Article Per Year (5 Year)
p-Index From 2021 - 2026
14.689
P-Index
This Author published in this journals
All Journal International Journal of Electrical and Computer Engineering IJCCS (Indonesian Journal of Computing and Cybernetics Systems) JURNAL SISTEM INFORMASI BISNIS Proceedings of KNASTIK Techno.Com: Jurnal Teknologi Informasi TELKOMNIKA (Telecommunication Computing Electronics and Control) Bulletin of Electrical Engineering and Informatics Jurnal Informatika SPEKTRUM INDUSTRI Jurnal Sarjana Teknik Informatika Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI) Jurnal Teknik Elektro Bulletin of Electrical Engineering and Informatics Jurnal Teknologi Jurnal Pseudocode Jurnal Teknologi Informasi dan Ilmu Komputer Telematika Jurnal Edukasi dan Penelitian Informatika (JEPIN) JUITA : Jurnal Informatika Scientific Journal of Informatics Seminar Nasional Informatika (SEMNASIF) Jurnas Nasional Teknologi dan Sistem Informasi JURNAL PENGABDIAN KEPADA MASYARAKAT Jurnal Teknologi Elektro INFORMAL: Informatics Journal Proceeding SENDI_U Khazanah Informatika: Jurnal Ilmu Komputer dan Informatika KLIK (Kumpulan jurnaL Ilmu Komputer) (e-Journal) Bulletin of Electrical Engineering and Informatics JOIN (Jurnal Online Informatika) Edu Komputika Journal Jurnal Teknologi dan Sistem Komputer JOIV : International Journal on Informatics Visualization Sinkron : Jurnal dan Penelitian Teknik Informatika Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) International Journal of Artificial Intelligence Research Jurnal Informatika Jurnal Khatulistiwa Informatika Journal of Information Technology and Computer Science (JOINTECS) Jurnal Ilmiah FIFO INTENSIF: Jurnal Ilmiah Penelitian dan Penerapan Teknologi Sistem Informasi AKSIOLOGIYA : Jurnal Pengabdian Kepada Masyarakat JURNAL MEDIA INFORMATIKA BUDIDARMA Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control CogITo Smart Journal IT JOURNAL RESEARCH AND DEVELOPMENT InComTech: Jurnal Telekomunikasi dan Komputer Insect (Informatics and Security) : Jurnal Teknik Informatika JOURNAL OF APPLIED INFORMATICS AND COMPUTING JURNAL REKAYASA TEKNOLOGI INFORMASI PROCESSOR Jurnal Ilmiah Sistem Informasi, Teknologi Informasi dan Sistem Komputer Applied Information System and Management ILKOM Jurnal Ilmiah Compiler MATRIK : Jurnal Manajemen, Teknik Informatika, dan Rekayasa Komputer Jurnal Teknologi Sistem Informasi dan Aplikasi CYBERNETICS Digital Zone: Jurnal Teknologi Informasi dan Komunikasi J-SAKTI (Jurnal Sains Komputer dan Informatika) JUMANJI (Jurnal Masyarakat Informatika Unjani) JURTEKSI RESISTOR (Elektronika Kendali Telekomunikasi Tenaga Listrik Komputer) Komputasi: Jurnal Ilmiah Ilmu Komputer dan Matematika Informatika : Jurnal Informatika, Manajemen dan Komputer Jurnal Ilmiah Mandala Education (JIME) JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Systemic: Information System and Informatics Journal EDUMATIC: Jurnal Pendidikan Informatika Building of Informatics, Technology and Science Jurnal Mantik Jutisi: Jurnal Ilmiah Teknik Informatika dan Sistem Informasi JISKa (Jurnal Informatika Sunan Kalijaga) Buletin Ilmiah Sarjana Teknik Elektro Mobile and Forensics Aviation Electronics, Information Technology, Telecommunications, Electricals, Controls (AVITEC) Journal of Robotics and Control (JRC) Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) Cyber Security dan Forensik Digital (CSFD) JTIULM (Jurnal Teknologi Informasi Universitas Lambung Mangkurat) International Journal of Advances in Data and Information Systems International Journal of Marine Engineering Innovation and Research Edunesia : jurnal Ilmiah Pendidikan Journal of Innovation Information Technology and Application (JINITA) Tematik : Jurnal Teknologi Informasi Komunikasi Infotech: Journal of Technology Information Jurnal Teknologi Informatika dan Komputer Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) Jurnal Teknik Informatika (JUTIF) JURPIKAT (Jurnal Pengabdian Kepada Masyarakat) Humanism : Jurnal Pengabdian Masyarakat International Journal of Robotics and Control Systems J-SAKTI (Jurnal Sains Komputer dan Informatika) Jurnal Informatika Teknologi dan Sains (Jinteks) Jurnal Algoritma Techno Jurnal Pengabdian Informatika (JUPITA) Jurnal INFOTEL Jurnal Informatika Polinema (JIP) Jurnal Informatika: Jurnal Pengembangan IT Jurnal Accounting Information System (AIMS) Scientific Journal of Informatics Control Systems and Optimization Letters Signal and Image Processing Letters Scientific Journal of Engineering Research SEMINAR TEKNOLOGI MAJALENGKA (STIMA) Edumaspul: Jurnal Pendidikan Methods in Science and Technology Studies JOCHAC
Abdul Fadlil
Ahmad Dahlan University
Religion Aerospace Engineering Arts Humanities Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry 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 Public Health Social Sciences Transportation Other

