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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 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 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 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) 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 Edunesia : jurnal Ilmiah Pendidikan Journal of Innovation Information Technology and Application (JINITA) 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) Techno Jurnal Pengabdian Informatika (JUPITA) Jurnal INFOTEL Jurnal Informatika: Jurnal Pengembangan IT Scientific Journal of Informatics Jurnal Karya untuk Masyarakat (JKuM) 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
Abdul Fadlil
Ahmad Dahlan University
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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
MEMBANGUN JEJAK DIGITAL POSITIF: CARA MEMANFAATKAN MEDIA SOSIAL SECARA PRODUKTIF Muammar; Razak, Farhan Radhiansyah; Fadlil, Abdul; Herman
Jurnal Pengabdian Informatika Vol. 2 No. 4 (2024): JUPITA Volume 2 Nomor 4, Agustus 2024
Publisher : Jurusan Informatika, Fakultas Matematika dan Ilmu Pengetahuan Alam, Universitas Udayana

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

Abstract

Penelitian ini mengeksplorasi pentingnya membangun jejak digital positif dan pemanfaatan media sosial secara produktif di kalangan siswa SMK 1 Al-Hikmah 1 Bumiayu. Dengan semakin meningkatnya penggunaan media sosial di Indonesia, siswa seringkali tidak menyadari dampak jangka panjang dari aktivitas mereka di dunia maya. Penelitian ini dilakukan melalui Program Pemberdaya Umat (Prodamat) yang bertujuan untuk meningkatkan kesadaran dan kewaspadaan terhadap jejak digital. Metode penelitian meliputi sosialisasi, pre-test dan post-test kuisioner, penyuluhan edukatif, pelatihan, observasi, serta wawancara. Hasil penelitian menunjukkan peningkatan pemahaman siswa mengenai pentingnya jejak digital dan cara memanfaatkan media sosial secara produktif. Edukasi yang diberikan melalui program ini terbukti efektif dalam meningkatkan pengetahuan siswa tentang jejak digital dan membantu mereka membangun reputasi online yang positif.
Pengembangan Korpus Bahasa Minang pada Spell Error Corpus for Minang Language (SPEML) Soyusiawaty, Dewi; Fadlil, Abdul; Sunardi, Sunardi
Jurnal Nasional Teknologi dan Sistem Informasi Vol 11 No 1 (2025): April 2025
Publisher : Departemen Sistem Informasi, Fakultas Teknologi Informasi, Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/TEKNOSI.v11i01.2025.17-26

Abstract

Bahasa Minang merupakan bahasa daerah kelima dengan jumlah penutur terbanyak di Indonesia, namun minim sumber daya linguistik dan teknologi pemrosesan bahasa alami yang mendukung. Keterbatasan ini menyulitkan pengembangan aplikasi seperti mesin penerjemah dan pemeriksa ejaan otomatis. Saat ini hanya tersedia korpus kesalahan ejaan dalam Bahasa Indonesia dengan kesalahan hanya satu karakter pada setiap token. Korpus belum mencakup kesalahan penulisan kata serapan. Selain itu belum ada korpus khusus yang dikembangkan untuk kesalahan ejaan dalam bahasa daerah di Indonesia, termasuk Bahasa Minang. Penelitian ini bertujuan mengembangkan korpus kesalahan ejaan Bahasa Minang, yang dinamakan Spell Error Corpus for Minang Language (SPEML). SPEML mencakup kesalahan ejaan sampai dengan tiga karakter dan kesalahan penulisan kata serapan. Pengembangan SPEML melibatkan proses pengumpulan data korpus Bahasa Minang, data kata serapan yang sering digunakan, serta pembentukan korpus kesalahan ejaan. Kesalahan ejaan dibentuk dengan mengacak token secara sistematis pada satu karakter, dua karakter, hingga tiga karakter, disesuaikan dengan panjang token. Hasil penelitian ini berupa SPEML yang mampu mengklasifikasikan tujuh jenis kesalahan ejaan, yaitu: penyisipan karakter, penghapusan karakter, pindah posisi karakter, penggantian karakter, kesalahan tanda baca, kesalahan kata nyata, dan kesalahan penulisan kata serapan. Pengembangan SPEML menjadi langkah awal dalam mendukung pengembangan teknologi pemrosesan bahasa alami untuk bahasa daerah, khususnya Bahasa Minang.
Real-Time Rice Leaf Disease Diagnosis: A Mobile CNN Application with Firebase Integration Azis, Abdul; Fadlil, Abdul; Sutikno, Tole
Jurnal Teknik Informatika (Jutif) Vol. 6 No. 3 (2025): JUTIF Volume 6, Number 3, Juni 2025
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2025.6.3.4452

