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All Journal Majalah Ilmiah Teknologi Elektro JTEV (Jurnal Teknik Elektro dan Vokasional ELKHA : Jurnal Teknik Elektro Bulletin of Electrical Engineering and Informatics Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI) Indonesian Journal of Science and Technology ELKOMIKA: Jurnal Teknik Energi Elektrik, Teknik Telekomunikasi, & Teknik Elektronika Emerging Science Journal IT JOURNAL RESEARCH AND DEVELOPMENT ILKOM Jurnal Ilmiah TELKA - Telekomunikasi, Elektronika, Komputasi dan Kontrol Kumawula: Jurnal Pengabdian Kepada Masyarakat Buletin Ilmiah Sarjana Teknik Elektro Mobile and Forensics Journal of Robotics and Control (JRC) Journal of Applied Engineering and Technological Science (JAETS) Indonesian Journal of Electrical Engineering and Computer Science International Journal of Robotics and Control Systems Prosiding Seminar Nasional Program Pengabdian Masyarakat Techno Jurnal Pengabdian dan Pemberdayaan Masyarakat Indonesia Proceeding International Pelita Bangsa Journal of Fuzzy Systems and Control (JFSC) Control Systems and Optimization Letters Majalah Ilmiah Teknologi Elektro Signal and Image Processing Letters
Alfian Ma’arif
Universitas Ahmad Dahlan, Yogyakarta, Indonesia
Aerospace Engineering Agriculture, Biological Sciences & Forestry Humanities Automotive Engineering Chemical Engineering, Chemistry & Bioengineering 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 Industrial & Manufacturing Engineering Library & Information Science Mechanical Engineering Medicine & Pharmacology Neuroscience Public Health Social Sciences

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Implementation of Heart Rate System using AD8232 and Arduino Microcontrollers Setiawan, Muhammad Haryo; Sari, Nurjanah Arvika; Prasetya, Wahyu Latri; Feter, Muslih Rayullan; Saputra, Dodi; Ma'arif, Alfian
Signal and Image Processing Letters Vol 2, No 1 (2020)
Publisher : Association for Scientific Computing Electrical and Engineering (ASCEE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/simple.v2i1.84

Abstract

The human heart's pivotal role in maintaining overall health by ensuring oxygen and nutrient delivery to tissues and waste elimination highlights the global importance of cardiac health. Electrocardiography (ECG) is a fundamental tool for assessing cardiac conditions, capturing intricate electrical signals during each heartbeat. ECG sensors are instrumental in this process, finding extensive applications in personal health monitoring, disease management, and medical research. This article emphasizes the significance of ECG sensors, particularly the AD8232 ECG sensor paired with the Arduino Nano microcontroller. It outlines their operational principles, measurement methods, and signal-processing techniques. The research aims to enhance the accuracy and efficiency of ECG data capture, contributing to advanced cardiac monitoring systems. Intelligent systems employing biopotential sensors and electrocardiographs enhance diagnostic precision, minimizing interpretational errors. ECG sensors, which record and translate the heart's electrical activity into interpretable data, are integral to modern medicine. They are used in diverse settings, from clinical environments to personal health monitoring. Ensuring ECG sensor accuracy is critical, as the data directly impacts diagnosis and treatment. This article offers insights into fundamental principles, measurement procedures, and programming techniques for ECG sensors, facilitating efficient data capture and processing. These findings promise user-friendly cardiac monitoring systems advancements, significantly contributing to medical technology and healthcare.
IoT-based Low-cost Children Tracker System Marhoon, Hamzah M; Ma'arif, Alfian; Aljanabi, Haider Dheyaa Kamil; Alanssari, Ali Ihsan; Nadheer, Israa
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.v5i1.62