Published : 216 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 216 Documents
Search

 14   15   16   17   18 
Sistem Pemilihan Karyawan Terbaik Menggunakan Metode TOPSIS Nasution, Musri Iskandar; Fadlil, Abdul; Sunardi, S
J-SAKTI (Jurnal Sains Komputer dan Informatika) Vol 4, No 2 (2020): EDISI SEPTEMBER
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/j-sakti.v4i2.219

Abstract

Merapi Online Corporation is a company located in Yogyakarta which is engaged in internet access services. Merapi Online Corporation gives rewards by selecting the best employees based on criteria as a provision of the company. This study designed a system to determine the best employee selection using a Decision Support System (DSS) with the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method. The TOPSIS method has the principle chosen because it has the shortest distance to positive ideal solution and the farthest distance from the negative ideal solution from a geometric point of view using Euclidean distance to determine the relative closeness of choice with the best solution. The stages of this research are the collection of employee and criteria data, then weighting the criteria and assessment, after that the calculation uses the TOPSIS method, and the final step is the analysis of the calculation results. The criteria used in this study are attendance, years of service, permission, and discipline. Research has been successfully carried out on a sample of four employees for ease in presenting the data. The results of this study obtained the preferences of each employee, which is then ranked. The biggest preference value is chosen to be the best employee.
Segmentasi Citra Kupu-Kupu Menggunakan Metode Multilevel Thresholding Maftukhah, Ainin; Fadlil, Abdul; Sunardi, S
J-SAKTI (Jurnal Sains Komputer dan Informatika) Vol 7, No 2 (2023): EDISI SEPTEMBER
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/j-sakti.v7i2.665

Abstract

Land conversion, pollution, logging, and the use of pesticides are the main causes of butterfly extinction. This used 50 types of butterflies using different RGB colors obtained from the Kaggle website. The goal is to separate the butterfly object from the background and produce the best accuracy from the segmentation proses. The method used is Multilevel Thresholding. The results of preprocessing on the image using Multilevel Thresholding segmentation are able to identify colors and butterfly objects. The first step is RGB image input, then the image is Segmented using Multilevel Thresholding. After that, the output is displaying the image, and using a threshold value of 0-255 with the results of image segmentation, the threshold value separates the object and the background. Multilevel Thresholding segmentation with color and shape identification obtains threshold values of 100 from the dataset train, 100, and 110 from the test dataset and 140, and 150 from the validation dataset. It was concluded that the results of threshold value of the Multilevel Thresholding segmentation obtained good results
Identifikasi Tulisan Tangan Huruf Katakana Jepang Dengan Metode Euclidean Riadi, Imam; Fadlil, Abdul; Annisa, Putri
J-SAKTI (Jurnal Sains Komputer dan Informatika) Vol 4, No 1 (2020): EDISI MARET
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/j-sakti.v4i1.184

Abstract

Katakana is one of the traditional Japanese letters used to absorption words from other languanges. In the inttroduction of an object a learning process is needed, which is obtained through the characteristics and experience of observing similar objects after being acquired. But manually it is quite difficult to distinguish between 5 hiragana vowels starting from the image data acquisition process, image processing, feature extraction using Gray Level Co-occurance Matrix (GLCM) while classifiers use the euclidean distance method. The results of the tests carried out showed an accuracy rate of around 78% using the euclidean method.
Analisis Forensik Aplikasi Dropbox pada Android menggunakan Metode NIJ pada Kasus Penyembunyian Berkas Saad, Saleh Khalifah; Umar, Rusydi; Fadlil, Abdul
J-SAKTI (Jurnal Sains Komputer dan Informatika) Vol 4, No 2 (2020): EDISI SEPTEMBER
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/j-sakti.v4i2.221

