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All Journal International Journal of Electrical and Computer Engineering JURNAL SISTEM INFORMASI BISNIS Techno.Com: Jurnal Teknologi Informasi TELKOMNIKA (Telecommunication Computing Electronics and Control) Jurnal Informatika Jurnal Sarjana Teknik Informatika CommIT (Communication & Information Technology) 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 JURNAL PENGABDIAN KEPADA MASYARAKAT Proceeding SENDI_U Khazanah Informatika: Jurnal Ilmu Komputer dan Informatika Register: Jurnal Ilmiah Teknologi Sistem Informasi KLIK (Kumpulan jurnaL Ilmu Komputer) (e-Journal) Edu Komputika Journal Sistemasi: Jurnal Sistem Informasi Jurnal Teknologi dan Sistem Komputer Jurnal Pengabdian UntukMu NegeRI Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) RABIT: Jurnal Teknologi dan Sistem Informasi Univrab SISFOTENIKA Jurnal Teknik Komputer AMIK BSI Jurnal Khatulistiwa Informatika Journal of Information Technology and Computer Science (JOINTECS) JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING Jurnal Ilmiah FIFO Emerging Science Journal Bina Insani ICT Journal JURNAL MEDIA INFORMATIKA BUDIDARMA Jurnal Penelitian Pendidikan IPA (JPPIPA) JIEET (Journal of Information Engineering and Educational Technology) SMARTICS Journal Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Insect (Informatics and Security) : Jurnal Teknik Informatika JITK (Jurnal Ilmu Pengetahuan dan Komputer) METHOMIKA: Jurnal Manajemen Informatika & Komputerisasi Akuntansi ILKOM Jurnal Ilmiah Jiko (Jurnal Informatika dan komputer) Query : Jurnal Sistem Informasi CYBERNETICS Krea-TIF: Jurnal Teknik Informatika IJID (International Journal on Informatics for Development) JURIKOM (Jurnal Riset Komputer) Jurnal Pemberdayaan: Publikasi Hasil Pengabdian Kepada Masyarakat JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Jurnal Mantik Jutisi: Jurnal Ilmiah Teknik Informatika dan Sistem Informasi JISKa (Jurnal Informatika Sunan Kalijaga) Jurnal Informatika dan Rekayasa Elektronik Journal of Information Systems and Informatics RADIAL: JuRnal PerADaban SaIns RekAyasan dan TeknoLogi Mobile and Forensics Jurnal Pengabdian Masyarakat Bumi Raflesia Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) Bubungan Tinggi: Jurnal Pengabdian Masyarakat Edunesia : jurnal Ilmiah Pendidikan Reswara: Jurnal Pengabdian Kepada Masyarakat Jurnal Teknik Informatika (JUTIF) Jurnal FASILKOM (teknologi inFormASi dan ILmu KOMputer) Jumat Informatika: Jurnal Pengabdian Masyarakat Jurnal SAINTIKOM (Jurnal Sains Manajemen Informatika dan Komputer) J-SAKTI (Jurnal Sains Komputer dan Informatika) Jurnal Pengabdian Kepada Masyarakat Patikala Techno SIENNA Jurnal Ilmiah Ilmu Terapan Universitas Jambi JOINCS (Journal of Informatics, Network, and Computer Science) Insand Comtech : Information Science and Computer Technology Journal Jurnal Pengabdian Informatika (JUPITA) Jurnal Informatika Polinema (JIP) Jurnal Informatika: Jurnal Pengembangan IT Jurnal Pengabdian Masyarakat Scientific Journal of Informatics Innovation, Technology, and Entrepreneurship Journal BACA: Jurnal Dokumentasi dan Informasi RADIAL: Jurnal Peradaban Sains, Rekayasa dan Teknologi Edumaspul: Jurnal Pendidikan Proceeding of Informatics Collaborations and Dessimenation Meeting (Infocoding)
Rusydi Umar
Universitas Ahmad Dahlan
Religion 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 Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Neuroscience Physics Social Sciences Other

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Analysis of Conti Ransomware Attack on Computer Network with Live Forensic Method Rusydi Umar; Imam Riadi; Ridho Surya Kusuma
IJID (International Journal on Informatics for Development) Vol. 10 No. 1 (2021): IJID June
Publisher : Faculty of Science and Technology, Universitas Islam Negeri (UIN) Sunan Kalijaga Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14421/ijid.2021.2423

