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All Journal International Journal of Electrical and Computer Engineering ComEngApp : Computer Engineering and Applications Journal JURNAL SISTEM INFORMASI BISNIS JTEV (Jurnal Teknik Elektro dan Vokasional Techno.Com: Jurnal Teknologi Informasi Jurnal Buana Informatika TELKOMNIKA (Telecommunication Computing Electronics and Control) Jurnal Informatika Jurnal Sarjana Teknik Informatika Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI) Prosiding Seminar Nasional Sains Dan Teknologi Fakultas Teknik Jurnal Teknik Elektro PIKSEL : Penelitian Ilmu Komputer Sistem Embedded and Logic CommIT (Communication & Information Technology) Jurnal Ilmiah Kursor Jurnal Informatika Jurnal Teknologi Informasi dan Ilmu Komputer Telematika Jurnal Edukasi dan Penelitian Informatika (JEPIN) JUITA : Jurnal Informatika Scientific Journal of Informatics Seminar Nasional Informatika (SEMNASIF) ELINVO (Electronics, Informatics, and Vocational Education) Annual Research Seminar INFORMAL: Informatics Journal Khazanah Informatika: Jurnal Ilmu Komputer dan Informatika Register: Jurnal Ilmiah Teknologi Sistem Informasi Proceeding of the Electrical Engineering Computer Science and Informatics Edu Komputika Journal Format : Jurnal Imiah Teknik Informatika Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) International Journal of Artificial Intelligence Research RABIT: Jurnal Teknologi dan Sistem Informasi Univrab SISFOTENIKA Journal of Information Technology and Computer Science (JOINTECS) JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING INTENSIF: Jurnal Ilmiah Penelitian dan Penerapan Teknologi Sistem Informasi JIKO (Jurnal Informatika dan Komputer) AKSIOLOGIYA : Jurnal Pengabdian Kepada Masyarakat JURNAL MEDIA INFORMATIKA BUDIDARMA JIEET (Journal of Information Engineering and Educational Technology) Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control CogITo Smart Journal IT JOURNAL RESEARCH AND DEVELOPMENT Insect (Informatics and Security) : Jurnal Teknik Informatika JITK (Jurnal Ilmu Pengetahuan dan Komputer) JOURNAL OF APPLIED INFORMATICS AND COMPUTING JURNAL REKAYASA TEKNOLOGI INFORMASI Abdimas Dewantara PROCESSOR Jurnal Ilmiah Sistem Informasi, Teknologi Informasi dan Sistem Komputer JURNAL TEKNIK INFORMATIKA DAN SISTEM INFORMASI JURNAL INSTEK (Informatika Sains dan Teknologi) ILKOM Jurnal Ilmiah Compiler Jiko (Jurnal Informatika dan komputer) MATRIK : Jurnal Manajemen, Teknik Informatika, dan Rekayasa Komputer JSiI (Jurnal Sistem Informasi) CYBERNETICS Digital Zone: Jurnal Teknologi Informasi dan Komunikasi IJID (International Journal on Informatics for Development) J-SAKTI (Jurnal Sains Komputer dan Informatika) JURIKOM (Jurnal Riset Komputer) Komputasi: Jurnal Ilmiah Ilmu Komputer dan Matematika JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Abdimas Umtas : Jurnal Pengabdian kepada Masyarakat EDUMATIC: Jurnal Pendidikan Informatika Building of Informatics, Technology and Science Jurnal Mantik NUKHBATUL 'ULUM : Jurnal Bidang Kajian Islam Jutisi: Jurnal Ilmiah Teknik Informatika dan Sistem Informasi JISKa (Jurnal Informatika Sunan Kalijaga) Buletin Ilmiah Sarjana Teknik Elektro Indonesian Journal of Business Intelligence (IJUBI) Mobile and Forensics Aviation Electronics, Information Technology, Telecommunications, Electricals, Controls (AVITEC) Jurnal Pengabdian Masyarakat Bumi Raflesia Cyber Security dan Forensik Digital (CSFD) Jurnal Abdi Insani JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) Journal of Computer System and Informatics (JoSYC) International Journal of Advances in Data and Information Systems Journal of Innovation Information Technology and Application (JINITA) Journal of Education Informatic Technology and Science Jurnal Bumigora Information Technology (BITe) Infotech: Journal of Technology Information Jurnal Teknologi Informatika dan Komputer SKANIKA: Sistem Komputer dan Teknik Informatika Jurnal Pengabdian kepada Masyarakat Nusantara Jurnal REKSA: Rekayasa Keuangan, Syariah dan Audit Jurnal Teknik Informatika (JUTIF) Jurnal FASILKOM (teknologi inFormASi dan ILmu KOMputer) Jurnal Computer Science and Information Technology (CoSciTech) Phasti: Jurnal Teknik Informatika Politeknik Hasnur Jurnal Pengabdian Masyarakat Indonesia EDUTECH : Jurnal Inovasi Pendidikan Berbantuan Teknologi J-SAKTI (Jurnal Sains Komputer dan Informatika) Decode: Jurnal Pendidikan Teknologi Informasi Jurnal Saintekom : Sains, Teknologi, Komputer dan Manajemen Jurnal Informatika Teknologi dan Sains (Jinteks) Techno Lambda: Jurnal Ilmiah Pendidikan MIPA dan Aplikasinya Engineering Science Letter Journal of Novel Engineering Science and Technology Jurnal Informatika: Jurnal Pengembangan IT Jurnal Software Engineering and Computational Intelligence Mohuyula : Jurnal Pengabdian Kepada Masyarakat Scientific Journal of Informatics Khazanah Informatika : Jurnal Ilmu Komputer dan Informatika JOCHAC
Imam Riadi
Department Of Information Systems - Universitas Ahmad Dahlan
Religion Aerospace Engineering Agriculture, Biological Sciences & Forestry Arts Humanities Automotive Engineering Chemical Engineering, Chemistry & Bioengineering 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 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 Other

