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All Journal International Journal of Electrical and Computer Engineering ComEngApp : Computer Engineering and Applications Journal JURNAL SISTEM INFORMASI BISNIS 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 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 International Journal of Advances in Intelligent Informatics 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) Komputasi: Jurnal Ilmiah Ilmu Komputer dan Matematika JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Abdimas Umtas : Jurnal Pengabdian kepada Masyarakat Jurnal Teknologi Terpadu 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) bit-Tech Mobile and Forensics Aviation Electronics, Information Technology, Telecommunications, Electricals, and Controls (AVITEC) Jurnal Pengabdian Masyarakat Bumi Raflesia Cyber Security dan Forensik Digital (CSFD) Jurnal Abdi Insani 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) 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 Euler : Jurnal Ilmiah Matematika, Sains dan Teknologi EDUTECH : Jurnal Inovasi Pendidikan Berbantuan Teknologi J-SAKTI (Jurnal Sains Komputer dan Informatika) Jurnal Pengabdian Kepada Masyarakat Patikala Jurnal Saintekom : Sains, Teknologi, Komputer dan Manajemen Jurnal Puan Indonesia Jurnal Informatika Teknologi dan Sains (Jinteks) Techno Wahana 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 semanTIK Jurnal Informatika Medis (J-INFORMED) Darma Abdi Karya: Jurnal Pengabdian Kepada Masyarakat Khazanah Informatika : Jurnal Ilmu Komputer dan Informatika JOCHAC Jurnal Repositor Proceeding of Informatics Collaborations and Dessimenation Meeting (Infocoding)
Imam Riadi
Department Of Information Systems - Universitas Ahmad Dahlan
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Determining Eligible Villages for Mobile Services using K-NN Algorithm Yudhana, Anton; Riadi, Imam; Djou, M Rosyidi
ILKOM Jurnal Ilmiah Vol 15, No 1 (2023)
Publisher : Prodi Teknik Informatika FIK Universitas Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33096/ilkom.v15i1.1546.11-20

Abstract

To maximize and get population document services closer to the community, the Disdukcapil district of Alor provides mobile services by visiting people in remote villages which difficult-to-reach service centres in the city. Due to a large number of villages and limited time and costs, not all villages can be served, so the kNN algorithm is needed to determine which villages are eligible to be served. The criteria used in this determination are village distance, difficulty level, and document ownership (Birth Certificate, KIA, family card, and KTPel). The classes that will be determined are "Very eligible", "Eligible", and "Not eligible". By applying Z-Score normalization with the value of K=5, the classification gets 94.12% accuracy, while non-normalized only gets 88.24% accuracy. Thus, applying normalization to training data can improve the kNN algorithm's accuracy in determining eligible villages for "ball pick-up" or mobile services.
ANALISIS STATISTIK LOG JARINGAN UNTUK DETEKSI SERANGAN DDOS BERBASIS NEURAL NETWORK Muhammad, Arif Wirawan; Riadi, Imam; Sunardi, Sunardi
ILKOM Jurnal Ilmiah Vol 8, No 3 (2016)
Publisher : Prodi Teknik Informatika FIK Universitas Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33096/ilkom.v8i3.76.220-225

Abstract

Distributed denial-of-service (DDoS) merupakan jenis serangan dengan volume, intensitas, dan biaya mitigasi yang terus meningkat seiring berkembangnya skala organisasi. Penelitian ini memiliki tujuan untuk mengembangkan sebuah pendekatan baru untuk mendeteksi serangan DDoS, berdasarkan log jaringan yang dianalisis secara statistik dengan fungsi neural network sebagai metode deteksi. Data pelatihan dan pengujian diambil dari CAIDA DDoS Attack 2007 dan simulasi mandiri. Pengujian terhadap metode analisis statistik terhadap log jaringan dengan fungsi neural network sebagai metode deteksi menghasilkan prosentase rata-rata pengenalan terhadap tiga kondisi jaringan (normal, slow DDoS, dan DDoS) sebesar 90,52%. Adanya pendekatan baru dalam mendeteksi serangan DDoS, diharapkan bisa menjadi sebuah komplemen terhadap sistem Intrusion Detection System (IDS) dalam meramalkan terjadinya serangan DDoS.
Analisis Sentimen Program Makan Bergizi Gratis Menggunakan Lexicon-Based dan Support Vector Machine Akbar, Zulfikri; Riadi, Imam; Umar, Rusydi
JURNAL FASILKOM Vol. 16 No. 1 (2026): Jurnal FASILKOM (teknologi inFormASi dan ILmu KOMputer)
Publisher : Unversitas Muhammadiyah Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37859/jf.v16i1.10948