Abstract

Smartphones are a testament to the development of digital technology. At this time, the smartphone is also experiencing growth in storage media, one of which is the Cloud storage media. One cloud storage application is the Dropbox Application. The development of cloud storage media does not rule out the possibility of a negative impact on the use or can be used as a medium for crime, such as storing evidence of criminal transactions and cybercrime. This study uses conversation scenarios for application conditions, including data deletion in applications. Data for each experiment will be taken using the National Institute of Justice (NIJ) Method. The method used in dealing with crime with smartphone media evidence is the National Institute of Justice (NIJ) Method. The conclusion of this study is that the use of the National Institute of Justice (NIJ) method ranks the digital forensic stages, starting with identification, collection, examination, analysis, and reporting very well. This method is widely used in handling digital crime cases. The results of the acquisition will then be analyzed by translating the hex codes resulting from the acquisition to produce evidence that can be understood by the judge later.
Evaluasi Optimalisasi Alat Forensik Keamanan Jaringan pada Lalu Lintas Virtual Router Firmansyah, Firmansyah; Fadlil, Abdul; Umar, Rusydi
Edu Komputika Journal Vol 10 No 2 (2023): Edu Komputika Journal
Publisher : Jurusan Teknik Elektro Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/edukomputika.v10i2.66963

Abstract

Penelitian ini bertujuan untuk mengevaluasi optimalisasi alat forensik keamanan jaringan pada lalu lintas virtual router (VR). Metodologi yang digunakan meliputi pemilihan beberapa alat forensik pada sistem operasi Windows seperti Wireshark, Windump, dan Network Miner, dengan pengujian dalam lingkungan jaringan virtual. Pengujian, mencakup simulasi berbagai skenario serangan untuk menilai efektivitas deteksi ancaman, kinerja alat forensik, dan dampak terhadap kinerja jaringan. Hasil utama menunjukkan bahwa alat-alat tersebut memiliki kemampuan deteksi yang beragam dengan variasi penggunaan sumber daya dan dampak pada latensi jaringan. Lalu lintas jaringan telah berhasil di rekam menggunakan alat Win-dump pada metode static forensik, alat Wireshark dan Network Miner pada metode live forensics. Hasil evaluasi alat rekam forensik jaringan meta-router merekomendasikan Win-dump sebagai alat rekam yang tidak membebani sistem operasi windows dengan penggunaan Memory adalah 1696 kb sedangkan aplikasi Wireshark dan Network Miner tercatat lebih dari 20MB. Berdasarkan penelitian ini metode static forensic yang telah dibangun dengan objek meta-router dapat digunakan investigator untuk mendeteksi serangan siber. Pemilihan dan konfigurasi yang tepat dari alat forensik sangat penting untuk mencapai keseimbangan antara keamanan dan kinerja jaringan, serta penyesuaian spesifik terhadap kebutuhan jaringan dapat meningkatkan efektivitas deteksi dan mitigasi ancaman.
Implementation of Word Trends Using a Machine Learning Approach with TF-IDF and Latent Dirichlet Allocation Rifaldi, Dianda; Fadlil, Abdul; Herman, -
JOIV : International Journal on Informatics Visualization Vol 8, No 4 (2024)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/joiv.8.4.2452

