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All Journal Jurnal Edukasi Elektro JREC (Journal of Electrical and Electronics) Jurnal Teknologi Jurnal sistem informasi, Teknologi informasi dan komputer Jurnal Informatika dan Teknik Elektro Terapan J-PEK (JURNAL PEMBELAJARAN KIMIA) JETT (Jurnal Elektro dan Telekomunikasi Terapan) JOURNAL OF MECHANICAL ENGINEERING, MANUFACTURES, MATERIALS AND ENERGY Electro Luceat Jurnal Penelitian Pendidikan IPA (JPPIPA) VOLT : Jurnal Ilmiah Pendidikan Teknik Elektro JET (Journal of Electrical Technology) InComTech: Jurnal Telekomunikasi dan Komputer RELE: Rekayasa Elektrikal dan Energi Jurnal Teknik Elektro Techne : Jurnal Ilmiah Elektroteknika SELAPARANG: Jurnal Pengabdian Masyarakat Berkemajuan JURNAL TIARSIE EQIEN - JURNAL EKONOMI DAN BISNIS TESLA: Jurnal Teknik Elektro Infotronik : Jurnal Teknologi Informasi dan Elektronika TELKA - Telekomunikasi, Elektronika, Komputasi dan Kontrol Barometer MULTINETICS EPIC : Journal of Electrical Power, Instrumentation and Control Journal of Sustainable Engineering: Proceedings Series TEKNOKOM : Jurnal Teknologi dan Rekayasa Sistem Komputer Aisyah Journal of Informatics and Electrical Engineering Jurnal Informatika dan Rekayasa Elektronik JE-Unisla Jurnal Teknologi Elekterika Jurnal Teknik Elektro dan Komputasi (ELKOM) JATI (Jurnal Mahasiswa Teknik Informatika) Jurnal Teknika Parameter Journal of Energy and Electrical Engineering (JEEE) International Journal Of Science, Technology & Management (IJSTM) Jurnal Teknologi Pertanian Gorontalo JTEIN: Jurnal Teknik Elektro Indonesia International Journal of Educational Research and Social Sciences (IJERSC) Jurnal Ilmiah Wahana Pendidikan Jurnal Energi Baru dan Terbarukan JURNAL ILMIAH GLOBAL EDUCATION Jurnal Teknik Elektro Teknologika PROSISKO : Jurnal Pengembangan Riset dan observasi Rekayasa Sistem Komputer INDIKATOR Electrician : Jurnal Rekayasa dan Teknologi Elektro Madani: Multidisciplinary Scientific Journal Jurnal Pendidikan dan Pengabdian Masyarakat Jurnal INFOTEL Jurnal Informatika Polinema (JIP) Power Elektronik : Jurnal Orang Elektro Jurnal Ecotipe (Electronic, Control, Telecommunication, Information, and Power Engineering) Media Elektrik Widya Teknik SNTE
Yuliarman Saragih
Universitas Singaperbangasa Karawang
Religion Aerospace Engineering Agriculture, Biological Sciences & Forestry Arts Humanities Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences 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 Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Nursing Physics Public Health Social Sciences Transportation Other

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Proses Perbaikan Data ODP (Optical Distribution Point) Tidak Sama dan Rename ODP Menggunakan UIM Tools Untuk Meluruskan Service di PT. TELKOM WITEL KARAWANG Fatwa Fauzandi; Yuliarman Saragih
Electrician : Jurnal Rekayasa dan Teknologi Elektro Vol. 18 No. 1 (2024)
Publisher : Department of Electrical Engineering, Faculty of Engineering, Universitas Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/elc.v18n1.2503

Abstract

Prototype Charging Station Untuk Kendaraan Listrik Menggunakan Panel Surya 5WP Maulana, Aldi Farid; Ibrahim, Ibrahim; Saragih, Yuliarman
Jurnal Ilmiah Wahana Pendidikan Vol 9 No 24 (2023): Jurnal Ilmiah Wahana Pendidikan
Publisher : Peneliti.net

