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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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Pelatihan Kreasi Konten Digital dengan Komunikasi melalui Tools Kecerdasan Artifisial Winiarti, Sri; Soyusiawaty, Dewi; Umar, Rusydi; Yuliansyah, Herman
Jurnal Pengabdian UntukMu NegeRI Vol. 9 No. 3 (2025): Pengabdian Untuk Mu negeRI
Publisher : LPPM UMRI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37859/jpumri.v9i3.10417

Abstract

Seiring dengan adanya kebijakan Kementrian Pendidikan Dasar dan Menengah Republik Indonesia terkait penerapan Kecerdasan Artifisial (KA) dalam pembelajaran jenjang Sekolah Dasar (SD) hingga Sekolah Menengah Atas (SMA), maka semua sekolah memerlukan adanya pemahaman terhadap pelaksanaan pembelajaran KA. Perkembangan KA telah memberikan peluang baru dalam mendukung kreativitas dan komunikasi digital dalam pelaksanaan pembelajaran. Namun, banyak guru masih kesulitan berinteraksi secara efektif dengan perangkat KA untuk menghasilkan konten pembelajaran yang meraik, khususnya untuk pembelajaran dengan model unplugged. Kegiatan pengabdian kepada masyarakat ini bertujuan meningkatkan kompetensi guru dalam berkomunikasi dengan perangkat KA melalui pelatihan bertema “Kreasi Konten Digital dengan Komunikasi melalui Tools Kecerdasan Artifisial.” Pelatihan dilaksanakan pada 9 Juli 2025 di Kabupaten Sleman dengan peserta sebanyak 24 guru Sekolah Menengah Pertama (SMP). Metode yang digunakan meliputi tranfer pengetahuan, praktik langsung Aplikasi KA, praktek mengajar dengan Aplikasi KA dengan pendekatan PjBL dan evaluasi pelaksanaan. Materi pelatihan berupa konsep KA dalam pembelajaran, cara berkomunikasi dengan perangkat KA yang efektif dengan menggunakan prompt yang efektif. Kegiatan pelatihan ini meningkatkan keterampilan komunikasi guru sebesar 17,4% (dari 69,4% menjadi 86,8%), menunjukkan efektivitas pendekatan PjBL dalam memperkuat literasi digital dan kreativitas guru.
Identification of Learning Javanese Script Handwriting Using Histogram Chain Code Arif Budiman; Abdul Fadlil; Rusydi Umar
Edumaspul: Jurnal Pendidikan Vol 7 No 1 (2023): Edumaspul: Jurnal Pendidikan
Publisher : Universitas Muhammadiyah Enrekang

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

Abstract

One of the wealth of the Indonesian nation is the many tribes with their own languages and scripts. One of the scripts that has existed since long before the independence of the State of Indonesia is the Javanese script, with the use of Latin script used by almost every aspect of life, both official official activities and daily use, the use of traditional scripts, especially Javanese script, is increasingly scarce. To facilitate learning the Javanese script, learning media is needed with the ability to recognize Javanese characters. In this study, pre-processing was used, especially feature extraction using the Histogram Chain Code (HCC) method and classification using artificial neural networks using the Multi Layer Perceptron method. This study compares four research models by setting the number of HCC feature extraction parameters obtained from one intact image and 3 divided images of 4, 9 and 16 parts respectively so that the total parameters of each HCC model are 8, 32, 72 and 128 parameters characteristic. The training and testing process using the Multi Layer Perceptron method uses 2000 handwritten Javanese script image data which is divided into 80%, namely 1600 images for the training process and 400 images for the testing process. This research resulted in different accuracies, namely 57%, 78%, 83% and 76%. The best accuracy is obtained from the HCC model with 72 parameters and the image is divided into 9 sections.
Advanced Chicken Breed Identification Using Transfer Learning Techniques with the VGG16 Convolutional Neural Network Architecture Nagala Wangsa kencana; Rusydi Umar; Murinto
Jurnal Penelitian Pendidikan IPA Vol 11 No 7 (2025): July
Publisher : Postgraduate, University of Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jppipa.v11i7.11870

Abstract

This study proposes a deep learning-based classification system to identify chicken breeds from image data. A dataset of 2,400 labeled images representing twelve distinct chicken breeds was collected and divided into training, validation, and testing sets. The system employs transfer learning by integrating the Mobile VGG16 convolutional neural network as the feature extraction backbone. The extracted features were then passed through custom classification layers to differentiate among the breeds. The model was trained using 1,800 images, validated with 300 images, and evaluated on a separate test set of 300 images. During testing, the model achieved an accuracy of 81% and a categorical cross-entropy loss of 0.378. These results indicate that the model can effectively recognize subtle visual distinctions between similar-looking chicken breeds. The system demonstrates practical potential for applications in poultry farming, biodiversity documentation, and automated livestock management. The findings confirm that deep convolutional neural networks, particularly VGG16 in a transfer learning setup, are capable of performing fine-grained classification tasks in real-world scenarios. The proposed method provides a reliable and scalable solution for automatic chicken breed identification based on image input.
Header investigation for spam email forensics using framework of national institute of standards and technology Mustafa, Mustafa; Riadi, Imam; Umar, Rusydi
ILKOM Jurnal Ilmiah Vol 13, No 2 (2021)
Publisher : Prodi Teknik Informatika FIK Universitas Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33096/ilkom.v13i2.849.163-167

