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All Journal International Journal of Electrical and Computer Engineering International Journal of Evaluation and Research in Education (IJERE) Journal of Food and Pharmaceutical Science Dinamik Seminar Nasional Aplikasi Teknologi Informasi (SNATI) Transmisi: Jurnal Ilmiah Teknik Elektro JURNAL SISTEM INFORMASI BISNIS Voteteknika (Vocational Teknik Elektronika dan Informatika) JTEV (Jurnal Teknik Elektro dan Vokasional ELKHA : Jurnal Teknik Elektro Jurnal Sistem Komputer TELKOMNIKA (Telecommunication Computing Electronics and Control) Bulletin of Electrical Engineering and Informatics Jurnal Informatika Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI) Prosiding Seminar Nasional Sains Dan Teknologi Fakultas Teknik Bulletin of Electrical Engineering and Informatics Jurnal Ilmiah Kursor Jurnal Algoritma Jurnal Teknologi Telematika : Jurnal Informatika dan Teknologi Informasi Jurnal Teknologi Informasi dan Ilmu Komputer Jurnal Edukasi dan Penelitian Informatika (JEPIN) JUITA : Jurnal Informatika International Journal of Advances in Intelligent Informatics Scientific Journal of Informatics Seminar Nasional Informatika (SEMNASIF) Komunikator ICON-CSE CESS (Journal of Computer Engineering, System and Science) Proceeding SENDI_U Khazanah Informatika: Jurnal Ilmu Komputer dan Informatika Register: Jurnal Ilmiah Teknologi Sistem Informasi ELKOMIKA: Jurnal Teknik Energi Elektrik, Teknik Telekomunikasi, & Teknik Elektronika JURNAL NASIONAL TEKNIK ELEKTRO KLIK (Kumpulan jurnaL Ilmu Komputer) (e-Journal) Bulletin of Electrical Engineering and Informatics JOIN (Jurnal Online Informatika) Journal of Electrical Technology UMY Format : Jurnal Imiah Teknik Informatika Jurnal Teknologi dan Sistem Komputer Jurnal ELTIKOM : Jurnal Teknik Elektro, Teknologi Informasi dan Komputer Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) International Journal of Artificial Intelligence Research 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) Bina Insani ICT Journal JURNAL MEDIA INFORMATIKA BUDIDARMA Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control CogITo Smart Journal IT JOURNAL RESEARCH AND DEVELOPMENT Jurnal Sains dan Informatika Insect (Informatics and Security) : Jurnal Teknik Informatika JRST (Jurnal Riset Sains dan Teknologi) JOURNAL OF APPLIED INFORMATICS AND COMPUTING JURNAL REKAYASA TEKNOLOGI INFORMASI JURNAL TEKNIK INFORMATIKA DAN SISTEM INFORMASI JURNAL INSTEK (Informatika Sains dan Teknologi) ILKOM Jurnal Ilmiah Compiler KACANEGARA Jurnal Pengabdian pada Masyarakat Jiko (Jurnal Informatika dan komputer) Journal of Science and Engineering MATRIK : Jurnal Manajemen, Teknik Informatika, dan Rekayasa Komputer JSiI (Jurnal Sistem Informasi) CYBERNETICS Krea-TIF: Jurnal Teknik Informatika J-SAKTI (Jurnal Sains Komputer dan Informatika) JURIKOM (Jurnal Riset Komputer) Jurnal Teknik Elektro dan Komputer TRIAC RESISTOR (Elektronika Kendali Telekomunikasi Tenaga Listrik Komputer) Jurnal Ilmiah Mandala Education (JIME) JSI (Jurnal sistem Informasi) Universitas Suryadarma Systemic: Information System and Informatics Journal Jurnal Pengabdian Kepada Masyarakat MEMBANGUN NEGERI Jurnal Mantik JISKa (Jurnal Informatika Sunan Kalijaga) Journal of Electronics, Electromedical Engineering, and Medical Informatics Buletin Ilmiah Sarjana Teknik Elektro RADIAL: JuRnal PerADaban SaIns RekAyasan dan TeknoLogi Mobile and Forensics Jurnal Informatika dan Rekayasa Perangkat Lunak Journal of Robotics and Control (JRC) Journal of Applied Engineering and Technological Science (JAETS) Jurnal Riset Rekayasa Elektro Jurnal Repositor Respati Indonesian Journal of Electrical Engineering and Computer Science Journal of Computer System and Informatics (JoSYC) International Journal of Advances in Data and Information Systems Journal of Innovation Information Technology and Application (JINITA) Reswara: Jurnal Pengabdian Kepada Masyarakat Infotech: Journal of Technology Information SKANIKA: Sistem Komputer dan Teknik Informatika Innovation in Research of Informatics (INNOVATICS) Jurnal Teknik Informatika (JUTIF) JURPIKAT (Jurnal Pengabdian Kepada Masyarakat) Jurnal Computer Science and Information Technology (CoSciTech) Journal Social Science And Technology For Community Service Jumat Informatika: Jurnal Pengabdian Masyarakat Jurnal SAINTIKOM (Jurnal Sains Manajemen Informatika dan Komputer) J-SAKTI (Jurnal Sains Komputer dan Informatika) Decode: Jurnal Pendidikan Teknologi Informasi Jurnal Informatika Teknologi dan Sains (Jinteks) Jurnal Algoritma Techno Jurnal Pengabdian Pada Masyarakat Amal Ilmiah: Jurnal Pengabdian Kepada Masyarakat SmartComp Journal of Food and Pharmaceutical Sciences Jurnal Informatika: Jurnal Pengembangan IT Control Systems and Optimization Letters Emitor: Jurnal Teknik Elektro Proceeding International Conference Of Innovation Science, Technology, Education, Children And Health Proceeding International Conference Of Innovation Science, Technology, Education, Children And Health Signal and Image Processing Letters Khazanah Informatika : Jurnal Ilmu Komputer dan Informatika JuTISI (Jurnal Teknik Informatika dan Sistem Informasi) RADIAL: Jurnal Peradaban Sains, Rekayasa dan Teknologi Scientific Journal of Engineering Research Dedikasi Nusantara
Anton Yudhana
Universitas Ahmad Dahlan, Yogyakarta
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A Comparative Study of Improved Ensemble Learning Algorithms for Patient Severity Condition Classification Edi Ismanto; Abdul Fadlil; Anton Yudhana; Kitagawa, Kodai
Journal of Electronics, Electromedical Engineering, and Medical Informatics Vol 6 No 3 (2024): July
Publisher : Department of Electromedical Engineering, POLTEKKES KEMENKES SURABAYA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35882/jeeemi.v6i3.452