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5281/zenodo.10403991

Abstract

Kata kunci: Sel Surya, Charger, Arduino, Energi terbarukan Abstract Along with the development of the times, the increase in energy needs is getting higher, in contrast to the current availability of fossils which are continuously depleting and have the possibility that they will run out in time. This makes every human being obliged to think about what can be used as alternative renewable energy to support energy needs in the future. Currently, many solar panels have been developed that function as a conversion of sunlight into electrical energy, but have weaknesses at night. The main problem with this system is how to store the energy in the battery and how long it takes to charge and the power that can be provided by a 5WP panel from 8:00 to 17:00. The power generated will later be used to recharge the cellphone battery through a charging station system that will be made. The scope of this research is about utilizing sunlight to recharge the battery. This charger station is designed to use the Arduino microcontroller as the system control center. The method used is that the light received by the solar panels is converted into electrical energy and stored in a battery bank or main storage by a solar charger controller. From the battery, the current flows to each branch of the cellphone charger module. The test results can be concluded that the highest achievement was 53.28 watts from the first day to the third day of measurement and the highest achievement was 33.6 watts from the battery bank charging test by the panel. It can be concluded that the tool works according to its purpose. The choice of battery capacity and panel can support the need for a cellphone charger for 24 hours.
Pendeteksi Face Mask Menggunakan Model CNN (Convolutional Neural Network) Saputra, Rivaldi Julian; Saragih, Yuliarman; Stefani, Arnisa
Jurnal Ilmiah Wahana Pendidikan Vol 9 No 24 (2023): Jurnal Ilmiah Wahana Pendidikan
Publisher : Peneliti.net

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5281/zenodo.10435426

Abstract

Health protocols are needed to prevent the spread of Covid-19. The use of face masks is one of the commonly used health protocols. Checking manually to detect faces that are not wearing masks is a long and tedious job. The basis of this research is Deep Learning which is a high-level, layered, and deep modeling algorithm that is widely applied to computer vision. Computer vision is a branch of computer science that can be used for image classification. Convulsional Neural Network is a deep learning algorithm that has good performance in image classification. Transfer learning is the latest method to speed up training time on datasets and to get better classification performance. This study classifies facial images to distinguish people wearing masks or not using Deep Learning. The system will classify and then give status to people wearing masks or not. This artificial intelligence system or what can be called Artificial Intelligence will help human work. This system can be added to more complex outputs such as opening doors, attendance, screening of people who enter public places that have closed rooms
Design of a microcontroller-based quadcopter prototype module Fly Sky XL163RX take off and landing Saragih, Yuliarman; Ibrahim, Ibrahim; Satrio Hadikusuma, Ridwan; Handayana, Kayat; Elisabet, Agatha
JURNAL INFOTEL Vol 15 No 3 (2023): August 2023
Publisher : LPPM INSTITUT TEKNOLOGI TELKOM PURWOKERTO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20895/infotel.v15i3.966

Abstract

This research paper presents the design and development of a microcontroller-based quadcopter prototype module, named Fly Sky XL163RX, with the capability of take off and landing. The objective of this study is to design a reliable and efficient quadcopter module that can be utilized for various applications, such as aerial photography, surveillance, and delivery services. The proposed quadcopter module is equipped with the Fly Sky XL163RX microcontroller, which serves as the control unit for managing the flight operations. The design process involves several key steps, including the selection of appropriate components, integration of sensors and actuators, and the development of control algorithms. The quadcopter module utilizes a combination of sensors, including gyroscopes, accelerometers, and altimeters, to gather real-time data and stabilize the flight. The control algorithm employs a proportional-integral-derivative (PID) controller to adjust the motor speeds and maintain stability during take off and landing. The Fly Sky XL163RX microcontroller offers a user-friendly interface and supports various communication protocols, allowing for easy customization and control of the quadcopter module. Additionally, the module incorporates safety features, such as emergency landing capabilities and collision avoidance systems, to enhance flight security and prevent potential accidents. The performance of the Fly Sky XL163RX quadcopter module was evaluated through extensive flight testing. The results demonstrate the module's capability to achieve stable take off and landing operations, as well as its responsiveness to user commands. The module's compact size and lightweight design make it suitable for indoor and outdoor applications. In conclusion, this research presents the design and development of the Fly Sky XL163RX microcontroller-based quadcopter module, which exhibits reliable and efficient take off and landing operations. The module's integration of sensors, control algorithms, and safety features contribute to its overall performance and usability. Future work may focus on enhancing the module's capabilities, such as implementing autonomous flight modes and improving battery efficiency.Quadcopter, Microcontroller, FlySky XL163RX, Take Off, Landing, Control Algorithm, Sensors, Actuators, PID Controller, Flight Testing, Aerial Applications.
ESP32 Real-Time Smoke Detection Integrated with WhatsApp in Tamansari, Karawang Nurdiyanto, Furkhon; Hafid, Izzul; Nurhayati, Syifa Silvia; Fadilah, Syarifah Nur; Saragih, Yuliarman
Journal of Energy and Electrical Engineering Vol 7, No 1: October 2025
Publisher : Teknik Elektro Universitas Siliwangi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37058/jeee.v7i1.15579

