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All Journal Jurnal Sains dan Teknologi Jurnal Simetris Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI) Journal of Telematics and Informatics Jurnal Simantec Jurnal sistem informasi, Teknologi informasi dan komputer Telematika : Jurnal Informatika dan Teknologi Informasi Jurnal Teknologi Informasi dan Ilmu Komputer Setrum : Sistem Kendali-Tenaga-elektronika-telekomunikasi-komputer Jurnal Transformatika Jurnal Edukasi dan Penelitian Informatika (JEPIN) JUITA : Jurnal Informatika Jurnal Informatika dan Teknik Elektro Terapan Jurnas Nasional Teknologi dan Sistem Informasi CESS (Journal of Computer Engineering, System and Science) Journal of Animation & Games Studies JOIN (Jurnal Online Informatika) Sistemasi: Jurnal Sistem Informasi Jurnal Pengabdian UntukMu NegeRI JOIV : International Journal on Informatics Visualization Sinkron : Jurnal dan Penelitian Teknik Informatika Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) JRSI (Jurnal Rekayasa Sistem dan Industri) Jurnal Pilar Nusa Mandiri Faktor Exacta Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Indonesian Journal of Information System JURNAL ILMIAH INFORMATIKA SELAPARANG: Jurnal Pengabdian Masyarakat Berkemajuan Jurnal ULTIMATICS Surya Abdimas MIND (Multimedia Artificial Intelligent Networking Database) Journal STRING (Satuan Tulisan Riset dan Inovasi Teknologi) Antivirus : Jurnal Ilmiah Teknik Informatika JUTIS : Jurnal Teknik Informatika JISKa (Jurnal Informatika Sunan Kalijaga) JATI (Jurnal Mahasiswa Teknik Informatika) Joined Journal (Journal of Informatics Education JATI EMAS (Jurnal Aplikasi Teknik dan Pengabdian Masyarakat) Journal of Innovation Information Technology and Application (JINITA) Jurnal Bakti Masyarakat Indonesia Innovation in Research of Informatics (INNOVATICS) Jurnal Dinamis Jurnal Teknik Informatika (JUTIF) Informatics and Digital Expert (INDEX) JURNAL REKAYASA INFORMASI SWADHARMA (JRIS) JUSTIN (Jurnal Sistem dan Teknologi Informasi) Jurnal Pengabdian Masyarakat untuk Negeri (UN-PENMAS) Jurnal Nasional Teknik Elektro dan Teknologi Informasi Ilmu Komputer untuk Masyarakat Abdi Teknoyasa Jurnal: International Journal of Engineering and Computer Science Applications (IJECSA) Jurnal Informatika dan Multimedia "JAMASTIKA" Jurnal Mahasiswa Teknik Informatika Tekmulogi: Jurnal Pengabdian Masyarakat SATIN - Sains dan Teknologi Informasi Prosiding SEMNAS INOTEK (Seminar Nasional Inovasi Teknologi) Intelmatics NERO (Networking Engineering Research Operation) Jurnal Informatika: Jurnal Pengembangan IT PADIMAS: Jurnal Pengabdian Masyarakat Jurnal Pengabdian Siliwangi Abdi Karya: Jurnal Pengabdian Kepada Masyarakat Khazanah Informatika : Jurnal Ilmu Komputer dan Informatika JuTISI (Jurnal Teknik Informatika dan Sistem Informasi) International Journal of Informatics and Computing Jasmine : Journal of Intelligent Systems and Machine Learning
Alam Rahmatulloh
Program Studi Informatika, Fakultas Teknik, Universitas Siliwangi
Religion Agriculture, Biological Sciences & Forestry Arts Humanities 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 Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Mechanical Engineering Medicine & Pharmacology Nursing Public Health Social Sciences Transportation Other

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IMPLEMENTASI JSON PARSING UNTUK PERTUKARAN DATA PADA APLIKASI VPN CLIENT BERBASIS MOBILE Guna, Nandana Surya; Rahmatulloh, Alam; Rachman, Andi Nur
NERO (Networking Engineering Research Operation) Vol 8, No 1 (2023): Nero - 2023
Publisher : Jurusan Teknik Informatika Fakultas Teknik Universitas Trunojoyo Madura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21107/nero.v8i1.20458