Abstract

Rice, the staple food for the majority of Indonesia's population, faces significant production threats from leaf diseases, which can decrease yields and jeopardize national food security. Traditional manual identification of these diseases is a major challenge for farmers, as it is often subjective, prone to misdiagnosis leading to incorrect treatments, time-consuming, demands specialized expertise, and is difficult to implement widely for effective real-time early prevention, allowing diseases to spread and significantly impact crop yields. This research addresses these challenges by developing an automated and easily accessible rice leaf disease diagnosis system. The system is manifested as a mobile application that integrates a Convolutional Neural Network (CNN) model, specifically utilizing the EfficientNetB0 architecture, for the classification of rice leaf images and leverages key Firebase services such as its Realtime Database for data synchronization and Cloud Storage for image management to ensure a scalable and responsive backend. The methodology involved several key stages. Firstly, the CNN model was developed by employing a transfer learning approach on the pre-trained EfficientNetB0 architecture. Secondly, the model underwent comprehensive testing using a dataset of 1,000 new rice leaf images, which were independently validated by agricultural experts. The results demonstrated that the developed CNN model achieved a global accuracy of 85.9%, with an average precision of 86.1% and recall of 85.9% (macro-average) in the expert validation testing phase with the 1,000 new images. However, the study also identified variations in the model's performance across different disease classes, highlighting areas that require further optimization to enhance detection effectiveness for specific types of rice leaf diseases. The primary benefit of this research is the provision of a practical rice leaf disease diagnosis tool that is readily accessible to farmers via a mobile application, empowering them with timely and accurate information for effective crop management. This can lead to reduced crop losses, improved yield quality, and contribute significantly to national food security. Furthermore, this research contributes to the field of applied machine learning and mobile computing in resource-constrained agricultural environments, offering valuable insights for the development of impactful informatics solutions.
Comparative Analysis Of Ant Lion Optimization And Jaya Algorithm For Feature Selection In K-Nearest Neighbor (Knn) Based Electricity Consumption Prediction Wahyusari, Retno; Sunardi, Sunardi; Fadlil, Abdul
Jurnal Teknik Informatika (Jutif) Vol. 6 No. 3 (2025): JUTIF Volume 6, Number 3, Juni 2025
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2025.6.3.4692

Abstract

The increase in demand for electrical energy is in line with increasing population, urbanization, industrial deployment, and technology. Accurate prediction of electrical energy consumption plays an important role in planning, analyzing, and managing electricity systems to ensure sustainable, safe, and economical electricity supply. K-Nearest Neighbors (KNN) is a simple and fast prediction algorithm based on the quality and relevance of the features used. This research proposes to improve the accuracy of energy consumption prediction through feature selection based on metaheuristic algorithms, namely Genetic Algorithm (GA), Ant Lion Optimization (ALO), Teaching Learning Based Optimization (TLBO), and Jaya Algorithm (JA). The dataset used is Tetouan City Power Consumption, with a preprocessing process of time feature extraction, min-max scaling normalization, and feature selection. The ALO+KNN and JA+KNN combinations delivered the best and most stable prediction performance, while TLBO+KNN performed poorly. GA+KNN showed the worst overall results among all combinations. The evaluation of model performance was based on RMSE, MAPE, and R² metrics. These findings highlight the importance of selecting a feature selection algorithm that aligns well with the characteristics of the model and dataset to enhance prediction accuracy.
Customer Segmentation Using RFM and K-Means Clustering to Support CRM in Retail Industry Syahra, Yohanni; Fadlil, Abdul; Yuliansyah, Herman
Sinkron : jurnal dan penelitian teknik informatika Vol. 9 No. 3 (2025): Article Research July 2025
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v9i3.14907

Abstract

In today’s highly competitive retail landscape, businesses face increasing challenges in retaining customer loyalty and achieving sustainable growth. A common issue, particularly among small and medium-sized enterprises (SMEs), is the absence of a structured method for identifying and categorizing customers based on their value and behavior. This study addresses the challenge by implementing a data-driven customer segmentation approach using Recency, Frequency, and Monetary (RFM) analysis combined with the K-Means clustering algorithm. The research utilized 2,353 transaction records from 369 unique customers collected over three years from a local retail business. After preprocessing and normalizing the RFM values using Min-Max scaling, the Elbow Method was applied to determine the optimal number of clusters, resulting in four distinct customer segments. Cluster 3, labeled “Loyal Customers,” consisted of customers with high purchase frequency and very high spending; Cluster 1 (“Potential Loyalists”) included those with moderate activity; Cluster 0 represented “At-Risk Customers,” and Cluster 2 comprised “One-Time Buyers.” This segmentation framework supports the development of targeted Customer Relationship Management (CRM) strategies, such as loyalty programs and re-engagement campaigns. However, the approach also has limitations, including potential data bias due to the use of static transaction records and the challenge of interpreting clusters without qualitative customer feedback. Despite these constraints, the study demonstrates the practical utility of combining RFM analysis with clustering techniques to extract actionable insights in environments with limited technical infrastructure.
Mask Detection System at the Entry of a Room Herdiyanto, Erik; Fadlil, Abdul
Signal and Image Processing Letters Vol 5, No 1 (2023)
Publisher : Association for Scientific Computing Electrical and Engineering (ASCEE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/simple.v5i1.49

