Article Per Year (5 Year)
p-Index From 2021 - 2026
9.98
P-Index
This Author published in this journals
All Journal Inersia : Jurnal Teknik Sipil dan Arsitektur Seminar Nasional Aplikasi Teknologi Informasi (SNATI) Semantik Journal of Education and Learning (EduLearn) Jurnal Pendidikan Fisika Indonesia Journal of Educational Science and Technology Proceedings Konferensi Nasional Sistem dan Informatika (KNS&I) Jurnal Intelektualita: Keislaman, Sosial, dan Sains CESS (Journal of Computer Engineering, System and Science) Jurnal Pendidikan Fisika Jurnal Pendidikan Agama Islam Jurnal Penelitian Pendidikan IPA (JPPIPA) Squalen Bulletin of Marine and Fisheries Postharvest and Biotechnology Journal of Natural Science and Integration Cetta: Jurnal Ilmu Pendidikan Technomedia Journal JURNAL PENDIDIKAN TAMBUSAI Jesya (Jurnal Ekonomi dan Ekonomi Syariah) Aptisi Transactions on Management IQTISHADUNA: Jurnal Ekonomi dan Keuangan Islam Aptisi Transactions on Technopreneurship (ATT) CCIT (Creative Communication and Innovative Technology) Journal MANAZHIM SENSITEK ADI Journal on Recent Innovation (AJRI) Journal of Innovation and Future Technology (IFTECH) ICIT (Innovative Creative and Information Technology) Journal MARLIN : Marine and Fisheries Science Technology Journal Journal Sensi: Strategic of Education in Information System CICES (Cyberpreneurship Innovative and Creative Exact and Social Science) Journal Cerita: Creative Education of Research in Information Technology and Artificial Informatics JISA (Jurnal Informatika dan Sains) Jurnal Inovasi Pendidikan MH Thamrin Jurnal Abdimas Ilmiah Citra Bakti (JAICB) ADI Bisnis Digital Interdisiplin (ABDI Jurnal) Integrated Science Education Journal ENVIRONMENTAL OCCUPATIONAL HEALTH AND SAFETY JOURNAL Nusantara Hasana Journal ADI Pengabdian kepada Masyarakat Jurnal (ADIMAS Jurnal) Studi Ilmu Manajemen dan Organisasi Bima Journal : Business, Management and Accounting Journal Journal of Artificial Intelligence and Engineering Applications (JAIEA) Startupreneur Business Digital (SABDA Journal) Jurnal Teknik Industri Universal Raharja Community (URNITY Journal) Jurnal MENTARI: Manajemen, Pendidikan dan Teknologi Informasi Jurnal Ilmiah Pendidikan dan Keislaman Jurnal Pendidikan dan Pengabdian Masyarakat Nanggroe: Journal Of Scholarly Service Jurnal Bintang Pendidikan Indonesia Indonesian Journal of Education Research (IJoER) Proceeding Mercu Buana Conference on Industrial Engineering Nanggroe: Journal of Scholarly Service El-Mal: Jurnal Kajian Ekonomi & Bisnis Islam Blockchain Frontier Technology (BFRONT) Jurnal Elementaria Edukasia International Transactions on Artificial Intelligence (ITALIC) Journal of Ekonomics, Finance, and Management Studies Jurnal Pendidikan MIPA Mathematics Education Journal Atom Indonesia IJIS Edu : Indonesian Journal of Integrated Science Education
Muhamad Yusup
Universitas Raharja
Religion 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 Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Immunology & microbiology Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Medicine & Pharmacology Neuroscience Nursing Physics Public Health Social Sciences Other

Published : 115 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 115 Documents
Search

 8   9   10   11   12 
Comparative Analysis of Machine Learning Methods in Predicting Diabetes Risk Based on Genetic Data Kusumaningrum, Sekar Ayu Wijaya; Soleh, Oleh; Yusup, Muhamad
JISA(Jurnal Informatika dan Sains) Vol 8, No 2 (2025): JISA(Jurnal Informatika dan Sains)
Publisher : Universitas Trilogi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31326/jisa.v8i2.2486