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IMPLEMENTATION OF RANDOM FOREST FOR ANIMAL PROTEIN CLASSIFICATION THROUGH HYPERPARAMETER OPTIMIZATION Ikhram, Ridho; Yudhana, Anton; Riadi, Imam
JITK (Jurnal Ilmu Pengetahuan dan Teknologi Komputer) Vol. 11 No. 3 (2026): JITK Issue February 2026
Publisher : LPPM Nusa Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33480/jitk.v11i3.7613

Abstract

Accurate identification of animal protein types is crucial to ensure food authenticity and safety, particularly in the context of compliance with halal principles. This study aims to implement the Random Forest (RF) algorithm to classify four types of animal protein—broiler chicken, free-range chicken, pork, and beef through hyperparameter optimization using GridSearchCV. The dataset was evaluated using 5-fold cross-validation, and feature importance analysis was conducted to identify the variables that contributed most to classification. Results showed that RF with optimized hyperparameters achieved a test accuracy of 92.81%, with macro-average precision, recall, and F1-score of 93%. The model performed best for the broiler chicken and pork classes, while the beef class exhibited a higher misclassification rate, likely due to the similarity of spectral characteristics among classes. ODOR, CO₂, H₂, NH₃, and VOC were identified as the key indicators for distinguishing animal protein types. This study contributes to halal authentication by integrating FTIR spectral data with optimized Random Forest, enabling efficient and accurate classification. Although RF proved reliable and capable of handling high-dimensional data, the study is limited by dataset size and spectral feature complexity. Future research is recommended to explore deep learning architectures, such as Convolutional Neural Networks (CNN), with larger FTIR datasets to improve model generalization and robustness
Analisis Efektivitas Pelatihan Kecerdasan Artifisial untuk Peningkatan Kompetensi Guru dalam Pengembangan Media Kreatif Sutikno, Tole; Ayuningtyas, Astika; Riadi, Imam; Winiarti, Sri; Rochmadi, Tri; Rosad, Safiq
Jurnal Pengabdian kepada Masyarakat Nusantara Vol. 6 No. 4 (2025): Edisi Oktober - Desember
Publisher : Lembaga Dongan Dosen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55338/jpkmn.v6i4.7546