Abstract

Recently many cases of missing children between ages 14 and 17 years have been reported. Parents always worry about the possibility of kidnapping their children. This work proposes an Android-based solution to aid parents to track their children in real-time. Nowadays, most mobile phones are equipped with internet service capabilities allowing them to connect with the world. The system's architecture is built on two main components: GPS satellite and IoT technology. The most important features of this work are the low cost, lightweight, and small size. The Blynk app is installed on the mobile phone and the GPS is attached to the NodeMCU microcontroller. The location information is reached through the Blynk app with the help of map services.
Electricity Power Monitoring Based on Internet of Things Saputra, Ekky Haqindytia; Ma'arif, Alfian; Alayi, Reza
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.v5i1.48

Abstract

Every year, electricity consumption in Indonesia has increased in line with population growth and the national economy. One of the factors causing an increase in electricity consumption in Indonesia, one of which is caused by the lifestyle of modern society which is wasteful in using electricity. Modern society is increasingly using electricity inefficiently. One potential solution to this problem is the use of the Internet of Things (IoT) concept. The Internet of Things, or IoT for short, is a system of connected computing devices whose sole purpose is to maximize the benefits of an internet connection. The system built using the PZEM-004T sensor which is processed by the Arduino Uno microcontroller will be sent to Wemos D1 Mini via serial communication (TX-RX) so that it can be displayed on the BLYNK New IoT application on a smartphone. As for the parameters that will be displayed in the BLYNK application, namely voltage, current, and power usage of electrical devices. By using this application, users will be able to more easily and effectively monitor and how much electrical energy is used by equipment remotely. This equipment has been tested from September to October, on 5 electronic devices such as lights, TVs, refrigerators, rice cookers, fans with satisfactory results, namely being able to monitor the use of electrical devices using smartphones through the blynk application.
Comparative Performance Analysis of LQR Based PSO and Fuzzy Logic Control for Active Car Suspension Abougarair, Ahmed; Aburakhis, Mohamed; Bakouri, Mohsen; Ma’arif, Alfian
Buletin Ilmiah Sarjana Teknik Elektro Vol. 7 No. 3 (2025): September
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/biste.v7i3.13237

Abstract

This study proposes a diffrent control strategy for active car suspension systems, comparing the performance of Proportional-Integral-Derivative (PID), Linear Quadratic Regulator (LQR), and fuzzy PD controller in optimizing ride comfort and handling. These methods were selected for their complementary strengths: PID for simplicity and industrial adoption, LQR for optimality in handling trade-offs between ride comfort and suspension travel, and fuzzy PD for adaptability to nonlinearities and road disturbances. A 4-DOF quarter-car model is employed to simulate vehicle dynamics, with road disturbances modeled as step and sinusoidal inputs. The PID controller is tuned using built-in tools such as the PID tuner app, while the LQR’s weighting matrices (Q and R) were optimized offline using PSO. The optimized weights were then substituted into the algebraic Riccati equation to derive the final feedback control gains, ensuring optimal performance while adhering to classical LQR theory. For the fuzzy PD controller, membership functions and rule bases are designed to adaptively adjust gains under varying road conditions. Simulation results demonstrate that the PSO-tuned LQR and fuzzy PD controllers outperform conventional PID by reducing body vertical displacement by 61% and 23%, respectively, and overshoot by 75% (fuzzy PD) and 60.2% (LQR) under step excitation. The LQR controller based PSO also shows superior adaptability to stochastic road inputs and minimizing the control signal by 83.3% compared to PID. By integrating PSO-based LQR gain optimization and adaptive fuzzy logic, this work advances active suspension control, offering a quantifiably superior alternative to classical approaches. This study contributes to the technological development of the automotive world in order to provide comfort and safety for the passenger under different conditions, which contributes to the design of more comfortable vehicles with better performance in the future.
A Comprehensive Review of Optimization Techniques in Industrial Applications: Trends, Classifications, and Future Directions Asih, Hayati Mukti; Mohamad, Effendi; Irianto, Irianto; Ma’arif, Alfian
Buletin Ilmiah Sarjana Teknik Elektro Vol. 7 No. 3 (2025): September
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/biste.v7i3.13261