Abstract

Public policy initiatives often trigger massive shifts in digital public opinion, such as the Free Nutritious Meal Program (MBG), which has garnered extensive attention from the Indonesian public on social media. Sentiment analysis serves as a vital instrument to map public opinion trends, particularly when dealing with large-scale, unstructured, and heterogeneous textual data. This study aims to analyze the distribution of public sentiment toward the MBG Program and evaluate the effectiveness of the lexicon-based method and Support Vector Machine (SVM) algorithm in classifying opinion texts. The dataset was collected from Twitter (X) via the Kaggle platform, comprising 10,524 public comments. The methodology begins with text preprocessing, including cleaning, case folding, tokenization, normalization, stopword removal, and stemming. Sentiment labeling was performed automatically using a lexicon-based approach referring to the InSet Lexicon to categorize data into three classes: positive, negative, and neutral. Subsequently, text representation was conducted using the Term Frequency–Inverse Document Frequency (TF–IDF) method and classified using an SVM model with a nested cross-validation scheme to maintain performance stability. The results indicate that public opinion is dominated by neutral sentiment at 48.1% (5,066 data points), followed by positive sentiment at 30.8%, and negative sentiment at 21.0%. This dominance of neutral sentiment reflects an informative, descriptive, and cautious public stance toward a policy still in its early implementation stages. Evaluation of the SVM model demonstrates highly stable and reliable performance, achieving an accuracy of 89.26%, with precision, recall, and F1-score each at 89%. This study concludes that the combination of lexicon-based automatic labeling and SVM is effective for public policy sentiment analysis, providing insights into public expectations and concerns regarding government programs.
Assesing Digital Evidence Availability in Discord Phishing using ISO/IEC 27037 and Anti-Forensics Analysis Yudhana, Anton; Rivai, Zulki Yanto; Riadi, Imam
International Journal of Advances in Data and Information Systems Vol. 7 No. 1 (2026): April 2026 - International Journal of Advances in Data and Information Systems
Publisher : Indonesian Scientific Journal

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59395/ijadis.v7i1.1518

Abstract

Phishing incidents on modern communication platforms pose significant challenges for digital forensics investigations, particularly regarding the availability and preservation of digital evidence. This research aims to evaluate the availability of digital evidence in Discord-based phishing cases by applying the ISO/IEC 27037 framework and interpreting the results from an anti-forensics perspective. This research uses a digital forensics case analysis approach on the victim’s mobile device by following the stages of identification, collection, acquisition, and preservation. The results show that of the five types of digital evidence identified, only 40% can be fully preserved, while 20% are partially preserved, and 40% cannot be preserved. The quantitative evaluation produced an average digital evidence availability score of 0.5, indicating that only half of the expected digital evidence could be retained even though the entire forensics procedure had been systematically applied. These findings confirm that the limitations in the availability of digital evidence are influenced not only by the investigation process but also by the technical characteristics of digital artifacts and the system mechanisms inherent to the Discord platform.
ScreenMy: a Lightweight Architecture of Tuberculosis-Diabetes Mellitus Screening System Integrating with EMRs Farid Suryanto; Merita Arini; Imam Riadi
JUITA: Jurnal Informatika JUITA Vol. 12 No. 2, November 2024
Publisher : Department of Informatics Engineering, Universitas Muhammadiyah Purwokerto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30595/juita.v12i2.21541