Abstract

This research develops an air quality monitoring system based on the ESP32 microcontroller, utilizing an MQ2 gas sensor and a DHT22 temperature-humidity sensor. The system is designed to monitor gas concentration and environmental conditions (temperature and humidity) in real-time in Tamansari Village, an area known for frequent open burning activities. Sensor readings are periodically transmitted to users via WhatsApp notifications using the CallMeBot API, providing early warnings when potentially hazardous gas levels are detected. Test results indicate that the system effectively detects changes in gas concentrations and temperature with reasonable accuracy and delivers timely alerts. Thus, the system can function as a supportive tool in mitigating air pollution risks in the study area.
Implementation of Hashicorp Vault as Multi-Factor Data Communication Security in Integration with Modern Infrastructure Saragih, Yuliarman; Hadikusuma, Ridwan Satrio; Bijokangko, Resi Sujiwo
Seminar Nasional Teknik Elektro Vol. 3 No. 1 (2023): SNTE II
Publisher : Forum Pendidikan Tinggi Teknik Elektro Indonesia Pusat

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

Abstract

The objective of this research is to examine how HashiCorp Vault can be effectively implemented as a multi-factor data communication security solution alongside modern infrastructure. Safeguarding sensitive data and digital secrets has become crucial in the digital age, particularly in advanced technological environments such as cloud systems, containers, and micro-based settings. The security of data transmission plays a pivotal role in preserving its confidentiality and integrity while being transferred across networks. In this study, HashiCorp Vault has been selected as the solution to enhance the security of the data communication process. By enabling multi-factor authentication and authorization, Vault strengthens security measures by requiring multiple methods of authentication before granting access. Additionally, Vault ensures the protection of digital secrets, including passwords, API keys, and certificates, through encrypted storage, thereby safeguarding them from unauthorized access. Moreover, this research focuses on the integration of Vault with commonly utilized modern infrastructures like Kubernetes, cloud providers, and external authentication systems. This integration enables comprehensive data communication security throughout the entire infrastructure, ensuring the safety and protection of data during its transit across various infrastructure components. To validate the effectiveness of the Vault implementation, a series of tests and performance evaluations will be conducted. These assessments encompass performance measurements, reliability testing of security measures, analysis of potential threats, and identification of relevant mitigations. The outcomes of this research aim to provide insights into the effectiveness and benefits of employing HashiCorp Vault as a multi-factor data communication security mechanism within the context of contemporary infrastructures. Furthermore, the study offers practical guidance to organizations contemplating the use of Vault as a reliable and trustworthy security solution in the everevolving technological landscape.
Implementation of an ESP-32 Wi-Fi CAM & Arduino-Based Robot for IoT Surveillance Kurniawan, Fery Andika; Rochimawati, Ima; Saddiq, Azhar; Saragih, Yuliarman; Saragih, Carolan Ignatius
Seminar Nasional Teknik Elektro Vol. 3 No. 1 (2023): SNTE II
Publisher : Forum Pendidikan Tinggi Teknik Elektro Indonesia Pusat

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

Abstract

Currently, it is impossible for border guarding personnel to constantly watch the whole border, making it difficult to monitor areas along international borders. The creation of an autonomous robot that can recognize trespassers and notify the neighborhood border security control unit has become essential to meet this need. In order to complete dangerous missions that are beyond the capability of human soldiers, many military departments have turned to robots. The Internet of Things (IoT), a night vision Pi camera, and numerous sensors have been integrated into the architecture of the spy robot platform in this study, which is based on the Raspbian operating system. This platform for surveillance robots intends to protect people's lives, minimize manual errors, and shield the nation from potential dangers. A night vision Pi camera, several sensors, and a Raspberry Pi (a small single-board computer) are all part of the system. Living object detection is done by the PIR sensor, and users are informed of it via a web server. The Pi camera simultaneously records moving objects, which are then shown on a website. Users can access the robot from a control room and direct its motion using wheel drive control buttons on the website. Additionally, the robot has sensors that can identify obstacles to help it navigate without running into anything.This spy robotbased surveillance system is adaptable to a variety of settings, including businesses, financial institutions, and shopping centers, where it may be tailored to meet particular security needs. This technology makes it possible to conduct continuous and automated surveillance, which enhances the total security measures in sensitive locations.
Strategi Optimasi Antrian SPKLU dengan Algoritma Genetika untuk Mengurangi Waktu Tunggu dan Ketidakseimbangan Slot Saragih, Yuliarman; Resi Sujiwo Bijokangko; Setiyo Budiyanto; Saragih, Carolan Ignatius
Seminar Nasional Teknik Elektro Vol. 4 No. 1 (2025): SNTE III
Publisher : Forum Pendidikan Tinggi Teknik Elektro Indonesia Pusat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46962/snte.25.067