Abstract

Kegiatan pengabdian kepada masyarakat ini bertujuan menganalisis efektivitas pelatihan pemanfaatan teknologi kecerdasan buatan (Artificial Intelligence/AI) dalam meningkatkan kompetensi guru, khususnya dalam pengembangan media pembelajaran kreatif. Pelatihan dilaksanakan di SMA Negeri 7 Yogyakarta dengan melibatkan guru-guru dalaliterasiemaparan teori dan praktik langsung menggunakan berbagai platform AI, seperti ChatGPT, Canva AI, serta generator gambar dan video berbasis AI. Evaluasi dilakukan melalui pre-test dan post-test untuk mengukur perubahan kemampuan peserta sebelum dan sesudah pelatihan. Hasil analisis menunjukkan peningkatan rata-rata skor dari 5,95 menjadi 9,50, yang menandakan adanya peningkatan signifikan pada aspek pengetahuan, keterampilan, dan sikap guru dalam menerapkan AI. Guru mampu menghasilkan media pembelajaran digital yang lebih interaktif dan relevan dengan kebutuhan siswa. Temuan ini menunjukkan bahwa pelatihan AI berperan penting dalam meningkatkan literasi teknologi guru sekaligus mendukung transformasi digital di lingkungan pendidikan menengah.
Hybrid LSTM Forecasting Framework with Mutual Information and PSO–GWO Optimization for Short-Term SARS-CoV-2 Prediction in Indonesia Nastiti, Faulinda Ely; Musa, Shahrulniza; Riadi, Imam
Jurnal Teknik Informatika (Jutif) Vol. 7 No. 1 (2026): JUTIF Volume 7, Number 1, February 2026
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2026.7.1.5485

Abstract

SARS-CoV-2 remains an endemic challenge in Indonesia, requiring reliable short-term forecasting tools that support informatics, digital epidemiology, and data-driven public health systems. Standard LSTM models, while widely used for epidemic forecasting, face notable limitations such as sensitivity to poor weight initialization, and reduced ability to capture interactions within heterogeneous high-dimensional data—resulting in inconsistent performance. This research introduces ADELMI (Adaptive Deep Learning Metaheuristic Intelligence), a unified hybrid forecasting framework specifically designed not only to enhance forecasting accuracy but also to overcome core weaknesses of traditional LSTM architectures when applied to complex epidemic datasets. ADELMI integrates Mutual Information and Pearson Correlation for dual feature selection with a hybrid Particle Swarm–Grey Wolf Optimization (PSO–GWO) approach for optimizing LSTM parameters. The dataset includes 657 daily observations and 82 epidemiological, vaccination, and meteorological variables sourced from the Ministry of Health and BMKG (2020–2021). Feature selection reduced the dataset to 20 relevant predictors for recovery and death and one dominant predictor for positive cases. The optimized 50-unit LSTM with early stopping achieved highly accurate 7-day forecasts, producing MAPE scores of 0.01% (positive cases), 1.44% (recoveries), and 3.00% (deaths) across 5-fold cross-validation. These results significantly outperform ARIMA, SIR, and baseline LSTM models. By unifying dual feature selection with hybrid PSO–GWO optimization, ADELMI improves LSTM stability, weight initialization, and multivariate interaction modeling, delivering more reliable forecasts across heterogeneous datasets. This advancement strengthens informatics through DL-metaheuristic multivariate epidemic modeling and enables proactive, adaptive surveillance against evolving threats such as influenza hybrids.
Penerapan Digital Forensic Research Workshop Framework pada Layanan Virtual Machine Asruddin, Asruddin; Riadi, Imam; Umar, Rusydi
Journal of Information System Research (JOSH) Vol 7 No 2 (2026): January 2026
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josh.v7i2.9034