Abstract

Type 2 Diabetes Mellitus (T2DM) is a global chronic disease caused by the interaction of genetic and environmental factors. The use of genetic data offers great potential for early detection and personalized intervention. However, the complex analysis of genetic data requires sophisticated approaches like machine learning. This study aims to compare the performance of three machine learning algorithms Logistic Regression, Random Forest, and K-Nearest Neighbors (KNN) in predicting T2DM risk based on genetic data. By using a Systematic Literature Review of studies published between 2019 and 2024, the accuracy data from each algorithm was compared. The analysis results show that Random Forest has the best performance with an accuracy of 99.3%. This algorithm excels due to its ability to handle high-dimensional datasets and reduce overfitting. In comparison, KNN achieved an accuracy of 87% and Logistic Regression 82%. These findings support the integration of machine learning into early detection systems and more precise and efficient clinical decision-making for T2DM management.
Spam Message Classification Using the Naïve Bayes Algorithm Based on RapidMiner Muhamad Yusup; Mochamad Isham Fadillah; Rifky Adinanta Fauzanie; Risca Lusiana Pratiwi; Rani Irma Handayani; Euis Widanengsih
Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 5 No. 2 (2026): February 2026
Publisher : Yayasan Kita Menulis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59934/jaiea.v5i2.1811

Abstract

This study implements the Naïve Bayes algorithm for classifying spam and non-spam (ham) messages using the RapidMiner Studio platform. The dataset used was obtained from the SMS Spam Collection Dataset on the Kaggle platform, which consists of 5,759 messages with a distribution of 4,075 ham messages and 1,291 spam messages. The research stages included text pre-processing, model training, and performance evaluation using accuracy, precision, recall, and F1-score metrics. The experimental results showed that the Naïve Bayes model achieved an accuracy of 89.64% with a precision of 56.93%, a recall of 100%, and an F1-score of 72.56%. The research findings indicate that the Naïve Bayes algorithm is effective in detecting spam messages with adequate accuracy, and prove that RapidMiner is an efficient tool for implementing machine learning methods in text classification.
Security and Privacy Enhancement in Decentralized Digital Data Sharing Environments Muhamad Yusup; Mardiana; Ageng Setiani Rafika; Putra Wahyudi, Otniel Feliks; Agung Lorenzo
APTISI Transactions on Management (ATM) Vol 10 No 1 (2026): ATM (APTISI Transactions on Management: January)
Publisher : Pandawan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/vp5s1m02

Abstract

This study examines the suitability of the IPFS as a decentralized architecture for secure digital data exchange. Traditional centralized protocols, such as HTTP, introduce structural vulnerabilities, including single points of failure, metadata exposure, and susceptibility to interception or unauthorized modification. As digital data exchange becomes increasingly essential in various sectors, ensuring data security and privacy has become a growing concern. The primary objective of this study is to evaluate IPFS’s ability to address these vulnerabilities and enhance the security and privacy of digital data-sharing environments. This research employs a structured literature review to synthesize findings from distributed-systems research, cryptographic studies, and peer-to-peer networking analyses. Additionally, the study benchmarks IPFS against traditional storage protocols, such as HTTP and FTP, to assess its advantages and limitations. The results demonstrate that IPFS offers significant advantages, including content-addressed storage, Merkle-DAG verification, and decentralized peer replication. These features improve fault tolerance, ensure data integrity, and reduce the risks of data tampering. However, limitations, such as content availability and reliance on node uptime, are also noted. While IPFS is not a complete security solution, it provides a strong foundational architecture for privacy-preserving, distributed data-sharing workflows when paired with complementary cryptographic and governance frameworks, making it a viable alternative for secure digital data exchange.
Development of Electronic Modules (E-Module) Assisted by Book Creator in Science Learning with Critical Thinking Skills Activities for Junior High School Students Listiyorini; Marlina, Leni; Yusup, Muhamad
Jurnal Penelitian Pendidikan IPA Vol 11 No 2 (2025): February
Publisher : Postgraduate, University of Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jppipa.v11i2.10025