Abstract

Today's technology makes communication very easy and can be used anywhere, even a distance of hundreds to thousands of kilometres is not a barrier in communicating. One of the tools or media that is widely used is via email. However, there are many disadvantages that may be obtained from the email, one of which is spamming or mail. The purpose of this research is to know the stages of spamming email analysis through header analysis. The method used in this study is the National Institute of Standards and Technology (NIST) and this method uses 4 stages, namely collection, examination, analysis, and reporting. The results of this study are expected to be able to find out the spam sender's email address, the spam email sender's IP address, and other information needed.
Enhancing Kubernetes-Based Microservices Deployment Efficiency Through DevOps and GitOps Maulana, Irvan; Umar, Rusydi; Yudhana, Anton
ILKOM Jurnal Ilmiah Vol 17, No 2 (2025)
Publisher : Prodi Teknik Informatika FIK Universitas Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33096/ilkom.v17i2.2562.107-119

Abstract

An effective and resilient means to deploy microservices to Kubernetes is an ongoing challenge. This challenge becomes more difficult with ever increasingly complex application architectures. This research explored a DevOps model based on GitOps that integrates ArgoCD and GitLab CI/CD, as a means to create a more effective, resilient, and scalable deployment. Twelve microservices that were deployed in a controlled experimentation format were used in a comparative approach to previous deployment practices that only considered manual deployments. The results show an overall deployment time improvement of 40%. For the deployments that were executed incorrectly, ArgoCD ensures service availability leveraging its self-healing capabilities. During the computation of each run we also experienced system performance in a sustained high-load environment. Upon high demand, we experienced the desired autoscaling behavior requested, which resulted in higher service responsiveness. In comparison to previous studies, this research considered statistical analysis, while also looking at an aspect of real-world orchestration and networking efficiency while adopting Kubernetes. Altogether, this research gives organizations practical advice on how they may optimize their deployment pipelines for efficient, scalable and resilient microservices.
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.
Comparison of Filter and Wrapper Feature Selection Methods for Heart Disease Risk Classification using K-Nearest Neighbors (k-NN) Deni Kuswandani; Herman Herman; Rusydi Umar
SISTEMASI Vol 15, No 3 (2026): Sistemasi: Jurnal Sistem Informasi
Publisher : Universitas Islam Indragiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32520/stmsi.v15i3.5989

Abstract

Feature selection plays a crucial role in improving the effectiveness of medical classification models. This study compares two feature selection approaches—filter and wrapper methods—in developing a k-Nearest Neighbors (k-NN) model for heart disease risk classification. The dataset consists of patients’ demographic data, lifestyle factors, and clinical indicators. In this study, the filter method was applied by considering data types: Pearson Correlation was used for numerical features, while the Chi-Square test was applied to categorical features. The selected features from both techniques were then combined, reducing the initial 20 features to four key variables considered most relevant for heart disease risk classification: BMI, homocysteine level, blood pressure, and stress level. This approach achieved high computational efficiency; however, it resulted in only a modest accuracy improvement (76.8%) and a low recall for the minority class (0.07). In contrast, the wrapper method using Sequential Forward Selection (SFS) produced a more informative subset of 11 features, achieving higher accuracy (80.00%) and a ROC-AUC of 0.657, indicating better discrimination capability for the minority class. These findings suggest that while the filter method excels in simplicity and computational efficiency, the wrapper method is more effective in improving classification performance. This study provides empirical insights into selecting appropriate feature selection strategies based on analytical objectives, particularly for clinical decision support systems.
Blockchain-Based Preservation Framework for Network Forensic Evidence Integrity Mirza Sutrisno; Sunardi; Rusydi Umar
Sienna Vol 7 No 1 (2026): Sienna Volume 7 Nomor 1 Juli 2026
Publisher : LPPM Universitas Muhammadiyah Kotabumi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47637/sienna.v7i1.2377