Abstract

The evolution of Electronic Health Records (EHR) has facilitated comprehensive patient record-keeping, enhancing healthcare delivery and decision-making processes. Despite these advancements, analyzing EHR data using ensemble machine learning methods poses unique challenges. These challenges include data dimensionality, imbalanced class distributions, and the need for effective hyperparameter tuning to optimize model performance. The study conducted a thorough comparative analysis of various ensemble machine learning (EML) models using Electronic Health Record (EHR) datasets. After addressing data imbalance and reducing dimensionality, the accuracy of the EML models showed significant improvement. Notably, the Gradient Boosting Machine (GBM) and CatBoost models exhibited superior performance with an accuracy of 73%, achieved through experiments involving dimensionality reduction and handling of imbalanced data. Furthermore, optimization techniques such as Grid Search and Random Search were employed to enhance the EML models. The results of model optimization revealed that the GBM + Random Search model performed the best, achieving an accuracy of 74%, followed by the XGBoost + Grid Search model with an accuracy of 73%. The GBM model also excelled in distinguishing between positive and negative classes, boasting the highest Area under Curve (AUC) value of 0.78, indicative of its superior classification capabilities compared to other models. This study emphasizes the significance of incorporating cutting-edge EML techniques into clinical workflows and emphasizes the revolutionary potential of GBM in classification modeling for patient severity conditions. Future research should focus on deep learning (DL) applications and the integration of these models.
Analisis File Carving Solid State Drive Menggunakan Metode National Institute of Standards and Technology: Analisis File Carving Solid State Drive Menggunakan Metode National Institute of Standards and Technology Khoirul Anam Dahlan; Anton Yudhana; Herman Yuliansyah
Jurnal SAINTIKOM (Jurnal Sains Manajemen Informatika dan Komputer) Vol 23 No 2 (2024): Agustus 2024
Publisher : PRPM STMIK TRIGUNA DHARMA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53513/jis.v23i2.9700