Abstract

Background: Early detection of diseases like tuberculosis (TB) and diabetes mellitus (DM) is critical for preventive healthcare. However, integrating effective screening programs within existing workflows can be challenging. Objective: This study explores the feasibility and impact of integrating an electronic screening system (ESS) within electronic medical records (EMRs) in private primary care settings. The pilot study focuses on ScreenMy, an ESS engine designed for bi-directional TB-DM screening. Methods: A pilot study investigated the integration process of ScreenMy into an EMR system. Interviews with developers assessed factors like installation ease, flexibility, and impact on the EMR's functionality. Findings: The findings revealed a smooth integration process due to ScreenMy's external design (requiring only plugin injection) and clear documentation.  The integration maintained EMR performance and efficiency, enhanced the developer experience, and offered flexibility for customization.  Developers, unfamiliar with prior integrated screening systems, found ScreenMy user-friendly and expressed interest in further system flexibility concerning data privacy. Conclusion: This investigation highlights the potential for seamless integration of screening systems like ScreenMy within EMRs. This paves the way for improved preventive healthcare delivery in primary care settings.
A Comparative Evaluation of Drone Detection Models on Aerial Imageryacross Varying Training Epochs Astika Ayuningtyas; Imam Riadi; Anton Yudhana
JUITA: Jurnal Informatika JUITA Vol. 13 Issue 3, November 2025
Publisher : Department of Informatics Engineering, Universitas Muhammadiyah Purwokerto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30595/juita.v13i3.26618

Abstract

Drone detection in aerial imagery has become increasingly important in security, surveillance, and military applications. This study aims to evaluate the performance of a deep learning model in detecting drone images by varying the number of training epochs (10, 20, and 50 epochs). A drone image dataset was used to train and test the model, with performance evaluated using precision, recall, mAP@0.5, and mAP@0.5:0.95 metrics. The experimental results indicate that increasing the number of epochs significantly enhances model performance. At 10 epochs, the model achieved a precision of 0.905, recall of 0.857, mAP@0.5 of 0.904, and mAP@0.5:0.95 of 0.455. At 20 epochs, recall improved to 0.879, and mAP@0.5:0.95 increased to 0.476. The best performance was observed at 50 epochs, with a precision of 0.918, recall of 0.886, mAP@0.5 of 0.920, and mAP@0.5:0.95 of 0.494. These findings demonstrate that increasing the number of training epochs not only improves detection accuracy but also enhances the model's generalization capability. The study concludes that training for 50 epochs is the optimal configuration for achieving the best performance in drone image detection, despite requiring longer training time. These results provide practical recommendations for implementing deep learning models in real-world drone detection applications.
Mobile Forensic Investigation of E-Commerce Fraud Using DFRWS Method and Perceptual Hashing Rizal Prambudi; Imam Riadi; 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 | DOI: 10.30595/juita.v14i1.27690

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.
Machine learning model for classifying the severity level of cybersecurity attacks Imam Riadi; Sri Winiarti; Herman Yuliansyah; Muhammad ‘Arif Bin Mohamad
International Journal of Advances in Intelligent Informatics Vol 12, No 2 (2026): May 2026
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/ijain.v12i2.2245

Abstract

Cyberattacks are becoming increasingly sophisticated, necessitating defense mechanisms that go beyond simple detection to include severity assessment for prioritizing mitigation. This study proposes a comprehensive machine learning framework to classify cyberattack severity levels (Low, Medium, High) using a modern, high-dimensional dataset. Addressing the critical challenge of class imbalance, the research integrates the Synthetic Minority Oversampling Technique (SMOTE) with a rigorous feature selection process involving SelectKBest. Four algorithms Naive Bayes, K-Nearest Neighbor (KNN), Random Forest (RF), and Support Vector Machine (SVM) were evaluated using 10-fold cross-validation. The results demonstrate that the SVM model with an RBF kernel achieves superior performance with an accuracy of 97.30% and a False Negative Rate (FNR) of only 3.1% for high-severity threats. This research contributes a robust, data-driven approach to severity classification that effectively handles feature non-linearity and class imbalance, offering actionable insights for real-time security operations.
IMPLEMENTATION OF RANDOM FOREST FOR ANIMAL PROTEIN CLASSIFICATION THROUGH HYPERPARAMETER OPTIMIZATION Ridho Ikhram; Anton Yudhana; Imam Riadi
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
Subject Area Classification of Journal Articles Based on Metadata Using Bag of Words and Naïve Bayes Ainunna’imah; Herman Yuliansyah; Imam Riadi
Engineering Science Letter Vol. 5 No. 02 (2026): Engineering Science Letter
Publisher : The Indonesian Institute of Science and Technology Research