Abstract

Network forensic investigations rely heavily on the integrity and traceability of Packet Capture (PCAP) files as primary digital evidence. Digital Forensic Research Workshop (DFRWS) implementations commonly employ centralized preservation mechanisms that remain vulnerable to unauthorized modification and provide limited provenance transparency. To address these limitations, this study proposes a blockchain-based preservation framework integrated into the preservation phase of the DFRWS model. The framework combines SHA-256 cryptographic hashing for integrity verification, blockchain-based provenance logging, and distributed ledger validation while maintaining off-chain evidence storage. Unlike many existing blockchain-based forensic frameworks that primarily emphasize provenance recording and chain-of-custody management, this study evaluates evidence preservation through an integrated validation approach consisting of controlled tampering simulation, cryptographic sensitivity analysis, and preservation latency measurement. Experimental evaluation using PCAP datasets representing attack and baseline traffic conditions demonstrated that unauthorized evidence modification was successfully detected through hash inconsistencies. Avalanche Effect analysis produced a value of 50.39%, confirming the strong cryptographic sensitivity of the SHA-256 mechanism to minimal data alteration. While SHA-256 enables reliable tampering detection, the integrated blockchain architecture provides tamper-resistant provenance recording, chain-of-custody traceability, and distributed verification of evidence integrity. The framework achieved an average preservation latency of 2.057 seconds within the experimental environment, providing preliminary evidence of feasibility for blockchain-assisted forensic logging under controlled conditions. Although no direct comparison with alternative preservation approaches was conducted, the findings provide a proof-of-concept validation and contribute empirical evidence regarding the potential of blockchain-supported provenance management to enhance trustworthiness and integrity assurance in network forensic workflows.
Identification of Bengawan Solo River Water Quality Patterns Using K-Means Clustering Based on Physicochemical and Environmental Parameters: Identifikasi Pola Kualitas Air Sungai Bengawan Solo Menggunakan Klasterisasi K-Means Berdasarkan Parameter Fisik-Kimia dan Lingkungan Widya Cholid Wahyudin; Tole Sutikno; Rusydi Umar; Widya Cholid Wahyudin
JOINCS (Journal of Informatics, Network, and Computer Science) Vol. 9 No. 1 (2026): April
Publisher : Universitas Muhammadiyah Sidoarjo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21070/joincs.v9i1.1710

Abstract

Abstract. River water quality needs to be monitored continuously because changes in physicochemical and environmental parameters may indicate early changes in aquatic conditions. This study aims to identify water quality patterns in the Bengawan Solo River using K-Means clustering based on physicochemical and environmental parameters. The dataset consists of 1,753 field observations with attributes including temperature, pH, electrical conductivity, total dissolved solids, water color, odor, and weather condition. The research stages include feature selection, data preprocessing, categorical encoding, Z-score standardization, K-Means clustering, and cluster number evaluation. The number of clusters was tested from K=2 to K=5. Cluster quality was evaluated using Silhouette Score, Davies-Bouldin Index, Calinski-Harabasz Score, and Inertia. After data cleaning, 1,751 observations were used in the clustering process. The evaluation results show that K=2 is the best cluster number, with a Silhouette Score of 0.187638 and a Calinski-Harabasz Score of 456.873808. The clustering results formed two main patterns, namely Cluster 0 with 840 observations or 47.97% and Cluster 1 with 911 observations or 52.03%. Based on average parameter characteristics, Cluster 0 has higher electrical conductivity and TDS values than Cluster 1; therefore, it is interpreted as a higher water quality risk pattern. These results indicate that K-Means can identify initial water quality patterns in an unlabeled Bengawan Solo River dataset.
Penguatan Literasi Digital Siswa SMK Mambaul Falah Kudus melalui Edukasi Ancaman Siber, Pinjaman Online, dan Cyber Bullying Achmad Ridwan; Widya Cholid Wahyudin; Wilda Rina Hasibuan; Anton Yudhana; Rusydi Umar
Jurnal Pengabdian Masyarakat Vol. 5 No. 1 (2026): Juni 2026
Publisher : Unity Academy

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70340/japamas.v5i1.487

Abstract

Penggunaan internet yang tinggi di kalangan siswa SMK Mambaul Falah Kudus berpotensi meningkatkan risiko cybercrime, cyber bullying, dan penyalahgunaan pinjaman online ilegal. Kegiatan Program Pemberdayaan Umat (PRODAMAT) ini bertujuan meningkatkan literasi digital dan keterampilan keamanan akun siswa melalui edukasi berbasis studi kasus dan praktik langsung. Metode kegiatan meliputi koordinasi mitra, observasi kebutuhan, penyusunan materi, pre-test, penyampaian materi, diskusi kasus, praktik pengaturan privasi dan two factor authentication, post-test, serta refleksi. Peserta kegiatan berjumlah 30 siswa kelas XI SMK Mambaul Falah Kudus. Hasil kegiatan menunjukkan peningkatan pemahaman pada aspek  cyber crime dari 55% menjadi 83%, cyber bullying dari 58% menjadi 86%, pinjaman online ilegal dari 50% menjadi 84%, dan keamanan digital dari 56% menjadi 85%. Peserta juga mampu mengenali tautan mencurigakan, membedakan pinjaman online legal dan ilegal, memblokir akun berisiko, serta memahami langkah pelaporan. Kegiatan ini berkontribusi bagi sekolah sebagai model edukasi literasi digital aplikatif untuk membangun perilaku internet yang aman, bijak, dan bertanggung jawab.
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