Abstract

ICMP flooding is a denial-of-service attack that overwhelms a target with high-rate ICMP packets, degrading service availability. End-to-end network forensic reporting from identification to evidence presentation remains limited. This study applies the Digital Forensic Research Workshop (DFRWS) process model - Identification, Preservation, Collection, Examination, Analysis, and Presentation - to investigate ICMP flooding in a controlled virtualized environment. Primary artifacts consist of baseline PCAPs (5 runs) and attack PCAPs (5 runs) analyzed using capinfos to extract capture duration (T), packet count (N), average et rate (pps), and file size. Results indicate that the baseline traffic (normal system activity in the VM laboratory) at 9 pps over 58.91 s with approximately 66 kB file size, while attack traffic reaches 2,000 pps over 6.39 s with an average file size of approximately 18.2 MB. Comparison of both conditions yields a packet-rate amplification of F = 2000/9 = 222× and a file-size increase of approximately 280× (18.2 MB versus 66 kB). The extreme pps spike observed during the attack condition reflects a volumetric attack pattern that operationally correlates with resource exhaustion and reduced service availability, indicating that the PCAP artifacts support not only statistical anomaly detection but also event-level evidence of a denial-of-service incident. All attack runs exceed 1,000 pps (5/5; 100%), and all baseline runs remain stable at 9 pps (5/5; 100% [1]), indicating consistent volumetric evidence. Preservation procedures using read-only storage and SHA-256 hashing ensure artifact integrity and traceability, thereby supporting the admissibility of the PCAPs as valid digital evidence in controlled virtual machine experiments.
PENERAPAN PRESENSI DARING BERBASIS WEBASSEMBLY DAN MICROSERVICES UNTUK PENGENALAN WAJAH PADA LEARNING MANAGEMENT SYSTEM Sismadi, Wawan; Riadi, Imam; Murinto, Murinto
EDUTECH : Jurnal Inovasi Pendidikan Berbantuan Teknologi Vol. 6 No. 2 (2026)
Publisher : Pusat Pengembangan Pendidikan dan Penelitian Indonesia (P4I)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51878/edutech.v6i2.9474

Abstract

The demand for reliable, real-time online attendance systems capable of handling large-scale users continues to increase alongside the widespread adoption of Learning Management Systems (LMS) in higher education and online training. Conventional attendance methods based on manual input or simple authentication mechanisms suffer from weaknesses such as susceptibility to fraud, limited automation, and degraded performance under high workloads. Face recognition has emerged as a promising alternative, as it enables automatic and non-intrusive user identity verification. However, most face-based attendance systems still rely on centralized server-side processing, which leads to high latency and limited scalability. This study aims to design and evaluate an online attendance architecture that integrates WebAssembly and Microservices by separating computational workloads between the client and server. The Design Science Research method is employed to develop a web-based face attendance application as the research artifact, in which face detection and feature extraction are executed entirely on the client side using OpenCV.js compiled to WebAssembly, while authentication, attendance recording, and session management are handled by a Microservices-based backend. The evaluation includes face recognition accuracy testing, end-to-end latency measurement, and system throughput analysis. Experimental results demonstrate that the proposed architecture reduces attendance latency by approximately 72 percent compared to a monolithic server-side processing approach, while simultaneously increasing request handling capacity without compromising accuracy. These findings indicate that the integration of WebAssembly and Microservices constitutes an effective architectural solution for real-time biometric attendance systems. ABSTRAKKebutuhan akan sistem presensi daring yang andal, real-time, dan mampu menangani skala pengguna besar terus meningkat seiring dengan meluasnya penggunaan Learning Management System (LMS) dalam pendidikan tinggi dan pelatihan daring. Metode presensi konvensional berbasis input manual maupun autentikasi sederhana memiliki kelemahan berupa potensi kecurangan, keterbatasan otomatisasi, serta performa yang menurun pada kondisi beban tinggi. Pengenalan wajah menjadi solusi alternatif yang menjanjikan karena mampu memverifikasi identitas pengguna secara otomatis dan non-intrusif. Namun, sebagian besar sistem presensi berbasis wajah masih bergantung pada pemrosesan terpusat di sisi server, yang mengakibatkan latensi tinggi dan keterbatasan skalabilitas. Penelitian ini bertujuan merancang dan mengevaluasi arsitektur presensi daring berbasis integrasi WebAssembly dan Microservices dengan pendekatan pemisahan beban komputasi antara klien dan server. Metode Design Science Research digunakan untuk mengembangkan artefak berupa aplikasi presensi wajah berbasis web, di mana proses deteksi dan ekstraksi fitur wajah dijalankan sepenuhnya di sisi klien menggunakan OpenCV.js yang dikompilasi ke WebAssembly, sedangkan autentikasi, pencatatan presensi, dan manajemen sesi ditangani oleh backend berbasis Microservices. Evaluasi dilakukan melalui pengujian akurasi pengenalan wajah, pengukuran latensi end-to-end, dan analisis throughput sistem. Hasil pengujian menunjukkan bahwa arsitektur yang diusulkan mampu menurunkan latensi presensi sekitar 72 persen dibandingkan pendekatan monolitik berbasis pemrosesan server, sekaligus meningkatkan kapasitas penanganan permintaan tanpa mengorbankan tingkat akurasi. Temuan ini menunjukkan bahwa integrasi WebAssembly dan Microservices merupakan solusi arsitektural yang efektif untuk sistem presensi biometrik real-time.
Forensik Digital Cyberbullying pada Grup WhatsApp Menggunakan National Institute of Standards and Technology Widiandana, Panggah; Sunardi, Sunardi; Riadi, Imam
Insect (Informatics and Security): Jurnal Teknik Informatika Vol. 12 No. 01 (2026): Maret 2026
Publisher : Universitas Muhammadiyah Sorong