Abstract

In recent years, optimization techniques have played a central role in enhancing operational efficiency and decision-making across diverse industrial sectors, including manufacturing, logistics, and transportation, energy, healthcare, and agriculture. These sectors face complex, large-scale, and often nonlinear challenges that demand both precision and adaptability. The research contribution of this review is to provide a structured classification of optimization methods—namely exact algorithms, heuristics, metaheuristics, and AI-integrated hybrid models—and to critically evaluate their practical applications, limitations, and emerging trends across industries. This study adopts a review approach to identify and compare those techniques in solving various optimization problems. Through a detailed analysis of over 30 recent publications for last four years, the review highlights how these techniques are being applied in real-world industrial environments, including cold chain logistics, smart energy systems, precision agriculture, and healthcare scheduling. The results indicate a growing reliance on hybrid and AI-enhanced models due to their superior scalability, adaptability, and potential alignment with Industry 4.0 and Sustainable Development Goals (SDGs). However, challenges remain in areas such as computational efficiency, model interpretability, and real-time data integration. In conclusion, this study provides valuable insights for both researchers and practitioners seeking to apply optimization techniques more effectively in industrial systems, while also identifying critical research gaps for future exploration by addressing the growing complexity and sustainability demands of modern industry.
Understanding Time Series Forecasting: A Fundamental Study Furizal, Furizal; Ma’arif, Alfian; Kariyamin, Kariyamin; Firdaus, Asno Azzawagama; Wijaya, Setiawan Ardi; Nakib, Arman Mohammad; Ningrum, Ariska Fitriyana
Buletin Ilmiah Sarjana Teknik Elektro Vol. 7 No. 3 (2025): September
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/biste.v7i3.13318

Abstract

Time series forecasting plays a vital role in economics, finance, engineering, etc., due to its predictive power based on past data. Knowing the basic principles of time series forecasting enables wiser decisions and future optimization. Despite its importance, some researchers and professionals find it difficult to use time series forecasting techniques effectively, especially with complex data settings and selection of methods for a particular problem. This study attempts to explain the subject of time series forecasting in a comprehensive and simple manner by integrating the main stages, components, preprocessing steps, popular forecasting models, and validation methods to make it easier for beginners in the field of study to understand. It explains the important components of time series data such as trend, seasonality, cyclical components, and irregular components, as well as the importance of data preprocessing steps, proper model selection, and validation to achieve better forecasting accuracy. This study offers useful material for both new and experienced researchers by providing guidance on time series forecasting techniques and approaches that will help in enhancing the value of decision making.
Long Short-Term Memory vs Gated Recurrent Unit: A Literature Review on the Performance of Deep Learning Methods in Temperature Time Series Forecasting Furizal, Furizal; Fawait, Aldi Bastiatul; Maghfiroh, Hari; Ma’arif, Alfian; Firdaus, Asno Azzawagama; Suwarno, Iswanto
International Journal of Robotics and Control Systems Vol 4, No 3 (2024)
Publisher : Association for Scientific Computing Electronics and Engineering (ASCEE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/ijrcs.v4i3.1546

Abstract

Temperature forecasting is a crucial aspect of meteorology and climate change studies, but challenges arise due to the complexity of time series data involving seasonal patterns and long-term trends. Traditional methods often fall short in handling this variability, necessitating more advanced solutions to enhance prediction accuracy. LSTM and GRU models have emerged as promising alternatives for modeling temperature data. This study is a literature review comparing the effectiveness of LSTM and GRU based on previous research in temperature forecasting. The goal of this review is to evaluate the performance of both models using various evaluation metrics such as MSE, RMSE, and MAE to identify gaps in previous research and suggest improvements for future studies. The method involves a comprehensive analysis of previous studies using LSTM and GRU for temperature forecasting. Assessment is based on RMSE values and other metrics to compare the accuracy and consistency of both models across different conditions and temperature datasets. The analysis results show that LSTM has an RMSE range of 0.37 to 2.28. While LSTM demonstrates good performance in handling long-term dependencies, GRU provides more stable and accurate performance with an RMSE range of 0.03 to 2.00. This review underscores the importance of selecting the appropriate model based on data characteristics to improve the reliability of temperature forecasting.
Improved Trajectory Tracking for Nonholonomic Mobile Robots Via Dynamic Weight Adjustment in Type-2 Fuzzy Model Predictive Control Hedroug, Mohamed Elamine; Bdirina, El Khansa; Guesmi, Kamel; Nail, Bachir; Tibermacine, Imad Eddine; Ma'arif, Alfian
International Journal of Robotics and Control Systems Vol 5, No 3 (2025)
Publisher : Association for Scientific Computing Electronics and Engineering (ASCEE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/ijrcs.v5i3.1926