Abstract

Recovery pada SSD dianggap sulit karena tingkat keberhasilan yang rendah dalam dunia teknisi, karenanya teknik file carving yang terbaharui menjadi salah satu solusi pengembalian file yang hilang, baik dengan sengaja ataupun tidak sengaja, sehingga masih ada harapan atas file yang telah hilang pada SSD, khususnya pada SSD Sata Geniune 120GB. Metode NIST memungkinkan untuk merangkum pelaporan yang dapat dipertanggungjawabkan dan valid, sehingga dapat digunakan dalam persidangan untuk membuktikan bahwa pelaku benar atau salah.setelah bukti fisik berupa SSD di kumpulkan, maka proses selanjutnya menggunakan laptop lenovo y520 yang dengan sistem operaasi ubuntu dan windows untuk pemeriksaan dan analisa untuk dibuatkan laporan. Dari 88 file yang di recovery, Software Foremost berhasil mengembalikan 46 file dengan tingkat keberhasilan 53% dan Software Autopsy berhasil mengembalikan 81 file dengan tingkat keberhasilan 94%, persentase keberhasilan diindikasikan dengan nilai hash yang sama menggunnakan MD5 dan file dapat dibuka tanpa kendala. Walaupun tidak sampai 100% yang biasa kita temukan dalam penelitian Harddisk atau Flashdisk, akan tetapi masih ada harapan kedepannya jika recovery pada SSD bisa mencapai 100%.
Implementasi Deployment Layanan Website Menggunakan Kubernetes Dengan Ci/Cd Jenkins: Implementasi Deployment Layanan Website Menggunakan Kubernetes Dengan Ci/Cd Jenkins Maulana, Irvan; Umar, Rusydi; Yudhana, Anton
Jurnal SAINTIKOM (Jurnal Sains Manajemen Informatika dan Komputer) Vol 23 No 2 (2024): Agustus 2024
Publisher : PRPM STMIK TRIGUNA DHARMA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53513/jis.v23i2.9992

Abstract

pemetintahan, perdagangan , dan lain-lain. Website adalah kumpulan halaman dalam suatu domain yang memuat tentang berbagai informasi agar dapat dibaca dan dilihat oleh pengguna internet melalui sebuah mesin pencari[13]. Informasi yang dapat dimuat dalam sebuah website umumnya berisi mengenai konten gambar, ilustrasi, video, dan teks untuk berbagai macam kepentingan. Website menjadi salah satu alat penyampai informasi paling popiler sat ini, mulai dari pemerintahan, media, berita, perusahaan maupun personal. Sehingga dibutuhkan website yang dapat terus berkembang dan pemeliharaan yang lebih sederhana. Penelitian ini berfokus pada pembangunan infrastruktur Continous Integration/Continous Delivery/Deployment (CI/CD) dengan manajemen cluster menggunakan kubernetes. Metode deployment aplikasi menggunakan CI/CD lebih efisien untuk perkembangan aplikasi yang berjalan terus menerus. Sedangkan kubernetes sangat membantu perkembangan aplikasi yang berbasis container dan microservices[1]. Selain itu, kubernetes juga memiliki beberapa kelebihan antara lain: auto-scaling dan load balancing. Penelitian ini menghasilkan sebuah produk infrastruktur CI/CD yang membuat proses deployment dan pengembangan aplikasi web dapat berjalan secara cepat, efisien dan efektif.
Analisis Perbandingan Model Fully Connected Neural Networks (FCNN) dan TabNet Untuk Klasifikasi Perawatan Pasien Pada Data Tabular Ismanto, Edi; Abdul Fadlil; Anton Yudhana
Computer Science and Information Technology Vol 5 No 3 (2024): Jurnal Computer Science and Information Technology (CoSciTech)
Publisher : Universitas Muhammadiyah Riau