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33506/insect.v12i01.5275

Abstract

Cyberbullying on instant messaging platforms such as WhatsApp is a serious problem due to its psychological impact on victims and the difficulty of obtaining valid digital evidence. This study aims to analyze and uncover digital evidence of cyberbullying in WhatsApp groups using digital forensic methods based on the National Institute of Standards and Technology (NIST) framework, which includes the stages of collection, examination, analysis, and reporting. The research object was simulated WhatsApp conversation data obtained through a logical acquisition process on an Android device. Acquisition and analysis were performed using the digital forensic tools Autopsy, SQLite Viewer, and Cellebrite UFED. The research stages were carried out by simulating a cyberbullying case, and the simulation results were then acquired using the NIST stages. The data studied in the group consisted of 243 messages. The results showed that the NIST method was able to identify important digital artifacts in the form of conversation databases and user metadata, as well as reveal 77 messages containing elements of cyberbullying, consisting of 39 verbal insults, 25 taunts, and 14 derogatory comments. Data integrity verification was performed using SHA-256 hash values, which showed consistency before and after the extraction process, thus fulfilling the principle of forensic soundness. These findings prove that the application of NIST-based digital forensic methods is effective in supporting cyberbullying investigations on WhatsApp groups and is relevant for use in academic, legal, and cybersecurity contexts.
Classification of Pineapple Disease Types Using the VGG16 and EfficiennetB7 Model Approaches: Classification Ediansa, Oka; Riadi, Imam; Murinto, Murinto
Insect (Informatics and Security): Jurnal Teknik Informatika Vol. 12 No. 01 (2026): Maret 2026
Publisher : Universitas Muhammadiyah Sorong

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33506/insect.v12i01.5292

Abstract

Penyakit pada buah nanas merupakan salah satu faktor utama penyebab penurunan kualitas hasil panen dan kerugian ekonomi bagi petani. Identifikasi penyakit secara manual seringkali tidak akurat karena subjektivitas pengamat. Penelitian ini bertujuan untuk mengklasifikasikan jenis penyakit pada buah nanas menggunakan pendekatan Deep Learning dengan membandingkan dua arsitektur populer, yaitu VGG16 dan EfficientNetB7. Dataset yang digunakan berjumlah 215 citra yang terbagi ke dalam empat kelas: Busuk Pangkal, Bercak Hitam, Busuk Inti Buah, dan Nanas Sehat. Karena keterbatasan jumlah data, teknik Transfer Learning dan augmentasi data diterapkan untuk meningkatkan performa model. Hasil penelitian menunjukkan bahwa EfficientNetB7 memberikan performa yang lebih unggul dibandingkan VGG16 dengan akurasi validasi sebesar 89,25%, precision 88,50%, dan f1-score 88,20%. Sementara itu, VGG16 mencapai akurasi validasi sebesar 84,50%. Meskipun EfficientNetB7 membutuhkan waktu komputasi yang lebih lama per epoch, keunggulannya dalam mengekstraksi fitur kompleks pada tekstur kulit nanas menjadikannya model yang lebih ideal untuk sistem deteksi penyakit tanaman. Penelitian ini diharapkan dapat menjadi rujukan dalam pengembangan teknologi otomasi pertanian untuk meningkatkan efisiensi penanganan penyakit pascapanen nanas.
Mobile Forensic Investigation of E-Commerce Fraud Using DFRWS Method and Perceptual Hashing Prambudi, Rizal; Riadi, Imam; Murinto, Murinto
JUITA: Jurnal Informatika JUITA Vol. 14 Issue 1, March 2026
Publisher : Department of Informatics Engineering, Universitas Muhammadiyah Purwokerto