Abstract

This paper presents an advanced methodology for trajectory control of non-holographic mobile robots. It addresses the challenges of dynamic environments and system uncertainty by proposing a fuzzy model predictive control (FMPC) system that combines Type-2 fuzzy logic (F2MPC) with model predictive control (MPC) to enhance tracking accuracy and adaptability.  A Takagi-Sugeno (T-S) fuzzy model changes the MPC weighting matrices in real-time based on speed and distance errors, while the Type-2 fuzzy system handles uncertainties better than Type-1 systems. Tests using circular and wavy trajectories show that the Type-2 Fuzzy MPC (F2MPC) works better than traditional methods, achieving fewer tracking errors (Integral Squared Error of 0.0011), faster convergence (in 1.2 seconds), and using 65% less energy for movement than conventional MPC. Robustness tests show the controller's stability under disturbances, with minimal deviation and quick recovery. The results highlight the F2MPC's precision, efficiency, and adaptability, making it a promising solution for complex robotic navigation tasks.  The study found that Type-2 fuzzy logic and predictive control improve trajectory tracking, paving the path for real-world applications and computational optimisations.
Parametric Analysis of Climate Factors for Monthly Weather Prediction in Ghardaïa District Using Machine Learning-Based Approach: ANN-MLPs Dahmani, Abdennasser; Ammi, Yamina; Ikram, Kouidri; Kherrour, Sofiane; Hanini, Salah; Al-Sabur, Raheem; Laidi, Maamar; Ma’arif, Alfian; Sharkawy, Abdel-Nasser
International Journal of Robotics and Control Systems Vol 5, No 1 (2025)
Publisher : Association for Scientific Computing Electronics and Engineering (ASCEE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/ijrcs.v5i1.1651

Abstract

In the rapidly developing field of smart cities, accurately predicting weather conditions plays a vital role in various sectors, including industry, tourism, agriculture, social planning, architecture, and economic development. Unfortunately, the instruments used (such as pyranometers, barometers, and thermometers) often suffer from low accuracy, high computational costs, and a lack of robustness. This limitation affects the reliability of weather predictions and their application across these critical areas. This study proposes artificial neural network-multilayer perceptrons (ANN-MLPs). A dataset of 480 data points was used, with 80% allocated for the training phase, 10% for the validation phase, and 10% for the testing phase. The best results were obtained with the structure 6-17-1 (6 inputs, 17 hidden neurons, and 1 output neuron) to predict weather condition data in the Ghardaïa district. Weather conditions parameters include air temperature, relative humidity, wind speed, and cumulative precipitation. Results showed that the most relevant input factors are, in order of importance: earth-sun distance (DT-S) with a relative importance (RI) of 31.10%, factor conversion (d) with an RI of 26.05%, and solar radiation (SR) with an RI of 16.26%. The contribution of the elevation of the sun (HI) has an RI of 13.29%. The optimal configuration includes seventeen neurons in the hidden layer with a logistic sigmoid activation function and a Levenberg–Marquardt learning algorithm, resulting in a root mean square error (RMSE) of 3.3043% and a correlation coefficient (R) of 0.9683. The proposed model can predict both short- and long-term climate factors such as solar radiation, air temperature, and wind energy in areas with similar conditions.
Development of an IoT-Monitoring and Control System for Solar Panel Surface Temperature Regulation Utilizing Water-Cooling Techniques Ariadita, Silfia Cindy; Ma'arif, Alfian
Control Systems and Optimization Letters Vol 1, No 3 (2023)
Publisher : Peneliti Teknologi Teknik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59247/csol.v1i3.44