Abstract

This study aims to enhance students' critical thinking skills on the topic of substances and their changes using Book Creator. The research employed the Rowntree development model, with the research subjects being students at SMPN 1 Air Kumbang, Banyuasin Regency. The method used in this study was research and development (R&D) with the Rowntree development model and Tessmer evaluation, tested on 100 junior high school students. The results showed very high validity, with a Content Validity Index (CVI) and a Content Validity Ratio (CVR) of 0.8333, classified as very high. In the One-to-One evaluation stage, the practicality test results showed a percentage of 96.3% for the usefulness aspect and 91.67% for the ease-of-use aspect. In the Small Group Evaluation stage, the practicality of the e-module reached 97.53% for usability, classified as very practical, and 91.67% for ease of use. These results indicate that the e-module is considered very practical. The field test stage was conducted on 100 seventh-grade students to assess the effectiveness of the e-module in improving critical thinking skills. The results showed an N-Gain score of 56.11%, categorized as moderately effective. These findings indicate a significant improvement in students' critical thinking skills using Book Creator.
Utilizing AI and Blockchain for Business Innovation in Digital Strategy Sunarya, Po Abas; Yusup, Muhamad; Fae, Nahlie
Technomedia Journal Vol 10 No 3 (2026): February
Publisher : Pandawan Incorporation, Alphabet Incubator Universitas Raharja

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/kwck2v12

Abstract

In the rapidly evolving digital era, businesses are confronted with the challenge of adapting to fast paced technological changes. Innovative technologies such as Artificial Intelligence (AI) and Blockchain have emerged as solutions that can accelerate business transformation. AI offers data analytics and automation capabilities that enhance operational efficiency, while Blockchain provides the transparency and security required in digital business transactions. This study aims to explore how AI and Blockchain can be leveraged to drive innovation in business strategies and strengthen competitive advantage in an increasingly digital market. The research employs a literature review approach to examine the implementation of AI and Blockchain across various industrial sectors. For example, in the e-commerce sector, major companies such as Amazon and Alibaba have implemented AI to improve customer experience through more accurate product recommendations. Additionally, Blockchain has been utilized by Walmart to enhance supply chain transparency, enabling product traceability from suppliers to consumers. The collected data were analyzed to understand the impact of these technologies on business models and the innovations adopted by companies. The findings indicate that AI accelerates decision making processes and enables personalized customer services, while Blockchain helps establish a more transparent and efficient business ecosystem. Both technologies contribute to the development of stronger and more adaptive digital business models. The implementation of AI and Blockchain in business strategies has proven to enhance innovation, improve operational efficiency, and reinforce competitive advantage. Therefore, adopting these technologies becomes a key factor in achieving success in digitally driven businesses.
Isolation and Selection of Radiation Resistant Fungi from Mamuju High Natural Radiation Soil for Uranium and Thorium Bioremediation Robifahmi, N.; Laksmana, R. I.; Pratama, A. A.; Kusuma, A. T.; Tjiptosumirat, T.; Tuasikal, B. J.; Nugraha, E. D.; Rijal, M. S.; Febrian, V. A.; Yusup, M.; Futy, W.; Mujiyanto, A.; Sugoro, I.
Atom Indonesia Vol 52, No 1 (2026): APRIL 2026
Publisher : National Research and Innovation Agency