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

Abstract

Electronic Health Records (EHR) store tabular data that is rich in information and play a critical role in supporting decision-making within the healthcare field, particularly for patient care classification. This study evaluates the performance of two artificial intelligence models, Fully Connected Neural Networks (FCNN) and TabNet, in processing tabular data for patient care classification tasks. The findings reveal that both models demonstrate strong performance, with TabNet showing a slight advantage. TabNet achieves an accuracy of 0.74, marginally surpassing FCNN's 0.73. Furthermore, TabNet excels in precision (0.74 vs. 0.72), recall (0.72 vs. 0.71), and F1-Score (0.73 vs. 0.71), highlighting its greater reliability in minimizing false positives and accurately detecting positive cases with a better balance between precision and recall. With its architecture specifically tailored for tabular data and its capacity for direct interpretability, TabNet offers enhanced efficiency and ease of implementation compared to FCNN, which demands more complex data preprocessing. For future research, it is suggested to employ larger and more diverse datasets, explore data with higher feature complexity, and conduct comprehensive hyperparameter tuning to further improve the performance of both models.
Prototipe Timbangan Digital dan Pengendali Konveyor Otomatis untuk Pembersih Limbah Kotoran Hewan Ternak Kambing Son Ali Akbar; Ruly Erwin AfanDika; Anton Yudhana; Dian Nova Kusuma Hardani
Jurnal Riset Rekayasa Elektro Vol 6, No 2 (2024): JRRE VOL 6 NO 2 DESEMBER 2024
Publisher : PROGRAM STUDI TEKNIK ELEKTRO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30595/jrre.v6i2.24537

Abstract

yang berbau. Untuk mengatasi hal ini, dikembangkan sebuah alat otomatisasi yang dapat membersihkan kotoran basah dan cair secara efisien. Sistem ini mengintegrasikan sensor loadcell untuk mengukur berat kotoran, Arduino Uno sebagai mikrokontroler, dan LCD 16x2 I2C untuk menampilkan hasil pengukuran. Penelitian dilakukan di peternakan Desa Jangkang, Sleman, D.I. Yogyakarta, dengan fokus pada pemisahan kotoran basah dan cair secara otomatis. Kandang yang dirancang memiliki ukuran 1,6 m x 3 m x 2,4. Konveyor yang digerakkan oleh motor DC memindahkan kotoran ke penampungan sementara, sekaligus memisahkan feses dari urine. Sistem beroperasi dengan kecepatan konveyor 160 cm, tegangan rata-rata 11,19 V, dan RPM sebesar 17,94, dengan waktu operasional rata-rata 20 detik. Hasil pengujian menunjukkan error 4,9% dan tingkat akurasi 96,49%. Inovasi ini berkontribusi pada peningkatan efisiensi pengelolaan limbah dan pengurangan bau, mendukung pengembangan sektor peternakan kambing secara berkelanjutan.
File carving Analyze of Foremost and Autopsy on external SSD mSATA using the Association of Chief Police Officer Method Dahlan, Khoirul Anam; Yudhana, Anton; Yuliansyah, Herman
ILKOM Jurnal Ilmiah Vol 16, No 3 (2024)
Publisher : Prodi Teknik Informatika FIK Universitas Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33096/ilkom.v16i3.2360.283-295

Abstract

File carving is a method for recovering files using software such as Foremost and Autopsy. The recovery is conducted for deleted files or formatted devices. Popularity Solid State Drive (SSD) has outperformed Hard Disk Drive (HDD) because SSD is faster, more efficient, and shock resistant. However, recovering SSD devices have a lower probability success rate than HDD because the security system often hampers files recovered on SSD. Based on previous research, the success rate of Security Digital High Capacity (SDHC) only achieved 50% more than SSD, whereas SSD can only return 85.7% of its success. Forensics Digital is a part of Forensics Knowledge for deliver valid digital evidence for law investigation. This research aims to increase the success rate of recovery files using two different software: Foremost and Autopsy. The research uses a 512GB Eaget brand SSD with a New Technology File System (NTFS). The file carving is also conducted using the Association of Chief Police Officers (ACPO) method. APCO has several stages: Planning, Capture, Analysis, and Presentation. The experiment results show that Autopsy software with deep recover mode returned 81 out of 88 files (92%), whereas Foremost software run on Debian to make sure no virus on device that could damage computer especially windows system. First attempt recovery can only return 46 out of 88 files (52%). The findings show that the Autopsy software has a higher successful return rate and can be used for evidence in law enforcement and digital forensics investigations.
Mass Classification of Breast Cancer Using CNN and Faster R-CNN Model Comparison Sunardi, Sunardi; Yudhana, Anton; Windra Putri, Anggi Rizky
Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Vol. 7, No. 3, August 2022
Publisher : Universitas Muhammadiyah Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22219/kinetik.v7i3.1462