Abstract

As the world's energy needs escalate and the availability of finite natural resources diminishes, there is an urgent need to explore sustainable alternatives. Renewable energy sources, including solar power, hold great promise due to their abundance, cost-effectiveness, and environmental friendliness. Solar panels, a cornerstone of renewable energy, have the potential to provide clean electricity, but their efficiency depends on temperature control. This research addresses this challenge by implementing an Internet of Things (IoT) monitoring and control system using the Blynk platform to regulate solar panel surface temperatures. The system's smart design uses water pumps to mitigate excessive temperatures, improving performance and energy efficiency. Extensive testing demonstrated the system's effectiveness, particularly in mitigating temperature spikes, improving system efficiency and sustainability. Our results demonstrate the remarkable potential of water-cooled systems and IoT technology to revolutionize solar energy harvesting, marking a significant step toward a sustainable energy future.
Co-Authors . Iswanto A. Mossa, Mahmoud A. Salah, Wael Abboud, Sarah Abdel-Nasser Sharkawy Abdel-Nasser Sharkawy Abdullah Çakan Abdullah Çakan Abdullah Çakan Abdulmaged, Riyam Bassim Abougarair, Ahmed Abougarair, Ahmed J Abougarair, Ahmed J. Abougarair, Ahmed Jaber Abu, N. S. Abu, Nur Syuhadah Aburakhis, Mohamed Adhianty Nurjanah Adli, M. H. Adriyanto, Feri Agus Aktawan, Agus Ahmad Nurimam Akbar, Afindra Hafiedz Al Ibrahmi, Elmehdi Al Madani Kurniawan, Aqsha Al-Quraan, Ayman Al-Sabur, Raheem Al-Tahir, Sarah O. Alanssari, Ali Ihsan Alayi, Reza Aldi Bastiatul Fawait Fawait Alfan Habibillah Alfan Habibillah Alfian, Eriko Alfian, Rio Ikhsan Ali Asghar Poorat Aljanabi, Haider Dheyaa Kamil Aljarhizi, Yahya ALYA MASITHA Alyazidi, Nezar M. Amelia, Shinta Ammi, Yamina Andino Maseleno Angelo Marcelo Tusset Anhar Anhar Aninditya Anggari Nuryono Anish Pandey Anna Nur Nazilah Chamim Ansarifard, Mehdi Anton Yudhana Antonius Rajagukguk Anuchart Srisiriwat Anwar, Miftahul Anwer, Noha Apik Rusdiarna Indra Praja Ardana, Regina Olivia Fitri Ariadita, Silfia Cindy Ariska Fitriyana Ningrum Arya Adiningrat Ashadi Setiawan Asih, Hayati Mukti Asno Azzawagama Firdaus Baballe, Muhammad Ahmad Bagas Putra Anggara Bakouri, Mohsen Bakti Setiawan Bangun Aji Saputra Barbara Gunawan Basil, Noorulden Bdirina, El Khansa Belabbas, Belkacem Benabdallah, Naima Benlaloui, Idriss Berlian Shanaza Andiany Bessous, Noureddine Bilah Kebenaran Binnerianto, Binnerianto Boulal, Abdellah Bousseksou, Radouane Boutabba, T. Bukhari, W. M. Cakan, Abdullah Carlos Antonio