Abstract

This study focuses on automatic mask detection tools that can open doors in a room to minimize violations of health protocols, one of which is the use of masks during the pandemic. The method used in this study is the CNN classification method. Where the CNN calcification method has several stages in it, including pre-processing, training, and testing. In the pre-processing, all image data used will be labeled using Labeling.axe. The training process at CNN uses TensorFlow framework version 1.15. In the testing process, the test and data testing will be carried out in real-time by entering new images and models that are made and then a classification process is carried out on objects caught by the camera, classified images are marked with boxes and names of data classes. This data class is divided into two, namely data on wearing masks and without masks. The results of the test were carried out by entering 200 facial image data. The system can correctly detect as much as 190 times from 200 data tested with an Accuracy rate of 95%. Based on the test results, it shows that the resulting model is good and suitable for the classification process of recognizing mask detection images. However, to produce a better model requires data with more variety and a larger amount of data.
Real Time Clock (RTC) Module Based Dance Humanoid Robot Timer System Amiruddin, Nanda Fahmi; Fadlil, Abdul
Signal and Image Processing Letters Vol 5, No 2 (2023)
Publisher : Association for Scientific Computing Electrical and Engineering (ASCEE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/simple.v5i2.56

Abstract

The Indonesian Dance Robot Contest (KRSTI) is a competition for the manufacture, design, and programming of dance robots with elements of the arts and culture of the dance department, especially the archipelago. The obstacle faced by the robot is when the robot is required to stop according to time on the music but there is a movement that appears when the time has been declared over. The method used is using the RTC module. The DS3231 type RTC module is a circuit that functions to store time and date with accuracy and precision and is integrated with the AT24c32 eeprom serial for other data storage purposes. The results of time research testing on this robot are running well, the first results obtained are that the robot can adjust the time when it runs. Furthermore, at the time of pause the RTC module does not interfere with the running of the robot. Finally, the success rate of the robot stopping at the specified time is 100%, the robot can be tested with time according to the user's wishes.
Penggunaan Teknologi Tools Powerpoint dan Canva untuk Media Informasi Riadi, Imam; Fadlil, Abdul; Andrianto, Fiki; Elvina, Ade; Fanani, Galih; Nasution, Dewi Sahara
Aksiologiya: Jurnal Pengabdian Kepada Masyarakat Vol 6 No 2 (2022): Mei
Publisher : Universitas Muhammadiyah Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30651/aks.v6i2.11781

Abstract

Program pemberdayaan masyarakat ini bertujuan untuk menggunakan media Power Point dan Canva sebagai media penyampaian informasi yang inovatif dan meningkatkan soft skill desain. Pelatihan ini diikuti 15 mahasiswa baru program studi Sistem Informasi STIMIK Muhammadiyah Jakarta. Program ini melakukan 2 sesi pertemuan online melalui Zoom Meating karena Universitas mempraktikkan home learning, ada kebijakan tersebut terkait wabah Covid19. Pertemuan pertama memberikan materi tentang perkembangan teknologi dan media informasi sebagai tambahan wawasan. Pertemuan kedua memberikan tutorial tentang cara menggunakan Power Point dan tools Canva untuk mendesain informasi, yaitu desain sertifikat, desain undangan, desain animasi PPT, dan konten digital lainnya. Hasil tes pretest dan postest menunjukkan bahwa nilai presentase mahasiswa baru meningkat sebesar 13%. Hasil ini mengindikasikan adanya sedikit peningkatan dalam pengetahuan wawasan dan soft skill tentang teknologi media informasi. 
Co-Authors Aang Anwarudin Abdul Azis Achmad Nugrahantoro Aditiya Dwi Candra Ahmat Taufik Aji Pamungkas Alfiansyah Imanda Putra Alfiansyah Imanda Putra Alfian Amiruddin, Nanda Fahmi Andrianto, Fiki Anggit Pamungkas Annisa, Putri Anton Yudhana Anwar Siswanto ANWAR, FAHMI Arief Setyo Nugroho Arief Setyo Nugroho Arif Budi Setianto Arif Budiman Arif Budiman Arif Wirawan Muhammad Aris Rakhmadi Asno Azzawagama Firdaus Atmojo, Dimas Murtia Aulia, Aulia Az-Zahra, Rifqi Rahmatika Aznar Abdillah, Muhamad Bagus Primantoro Basir, Azhar Candra, Aditiya Dwi Darajat, Muhammad Nashiruddin Davito Rasendriya Rizqullah Putra 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 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 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 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 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 Muntiari, Novita Ranti Murinto Murinto - Murinto Murinto Murni Murni Musliman, Anwar Siswanto Mustofa Mustofa Muwardi, Fitri Nasution, Dewi Sahara Nasution, Musri Iskandar Nurwijayanti Pahlevi, Ryan Fitrian Ponco Sukaswanto Poni Wijayanti 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 Siti Helmiyah 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 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 Yulianto, Dinan Yulianto, Muhammad Anas Yuminah yuminah yuminah, Yuminah Yuminah, Yuminah Yuwono Fitri Widodo Zein, Wahid Alfaridsi Achmad Zulhijayanto -