Abstract

Threat of breast cancer is a frightening type and threatens the female population worldwide. Early detection is preventive solution to determine cancer diagnosis or tumors in the female breast area. Today, machine learning technology in managing medical images has become an innovative trend in the health sector. This technology can accelerate diagnosing disease based on the acquisition of accuracy values. The primary purpose of this research is to innovate by comparing two deep learning models to build a prediction system for early-stage breast cancer. This research utilizes Convolutional Neural Network (CNN) sequential models and Faster Region-based Convolutional Neural Network (R-CNN) models that can determine the classification of normal or abnormal breast image data, which can determine the normal or abnormal classification of breast image. The dataset's source in this study came from the Mammographic Image Analysis Society (MIAS). This dataset consists of 322 mammogram data with 123 abnormal and 199 normal classes. The experimental results of this study show that the accuracy of the CNN and R-CNN models in image classification are 91.26% and 63.89%, respectively. Based on these results, the CNN sequential model has better accuracy than the Faster R-CNN model, because it does not require unique characteristics to detect breast cancer.
Public Opinion Analysis of Presidential Candidate Using Naïve Bayes Method Firdaus, Asno Azzawagama; Yudhana, Anton; Riadi, Imam
Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Vol. 8, No. 2, May 2023
Publisher : Universitas Muhammadiyah Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22219/kinetik.v8i2.1686

Abstract

Elections for president and vice president will take place in 2024. Heading into the election, promoted candidates were vying for public sympathy. People often discussed as presidential candidates are Anies Baswedan, Ganjar Pranowo, and Prabowo Subianto. Therefore, we need a way to predict potential candidates and voter demographics from public opinion on Twitter using sentiment analysis. One of his methods commonly used to classify sentiment analysis is Naive Bayes. This study used the naive Bayes classifier and the TF-IDF extraction function to add weights to the text. Use the scikit-learn Python library to help determine the polarity of negative and positive sentiment classes in your dataset. The datasets used were Twitter datasets acquired from October to December 2022, for a total of 15,000 datasets. The best test scenario obtained by splitting the test and training data is 70% test data and 30% training data, with the highest accuracy generated from the 95% Ganjar dataset. Using the Anies, Ganjar, and Prabowo test data, the positive mood scores for each candidate were 833, 77, and 524, respectively, while the negative mood scores were 637, 1423, and 976, respectively. The test was performed using a confusion matrix and k-fold cross-validation, and the best results were obtained on the Ganjar data set. That is a confusion matrix of 94.93% and a k-fold cross-validation of 94.46%. The lowest f1-score for the positive class is 67% for the Anies dataset and 27% for the negative class for the Ganjar dataset.
Thorax X-ray Image Segmentation Technique Using Four Variants of Thresholding Algorithm Subandi, Rio; Herman; Yudhana, Anton
Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Vol. 9, No. 1, February 2024
Publisher : Universitas Muhammadiyah Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22219/kinetik.v9i1.1809