Abstract

Ransomware viruses have become a dangerous threat increasing rapidly in recent years. One of the variants is Conti ransomware that can spread infection and encrypt data simultaneously. Attacks become a severe threat and damage the system, namely by encrypting data on the victim's computer, spreading it to other computers on the same computer network, and demanding a ransom. The working principle of this Ransomware acts by utilizing Registry Query, which covers all forms of behavior in accessing, deleting, creating, manipulating data, and communicating with C2 (Command and Control) servers. This study analyzes the Conti virus attack through a network forensic process based on network behavior logs. The research process consists of three stages, the first stage is simulating attacks on the host computer, the second stage is carrying network forensics by using live forensics methods, and the third stage is analysing malware by using statistical and dynamic analysis. The results of this study provide forensic data and virus behavior when running on RAM and computer networks so that the data obtained makes it possible to identify ransomware traffic on the network and deal with zero-day, especially ransomware threats. It is possible to do so because the analysis is an initial step in generating virus signatures based on network indicators.
PERANCANGAN KLASIFIKASI PASIEN STROKE DENGAN METODE K-NEAREST NEIGHBOR Rahmat Ardila Dwi Yulianto; Imam Riadi; Rusydi Umar
Rabit : Jurnal Teknologi dan Sistem Informasi Univrab Vol 8 No 2 (2023): Juli
Publisher : LPPM Universitas Abdurrab

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36341/rabit.v8i2.3454

Abstract

Stroke is a disease characterized by impaired brain function caused by a lack of oxygen supply and blood flow to the brain, affecting several brain functions that make sufferers experience difficulty in carrying out activities. the classification of stroke patients found is still in the form of medical records that have not been integrated so it takes longer time to detect. The K-NN algorithm is part of a machine learning algorithm that can be used to classify one of the cases, namely the classification of stroke patients. K-NN is used as a class determining algorithm to enter new data that is input according to the format. Based on the results obtained, this study leads to system design using the Unified Model Language (UML) and system user interface design.
Penerapan Digital Forensic Research Workshop Framework pada Layanan Virtual Machine Asruddin Asruddin; Imam Riadi; Rusydi Umar
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.
Anomaly Detection in Cloud Device-Based Information Technology Infrastructure Using Isolation Forest Algorithm Andi Zulherry .; Imam Riadi; Rusydi Umar
JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING Vol. 9 No. 2 (2026): Issues January 2026
Publisher : Universitas Medan Area

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

Abstract

Cloud device-based information technology infrastructure generates large volumes of operational data that are dynamic and heterogeneous, increasing the complexity of monitoring and anomaly detection processes. Conventional rule-based approaches and supervised learning methods are often less effective due to limited labeled data and their inability to detect newly emerging anomaly patterns. Therefore, this study aims to apply and evaluate the Isolation Forest algorithm as an anomaly detection method for cloud device-based information technology infrastructure. The research data consist of system and network performance metrics, including CPU usage, memory utilization, disk activity, and network traffic collected from a cloud environment. The research stages include data preprocessing, normalization, and feature selection to improve data quality and model performance. The Isolation Forest algorithm is implemented using an unsupervised learning approach, where anomalies are identified based on the algorithm’s ability to isolate data points that exhibit characteristics deviating from the majority of normal data. Model performance is evaluated using a confusion matrix with accuracy, precision, recall, and F1-score metrics, while parameter optimization is conducted using the grid search method to obtain the best configuration. The results indicate that the Isolation Forest algorithm is able to detect anomalies effectively, achieving high accuracy and a good balance between precision and recall. The model with optimal parameters demonstrates improved performance by reducing detection errors compared to the baseline configuration. Thus, the Isolation Forest algorithm can serve as a reliable and scalable solution to support monitoring activities and enhance the reliability of cloud infrastructure.
Digitalisasi Portofolio Siswa Berbasis Website di SMK Informatika Wonosobo Imam Riadi; Rusydi Umar; Alwas Muis; Muhajir Yunus
Jurnal Pengabdian Masyarakat Bumi Rafflesia Vol 6 No 3 (2023): DESEMBER: Jurnal Pengabdian Masyarakat Bumi Rafflesia
Publisher : Universitas Muhammadiyah Bengkulu