Abstract

Meningkatnya permintaan akan transmisi data yang aman pada perangkat mobile, penting untuk mengembangkan metode yang efisien untuk pertukaran data sambil menjaga integritas dan kerahasiaan informasi. Penelitian ini bertujuan untuk mengatasi masalah implementasi JSON Parsing dalam pertukaran data pada aplikasi klien VPN berbasis mobile menggunakan layanan web. Salah satu tantangan yang dihadapi selama proses pengembangan adalah pembatasan alamat IP web service. Untuk mengatasi pembatasan ini, pengguna harus menghubungkan perangkat ke jaringan VPN, yang memungkinkan untuk mengubah kata sandi dan membuat catatan kehadiran dengan aman. Penelitian ini juga mencakup pengujian penerimaan untuk mengevaluasi kinerja aplikasi. Hasil pengujian menunjukkan hasil yang memuaskan, menandakan keberhasilan implementasi JSON Parsing dan fungsi layanan web. Selain itu, pengujian kinerja jaringan mengungkapkan bahwa waktu respons dipengaruhi oleh metode dan lokasi jaringan yang dipilih. Waktu respons untuk pengambilan data kehadiran pada jaringan default adalah 1187 ms, namun respons untuk pengiriman data kehadiran dan pengubahan kata sandi adalah 403 karena web service membatasi akses dengan alamat IP. Sementara itu, jaringan SgVPN untuk permintaan pengubahan password memiliki waktu respons sekitar 1088 ms, pengambilan data kehadiran sekitar 1727 ms, dan pengiriman data kehadirans sekitar 955 ms. Sedangkan pada jaringan DeVPN, permintaan pengubahan password memiliki waktu respons sekitar 1264 ms, pengambilan data kehadiran sekitar 1793 ms, dan pengiriman data kehadirans sekitar 1351 ms. Temuan ini menekankan pentingnya mempertimbangkan lokasi jaringan dalam upaya mengoptimalkan waktu respons aplikasi.Kata kunci: Aplikasi Klien VPN, Jaringan VPN, JSON Parsing, Layanan Web, Waktu Respons
Analisis Malware Aquvaprn.exe Untuk Investigasi Sistem Operasi Dengan Metode Memory Forensics Aditya, Hafish Naufal; Widiyasono, Nur; Rahmatulloh, Alam
Jurnal Teknik Informatika dan Sistem Informasi Vol 10 No 2 (2024): JuTISI
Publisher : Maranatha University Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28932/jutisi.v10i2.6562

Abstract

In today's digital age, data has become a valuable asset. Various techniques are used to steal personal data that could potentially be misused by irresponsible parties. The object used in this study is AQUVAPRN.exe, which is a type of malware known as a Remote Access Trojan (RAT). When this malware runs, the creator of the malware can access personal data from the infected operating system without the user's knowledge. AQUVAPRN.exe works in the background when an application is executed, creating several processes such as modifying the registry, creating files, reading files, and making continuous internet connections to a specific IP address without the user's knowledge. The result obtained from the AQUVAPRN.exe malware is an IP address of 109.51.76.80, with the domain located in Lisbon, Portugal, and has an MD5 hash value of 55c2c12970cda52f58bfad7b8c7d37d5. It is also known that the AQUVAPRN.exe malware uses an anti-reverse engineering technique, specifically obfuscation, which obstructs or hinders the malware from being analyzed or reverse-engineered to determine the code used to create the malware. The PID of the AQUVAPRN.EXE process is 8332 with a virtual tool (Virtual Address) of 0x8e0f57042080.
Performance Analysis and Accuracy of Machine Learning Algorithms for Heart Disease Prediction Yuliasari, Silpani; Rahmatulloh, Alam
Telematika Vol 22 No 3 (2025): Edisi Oktober 2025
Publisher : Jurusan Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31315/telematika.v22i3.14022