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55981/aij.2026.1590

Abstract

Microorganisms from high natural radiation environments hold potential as bioremediation agents for radioactive waste. In this study, isolation and selection of fungi from Mamuju high natural radiation soil was done for radioactive bioremediation. The methods included fungal isolation from soil samples, radiosensitivity tests, sensitivity tests to uranium and thorium, and absorption tests under gamma radiation (100 Gy hour-1). Results revealed three fungal isolates with high growth ratios and resistance to gamma radiation: Talaromyces flavus (A3), Gongronella butleri (A4), and Aspergillus sp. (F1). Isolates A3 and A4 survived up to 2 kGy, while F1 endured up to 8 kGy. At 24 hours, A3 absorbed uranium at 96% with a biomass of 0.73 g and thorium at 84% with 0.98 g biomass. A4 achieved the highest uranium absorption of 97% (biomass 4.11 g) and thorium absorption of 100% (biomass 0.74 g). F1 demonstrated 96% uranium absorption (biomass 1.29 g) and 87% thorium absorption (biomass 2.17 g). These isolates exhibited significant potential for bioremediation of uranium and thorium-contaminated environments, showing unique adaptations to high radiation conditions and effective radioactive metal uptake.
The Implementation of Digital Storytelling to Enhance Early Childhood Learning Experiences Hardini, Marviola; Yusup, Muhamad; Kareem, Yasir Mustafa; Astuti, Eka Dian
Jurnal MENTARI: Manajemen, Pendidikan dan Teknologi Informasi Vol 4 No 2 (2026): March
Publisher : Pandawan Sejahtera Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/mentari.v4i2.1014

Abstract

This study examines how digital storytelling can enhance early childhood learning experiences in preschool settings, in response to the growing integration of technology in education and the need to ensure its alignment with develop-mentally appropriate practices. The objective of this research is to explore how the implementation of digital storytelling influences children’s cognitive engagement, social interaction, and creative expression. Employing a qualitative de- scriptive approach, the study involves 18 children aged 4-6 years in a preschool setting and utilizes classroom observations, structured interviews with teachers, and documentation of learning activities to analyze the implementation process and its pedagogical impact. The findings indicate a tendency toward improved attention span, vocabulary development, and collaborative behavior, as well as enhanced imagination and emotional expression during digital storytelling ses- sions. Teachers reported that digital tools contributed to more interactive and adaptive learning environments, enabling children to connect personal experi- ences with narrative content in meaningful ways. The study concludes that integrating digital storytelling in early childhood education holds strong poten- tial as a developmentally aligned instructional strategy, supporting both child independence and holistic development. It further highlights the importance of thoughtful technological integration in preschool classrooms as a bridge be- tween modern educational innovation and child-centered learning philosophies.
Implementation of Waste Management Policy in South Tangerang City from the Perspective of Environmental Law and the Effectiveness of Law Enforcement Yusup, Muhamad; Panjaitan, Paris; Sadikin, Mohamad; M, Mentari; Sitorus, Novandrik Yeriko; Suryani, N. Lilis
Nanggroe: Jurnal Pengabdian Cendikia Vol 5, No 1 (2026): April 2026
Publisher : Yayasan Daarul Huda Kruengmane

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5281/zenodo.19924220

Abstract

Waste management in South Tangerang City has become an increasingly complex environmental issue along with population growth and urbanization. Although various regulations are already in place, such as Law Number 18 of 2008 and related regional regulations, the implementation of waste management policies still faces numerous challenges, including issues related to legal substance, law enforcement structure, and the legal culture of the community. This Community Service Program (PKM) aims to analyze the implementation of waste management policies from an environmental law perspective and to evaluate the effectiveness of law enforcement in South Tangerang City. The method used is a normative-empirical approach, with activities including seminars, interactive discussions, and workshops involving the community and stakeholders. The findings indicate a gap between preventive regulations and the reality in the field, which remains largely reactive. The main factors contributing to the low effectiveness of law enforcement include limited facilities and infrastructure, weak supervision, and low public awareness regarding waste management. Through this activity, it is expected that public understanding of the importance of environmentally based waste management will increase, along with greater active participation in preserving environmental sustainability. In addition, strengthening derivative regulations, optimizing law enforcement, and implementing technology-based and community-based waste management systems are necessary to achieve effective and sustainable waste management.
Implementation of Waste Management Policy in South Tangerang City from the Perspective of Environmental Law and the Effectiveness of Law Enforcement Yusup, Muhamad; Panjaitan, Paris; Sadikin, Mohamad; M, Mentari; Sitorus, Novandrik Yeriko; Suryani, N. Lilis
Nanggroe: Jurnal Pengabdian Cendikia Vol 5, No 1 (2026): April 2026
Publisher : Yayasan Daarul Huda Kruengmane