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Abstract

Siswa dilatih untuk memiliki skill dan pengetahuan agar dapat bekerja pada industri. Setiap siswa dituntut memiliki pengetahuan yang dapat digunakan untuk mencari kerja setelah lulus. Kebutuhan akan adaptasi terhadap perkembangan teknologi informasi dan komunikasi dalam dunia pendidikan semakin meningkat. Sehingga dibutuhkan pelatihan terkait penggunaan teknologi informasi untuk membantu siswa beradaptasi dengan perkembangan teknologi. Tujuan pelatihan ini yaitu untuk memperkenalkan siswa tentang konsep portofolio digital berbasis website dan membekali mereka dengan keterampilan menggunakan teknologi informasi yang relevan untuk membangun dan mengelola portofolio. Manfaat pelatihan ini yaitu membantu siswa untuk mempresentasikan karya-karya mereka secara efektif kepada pihak-pihak yang berkepentingan seperti calon perguruan tinggi dan pemberi kerja. Metode analisis data pada pelatihan ini menggunakan metode likert dengan memberikan pernyataan dan memberikan jawaban mulai dari sangat setuju, setuju, netral, tidak setuju, dan sangat tidak setuju. Siswa berhasil membangun portofolio digital yang menarik dan profesional, memamerkan karya-karya mereka dengan efektif. Metode pengumpulan data pada kegiatan ini yaitu menggunakan kuesioner. ini menunjukkan bahwa pelatihan portofolio menggunakan website sangat mudah dipahami oleh siswa. Selain itu, seluruh siswa berharap pelatihan seperti sering diadakan untuk membantu dalam memanfaatkan teknologi informasi untuk pengembangan diri. Penerapan pelatihan ini di SMK Informatika Wonosobo memberikan manfaat yang signifikan bagi siswa dalam menghadapi tantangan di era digital.   Kata Kunci: Google sites, pelatihan, portofolio, website
Literasi Keamanan Siber UMKM Diaspora Indonesia–China melalui Pelatihan Anti-Penipuan Berbasis GIS Aziz, Muhammad; Umar, Rusydi; Ibdal
Jurnal Pengabdian UntukMu NegeRI Vol. 10 No. 2 (2026): Pengabdian Untuk Mu negeRI
Publisher : LPPM UMRI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37859/jpumri.v10i2.11560

Abstract

Abstract The growth of cross-border digital trade creates economic opportunities for Indonesian–Chinese diaspora Micro, Small, and Medium Enterprises (MSMEs), while increasing exposure to online fraud, phishing, invoice manipulation, and digital identity misuse. Limited cybersecurity literacy constrains MSMEs’ capabilities in supplier verification, account protection, and international transaction risk mitigation. This community service program aimed to strengthen the digital security capacity of diaspora MSMEs through Geographic Information System (GIS)-based anti-fraud training. A participatory approach was employed, including needs assessment, GIS-based digital risk mapping, bilingual Indonesian–Mandarin module development, international hybrid training, anti-fraud simulations, cyber hygiene clinics, and implementation assistance. Key technologies included Digital Threat Mapping, a Digital Vulnerability Assessment (DVA) Dashboard, and Standard Operating Procedures (SOPs) for cross-border transaction verification. Results demonstrated improved participant understanding of phishing prevention, account security, two-factor authentication (2FA), and digital supplier verification. GIS visualization identified digital threat hotspot patterns between Indonesia and China, while the DVA Dashboard enabled participants to conduct independent cybersecurity vulnerability assessments. The program demonstrates that integrating cybersecurity literacy, spatial analysis, and digital ethics can enhance diaspora MSMEs’ resilience within the global digital economy ecosystem. Keywords: Cybersecurity Literacy; GIS-Based Risk Mapping; Cross-Border Digital Trade; Diaspora MSMEs; Digital Security
A CLUSTER-LABEL-BASED FRAMEWORK FOR WATER QUALITY RISK PATTERN CLASSIFICATION USING NAIVE BAYES AND RANDOM FOREST Wahyudin, Widya Cholid; Sutikno, Tole; Umar, Rusydi
Jurnal Ilmiah Ilmu Terapan Universitas Jambi Vol. 10 No. 3 (2026): Volume 10, Nomor 3, June 2026
Publisher : LPPM Universitas Jambi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22437/jiituj.v10i3.57126