Abstract

Purpose: This research aims to analyze the performance and accuracy of machine learning algorithms in predicting heart disease, which is a cause of death throughout the world.Design/methodology/approach: The algorithms analyzed include Logistic Regression, Naive Bayes, Support Vector Machine, K-Nearest Neighbors, Decision Tree, Random Forest, XGBoost, and Neural Network. A publicly available dataset containing patients' medical records was utilized, with the methodology encompassing data collection, Exploratory Data Analysis (EDA), model training, and performance evaluation.Findings/result: The results indicate that the Random Forest algorithm achieved the highest accuracy with an accuracy of 90.16%, followed by Logistic Regression and Naive Bayes with accuracies of 85.25%. The K-Nearest Neighbors algorithm exhibits the lowest accuracy at 67.21%.Originality/value/state of the art: This research highlights the advantages of certain machine learning algorithms in predicting heart disease and contributes knowledge to early detection technology in the health sector.
Analysis of the Effectiveness of Data Warehousing in Management Information Systems Using the Neural Networks Method Ginting, Muliani; Rahmatulloh, Alam
Telematika Vol 22 No 3 (2025): Edisi Oktober 2025
Publisher : Jurusan Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31315/telematika.v22i3.14027

Abstract

Purpose: The purpose of this research is to investigate the effectiveness of data warehousing and the application of Neural Networks methods in analyzing bicycle travel app user data, with a focus on enhancing the annual membership of app users in North America.Design/methodology/approach: This study utilizes a dataset that includes membership and usage data from relevant bicycle travel apps. It involves comparing the performance of different Neural Networks architectures, such as Feedforward Neural Networks, Convolutional Neural Networks (CNN), and other suitable models, to evaluate their effectiveness in predicting user membership.Findings/result: The analysis results demonstrate that the implementation of Neural Networks can improve prediction accuracy, with the most effective model achieving 76.03% accuracy. The research also highlights the importance of preprocessing steps, such as data normalization and transformation, in contributing significantly to model performance. However, challenges such as overfitting were identified, suggesting the need for further testing with model and parameter variations.Originality/value/state of the art: This research provides valuable insights for application developers and policy makers, helping them create data-driven strategies to improve the bicycle travel management information system. It also supports efforts to sustainably grow user membership. The study contributes to the field by exploring the practical application of Neural Networks for data analysis in the context of bicycle travel management, filling a gap in current research on effective predictive models for user membership growth.
Performance Analysis of SVM Kernels in Sentiment Classification on Indonesian Local Skincare Dataset Merdiriyani, Sindy; Rahmatulloh, Alam
Telematika Vol 22 No 3 (2025): Edisi Oktober 2025
Publisher : Jurusan Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31315/telematika.v22i3.14033

Abstract

Purpose: Sentiment analysis is an important aspect of understanding consumers' views on products, especially in the growing skincare industry. This study aims to compare the accuracy and effectiveness of various kernels in the Support Vector Machine (SVM) algorithm, including linear, polynomial (poly), and radial basis function (RBF) kernels, in predicting three types of sentiment: positive, neutral, and negative based on reviews of local Indonesian skincare products.Design/methodology/approach: The dataset used includes consumer reviews classified by rating, which are then processed using Term Frequency-Inverse Document Frequency (TF-IDF) technique for feature extraction.Findings/result: The evaluation results show that the RBF kernel achieves the highest accuracy of 74.78%, followed by the linear kernel with 74.51% accuracy, and the polynomial kernel with 74.10% accuracy. Although the difference between the three kernels is not significant, the RBF kernel excels in positive sentiment classification, while all three kernels struggle in predicting neutral and negative classes.Originality/value/state of the art: These findings make an important contribution to the development of effective sentiment analysis methods, especially in the context of datasets with high class imbalance. To handle class imbalance, techniques such as oversampling smaller classes or using cost-sensitive learning techniques to give more weight to negative and neutral classes can be used. 
Design Thinking Approach for User Interface Design and User Experience on Campus Academic Information Systems Darmawan, Irfan; Saiful Anwar, Muhammad; Rahmatulloh, Alam; Sulastri, Heni
JOIV : International Journal on Informatics Visualization Vol 6, No 2 (2022)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30630/joiv.6.2.997