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56741/IISTR.esl.002041

Abstract

The rapid growth of scientific publications poses challenges in grouping journal articles based on subject area, especially when using metadata such as titles, abstracts, and keywords. However, differences in feature representation and classification algorithms often result in varying performance, requiring comparative studies to determine the optimal model combination. This study compares four combinations of subject area classification models, namely TF-IDF + Naïve Bayes, TF-IDF + Support Vector Machine, Bag-of-Words + Support Vector Machine, and Bag-of-Words + Naïve Bayes. The research process included text preprocessing, feature extraction, and testing using an 80% training and 20% testing data split scheme in five scenarios. The evaluation was performed using confusion matrices, accuracy, precision, recall, and F1-score. The experimental results showed variations in performance between models, with an average F1-score of 0.8103 for TF-IDF + Naïve Bayes, 0.8494 for TF-IDF + Support Vector Machine, 0.8297 for Bag-of-Words + Support Vector Machine, and 0.8335 for Bag-of-Words + Naïve Bayes as the best performance. These findings indicate that a word frequency-based approach combined with Naïve Bayes is effective for classifying journal article subject areas based on metadata, although challenges remain in subject areas with semantic proximity.
Co-Authors Abdul Fadlil Abdul Fadlil Abdullah Hanif Abdullah Hanif Abe, Tuska Achmad Nugrahantoro Achmad Syauqi Ade Elvina Adiniah Gustika Pratiwi Agung Wahyudi Agus Wijayanto Ahmad Azhar Kadim Ahmad Azhari Ahmad Luthfi Ahmad, Muhammad Sabri Aini, Fadhilah Dhinur Ainunna’imah Akbar, Zulfikri Al Amany, Sarah Ulfah Alawi, Hanna Syahida Alwas Muis Andi Zulherry Andi Zulherry . Andrianto, Fiki Anggara, Rio Annisa, Putri Anshori, Ikhwan Anton Yudahana Anton Yudhana Anton Yudhana ANWAR, FAHMI anwar, nuril Apriliani, Evinda Aprilliansyah, Deco Arif Rahman Arif Rahman Arif Rahman Arif Wirawan Muhammad Arif Wirawan Muhammad Arif Wirawan Muhammad Ariqah Adliana Siregar Arizona Firdonsyah Asno Azzawagama Firdaus Asruddin Astika AyuningTyas, Astika Aulia, Aulia Aulyah Zakilah Ifani Bambang Robiin Bashor Fauzan Muthohirin Basir, Azhar Basit Adhi Prabowo Bernadisman, Dora Budi Barata Kusuma Utami Budin, Shiha Busthomi, Iqbal D.E Purwadi Putra, Izzan Julda Davito Rasendriya Rizqullah Putra Davito Rasendriya Rizqullah Putra Deco Aprilliansyah Dedy Sumarhadi Devaldi Caliesta Octadiani Dewi Astria Faroek Dewi Estri Jayanti Dewi Estri Jayanti H Dian Novianti Dikky Praseptian M Djou, M Rosyidi 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 Farid Suryanto Fatmawaty, Virdiana Sriviana FAULINDA ELY NASTITI Fauzan Natsir Fauzan, Fauzan Firdonsyah, Arizona Firmansyah Firmansyah Firmansyah Firmansyah Fithriatus