Abstract

In today's technological age, the prevalence of social media has become ubiquitous, facilitating the easy dissemination of information and communication. This has led to the uploading of various content, including opinions on mental health, particularly in Indonesia. Mental health refers to an individual's emotional, psychological, and social well-being, commonly affecting individuals from adolescence to adulthood. This research utilized Twitter data on mental health issues gathered from October to November 2022, employing TF-IDF and Latent Dirichlet Allocation (LDA) to conduct topic modeling for word trend analysis based on user-generated content. The sentiment analysis concept was used to label text as either negative or positive sentiment. Subsequently, TF-IDF weighed the word frequency in the documents/tweets, categorizing the data based on the resulting sentiments. Manual labeling ensured accuracy, avoiding potential errors from libraries provided in the Indonesian language. Employing these two topic modeling techniques, conclusions were drawn for each concept, aiming to identify word trends, mainly focusing on mental health discourse within Twitter user-generated content. Results indicated the synchronicity of the keyword 'mental health' with word trends generated by LDA. At the same time, TF-IDF produced word trends based on positive and negative labels, revealing commonly used terms by Twitter users to express these concerns. Furthermore, subsequent research can be experimented by comparing topic modeling techniques using Latent Semantic Allocation (LSA), Probabilistic Latent Semantic Analysis (pLSA), and Hierarchical Dirichlet Process (HDP), where LSA and pLSA present approaches closely aligned with LDA.
Pengaruh Seleksi Fitur Terhadap Klasifikasi Indeks Standar Pencemar Udara Menggunakan Naïve Bayes Irjayana, Rizky Caesar; Fadlil, Abdul; Umar, Rusydi
Insect (Informatics and Security): Jurnal Teknik Informatika Vol. 11 No. 1 (2025): Maret 2025
Publisher : Universitas Muhammadiyah Sorong

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33506/insect.v11i1.4303

Abstract

Tujuan penelitian ini adalah untuk mengklasifikasikan kualitas udara sesuai dengan Indeks Standar Pencemar Udara (ISPU) menggunakan algoritma Naïve Bayes serta mengevaluasi dampak penambahan fitur PM2.5 terhadap akurasi model dengan membagi dataset kedalam tiga kategori diantaranya BAIK, SEDANG dan TIDAK SEHAT. ISPU merupakan indikator penting dalam mengukur kualitas udara berdasarkan konsentrasi polutan seperti PM10, PM2.5, SO2, CO, O3, NO2 dan HC. Dengan tingginya volume data yang dikumpulkan setiap hari, diperlukan metode klasifikasi yang efektif untuk menyampaikan data kualitas udara dengan tepat. Penelitian ini mengusulkan dua skenario klasifikasi berdasarkan Peraturan NOMOR P.14/MENLHK/SETJEN/KUM.1/7/2020, yaitu: tanpa fitur PM2.5 dan dengan fitur PM2.5. Evaluasi dilakukan menggunakan K-Fold Cross Validation dengan K = 2, 3, 4, dan 5, dimana K = 5 menghasilkan akurasi tertinggi. Hasil penelitian menunjukkan bahwa penambahan fitur PM2.5 meningkatkan akurasi model dari 82,89% menjadi 93% dan F1-score dari 82,6% menjadi 92,8%, menunjukkan peningkatan sekitar 10%. Kontribusi utama penelitian ini adalah analisis komprehensif terhadap dampak fitur PM2.5 serta evaluasi berbagai nilai K dalam K-Fold Cross Validation. Dengan demikian, penemuan ini dapat menjadi sumbangsih ilmu pengetahuan pada ranah pengembangan sistem pemantauan kualitas udara yang lebih akurat untuk mendukung kebijakan lingkungan dan kesehatan masyarakat.
Improving the Accuracy of Batik Classification using Deep Convolutional Auto Encoder Dzulqarnain, Muhammad Faqih; Fadlil, Abdul; Riadi, Imam
Compiler Vol 13, No 2 (2024): November
Publisher : Institut Teknologi Dirgantara Adisutjipto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28989/compiler.v13i2.2649

Abstract

This research investigates the development of model deep convolutional autoencoders to enhance the classification of digital batik images. The dataset used was sourced from Kaggle. The autoencoder was employed to enrich the image data prior to convolutional processing. By forcing the autoencoder to learn a lower-dimensional latent representation that captures the most salient features of the batik patterns. The performance of this enhanced model was compared against a standard convolutional neural network (CNN) without the autoencoder. Experimental results demonstrate that the incorporation of the autoencoder significantly improved the classification accuracy, achieving 99% accuracy on the testing data and loss value of 3.4%. This study highlights the potential of deep convolutional autoencoders as a powerful tool for augmenting image data and improving the performance of deep learning models in the context of batik image classification.
Comparison of Machine Learning Methods for Predicting Electrical Energy Consumption Wahyusari, Retno; Sunardi, Sunardi; Fadlil, Abdul
Aviation Electronics, Information Technology, Telecommunications, Electricals, and Controls (AVITEC) Vol 7, No 1 (2025): February
Publisher : Institut Teknologi Dirgantara Adisutjipto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28989/avitec.v7i1.2722