Abstract

Pertumbuhan penggunaan kendaraan listrik (EV) memicu kebutuhan akan sistem manajemen Stasiun Pengisian Kendaraan Listrik Umum (SPKLU) yang efisien, khususnya dalam mengoptimalkan penjadwalan pengisian dan pemerataan beban antar stasiun. Penelitian ini mengusulkan penerapan Genetic Algorithm (GA) untuk mengoptimalkan penugasan EV ke SPKLU dengan mempertimbangkan jarak, perkiraan waktu tiba (Estimated Time of Arrival), kapasitas slot, dan durasi pengisian. Metode ini dibandingkan dengan pendekatan konvensional tanpa AI yang hanya mengandalkan jarak terdekat. Dataset yang digunakan bersifat sintetis, mencakup 30 EV dan 6 SPKLU dengan kapasitas slot bervariasi (5–7 slot). Simulasi dijalankan menggunakan pestimasi waktu ketibaan OpenRouteService untuk perhitungan jarak dan waktu tempuh aktual. Hasil menunjukkan bahwa GA mampu menurunkan rata-rata waktu tunggu EV sebesar 64,4% (dari 11,8 menit menjadi 4,2 menit), mempercepat total waktu penyelesaian dari 410 menit menjadi 320 menit, serta mengurangi variansi utilisasi slot antar SPKLU sebesar 67,86%. Temuan ini membuktikan bahwa GA tidak hanya meningkatkan efisiensi operasional, testimasi waktu ketibaanpi juga memeratakan beban infrastruktur pengisian. Penelitian ini memberikan kontribusi terhadap pengembangan strategi optimasi SPKLU berbasis AI dan membuka peluang untuk penerapan realtime dengan integrasi data lalu lintas dinamis.
Sistem Klasifikasi Penyakit Kulit dengan Analisis Citra dan Sistem Pakar Penyakit Kulit dengan Antarmuka Web untuk Peningkatan Produktivitas Pelayanan Puskesmas Desa Kendaljaya Kecamatan Pedes Saragih, Yuliarman; Dwijaksara, Ni Luh Bella Windu Febriyanti; Sukanta; Arjuno Putro Bayu; Siti Masitoh; Resi Sujiwo Bijokangko; Saragih, Carolan Ignatius
Jurnal Pendidikan dan Pengabdian Masyarakat Vol. 8 No. 4 (2025): November
Publisher : FKIP Universitas Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jppm.v8i4.9911

Abstract

Peningkatan kualitas pelayanan kesehatan primer di daerah pedesaan masih menjadi tantangan, khususnya dalam diagnosis penyakit kulit yang membutuhkan waktu dan keahlian spesifik. Pengabdian kepada masyarakat ini bertujuan untuk mengembangkan dan mengimplementasikan sistem klasifikasi penyakit kulit berbasis analisis citra menggunakan algoritma YOLOv8 serta sistem pakar gejala yang terintegrasi dalam antarmuka web. Sistem ini diterapkan di Puskesmas Desa Kendaljaya, Kecamatan Pedes, Kabupaten Karawang, untuk mendukung efisiensi tenaga medis dan meningkatkan akses masyarakat terhadap diagnosis awal penyakit kulit. Metode yang digunakan meliputi pendekatan riset terapan kolaboratif, pelatihan model dengan dataset terbuka, integrasi antarmuka web, serta pelibatan pengguna dalam uji coba langsung. Evaluasi dilakukan secara kuantitatif dan kualitatif melalui kuisioner, observasi penggunaan sistem, dan wawancara mendalam. Hasil implementasi menunjukkan bahwa sistem mampu mengklasifikasikan lebih dari 30 jenis penyakit kulit dengan akurasi tinggi, serta meningkatkan efisiensi layanan dengan waktu diagnosis yang lebih singkat. Masyarakat juga menunjukkan antusiasme tinggi dalam penggunaan sistem, terutama generasi muda. Kegiatan ini memberikan kontribusi signifikan terhadap peningkatan literasi digital masyarakat dan penguatan pemanfaatan teknologi cerdas dalam pelayanan kesehatan primer. Sistem yang dikembangkan berpotensi untuk direplikasi pada layanan kesehatan lainnya, terutama di wilayah dengan keterbatasan tenaga medis.
PERBANDINGAN ALGORITMA MACHINE LEARNING UNTUK PREDIKSI NILAI UJIAN SISWA Luthfi Luqman Fattah; Yuliarman Saragih; Budiman Faisal Tanjung; Naufal Akmal Nugraha
PROSISKO: Jurnal Pengembangan Riset dan Observasi Sistem Komputer Vol. 12 No. 3 (2025): Prosisko Vol. 12 No. 3 November 2025
Publisher : Pogram Studi Sistem Komputer Universitas Serang Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30656/prosisko.v12i3.10699