Márquez-Vera Carlos Sánchez-López Carlos Sánchez-López Cengiz Deniz Chico Hermanu Chivon, Choeung Chojaa, Hamid Chotikunnan, Phichitphon Chotikunnan, Rawiphon Dahmani, Abdennasser Dhias Cahya Hakika Dhiya Uddin Rijalusalam Dhiya Uddin Rijalusalam Dhiya Uddin Rijalusalam Dhiya Uddin Rijalusalam Diab, Yasser Dianda Rifaldi Dimas Chaerul Ekty Saputra Dimas Dwika Saputra Dimas Herjuno Dodi Saputra Dodi Saputra Dwi Ana Ratna Wati Dyah Mutiarin Edwin A. Umoh Eka Suci Rahayu Eka Suci Rahayu Eka Widya Suseno Ekinci, Serdar Elbadaoui, Sara Elzein, I. M. Eskandar Jamali Faalah, Fadjar Nur Fadhil Mohammed, Abdullah Fadlur Rahman T. Hasan Fahassa, Chaymae Fahmi Syuhada Faikul Umam Farnaz Jahanbin Fathurrahman, Haris Imam Karim Fathurrahman, Haris Imam Karim Fatma Nuraisyah, Fatma Febryansah, M. Iqbal Ferydon Gharadaghi Feter, Muslih Rayullan Fitri Arofiati Frisky, Aufaclav Zatu Kusuma Furizal Furizal Furizal Furizal, Furizal Gatot Supangkat Gatot Supangkat Gonibala, Fajriansya Guntur Nugroho Habachi, Rachid Hadoune, Aziz Hamdi Echeikh Hamzah M Marhoon Hamzah M. Marhoon Hanini, Salah Hanna, Ahmad Zyusrotul Haq, Qazi Mazhar ul Hari Maghfiroh Hari Maghfiroh Haryo Setiawan Hasibuan, Ahmad Firdaus Hassan, Ammar M. Hassan, Reem Falah Hassanine, Abdalrahman M. Hedroug, Mohamed Elamine Hendriyanto, Raeyvaldo Dwi Heroual, Samira Hossein Monfared Houari Khouidmi Ikhsan Alfian, Rio Ikram, Kouidri Ilham Mufandi Imam Riadi Iman Permana Iman Sahrobi Tambunan Imura, Pariwat Ipin Prasojo Irfan Ahmad Irfan Ahmad Irianto Irianto Israa Al_barazanchi ISTIARNO, RYAN Iswanto Iswanto Iswanto Iswanto Iswanto Iswanto Iswanto Iswanto Iswanto Suwarno Iswanto Suwarno Iswanto Suwarno Iswanto Suwarno Izci, Davut Javana, Kanyanat Jazaul Ikhsan Jihad Rahmawan Joko Pitoyo Joko Slamet Saputro Jonattan Niño Parada Juwitaningtyas, Titisari Kamel Guesmi, Kamel Kariyamin, Kariyamin Keawkao, Supachai Kemal Thoriq Al-Azis Kherrour, Sofiane Khoirudin Wisnu Mahendra Khotakham, Wanida Kurniasari, Indah Dwi Kusuma, Isnainul Laidi, Maamar Laveet Kumar Li-Yi Chin Listyantoro, Fiki Lora Khaula Amifia Loulijat, Azeddine Magdi S. Mahmoud Magdi Sadek Mahmoud Magdi Sadek Mahmoud Maghfiroh, Hari Maharani, Siti Mutia Mahmoud A. Mossa Mahmoud Zadehbagheri Mahmoud Zadehbagheri Mahmoud, Magdi S. Mahmoud, Magdi Sadek Mahmoud, Mohamed Metwally MAJDOUBI, Rania Mangku Negara, Iis Setiawan Mangkunegara, Iis Setiawan Marco Antonio Márquez Vera Marco Antonio Márquez Vera Marhoon, Hamzah M Marhoon, Hamzah M. Mechnane, F. Meiyanto Eko Sulistyo Mekonnen, Atinkut Molla Miftahul Anwar Mila Diah Ika Putri Moch. Iskandar Riansyah Mohamad, Effendi Mohamed Akherraz Mohammad Javad Kiani Mohammed, Abdullah