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5281/zenodo.19924220

Abstract

Waste management in South Tangerang City has become an increasingly complex environmental issue along with population growth and urbanization. Although various regulations are already in place, such as Law Number 18 of 2008 and related regional regulations, the implementation of waste management policies still faces numerous challenges, including issues related to legal substance, law enforcement structure, and the legal culture of the community. This Community Service Program (PKM) aims to analyze the implementation of waste management policies from an environmental law perspective and to evaluate the effectiveness of law enforcement in South Tangerang City. The method used is a normative-empirical approach, with activities including seminars, interactive discussions, and workshops involving the community and stakeholders. The findings indicate a gap between preventive regulations and the reality in the field, which remains largely reactive. The main factors contributing to the low effectiveness of law enforcement include limited facilities and infrastructure, weak supervision, and low public awareness regarding waste management. Through this activity, it is expected that public understanding of the importance of environmentally based waste management will increase, along with greater active participation in preserving environmental sustainability. In addition, strengthening derivative regulations, optimizing law enforcement, and implementing technology-based and community-based waste management systems are necessary to achieve effective and sustainable waste management.
Predicting Supply Chain Risks Using Machine Learning for Resilient Operations Widayanti, Riya; Setiyowati, Harlis; Yusup, Muhamad; Rodriguez, Marta
ADI Journal on Recent Innovation (AJRI) Vol. 7 No. 2 (2026): March
Publisher : ADI Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34306/ajri.v7i2.1376

