGUNAKAN GENERATIF AI UNTUK PASIEN HIPERTENSI Jody Yuantoro; Ilyas Nuryasin; Bashor Fauzan Muthohirin; Mutiara Titani; Akrom Akrom; Abdul Fadlil
JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Vol 10, No 4 (2025)
Publisher : STKIP PGRI Tulungagung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29100/jipi.v10i4.7009

Abstract

Penelitian ini mengembangkan sebuah aplikasi seluler yang memanfaatkan AI Generatif untuk menyederhanakan pencatatan dan evaluasi tekanan darah bagi pasien hipertensi. Tujuannya adalah untuk menciptakan alat yang mudah diakses dan akurat untuk memantau tekanan darah. Aplikasi ini dirancang untuk menangkap pembacaan tekanan darah dari gambar sfigmomanometer aneroid digital yang diambil dengan kamera ponsel pintar. AI Generatif dengan model gemini-1.5-flash, yang diimplementasikan dengan teknik prompting spesifik untuk mengekstrak informasi sistolik, diastolik, dan denyut nadi dari gambar sfigmomanometer aneroid digital secara otomatis. Hasil dari penelitian ini adalah aplikasi seluler fungsional yang menggabungkan fitur-fitur seperti entri data otomatis, visualisasi data melalui time-series dan scatter plot, klasifikasi tekanan darah berdasarkan pedoman ACC/AHA 2017, pengingat pengobatan, dan sumber daya edukasi tentang manajemen hipertensi dan hasil pengujian fitur tekanan darah dengan metode blackbox dan System Usability Scale (SUS) menunjukkan aplikasi berfungsi sesuai tujuan dan memenuhi kriteria fungsional.
Penguatan Kompetensi Digital Guru melalui Pelatihan Perancangan Game Edukasi Berbasis Scratch di SMPN 1 Teluk Mengkudu Mhd. Basri; Indah Purnama Sari; Andi Zulherry; Imam Riadi; Abdul Fadlil
Wahana Jurnal Pengabdian kepada Masyarakat Vol. 5 No. 1 (2026): Edisi Juni
Publisher : Ilmu Bersama Center

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56211/wahana.v5i1.1958

Abstract

Perkembangan teknologi informasi menuntut guru untuk memiliki kompetensi digital yang memadai, khususnya dalam merancang media pembelajaran yang interaktif dan menarik bagi peserta didik generasi Z. Namun, sebagian besar guru SMP masih mengalami keterbatasan dalam memanfaatkan aplikasi pemrograman visual untuk mengembangkan media pembelajaran berbasis permainan (game edukasi). Kegiatan pengabdian ini bertujuan untuk meningkatkan kompetensi digital guru-guru SMP Negeri 1 Teluk Mengkudu melalui pelatihan perancangan game edukasi berbasis Scratch. Metode pelaksanaan menggunakan pendekatan workshop dan hands-on training yang melibatkan 37 guru dari berbagai mata pelajaran. Kegiatan diawali dengan pre-test untuk mengukur kemampuan awal peserta terkait pemanfaatan Scratch dan pemahaman dasar pemrograman visual, dilanjutkan dengan pelatihan intensif selama dua hari yang mencakup penyampaian materi, demonstrasi, dan praktik langsung pembuatan game edukasi, kemudian diakhiri dengan post-test untuk mengukur peningkatan kompetensi peserta. Hasil pre-test menunjukkan nilai rata-rata sebesar 5,95, yang mengindikasikan bahwa sebagian besar guru belum familiar dengan pembuatan media pembelajaran interaktif berbasis Scratch. Setelah mengikuti pelatihan, hasil post-test menunjukkan peningkatan nilai rata-rata menjadi 9,50, atau terjadi peningkatan signifikan sebesar 3,55 poin dibandingkan sebelum pelatihan. Peningkatan tersebut menunjukkan bahwa pelatihan berbasis Scratch efektif dalam meningkatkan pemahaman dan keterampilan guru dalam merancang media pembelajaran interaktif berbasis game edukasi. Kegiatan ini diharapkan dapat menjadi model pelatihan berkelanjutan guna mendukung penguatan kompetensi digital guru serta transformasi pembelajaran berbasis teknologi di tingkat sekolah menengah pertama.
ANALISIS DETEKSI TINGKAT STRES BERBASIS PERILAKU DIGITAL MENGGUNAKAN MODEL ARTIFICIAL NEURAL NETWORK Munawaroh Munawaroh; Abdul Fadlil; Imam Riadi
JURNAL INFORMATIKA DAN KOMPUTER Vol 10, No 2 (2026): Juni 2026
Publisher : Lembaga Penelitian dan Pengabdian Masyarakat - Universitas Teknologi Digital Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26798/jiko.v10i2.2722

Abstract

This study aims to analyze the capability of an Artificial Neural Network (ANN) model in detecting stress levels based on digital behavioral data. The dataset comprises 3,685 Indonesian respondents represented through six digital behavior variables (X1–X6) covering smartphone and social media usage patterns, and six psychological stress symptom variables (S1–S6) based on an adapted PSS-10. A Multilayer Perceptron (MLP) was trained using a two-stage experimental design: Stage 1 using only X1–X6, Stage 2 integrating X1–X6 and S1–S6. Evaluation involved 27 parameter combinations per stage. Results show Stage 1 failed with mean accuracy 77.34% (Macro F1=0.29) due to insufficient discriminative signal, while Stage 2 succeeded with peak accuracy 98.10% and Macro F1=0.97 at optimal configuration (80:20 split, k=8, hidden=16). The +18.16% improvement quantifies the mediation role of psychological variables in the transactional stress model.
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 Andrianto, Fiki 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 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 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 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 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 Rizky Andhika Surya Rochmadi, Tri Rohmat Ibrahim 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 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 Zulhijayanto -