Fadhil Mossa, Mahmoud A. Moutchou, Mohamed Much. Fuad Saifuddin Muchammad Naseer Muhaimin Toh-arlim Muhammad Abdus Shomad Muhammad Ahmad Baballe Muhammad Amin Muhammad Arif Seto Muhammad Fuad Muhammad Heri Zulfiar Muhammad Iman Nur Hakim Muhammad Irfan Pure Muhammad Maaruf Muhammad Nizam Muhammed N. Umar Murni Murni Nadheer, Israa Nail, Bachir Nakib, Arman Mohammad Natawangsa, Hari Naufal Rahmat Setiawan Nia Maharani Raharja Nia Maharani Raharja Nia Maharani Raharja Nia Maharani Raharja Nia Maharani Raharja Nia Maharani Raharja Nia Maharani Raharja Nima Shafaghatian Nirapai, Anuchit Noorulden Basil Noorulden Basil Mohamadwasel Nugroho H, Yabes Dwi Nugroho, Oskar Ika Adi Nuntachai Thongpance Nur Syuhadah Abu Nur’Aini, Etika Nuryono Satya Widodo Nuryono, Aninditya Anggari Olunusi, Samuel Olugbenga Omar Muhammed Neda Omokhafe J. Tola Ouhssain, Said Oun, Abdulhamid A. Phichitphon Chotikunnan Phichitphon Chotikunnan Pisa, Pawichaya Pranoto, Kirana Astari Prasetya, Wahyu Latri Prisma Megantoro Puriyanto, Riky D. Puriyanto, Riky Dwi Puriyanto, Riky Dwi Purwono Purwono, Purwono Purwono, Purwono Putra, Rean Andhika Putra, Rizal Kusuma Qazi Mazhar ul Haq Qolil Ariyansyah Rachmad Andri Atmoko Rachmawan Budiarto Radhwan A. A. Saleh Rahim Ildarabadi Rahmadhia, Safinta Nurinda Rahmadini, Vatia Fahrunisa Rahmaniar, Wahyu Rahmat Setiawan, Naufal Rahmat Setiawan, Naural Ramadhan, Yogi Reza Ramadhani, Nur Ramelan, Agus Ramli, Nor Hanuni Rania Majdoubi Ravi Sekhar Rawiphon Chotikunnan REKIK, Chokri Reza Alayi Reza Alayi Reza Alayi Ridha, Hussein Mohammed Rikwan, Rikwan Rio Ikhsan Alfian Ritonga, Asdelina Riyanarto Sarno Roongprasert, Kittipan Sabbar, Bayan Mahdi Sagita, Muhamad Rian Salah, Wael Salah, Wael A. Salamollah Mohammadi-Aykar Samir Ladaci Saputra, Ekky Haqindytia Sari, Nurjanah Arvika Sashikala Mishra Sawan, Salah I. Semma, El Alami Setiawan, Muhammad Haryo Setiawan, Naufal Rahmat Shafeeq Bakr, Zaid Sharkawy, Abdel-Nasser Shinta Amelia Shomad, Muhammad Abdus Siti Fatimah Anggraini Siti Jamilatun Subrata, Arsyad Cahya Suko Ferbriyanto sunardi sunardi Sunardi Sunardi Sunardi, Sunardi Sunat, Khamron Suwarno, Iswanto Syuhada, Fahmi Taufan Maulana Hazbi Tayane, Souad Tayeb Allaoui Thajai, Phanassanun Thongpance, Nuntachai Tibermacine, Imad Eddine Tohari Ahmad Tony K Hariadi Touti, Ezzeddine Umoh, Edwin Vera, Marco Antonio Marquez Vernandi Yusuf Muhammad Vicky Fajar Setiawan Wahyu Caesarendra Wahyu Rahmaniar Wahyu Rahmaniar Wibisono, Muhammad Damar Wijaya, Setiawan Ardi Wulandari, Annastasya Nabila Elsa Yaser Ebazadeh Yaser Ebazadeh Yassine Zahraoui Yunandha, Isro D. Yutthana Pititheeraphab Zahraoui, Yassine Zaineb Yakoub Zy, Ahmad Turmudi