Abstract

River water quality monitoring requires an analytical approach that can classify risk patterns from field observations, especially when independent official water quality labels are unavailable. Method: This study classified water quality risk patterns in the Bengawan Solo River using Naive Bayes and Random Forest based on K-Means cluster labels. The initial dataset consisted of 1,753 observations with ten attributes. After feature selection and missing-value removal, 1,751 observations with seven features were used, namely temperature, pH, electrical conductivity, total dissolved solids, water color, odor, and weather condition. K-Means with K=2 generated higher-risk and lower-risk pattern labels, which were then used as classification targets. Results: Naive Bayes achieved an accuracy of 0.988604, precision of 0.988880, recall of 0.988339, and F1-score of 0.988577. Random Forest achieved an accuracy of 0.980057, precision of 0.980499, recall of 0.979655, and F1-score of 0.980004. Discussion: The findings indicate that cluster-derived labels can be recognized consistently by supervised models, while Random Forest feature importance shows that total dissolved solids and electrical conductivity are the most dominant parameters. The results should be interpreted as cluster label based risk pattern classification, not as official pollution status prediction. The novelty of this study lies in integrating cluster-derived labels, supervised classification, and feature-importance analysis for unlabeled water-quality data, while the findings highlight the practical importance of total dissolved solids and electrical conductivity in preliminary water-quality monitoring.
PENERAPAN ALGORITMA K-NEARST NEIGHBOR DALAM KLASIFIKASI JENIS LEMAK HEWANI BERBASIS TEKNOLOGI MECHINE LEARNING Wisnu Dwi Haryanto; Anton Yudhana; Rusydi Umar
JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Vol 11, No 2 (2026)
Publisher : STKIP PGRI Tulungagung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29100/jipi.v11i2.8168

Abstract

Lemak hewan memiliki karakteristik kimia yang berbeda-beda dan penting untuk dianalisis dalam berbagai industri termasuk pangan, farmasi, dan kosmetik. Penelitian ini bertujuan untuk mengklasifikasikan jenis lemak hewan seperti ayam, ayam kampung, sapi, dan babi berdasarkan kandungan senyawa kimianya, yaitu CH₄, CO₂, VOC, HCHO, ODOR, dan SMOKE. Algoritma K-Nearest Neighbor (KNN) digunakan sebagai metode klasifikasi dengan nilai k=3. Dataset dibagi menjadi 80% data latih dan 20% data uji, dan diolah menggunakan Google Colab berbasis Python 3. Hasil penelitian menunjukkan bahwa metode KNN mampu mencapai tingkat akurasi sebesar 98,7%. Evaluasi menggunakan confusion matrix dan classification report menunjukkan nilai precision dan recall di atas 97% untuk semua kelas. Hasil ini membuktikan bahwa algoritma KNN efektif dalam mengklasifikasikan jenis lemak hewan berdasarkan data kandungan kimia.
Experimental Evaluation of Avalanche Effect and Hash Consistency in SHA-256, SHA3-256, and BLAKE2b-256 for Smart Grid Data Integrity Verification Muhammad Ridwan; Rusydi Umar; Muhammad Kunta Biddinika; Puguh Wahyu Prasetyo
Journal of Information System and Informatics Vol 8 No 4 (2026): August
Publisher : Asosiasi Doktor Sistem Informasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63158/journalisi.v8i4.1685