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

Abstract

Social media platforms have enabled real-time communication and broad user interaction, but they are often exploited for cybercrime. One such vulnerable medium is e-commerce applications, which facilitate transactions and store sensitive user data. This study investigates digital evidence in a simulated fraud case involving an e-commerce application by applying mobile forensic techniques guided by the Digital Forensic Research Workshop framework. The investigation focused on recovering user accounts, text messages, images, and videos from an Android smartphone. Two forensic tools Oxygen Forensic Detective and MOBILedit Forensic Express were used for data extraction and analysis. To improve the reliability of visual evidence, the study incorporated perceptual hashing and wavelet hashing techniques to validate compressed image files. The results showed that Oxygen Forensic Detective recovered 71.4% of digital evidence, while MOBILedit achieved 57%. Although both tools successfully recovered multimedia files, Oxygen performed better in extracting text messages. These findings demonstrate the effectiveness of mobile forensic methods in identifying and validating digital evidence in e-commerce fraud cases. Moreover, integrating the DFRWS methodology with perceptual hashing significantly improves the interpretation of manipulated or compressed images, thus enhancing the evidentiary value for legal proceedings.
Co-Authors ., Andi Zulherry Abdul Fadlil Abdul Fadlil Abdullah Hanif Abdullah Hanif Abe, Tuska Achmad Nugrahantoro Achmad Syauqi Ade Davy Wiranata Ade Elvina Adhi Prabowo, Basit Adiniah Gustika Pratiwi Agung Wahyudi Agus Wijayanto Ahmad Azhar Kadim Ahmad Azhari Ahmad Luthfi Ahmad, Muhammad Sabri Aini, Fadhilah Dhinur Akrom, Akrom Al Amany, Sarah Ulfah Alawi, Hanna Syahida Andrianto, Fiki Anggara, Rio Annisa, Putri Anshori, Ikhwan Anton Yudahana Anton Yudhana Anton Yudhana ANWAR, FAHMI anwar, nuril Apriliani, Evinda Aprilliansyah, Deco Ardi Pujiyanta Arif Rahman Arif Rahman Arif Wirawan Muhammad Arif Wirawan Muhammad Arif Wirawan Muhammad Arini, Merita Ariqah Adliana Siregar Arizona Firdonsyah Asno Azzawagama Firdaus Asruddin, Asruddin Astika AyuningTyas, Astika Aulia, Aulia Aulyah Zakilah Ifani Bahagiya, Multika Untung Bashor Fauzan Muthohirin Basir, Azhar Bernadisman, Dora Budi Barata Kusuma Utami Budin, Shiha Busthomi, Iqbal Chandra Kurniawan, Gusti D.E Purwadi Putra, Izzan Julda Davito Rasendriya Rizqullah Putra Davito Rasendriya Rizqullah Putra Deco Aprilliansyah Dewi Astria Faroek Dewi Estri Jayanti Dikky Praseptian M Dwi Aryanto Eddy Irawan Aristianto Ediansa, Oka Eko Brillianto Eko Handoyo Eko Handoyo Elfatiha, Muhammad Ihya Aulia Elvina, Ade Ervin Setyobudi Fadhilah Dhinur Aini Fadhilah Dhinur Aini Fadlil , Abdul Fahmi Anwar Fahmi Auliya Tsani Faiz , Muhammad Nur Faiz Isnan Abdurrachman Fakhri, La Jupriadi Fanani, Galih Fatmawaty, Virdiana Sriviana Faulinda Ely Nastiti Fauzan Natsir Fauzan, Fauzan Firdonsyah, Arizona Fithriatus Shalihah Fitri, Fitriyani Tella Fitriyani Tella Furizal Furizal, Furizal Galih Fanani Galih Pramuja Inngam Fanani Guntur Maulana Zamroni Guntur Maulana Zamroni, Guntur Maulana