Abstract

Abstract—Currently, an academic system with structured data is needed for all lecture institutions, especially universities in Indonesia, Siliwangi University, with its academic system, namely the Campus Academic Information System (SIMAK). Over time, complaints from the visual aspect and user experience that did not keep up with the times became a new problem for SIMAK with student access rights. Therefore, the UI/UX aspect in developing an application is vital in accessing the available features. In this study, the method applied is Design Thinking to develop SIMAK WEB and SIMAK MOBILE application designs according to the data and input obtained from users. The research stages include Empathize, Define, Ideate, Prototype, and Test. The final result is user testing from expert users with ten examiners, each producing a success rate percentage of 100% for SIMAK WEB and a percentage of 90% for SIMAK MOBILE. In addition, the User Experience Questionnaire (UEQ) assessment from the same expert user plus end-users of 39 respondents and 33 respondents for web and mobile respectively increased 6 UEQ scales, namely Attractiveness, Clarity, Efficiency, Accuracy, Stimulation and lastly especially Novelty which has an increase of 5.286 and 5.264 from the initial value of -0.880. The Novelty scale is the only scale with a negative impression initially and was successfully evaluated in this study with a good score. The implication for further research is that an in-depth study and application of unique methods regarding the conversion of designs into prototype form is necessary so that coding can run smoothly. Keywords— Design Thinking, Campus Academic System, User Experience, User Experience Questionnaire, User Interface
Identification of Mirai Botnet in IoT Environment through Denial-of-Service Attacks for Early Warning System Rahmatulloh, Alam; Muhammad Ramadhan, Galih; Darmawan, Irfan; Widiyasono, Nur; Pramesti, Dita
JOIV : International Journal on Informatics Visualization Vol 6, No 3 (2022)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30630/joiv.6.3.1262

Abstract

The development of computing technology in increasing the accessibility and agility of daily activities currently uses the Internet of Things (IoT). Over time, the increasing number of IoT device users impacts access and delivery of valuable data. This is the primary goal of cybercriminals to operate malicious software. In addition to the positive impact of using technology, it is also a negative impact that creates new problems in security attacks and cybercrimes. One of the most dangerous cyberattacks in the IoT environment is the Mirai botnet malware. The malware turns the user's device into a botnet to carry out Distributed Denial of Service (DDoS) attacks on other devices, which is undoubtedly very dangerous. Therefore, this study proposes a k-nearest neighbor algorithm to classify Mirai malware-type DDOS attacks on IoT device environments. The malware classification process was carried out using rapid miner machine learning by conducting four experiments using SYN, ACK, UDP, and UDPlain attack types. The classification results from selecting five parameters with the highest activity when the device is attacked. In order for these five parameters to be a reference in the event of a malware attack starting in the IoT environment, the results of the classification have implications for further research. In the future, it can be used as a reference in making an early warning innovative system as an early warning in the event of a Mirai botnet attack.
Analisis Cost-Performance Arsitektur Komputasi Edge, Cloud, dan Hybrid untuk Industri 4.0 Lapandu, Raihan Azhar; Widiyasono, Nur; Rahmatulloh, Alam
Prosiding SEMNAS INOTEK (Seminar Nasional Inovasi Teknologi) Vol. 9 No. 2 (2025): Prosiding Seminar Nasional Inovasi Teknologi Tahun 2025
Publisher : Universitas Nusantara PGRI Kediri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29407/5jeq4524

Abstract

 Pemilihan arsitektur komputasi Edge, Cloud, atau Hybrid menjadi tantangan krusial di Industri 4.0 karena perbedaan signifikan dalam performa dan biaya operasional. Berbeda dari studi yang hanya berfokus pada aspek teknis, penelitian ini menyajikan analisis cost-performance yang komprehensif. Menggunakan skenario simulasi predictive maintenance, trade-off antara metrik teknis (utilisasi CPU, RAM, latensi, dan penyimpanan) dievaluasi dengan estimasi biaya harian. Lebih lanjut, penelitian ini mengusulkan sebuah decision matrix sebagai alat bantu pengambilan keputusan. Hasil menunjukkan Edge unggul dalam latensi rendah (17,5 ms) dan efisiensi biaya. Cloud menawarkan skalabilitas superior dengan biaya lebih tinggi, sementara Hybrid menjadi kompromi seimbang meski memiliki overhead dan kompleksitas tertinggi. Temuan ini memberikan kontribusi aplikatif berupa panduan empiris bagi para praktisi untuk memilih arsitektur yang paling sesuai dengan prioritas operasional dan ketersediaan anggaran. 
PELATIHAN TEKNOLOGI ROBOTIKA BAGI GURU DAN SISWA SEKOLAH DASAR : TRAINING OF ROBOTICS TECHNOLOGY FOR ELEMENTARY SCHOOL TEACHERS AND STUDENTS Rohmat Gunawan; Alam Rahmatulloh; Randi Rizal; Perdi Setiawan; Erna Haerani
PADIMAS Jurnal Pengabdian Masyarakat Vol. 4 No. 02 (2025): Padimas (Jurnal Pengabdian Masyarakat)
Publisher : PADIMAS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32665/padimas.v4i02.5624