Abstract

Ensuring the integrity of Smart Grid data is essential for preventing unauthorized data modification during transmission and storage. Cryptographic hash functions provide an efficient mechanism for integrity verification; however, their diffusion characteristics and computational performance under identical conditions require further evaluation. This study experimentally compares SHA-256, SHA3-256, and BLAKE2b-256 for Smart Grid data integrity verification using avalanche effect analysis, hash consistency evaluation, and computational performance benchmarking with a standardized 256-bit digest length. The results show that all evaluated algorithms achieved avalanche effect values close to the theoretical 50% criterion (SHA-256: 49.97%, SHA3-256: 49.96%, and BLAKE2b-256: 50.04%) and maintained a 100% hash consistency rate, indicating comparable diffusion capability and deterministic behavior. In terms of computational performance, BLAKE2b-256 achieved the shortest average execution time (11.14 ms), outperforming SHA-256 (13.24 ms) and SHA3-256 (16.87 ms). These findings indicate that all evaluated algorithms are suitable for Smart Grid data integrity verification, while BLAKE2b-256 provides the highest computational efficiency under the experimental conditions. The results are limited to the experimental evaluation of cryptographic hash function behavior and do not represent a comprehensive assessment of Smart Grid cybersecurity.
Optimizing KNN Classification for Heart Disease Prediction Using Sequential Forward Selection Herman; Rusydi Umar; Deni Kuswandani
Journal of Information System and Informatics Vol 8 No 4 (2026): August
Publisher : Asosiasi Doktor Sistem Informasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63158/journalisi.v8i4.1744