Habie, Khairul Fathan Hafizh, Muhammad Nasir Hanif, Abdullah Harman, Rika Haryanto, Eri Helmiyah, Siti Herman Herman Herman Herman Herman Yuliansyah Herman Yuliansyah, Herman Hidayati, Anisa Nur Himawan I Azmi Iis Wahyuningsih Ikhram, Ridho Ikhsan Zuhriyanto Ikhwan Anshori Iqbal Busthomi Irhas Ainur Rafiq Irhash Ainur Rafiq Iwan Tri Riyadi Yanto, Iwan Tri Riyadi Jamalludin Jamalludin Jamalludin, Jamalludin Jayawarsa, A.A. Ketut Joko Handoyo Joko Triyanto Kariyamin, Kariyamin Kartoirono, Suprihatin Kurniawan, Endang Kurniawan, Gusti Chandra Kusuma, Ridho Surya Laura Sari Luh Putu Ratna Sundari M Rosyidi Djou M. Rosyidi Djou M.A. Khairul Qalbi Mahsun Mahsun Maulana, Irvan Miladiah Miladiah Miladiah, Miladiah Muammar Muammar, Muammar Muchlas Muchlas Muflih, Ghufron Zaida Muh. Hajar Akbar Muhajir Yunus Muhamad Abduh, Muhamad Muhamad Caesar Febriansyah Putra, Muhamad Caesar Febriansyah Muhammad Abdul Aziz Muhammad Abdul Aziz Muhammad Fahmi Mubarok Nahdli Muhammad Faqih Dzulqarnain, Muhammad Faqih Muhammad Fauzan Gustafi Muhammad Ihya Aulia Elfatiha Muhammad Irwan Syahib Muhammad Kunta Biddinika Muhammad Muhammad Muhammad Nur Faiz Muhammad Syukri Muhammad Yanuar Efendi Muhammad Zulfadhilah Muis, Alwas Murinto Murinto Murinto Murni Murni Murti, Raden Hario Wahyu Musa, Shahrulniza Mushab Al Barra Mustafa Mustafa Mustafa Mustafa NANNY, NANNY Nasrulloh, Imam Mahfudl Nasution, Dewi Sahara Nia Ekawati, Nia Nur Faiz, Muhammad Nur Hamida Siregar Nur Miswar Nur Widiyasono, Nur Nuril Anwar Nuril Anwar, Nuril Nurmi Hidayasari Panggah Widiandana Prabowo, Basit Adhi Pradana Ananda Raharja Prakoso, Danar Cahyo Prambudi, Rizal Prambudi, Rizal Prambudi Prasetyaningrum, Putri Taqwa Prasongko, Riski Yudhi Purwaningrum, Santi Purwanto Purwanto Purwono Purwono, Purwono Putra, Marta Dwi Darma Putri Annisa Putro, Aldibangun Pidekso Raden Hario Wahyu Murti Raden Mohamad Herdian Bhakti Rafiq, Irhash Ainur Rahmat Ardila Dwi Yulianto Ramadhani, Erika Ramansyah Ramansyah Rauli, Muhamad Ermansyah Rauli, Muhamad Ermansyah Ridho Surya Kusuma Rio Anggara Rio Widodo Robiin, Bambang Rochmadi, Tri Roni Anggara Putra Rudy Ansari, Rudy Ruslan, Takdir Rusydi Umar Rusydi Umar Rusydi Umar Ruuhwan Ruuhwan Safiq Rosad Sahiruddin Sahiruddin Salim, Mansyur Santi Purwaningrum Sari, Laura Shiha Budin Sismadi, Wawan Sri Mulyaningsih Sri Winiarti Sri Winiati St Rahmatullah Sudinugraha, Tri Sugandi, Andi Suhartono, Bambang Sukma Aji Sunardi Sunardi - Sunardi Sunardi sunardi sunardi Sunardi, Sunardi Suprihatin Suprihatin Suprihatin Suprihatin Suprihatin Supriyanto Suryanto, Farid Syaefudin, Rizal Syahib, Muhammad Irwan Syahida Alawi, Hanna Syahrani Lonang Syarifudin, Arma Taufiq Ismail Taufiq Ismail Tawar Tawar Tole Sutikno Tri Lestari Tri Lestari Triyanto, Joko Umar, Rusdy Veithzal Rivai Zainal Verry Noval Kristanto W, Yunanri Wahyusari, Retno Wardiwiyono, Sartini Wasito Sukarno Weni Hawariyuni, Weni Wicaksono Yuli Sulistyo Wicaksono Yuli Sulistyo Wicaksono, Sonny Abriantoro Widiandana, Panggah WIDODO, RIO Winiati, Sri Wintolo, Hero Wisnu Pranoto Yana Mulyana Yana Mulyana Yana Safitri, Yana Yudi Kurniawan Yudi Kurniawan Yudi prayudi Yulian Wahyu Permadi Yuliansyah, Herman Yuliansyah, Herman Zein, Wahid Alfaridsi Achmad