Abstract

Pembelajaran teknologi informasi dan rancang bangun perangkat elektronik di setiap jenjang pendidikan masih terbatas di beberapa sekolah tertentu saja. Penggunaan robot edukasi dalam sektor pendidikan masih sangat minim, terutama pada jenjang Sekolah Dasar (SD). Padahal, minat peserta didik terhadap bidang ini semakin meningkat, ditandai semakin banyaknya kontes robotika di daerah maupun skala nasional. Mengenalkan teknologi robot sejak dini, dapat mendorong anak untuk berpikir logis, belajar menganalisis masalah, belajar dari setiap kesalahan, mengenal Science Technology Engineering Mathematics (STEM), serta mendorong anak untuk berpikir kreatif. Tujuan dari kegiatan pengabdian ini melakukan sosialisasi teknologi informasi dan rancang bangun komponen eleketronik (khususnya komponen penyusun robot). Terdapat 3 aktivitas utama yang dilakukan dalam kegiatan pengabdian ini, diantaranya: persiapan awal, pelaksanaan, evaluasi dan pelaporan. Kegiatan pengabdian masyarakat telah dilaksanakan pada hari Jumat 8 Agustus 2025 dimulai pukul 08:00 sampai dengan selesai, diikuti oleh guru dan 35 siswa kelas VI Sekolah Dasar Negeri (SDN) Citapen Kota Tasikmalaya, yang berlokasi di Jalan Tentara Pelajar No. 16 Kelurahan Empangsari Kecamatan Tawang Kota Tasikmalaya Jawa Barat. Hasil evaluasi responden terhadap kegiatan pengabdian ini, rata-rata kategori “Sangat Setuju”=64%, “Setuju”=32%, “Netral”=4%, “Tidak Setuju”=0%, “Sangat Tidak Setuju”=0%.
Analisis Sentimen Media Sosial Terhadap DPR RI: Perbandingan Akurasi Extra Trees Dan Random Forest Dengan Pendekatan Komputasi Hijau Komara Kusumah, R Herick Fauzi; Aradea, A; Rahmatulloh, Alam
JUSTIN (Jurnal Sistem dan Teknologi Informasi) Vol 14, No 1 (2026)
Publisher : Jurusan Informatika Universitas Tanjungpura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26418/justin.v14i1.92556