Abstract

This research investigates how to accurately predict electrical energy consumption to address growing global energy demands. The study employs three Machine Learning (ML) models: k-Nearest Neighbors (KNN), Random Forest (RF), and CatBoost. To enhance prediction accuracy, the researchers included a data pre-processing step using min-max normalization. The analysis utilized a dataset containing 52,416 records of power consumption from Tetouan City. The dataset was divided into training and testing sets using different ratios (90:10, 80:20, 50:50) to evaluate model performance. Root Mean Square Error (RMSE) and Mean Absolute Percentage Error (MAPE) were used to assess prediction accuracy. Min-max normalization significantly improved KNN's performance (reduced RMSE and MAPE). RF achieved similar accuracy with and without normalization. CatBoost also demonstrated stable performance regardless of normalization. Data pre-processing, specifically min-max normalization, is crucial for improving the accuracy of distance-based algorithms like KNN. Decision tree-based algorithms like RF and CatBoost are less sensitive to data normalization. These findings emphasize the importance of selecting appropriate pre-processing techniques to optimize energy consumption prediction models, which can contribute to better energy management strategies.
SISTEM PENGENALAN CITRA JENIS-JENIS TEKSTIL Abdul Fadlil
Spektrum Industri Vol. 10 No. 1: April 2012
Publisher : Universitas Ahmad Dahlan Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/si.v10i1.1617