Abstract

Pneumonia is a respiratory infection caused by bacteria, viruses or fungi, and has been recognized as a fairly common and threatening disease. When diagnosing this disease, doctors usually also use thorax X-ray images. Nowadays, diagnosing pneumonia has been made possible with the help of machine learning technology. Doctors or medical personnel in locations where there are no pulmonary specialists or experts can be assisted by this technology. Machine learning algorithms are used to process digital images that have passed the pre-processing and segmentation stages. This paper offers a solution to segmentation technique of thorax X-ray digital image using a combination of four thresholding algorithms. This combination aims to find the best CNN model with segmentation techniques in the form of the most suitable thresholding algorithm. The result of this research is four different data sets. The thresholding algorithms used include binary, thresh binary inv, thresh to zero, thresh tozero inv with a threshold value of 150. The data used in this research is a thorax X-ray image dataset, as many as 5,856 images acquired from the Kaggle repository data. The program code in this research uses the Python programming language in the Anaconda environment. This research has resulted in a comparison of the accuracy values obtained using 4 variants between thres_binary thresholding algorithm and thres_binary_inv. The thres_tozero obtained 95% of accuracy while thres_tozero_inv obtained 94% of accuracy.
Analysis of Radiation Structure of Circular Microstrip Antenna using Characteristic Mode Analysis for ISM Band SABILA, LIYA YUSRINA; AMRI, MUHAMMAD MIFTAHUL; YUDHANA, ANTON; AKRIMA, ASRA; PRATAMA, IGO PUTRA
ELKOMIKA: Jurnal Teknik Energi Elektrik, Teknik Telekomunikasi, & Teknik Elektronika Vol 11, No 1: Published January 2023
Publisher : Institut Teknologi Nasional, Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26760/elkomika.v11i1.100