Abstract

Peningkatan kualitas pendidikan tidak hanya bergantung pada metode pembelajaran, tetapi juga pada kemampuan institusi untuk memahami dan mengantisipasi performa akademik siswa. Penelitian ini bertujuan untuk membangun dan membandingkan tiga model prediksi nilai ujian siswa berdasarkan data kebiasaan harian menggunakan algoritma Regresi Linier, Random Forest, dan XGBoost. Data diperoleh dari platform publik dengan jumlah 1000 entri siswa yang mencakup berbagai atribut seperti durasi belajar, kehadiran, aktivitas ekstrakurikuler, dan kesehatan mental. Setiap model diuji menggunakan metrik evaluasi seperti Root Mean Squared Error (RMSE), Mean Absolute Error (MAE), dan koefisien determinasi (R²). Hasil penelitian menunjukkan bahwa model Regresi Linier memberikan performa terbaik dengan nilai RMSE terendah sebesar 5,139 dan R² tertinggi sebesar 0,897. Analisis lebih lanjut menunjukkan bahwa variabel durasi belajar memiliki kontribusi paling dominan dalam prediksi nilai ujian. Temuan ini mengindikasikan bahwa hubungan antara variabel input dan nilai ujian siswa cenderung linear dan stabil, sehingga dapat dimodelkan secara efektif menggunakan pendekatan sederhana. Penelitian ini memberikan kontribusi dalam penerapan analisis prediktif berbasis machine learning untuk keperluan evaluasi pendidikan dan dapat menjadi dasar bagi pengembangan sistem pendukung keputusan di lingkungan sekolah maupun perguruan tinggi.
Co-Authors -, ibrahim Adinda Larasati, Putri Adzilla, Wilma Nurrul Agni Andhini Agung Wijiantoro Ahmad Al-Baehaqi Salam Ahmad Fadhlul Kamal, Ahmad Fadhlul Kamal Akhmad Irfansyah Salim Al Sulaiman, Ramdhani Alfian, Reza Alia Hurul Aini Alinda Endang Poerwati Alwin Amadeuz Ezrafel Amiruddin, Syuraih Amnur Pinomo Manurung Amran Nur Afif Ananda Fauziah Andalisto, Ditra Andi Boy Panroy Manullang Andromeda, Safrian Anugrah Restu Rahayu Apid Hapid Maksum Arfianti, Selfi Arianne Gatari Arifin, Sulthon Muakhor Arjuno Putro Bayu Arnisa Stefanie Aulia Maulana, Dava Aulia Safitri, Regita Ayu Nur Indahsari Azis, Dhika Aditya Azizi, Muhammad Fachri Baihaki Baihaki Bangun Widyatmoko Bayu Megantoro, Ramadhani Berliani, Dhea Bima Pratama, Tyo Budiman Faisal Tanjung Cahyadi, Devi Cintiya Septa Hasannah Dalimunthe, Mhd Erpandi Damiri, Adam Dasep Heriansyah Dene Herwanto Dhika Aditya Azis Dian Budhi Santoso Donni Angger Basuki Dwi Prasetyo Dwijaksara, Ni Luh Bella Windu Febriyanti Edison Sembirin Colia Edmund Ucok Armin Eko Sediyono Eko Setyono Elisabet, Agatha Endang Erik, Muhammad Estimate Ria Ristanry Fadilah, Syarifah Nur Falentina Lavi Fariq Naufal, Muhammad Fariza Haqi Faturrahman, Luthfan Akmal Fatwa Fauzandi Fauzan, Muhammad Raihan Gaby Aditya Nugraha