Shalihah Fitri, Fitriyani Tella Fitriyani Tella Furizal Furizal, Furizal Galih Fanani Galih Pramuja Inngam Fanani Guntur Maulana Zamroni Guntur Maulana Zamroni, Guntur Maulana Gusti Chandra Kurniawan Habie, Khairul Fathan Hafizh, Muhammad Nasir Hanif, Abdullah Harman, Rika Haruno Sajati Haryanto, Eri Helmiyah, Siti Herman Herman Herman Herman Herman Yuliansyah Herman Yuliansyah Herman Yuliansyah Herman Yuliansyah, Herman Hero Wintolo Hidayati, Anisa Nur Himawan I Azmi Iis Wahyuningsih Ikhsan Zuhriyanto Ikhwan Anshori Imroatul Khuluqi Izzah Indah Purnama Sari 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.A. Khairul Qalbi Mahsun Mahsun Maulana, Irvan Mega Fatimah Rosana Merita Arini Mhd. Basri Miladiah Miladiah Miladiah, Miladiah Mohammad Faiq Badruz Zaman 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 Arief Sutisna Muhammad Fahmi Mubarok Nahdli Muhammad Faqih Dzulqarnain Muhammad Faqih Dzulqarnain, Muhammad Faqih Muhammad Fauzan Gustafi Muhammad Ihya Aulia Elfatiha Muhammad Irwan Syahib Muhammad Kunta Biddinika Muhammad Muhammad Muhammad Nur Faiz Muhammad Yanuar Efendi Muhammad Zulfadhilah Muhammad ‘Arif Bin Mohamad Munawaroh Munawaroh Murinto Murinto Murinto 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 Ekawati Niki Ratama NORITA SINAGA 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 Prasetyaningrum, Putri Taqwa Purwaningrum, Santi Purwanto Purwanto Purwono Purwono, Purwono Puspa Ira Dewi Candra Wulan 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 Reyhanssan Islamey Ridho Ikhram Ridho Ikhram Ridho Surya Kusuma Rika Harman Rio Widodo Riski Yudhi Prasongko Rivai, Zulki Yanto Rizal Prambudi Rochmadi, Tri Roni Anggara Putra Rosalia Setia Nursanti Rudy Ansari Rudy Ansari Ruslan, Takdir Rusydi Umar Rusydi Umar Rusydi Umar Ruuhwan Safiq Rosad Sahiruddin Sahiruddin Salim, Mansyur Santi Purwaningrum Sari, Laura Shiha Budin Simanjuntak, Pastima Sismadi, Wawan Sri Mulyaningsih Sri Winiarti Sri Winiarti Sri Winiati St Rahmatullah Sudaryanto Sudaryanto Sudinugraha, Tri Sugandi, Andi Suhartono, Bambang Sukma Aji Sunardi Sunardi - Sunardi Sunardi sunardi sunardi Sunardi, Sunardi Suprihatin Suprihatin Suprihatin Suprihatin Suprihatin Suprihatin Supriyanto Syaefudin, Rizal Syahida Alawi, Hanna Syahrani Lonang Syarifudin, Arma Taufiq Ismail Taufiq Ismail Tawar Tawar Tole Sutikno Tri Ferga Prasetyo Tri Lestari Tri Lestari Tri Rochmadi Triyanto, Joko Umar, Rusdy Veithzal Rivai Zainal Verry Noval Kristanto W, Yunanri Wahyusari, Retno Wardiwiyono, Sartini Wasito Sukarno Wawan Sismadi Weni Hawariyuni, Weni Wicaksono Yuli Sulistyo Wicaksono Yuli Sulistyo Widiandana, Panggah WIDODO, RIO Winiati, Sri Wintolo, Hero Wisnu Pranoto Yana Mulyana Yana Mulyana Yana Safitri, Yana Yohanni Syahra Yudi Kurniawan Yudi Kurniawan Yudi prayudi Yulian Wahyu Permadi Yuliansyah, Herman Yuliansyah, Herman Zein, Wahid Alfaridsi Achmad