Abstract

ABSTRAKMakalah ini bertujuan untuk melihat karakteristik struktur radiasi menggunakan Analisis Mode Karakteristik pada antena sirkular array. Kontribusi utama dari pekerjaan ini adalah menganalisis penyebab masalah antena yang tidak sesuai dengan impedansinya pada frekuensi 2,4 GHz melalui mode distribusi arus pada patch atau radiasi. Pencocokan impedansi dapat dicapai dengan menetapkan slot ke dua patch yang tersusun dan memberikan efek peningkatan bandwidth dan gain. Untuk validasi hasil performansi antena dapat dilihat dari mode aktif pada frekuensi yang sesuai. Ditemukan bahwa antena yang diusulkan memiliki dua mode aktif pada frekuensi 2,4 GHz. Ditemukan bahwa antena yang digunakan cukup akurat. Hal ini dibuktikan dengan nilai S11 sebesar -19,606 dB dan gain sebesar 3,45 pada frekuensi 2,45 GHz.Kata kunci: antena, mikrostrip, characteristic mode analysis, ISM Band, 2.4 GHz ABSTRACTThis paper aims to see the characteristics of the radiation structure using Characteristic Mode Analysis on circular array antennas. The main contribution of this work is to analyze the causes of the problem of the antenna not matching its impedance at the 2.4 GHz frequency through the current distribution modes on the patch or radiation. Matching impedance can be achieved by assigning slots to the two arrayed patches and increasing bandwidth and gain. It can be seen from the active modes at the appropriate frequency to validate the results of antenna performance. The proposed antenna has two active modes at a frequency of 2.4 GHz. It is found that the proposed antenna is entirely accurate. It is proven by the S11 value of -19.606 dB and the gain of 3.45 at a frequency of 2.45 GHz.Keywords: antenna, microstrip, characteristic mode analysis, ISM Band, 2.4 GHz
Co-Authors Aang Anwarudin Abd. Rasyid Syamsuri Abdel-Nasser Sharkawy Abdillah, Muhamad Aznar Abdul Azis Abdul Djalil Djayali Abdul Fadil Abdul Fadil Abdul Fadlil Abdul Fadlil Abe, Tuska Ade Firli Ansyori Adi Permadi Agung Dwi Nugroho, Agung Dwi Agus Jaka Sri Hartanta Ahmad Azhar Kadim Ahmad Ikrom Ahmad Ikrom Ahmad Syahril Mohd Nawi Ahmadi, Ahwan Akhwandi, Dasef AKRIMA, ASRA Alameka, Faza Alameka, Faza alders paliling Aldi Bastiatul Fawait Fawait Alfian Ma’arif Alin Khaliduzzaman Aminuyati Andhy Sulistyo Andiko Putro Suryotomo Andri Pranolo Anggara Ibnu Sidharta Annafii, Moch. Nasheh Anom Wahyu Asmorojati Anshori, Ikhwan Anton Satria Prabuwono Anton Satria Prabuwono Anwar Siswanto Anwarudin, Aang Ardiansyah, Ricy Arief Setyo Nugroho Aris Rakhmadi Ashari, Irvan Asno Azzawagama Firdaus Asra Akrima Astika AyuningTyas, Astika Aznar Abdillah, Muhamad Azrul Mahfurdz Bahagiya, Multika Untung Balza Achmad Basri, Mhd. Bella Okta Sari Miranda Belly Apriansyah Bintang, Rauhulloh Noor budi putra Budi Setianto, Arif Bulaka, Bardan Cahya Subrata, Arsyad Choirul Fajri Darso, Muhammad Daryono Daryono Dasef Akhwandi Deni Murdiani Denny Yoga Pratama Dewi Eko Wati Dian Nova Kusuma Hardani Didi Siprian Drezewski, Rafal Dwi Susanto Dwi Susanto Dwi Susanto Dzakarasma Tazakka Ma’arij Edi Ismanto Eka Rahmat B Eko Prianto Eko Prianto Elvina, Ade Fadil, Abdul Fadlil, Abdul Fadlillah Mukti Ayudewi Fahmi, Miftahuddin Fahrizal Djohar Fakhri, La Jupriadi Fathoni, Listya Febri Fatma Nuraisyah, Fatma Faza Alameka Faza Alameka Febryansah, M. Iqbal Fitrah Juliansyah Fitri Anggraini Fitri Anggraini, Fitri Fitriyanto, Rachmad Furizal Furizal Furizal Furizal, Furizal Galih Pramuja Inngam Fanani H, Hermansa Habibah, Nurina Umy Habsah Hasan Hadi Sasongko, Hadi Halil, Nur Ihsan Hanif, Abdullah Hanif, Kharis Hudaiby Hartanta, Agus Jaka Sri Hartono, Susilo Helmiyah, Siti Herman Herman Herman Herman Herman Herman Yuliansyah Herman Yuliansyah, Herman Hermansa Herwindo Rahadian Hidayat, Lalu Amam Hikmatyar Insani Himawan I Azmi Igo Putra Pratama Iif Alfiatul Mukaromah Ikhsan Sugianto Ikhsan Zuhriyanto Ikhsan Zuhriyanto Ikhsan