Gemilang, Bintang Gina Lova Sari Gultom, Roy Morales Gun Gun Gumilar Gustina Indriati Hadikusuma, Ridwan Satrio Hafid, Izzul Hamdan Sardi Selian Hana Graceila Sitindjak Hana Graceila Sitindjak Hanafi, Zikri Handayana, Kayat Hasan Mardiansyah Heri Santoso, Makmur Hiermy, Ulpen Hutapea, Marshal I Ketut Suada Ibrahim Ibrahim - ibrahim - Ibrahim Ibrahim Ibrahim Ibrahim Ibrahim Ibrahim Ibrahim Ibrahim Ibrahim Ibrahim Imam Budi Santoso Indri Purwita Sary Iwan Setyawan Josya Marvin Immanuel Kintania Pracipta Komalasari, Ayu Koo Tito Novelianto Kurniadi, Ananda Rizky Kurniawan, Fery Andika Kusuma, Adillah Surya Lamada, Ibrahim Latifa, Ulinnuha Lawang, Robert M.Z. Lela Nurpulaela Lila Setiyani Lilis Pitriyanti Luthfi Luqman Fattah M Fauzan Reza Firdaus M Irwan Darmawan Maeleva, Syabandani Makmur Heri Santoso Manurung, Amnur Pinomo Mardiansyah, Hasan Marno, Marno Marza Ihsan Marzuki Maulana, Aldi Farid Meiyussad, Danzwarnas Mochammad Afrie Adam Mohammad Daffa Ananda Mohammad Daffa Ananda, Mohammad Daffa Ananda Muham, Joshua Michael Sembiring Muhamad Irsal MI Muhamad Nuh Ruhyat Muhamad Nuh Ruhyat muhamad sahrul Muhammad Fahmi Hakim Muhammad Iqbal Alfarizi Muhammad Rifqi Setyanto Muhammad Sahidal Mulya Sanjaya, Rezha Mulyahani, Alvina Naufal Akmal Nugraha Novita, Asri Dwi Nugroho Susanto Nunu, Muhamad Nuh Ruhyat Nur Rachmad Ramadhan Nur Samsul Huda Nurdiyanto, Furkhon Nurhadi Nurhayati, Syifa Silvia Nurjeli Nurjeli Nurkholiq Fahrurozi, Riziq Pane, Krisdayanti Dormauli Pitriya Tiar Pradicta Nurhuda Prasetiyo, Teguh Puji Waluyo Puji Waluyo Raden Mohamad Herdian Bhakti Rahmat Hidayat Rahmat Hidayat Renaldi Irwansyah Reni Rahmadewei Reni Rahmadewi Reni Rahmadewi Reni Rahmadewi Reni Rahmadewi, Reni Resi Sujiwo Bijokangko Resi Sujiwo Bijokangko Ricko Immanuel Wicaksana Ridwan Satrio Hadikusuma Ridwan Satrio Hadikusuma Ridwan Satrio Hadikusuma Ridwan Satrio Hadikusuma Ridwan Satrio Hadikusuma, Ridwan Satrio Hadikusuma Riyan Setiyawan Rizal Pratama Rizki Priadi, Akbar Robert M.Z Lawang Robert M.Z. Lawang Robi Bagja Nugraha Rusdianto Roestam Saddiq, Azhar Safrian Andromeda Sandi Sandi Saputra, Rivaldi Julian Saragih, Carolan Ignatius Sarti Do Afsindir Satrio Hadikusuma, Ridwan Sella Monica Setiyo Budiyanto Setyanto, Muhammad Rifqi Siti Masitoh Soehatman Ramli Steafanie, Arnisa Stefani, Arnisa Subagja, Fajar Eka Subekhi, Ikhwan Sudirman Sukanta Sukanta Suparmin Supriyadi, Adimas Prasetyo Suroyo Suroyo Suroyo Suroyo Suryomukti, Muhammad Tanjung, Budiman Faisal Taufiqurrahman Taufiqurrahman Teguh Kurniawan Ulinnuha Latifa Ulinnuha Latifa Wahyu Ramadhan Weko Susanto Weko Susanto Wilma Nurrul Adzilla Yogi Setiawan Yudha Wijaya Matrutty Yuliana Yuliana Yusrodi Zaky Hanafian Alhuda