Abstract

Irrelevant attributes often degrade the effectiveness of distance-based algorithms like K-Nearest Neighbors (KNN) in heart disease prediction. This study enhances a KNN model using Sequential Forward Selection (SFS) on the Cleveland dataset to optimize computational efficiency and precision while maintaining stable recall. To rigorously prevent data leakage, data partitioning was executed prior to mode imputation and normalization, followed by feature selection within a 5-fold stratified cross-validation framework. To further guarantee model robustness and rule out arbitrary selection, a 5-repeated 10-fold cross-validation and a 50-iteration feature stability analysis were executed. Compared to a baseline model (k=7, Euclidean; 80.33% accuracy) utilizing all 13 original attributes, the optimal 7-feature subset (cp, trestbps, chol, thalach, oldpeak, ca, thal) reduced the dimensional space by 46% and achieved 81.97% Accuracy, 77.42% Precision, 85.71% Recall, 78.79% Specificity, 0.9183 ROC-AUC, and an 81.36% F1-Score on an independent hold-out test set comprising 61 samples. Although McNemar's test (p = 1.0000) indicated the absolute accuracy improvement was not statistically significant, the 7-feature model successfully eliminated unstable features and reduced statistical noise. Ultimately, applying SFS provides a highly efficient, computationally lightweight framework for heart disease prediction without compromising predictive reliability.
Co-Authors Aang Anwarudin Abdul Fadlil Abdul Fadlil Abdul Fadlil Abdul Hadi Abdullah Hanif Abe, Tuska Achmad Dito Achmad Nugrahantoro Achmad Ridwan Agus Prasetyo Marsaid Ahmad Fajar Sidiq Ahmad Ikrom Ahnafi, Muhammad Ghazi Ahwan Ahmadi Aini, Fadhilah Dhinur Aji Nugroho Akbar, Zulfikri Alameka, Faza Alameka, Faza Aldi Rifki Andriawan Alfiansyah Imanda Putra Alfiansyah Imanda Putra Alfian Alwas Muis Anak Agung Gede Sugianthara Andhy Sulistyo Andi Zulherry . Anggara, Rio Anton Yudhana Anton Yudhana Anwarudin, Aang Ardi Pujiyanta Ardiansyah, Ricy Arfiani Nur Khusna Arief Setyo Nugroho Arief Setyo Nugroho Arief Setyo Nugroho Arief Setyo Nugroho Arif Budiman Arif Budiman Arif Wirawan Muhammad Arizona Firdonsyah Asruddin Asruddin Asy’am, Muhammad Hasfar Aulyah Zakilah Ifani Az-Zahra, Rifqi Rahmatika Bashor Fauzan Muthohirin Bella Okta Sari Miranda Bintang, Rauhulloh Noor Busthomi, Iqbal Bustomi, Iqbal Dani Wahyudi Deni Kuswandani Deni Murdiani Dewi Astria Faroek Dewi Estri Jayanti Dewi Estri Jayanti Dewi Sahara Dewi Sahara Nasution Dewi Soyusiawaty Dwi Susanto Dzakwan, M Sabiq Eko Handoyo Elfaditiya Wardaya Ermin Ermin Fadhilah Dhinur Aini Fadlil, Abdu Fadlillah Mukti Ayudewi Fahmi Anwar Faiz Isnan Abdurrachman Faizin Ridho Fathia Irbati Ammatulloh Fauzan, Fauzan Faza Alameka Faza Alameka Fijaya Dwi Bimasakti Firmansyah Firmansyah Firmansyah Firmansyah Firmansyah Yasin Fitrah Juliansyah Fitrah Juliansyah Gema Kharismajati Gustafi, Muhammad Fauzan Gustafi, Muhammad Fauzan H, Hermansa Hadi, Wisnu Setiawan Hafidz, Muhammad Nasir Hanif, Abdullah Hanif, Kharis Hudaiby Helmiyah, Siti Herman Herman Herman Herman Herman Herman Herman Herman Yuliansyah, Herman Hermansa Husnul Dzikri Ibdal Imam Mahfudl Nasrulloh Imam Riadi Imam Riadi Imam Riadi Imam Riadi Imam Riadi Imam Riadi Imam Riadi Indra Gunawan Iqbal Busthomi Iqbal Busthomi Irjayana, Rizky Caesar Izzan Julda D.E Purwadi Putra Jaka Dernata Jefree Fahana Jihan Wala Juliansyah, Fitrah Kencana, Nagala Wangsa Kgs Muhammad Rizky Alditra Utama Khoirul Anam Dahlan Kusuma, Ridho Surya Lisna Zahrotun Lukman Nurhakim Maftukhah, Ainin Mardhiatul Ihsaniah Maulana, Irvan Maya Anggriani Miladiah Miladiah Miladiah, Miladiah Mirza Sutrisno Moch. Nasheh Annafii Mochammad Imron Awalludin Muhajir Yunus Muhammad Abdul Aziz Muhammad Abdul Aziz Muhammad Aziz Muhammad Aziz Muhammad Fahmi Mubarok Nahdli Muhammad Fauzan Gustafi Muhammad Fauzan Gustafi Muhammad Ihya Aulia Elfatiha Muhammad Irwan Syahib Muhammad Jundullah Muhammad Kunta Biddinika Muhammad Noor Fadillah Muhammad Noor Fadillah Muhammad Nur Ardhiansyah Muhammad Nur Faiz Muhammad Ridwan Munaldi Muntiari, Novita Ranti Murinto Murinto Murinto Mustafa Mustafa Muzakkir Pangri N, Musri Iskandar Nagala Wangsa kencana Nasrulloh, Imam Mahfudl Nugroho, Ismail Adji Ockhy Jey Fhiter Wassalam Panggah Widiandana Periyanto, Ari Peryanto, Ari Prasetyo Hari Prabowo prayudi, Andi Puguh Wahyu Prasetyo, Puguh Purwanto Purwanto Purwono Purwono P Purwono, Purwono Putra, Alfiansyah Imanda Putra, Fajar R. B Putra, Fijaya Dwi Bima Sakti Putri Silmina, Esi Rahmat Ardila Dwi Yulianto Ramdhani, Rezki Resmi - Aini Rezki Ramdhani Rezki Rezki Ridho Surya Kusuma Rifqi Rahmatika Az-Zahra Roy Mubarak Roy Mubarak Saad, Saleh Khalifah Sabarudin Saputra Sahiruddin Sahiruddin Sakti, Fijaya Bima Dwi Saleh khalifa saad Sarjimin, Sarjimin Sarmin, Sarmini Septa, Frandika Sismadi, Wawan Siswanto, Anwar Sonny Abriantoro Wicaksono Sri Rahayu Astari Sri Rahayu Astari Sri Winiarti Subandi, Rio Subhan Subhan Sugandi, Andi Sunardi Sunardi Sunardi, Sunardi suwanti suwanti Tarisno Amijoyo Tella, Fitriyani Tole Sutikno Tri Lestari Tri Lestari Tri Lestari Utama, Kgs Muhammad Rizky Alditra Utama, Kiagus Muhammad Rizky Aditra Veithzal Rivai Zainal Wala, Jihan Wasito Sukarno Wawan Sismadi Widya Cholid Wahyudin Widya Cholid Wahyudin Widya Cholid Wahyudin Wilda Rina Hasibuan Winoto, Sakti Wisnu Dwi Haryanto Yuminah yuminah Yuminah, Yuminah yuminah, Yuminah