Abstract

Sistem pengenalan untuk identifikasi tekstil berbasis komputer merupakan proses memasukkan informasi berupa citra kain ke dalam komputer. Selanjutnya komputer menterjemahkan serta mengidentifikasi jenis kain tersebut. Pada penelitian ini telah dilakukan perancangan sistem identifikasi tekstil yang memanfatkan mikroskop digital untuk akuisisi data citra kain. Selanjutnya dilakukan pemrosesan awal, ekstraksi ciri dan pengklasifikasi. Pada pengembangan sistem ini terdiri 2 yaitu tahap penetuan pola standar referensi dan pengujian. Data yang digunakan sebagai standar refrensi sebanyak 5 sampel untuk masing-masing jenis kain yaitu blacu, finished dan rajut. Sedangkan untuk pengujian unjuk kerja sistem menggunakan 100 sampel untuk masing- masing jenis kain. Pengujian unjuk kerja sistem dilakukan dengan melakukan variasi ukuran citra dan metode metrik jarak. Hasil pengujian sistem identifikasi citra kain menunjukkan tingkat akurasi yang tinggi sebesar 93% untuk ukuran citra asli 600x800 dengan metode ekstraksi ciri histogram dan teknik klasifikasi metrik jarak Squared Chi Squared. Kata kunci: Identifikasi Kain, Histogram, Metrik Jarak
Co-Authors Aang Anwarudin Abdul Azis Achmad Nugrahantoro Aditiya Dwi Candra Ahmad Naufal, Ahmad Ahmat Taufik Aji Pamungkas Akrom, Akrom Alfiansyah Imanda Putra Alfiansyah Imanda Putra Alfian Amiruddin, Nanda Fahmi Andrianto, Fiki Anggit Pamungkas Annisa, Putri Anton Yudhana Anwar Siswanto ANWAR, FAHMI ardi, Ardi Pujiyanta Arief Setyo Nugroho Arief Setyo Nugroho Arif Budi Setianto Arif Budiman Arif Budiman Arif Wirawan Muhammad Aris Rakhmadi Asep Ririh Riswaya Asno Azzawagama Firdaus Atmojo, Dimas Murtia Aulia, Aulia Az-Zahra, Rifqi Rahmatika Aznar Abdillah, Muhamad Bagus Primantoro Bashor Fauzan Muthohirin Basir, Azhar Budiman, Dheni Apriantsani Candra, Aditiya Dwi Darajat, Muhammad Nashiruddin Davito Rasendriya Rizqullah Putra Dewi Soyusiawaty Dewi Soyusiawaty Dhimas Dwiki Sanjaya Dian Permata Sari Dianda Rifaldi Dikky Praseptian M Dimas Murtia Atmojo Doddy Teguh Yuwono Dwi Susanto Dwi Susanto Edy Fathurrozaq Egi Dio Bagus Sudewo Eko Budi Cahyono Eko Prianto Eko Prianto Elvina, Ade Ermin Al Munawar Ermin Ermin Esthi Dyah Rikhiana Fahmi Anwar Fahmi Auliya Tsani Fahmi Auliya Tsani Fahmi Fachri Fanani, Galih Faqihuddin Al-anshori Faqihuddin Al-Anshori, Faqihuddin Fathurrahman, Haris Imam Karim Fauzi Hermawan Fiki Andrianto Firmansyah Firmansyah Firmansyah Firmansyah Firmansyah Yasin Fitri Muwardi Furizal Gusrin, Muhaimin Gustina, Sapriani Hafizh, Muhammad Nasir Haksono, Muhammad Rizky Hanif, Abdullah Hanif, Kharis Hudaiby Harman, Rika Helmiyah, Siti Hendril Satrian Purnama Herdiyanto, Erik Herman Herman Herman Yuliansyah, Herman Herman, - Ibnu Rifajar Ibrahim Mohd Alsofyani Ibrahim, Rohmat Ihyak Ulumuddin Ikhsan hidayat Ilhamsyah Muhammad Nurdin Imam Riadi Imam Riadi Imam Riadi Imam Riadi Imam Riadi Imam Riadi Imam Riadi Irjayana, Rizky Caesar Irwansyah Irwansyah Izzan Julda D.E Purwadi Putra januari audrey Jayawarsa, A.A. Ketut Jogo Samodro, Maulana Muhamammad Joko Supriyanto Joko Supriyanto Kamilah, Farhah Kartika Firdausy Khoirunnisa, Itsnaini Irvina Kusuma, Nur Makkie Perdana Laura Sari Lestari, Yuniarti Lin, Yu-Hao Luh Putu Ratna Sundari M. Nasir Hafizh Maftukhah, Ainin Maulana Muhammad Jogo Samudro Mini, Ros Mohd Hatta Jopri Muammar Mudinillah, Adam Mufaddal Al Baqir Muh. Fadli Hasa Muhaimin Gusrin Muhajir Yunus Muhamad Daffa Al Fitra Muhamad Rosidin Muhammad Faqih Dzulqarnain, Muhammad Faqih Muhammad Johan Wahyudi Muhammad Kunta Biddinika Muhammad Ma’ruf Muhammad Nasir Hafizh Muhammad Nur Faiz Muhammad Nurdin, Ilhamsyah Muhammad Rizki Setyawan Mukti, Sindhu Hari Muntiari, Novita Ranti Murinto Murinto - Murinto Murinto Murni Murni Musliman, Anwar Siswanto Mustofa Mustofa Muthorihin, Bashor Fauzan Mutiara Titani Muwardi, Fitri Nasution, Dewi Sahara Nasution, Musri Iskandar Nilam Tri Astuti Nurwijayanti Pahlevi, Ryan Fitrian Ponco Sukaswanto Poni Wijayanti Prabowo Soetadji Prabowo, Basit Adhi Prayogi, Denis Priambodo, Bambang Putra, Fajar R. B Putri Annisa Putri Annisa Putri Purnamasari Putri Silmina, Esi Ramadhani, Muhammad Ramdhani, Rezki Razak, Farhan Radhiansyah Rezki Rezki Rifqi Rahmatika Az-Zahra Rizky Andhika Surya Rochmadi, Tri Roni Anggara Putra Rusydi Umar Rusydi Umar S Sunardi S, Sunardi Saad, Saleh Khalifah Safiq Rosad Saifudin Saifudin Saifullah, Shoffan Saleh khalifa saad Santi Purwaningrum Sarmini Sarmini Septa, Frandika Setyaputri, Khairina Eka Setyaputri, Khairina Eka Setyaputri, Khairina Eka Shinta Nur Desmia Sari Siswahyudianto Siti Helmiyah Sri Winiarti Subandi, Rio Sukaswanto, Ponco Sukma Aji Sulis Triyanto Sunardi Sunardi Sunardi Sunardi, Sunardi Surya Yeki Surya Yeki Syamsiar, Syamsiar Syarifudin, Arma Tole Sutikno Tresna Yudha Prawira Tri Ferga Prasetyo Tristanti, Novi Tuswanto Tuswanto Virdiana Sriviana Fatmawaty Wahju Tjahjo Saputro Wahyusari, Retno Winoto, Sakti Wintolo, Hero Wulandari, Cisi Fitri Yana Mulyana Yana Mulyana Yasidah Nur Istiqomah Yeki, Surya Yohanni Syahra Yossi Octavina Yuantoro, Jody Yulianto, Dinan Yulianto, Muhammad Anas Yuminah yuminah yuminah, Yuminah Yuminah, Yuminah Yuwono Fitri Widodo Zein, Wahid Alfaridsi Achmad Zulhijayanto -