Abstract

Analisis sentimen terhadap DPR RI penting untuk memahami opini publik dan dampaknya terhadap persepsi masyarakat. Penelitian sebelumnya menggunakan metode seperti SVM, Naïve Bayes, dan Decision Tree dengan fokus utama pada akurasi, namun masih kurang mempertimbangkan efisiensi komputasi dan dampak lingkungan. Oleh karena itu, penelitian ini membandingkan performa Extra Trees Classifier dan Random Forest Classifier dalam analisis sentimen dari TikTok dan YouTube, tidak hanya dari segi akurasi tetapi juga efisiensi energi dengan pendekatan komputasi hijau. Proses mencakup pengumpulan data, preprocessing, transformasi TF-IDF, pemodelan, serta evaluasi berdasarkan akurasi, precision, recall, F1-score, dan efisiensi energi. Hasil menunjukkan Extra Trees memiliki akurasi lebih tinggi (92%) dibandingkan Random Forest (90,3%), tetapi Random Forest lebih hemat energi dengan konsumsi 0,0213 kWh dan waktu pemrosesan 8 menit dibandingkan Extra Trees yang membutuhkan 0,0248 kWh dan 22 menit. Dari perspektif komputasi hijau, Random Forest lebih ramah lingkungan karena menghasilkan emisi karbon lebih rendah. Pemilihan model bergantung pada prioritas: Extra Trees lebih akurat, sedangkan Random Forest lebih efisien dalam energi dan waktu pemrosesan. Penelitian ini diharapkan dapat memberikan wawasan bagi akademisi, pengembang teknologi, dan pembuat kebijakan dalam memilih model analisis sentimen yang optimal dan berkelanjutan.
Co-Authors Aditya, Hafish Naufal Aemy, Nandhitta Albi Fitransyah Aldy Putra Aldya Alpan Hikmat Muharram Permana Amaludin, Luthfi Andi Nur Rachman Andi Nurachman Anggi Putri Meriani Anggi Putri Meriani Anjar Ginanjar ANWAR, FAHMI Aradea, A Ardhan Dimas Nuryadin Asep Kurniawan Asep Rizki Maulana Asih, Dwi Ramti Aulia, Karina A’izzah, Virra Retnowati Budi Permana Darmawan, Muhamad Aditya Dewi Rahmawati Dita Pramesti Dodi Muhamad Kodar Dwi Ramti Asih Eka Wahyu Hidayat Eka Wahyu Hidayat El Akbar, R Reza El-Akbar, R Reza Elmeftahi, Souhayla Ernawati, Rita Sri Faisal Al Isfahani Faisal Muhammad Dzikry Faisal, Fikri Ahmad Faridah Hanifah Farras, Daffa Haidar Fatchul Arifin Ficry Cahya Ramdani Firdaus, Muhamad Akbar Firmansah, Teguh Anugrah Firmansyah MSN Firmansyah, Faldi Ramadhan Fuji Nugraha Gagan Akhmad Fauzi Galih Permana Genta Nazwar Tarempa Geri Nugraha Ginting, Muliani Guna, Nandana Surya Gunawan, Rohmat Gunawan, Rohmat Gunawan, Rohmat Haerani, Erna Heni Sulastri Heni Sulastri Herlambang, Andriana Herman Dwi Surjono Hidayat, Deri Kurnia Hidayat, Eka Wahyu Hilman Septian husen husen Husen Husen Husen, - Ihsanuddin Ihsan Ikhsan Nur Rizkiana Ilham Yuslin Anugrah Indra Sontana Iqbal Muhammad Fajar Nuralam Irfan Darmawan Ivang Fahmi Fauzi Kodar, Dodi Muhamad Komara Kusumah, R Herick Fauzi Kusumah, R Herick Fauzi Komara Laely Armiyati Lapandu, Raihan Azhar Leka Destrilia Leviana, Rika Maulana, Dikri Merdiriyani, Sindy Meriani, Anggi Putri Mochamad Dzikri Daely Muhammad Quraish Shihab Muhammad Ramadhan, Galih Muhammad Saiful Anwar Nadhilah Hazrati Neng Ika Kurniati Neng Ika Kurniati Neng Ika Kurniati Neng Ika Kurniati Nida, Siti Nabilah Nugraha, Cindera Syaiful Nugroho, Rizal Nur Widiyasono Nur Widiyasono, Nur Perkasa, Mochamad Althaf Pramasetya Popy, Popy Anisa Purwayoga, Vega Putra, Aldy R. Reza El Akbar R. Wahjoe Witjaksono Rachman, Andi Nur Rahmi Nur Shofa Rahmi Nur Shofa Rahmi Nur Shofa Rakhman, Maulana Decky Ramdani, Setiadi Randi Rizal Rianto, Rianto Ridwan Muhammad Raihan Ridwan Nur Qomar Rifki Mubarok Riki Ahmad Fauji Rita Sri Ernawati Rizal Nugroho Rizal, Randi Rizal, Randi Rizkie Irfan Awaludin Rochim, Rachma Verina Rohmat Gunawan Rohmat Gunawan Ruuhwan Salma Nur Fithriyah Salman, Ade Selamat, Siti Rahayu Septian, Hilman Setiawan, Muhamad Bayu Setiawan, Perdi Sheptianna Healtha Rukiman Shofa, Rahmi Nur Sholihat Ruhaedi, Hedy Sulastri, Heni Sulastri, Heni Sulastri, Heni Virra Retnowati A’izzah Visi Tinta Manik Warih Puspitasari Yuliasari, Silpani Yuzar, Arnefia ZK Abdurahman Baizal