Zuhriyanto Ikhwan Anshori Ikrom, Ahmad Ilham Mufandi Imam Riadi Imam Riadi Imam Riadi Imam Riadi Imam Riadi Imam Riadi Imam Riadi Imam Riadi Imam Riadi Intan Puspitasari Irfan, Syahid Al Irwansyah Irwansyah Ivan Triyatno Jafri Din Jaka Dernata Jaka Dernata Jaka Japkowicz, Nathalie Jendri Juliansyah, Fitrah Kalbuadi, Dimas Baskoro Kartika Firdausy Kaspul Anwar Kaswijanti, Wilis Kawarul Hawari Ghazali Kgs Muhammad Rizky Alditra Utama Kgs Muhammad Rizky Alditra Utama Khaliduzzaman, Alin Khalif, Fajar Al Khoir, Syaiful Amrial Khoirul Anam Dahlan Kintung Prayitno, Kintung Kitagawa, Kodai Kurniawan, Gusti Chandra Kusuma , Damar Yoga Listya Febri Fathoni Liya Yusrina Sabila Luh Putu Ratna Sundari Lutfatul Kholifah M Rosyidi Djou M Rosyidi Djou M. Rosyidi Djou Mahsun Mahsun Mardi Sugama Marlina Mustafa, Marlina Maulana, Irvan Mawadati, Siti Mawarni, Syifa’ah Setya Mega Reski4, Julia Miftahuddin Fahmi Miftahus Surur, Miftahus Miko Wardani Mitra Adhimukti Moch. Nasheh Annafii Muchamad Kurniawan Muchlas Muchlas Muchlas Muchlas, Muchlas Mudinillah, Adam Muflih, Ghufron Zaida Muh. Fadli Hasa Muhamad Caesar Febriansyah Putra Muhamad Caesar Febriansyah Putra, Muhamad Caesar Febriansyah Muhamad Fahrul Reza Muhamad Rosidin Muhammad Aris Fajar Ilmawan Muhammad Darso Muhammad Irfan Pure Muhammad Jundullah Muhammad Kunta Biddinika Muhammad Kunta Biddinika Muhammad Miftahul Amri Muhammad Noor Fadillah Muhammad Noor Fadillah Muhammad Nur Faiz Muhammad Nur Faiz Muhammad Rizki Setyawan Muhammad Sabiq Dzakwan Muhammad Sabiq Dzakwan Muhammad, Khairul Muis, Alwas Mukaromah, Iif Alfiatul Murinto Murinto Mushab Al Barra Mushlihudin Mushlihudin Mushlihudin Mushlihudin Mushlihudin, Mushlihudin Mushlihudin, Mushlihudin Musliman, Anwar Siswanto Nathalie Japkowicz Novitasari, Putri Rachma Nuraeni, Eneng Nuryana, Zalik Nuryono Satya Widodo Ockhy Jey Fhiter Wassalam Peryanto, Ari Prasongko, Riski Yudhi Pratama, Denny Yoga Pratama, Genta Pratama, Gilang Ariya PRATAMA, IGO PUTRA prayudi, Andi Prianto, Eko Prihatmadi, Farhan Adyaqsa Priyatno Priyatno Putra, Aji Surya Kurniawan Putra, Marta Dwi Darma Putra, Satriya Dwi Putra, Seno Aji Putri, Dadva Pramesty Etsria Rachmad Fitriyanto Rachmad Very Ananda Saputra Raden Mohamad Herdian Bhakti Rafal Drezewski Rahmawan, Jihad Raja Bidin Raja Hassan Ramadhani, Muhammad Ramdhani, Rezki Rani Rotul Muhima Rauhulloh Ayatulloh Khomeini Noor Bintang Renangga Yudianto Reski, Julia Mega Resmi Aini Retnosyari Septiyani Reza, Muhamad Fahrul Rezki Ramdhani Rio Subandi Riski Prasongko Yudhi Prasongko Riski Yudhi Prasongko Rizky Andhika Surya Rosyady, Phisca Aditya Ruly Erwin AfanDika Rumagia, Yusril Rusdi Umar Rusydi Umar Rusydi Umar Rusydi Umar Rusydi Umar S, Sunardi Sabarudin Saputra Saberi Mawi Sabila, Liya Yusrina Safiq Rosad Sahta, Bobo Saifullah, Shoffan Samadri Samadri Saputra, Candra Deska Saputra, I Gede Purwana Edi saputro, tahap Sarjimin Sarjimin Sarjimin, Sarjimin Satriya Dwi Putra Sefindra Purnama Seno Aji Putra Septa, Frandika Septiyani, Retnosyari Septiyawan Rosetya Wardhana Sharipah Salwa Mohamed Shoffan Saifullah Sidharta, Anggara Ibnu Sidiq, Ahmad Fajar Sigit Wijaya Silmina, Esi Putri Siswaya Siswaya Siswaya, Siswaya Siti Hajar Siti Helmiyah Siti Helmiyah Son Ali Akbar sri suharti Sri Suharti Subandi, Rio Sulistyo, Andhy Sunardi Sunardi - Sunardi - Sunardi Sunardi sunardi sunardi Sunardi, Sunardi Suwanti Suwanti Suyadi Suyadi Syahid Al Irfan Syahrani Lonang Syed Abdullah Syinta Brata Tarisno Amijoyo Tiara Widyakunthaningrum Tole Sutikno Tri Wahono Tugiman Tugiman Umar, Rusydi Ummi Syafiqoh Ummi Syafiqoh Utama, Kgs Muhammad Rizky Alditra Utama, Kiagus Muhammad Rizky Aditra W, Yunanri Wahidah Mahanani Rahayu Wahyu Prawoto Wahyu Sapto Aji Wardani, Miko Wicaksono Yuli Sulistyo Wicaksono Yuli Sulistyo Widhianto, Trisno Wijaya, Setiawan Ardi Wilis Kaswijanti Windra Putri, Anggi Rizky Wintolo, Hero Yudianto, Renangga Zeehaida Mohamed