Abstract

Rising supply chain disruptions highlight increasing vulnerabilities in global logistics networks caused by geopolitical conflicts, fluctuating demand, transportation failures, and environmental instability. These challenges reveal the limitations of conventional risk assessment approaches that rely heavily on manual analysis and historical data. Machine Learning (ML) offers a promising approach to enhance predictive intelligence and support more accurate decision making in complex supply chain environments. This study aims to develop and evaluate a Machine Learning based risk prediction model capable of identifying potential supply chain disruptions and enabling early detection of critical risk factors in global logistics operations. A quantitative experimental approach was employed using supply chain datasets integrated with disruption indicators from international logistics activities. The dataset consisted of more than 5,000 operational records collected between 2018 and 2024. Several machine learning algorithms were implemented and compared, including Random Forest, Gradient Boosting, and Support Vector Machines. Experimental results indicate that the Gradient Boosting algorithm achieved the highest predictive performance with an accuracy of 94.2%. The model successfully identified key determinants of supply chain risk, including demand variability, supplier reliability, and transportation delays. These findings confirm that machine learning based predictive models can enhance supply chain resilience by enabling early risk detection and supporting proactive decision making in global logistics operations.
Co-Authors A. Setiawan A. Suhandi Abbas, Diego Abidin Pasaribu, Abidin Achmad Samsudin Adi Rusdi Widya Adimayuda, Rizal Adnan, Haidar Bustomi Adyatama, Rendhika Afifah, Rufnia Ayu Agung Lorenzo Agung Rizky Ahmad Alwi Nurudin Ahmad Asroni Ahmad Munawar Ahmad Yadi Fauzi Alwiyah Alwiyah Amalia, Wardah Amallia, Naila Amarto, Usman Amarulloh Amarulloh Amin Solihin, Amin Aminudin, Adam Hadiana Ana Nurmaliana Andrew Tirta Andri Saepudin Anggy Giri Prawiyogi Anita Bawaiqki Wandanaya Ankur Singh Bist Anwar, Aang Solahudin Anwar, Muhammad Rehan Apertha, Fanny Khairul Putri Apit Fathurohman Ari Asmawati ariq, Muhammad faris Ary Budi Warsito Ary Budi Warsito Ary Budi Warsito Ary Budi Warsito Ary Budi Warsito, Ary Budi Aspuri, Muhamad Astuti, Eka Dian Augury El Rayeb Aulia Edliyanti Ayi Rakhmat Ramdani Azahrah, Tiara Azuddin, Muna Bachtiar Bachtiar Baiq Ratna Mulhimmah Bambang Triwibowo Basuki, Sucipto Bhupesh Rawat Bimastari, Inda Hasanah Binar Kurnia Prahani budiarty, frizca Ceria Marcelina Chandra, Ratna Dwi Costu, Bayram Damayanti, Fitria Siska Danny Manongga Devi, Lakshmi Dewi Listiani Sukamto Dewi, Yessica Chrisna Diah Aryani Diah Aryani Diah Aryani Diah Aryani, Diah Dimas Prastama Julianto Edwards, John Eko Prasetiyani Eko Prasetiyani Eliando Erham Budi Wiranto Erlita Rasdiana Erni Astuti Euis Siti Nur Aisyah, Euis Siti Nur Euis Widanengsih FACHROZI. F Fadilah, Jasmine Fae, Nahlie Fahreza, Aulianda Zahrina Faizin, Mohammad Noor Faradila, Alya Febrian, V. A. Fidrian Millen Prayogi Firmanul Catur Wibowo Fitria Siska damayanti Fratiwi, Nuzulira Janeusse Fredy Susanto Futy, W. Garcia, Alessandro Daeli Giandari Maulani, Giandari Hamdi Akhsan Hani Dewi Ariessanti Hani Dewi Arriesanti Haratua, Chandra Sagul Harianja, M Rokhati Haris - Harlis Setiyowati Hatami, Alifa Syauqi Henderi . Hera Novia Hidayatullah, Baeti Sarif I. Sugoro Ida Kaniawati Ida Sriyanti Ifran Sanni Ika Lestari, Ika Ilamsyah - Ilamsyah Ilamsyah Ilamsyah Ilamsyah, Ilamsyah Irawan, Muhammad Zhudy Irenta Irwan Sembiring Irwandani Irwandani Ismet Jaka Suwita Kamal, ⁠Abdullah Arif Kareem, Yasir Mustafa Khairunnas, Siti Khoirul Rodzikin Kistiono Kistiono Kistiono Krisandi Aprilyanto Kurniaji, Ridwan Kurniasari, Reni Oktavia Kurniasih Kurniasih Kurniawan, Rano Kusuma, A. T. Kusuma, Luqman Hafidz Kusumaningrum, Sekar Ayu Wijaya Laksmana, R. I. Laurentius Andriyanto Leni Marlina Lilik Agustin Listiyorini Listiyorini, Listiyorini M, Mentari Mahdayeni, Mahdayeni Mahmudulhasan Maimunah, Ira MARDIANA Mardiana Mardiana Markos Siahaan, Sardianto Marviola Hardini Marzani, Marzani Masrifah, Masrifah Maulana Yusuf Maulana Yusuf Maulana, Sabda Melinia, Sela Melly Ariska Meri Mayang Sari Miftakhul Khasanah Millah, Shofiyul Mochamad Isham Fadillah Moh. Iqbal Awi Makaram Mohamad Sadikin Mohamad Syarif Sumantri Muh. Salahuddin, Muh. Muhammad Faisal Muhammad Nurtanto Mujiyanto, A. N.Y. Rustaman Nadiya Nasution, Erni Juliana Al Hasanah Nidhi Mehra Ninda Lutfiani Ninu Apriyani Nofia Supriyani Novmewi, Yusuf Nugraha, E. D. Nuke Puji Lestari Santoso Nur Azizah Nurbani, Siti Zachro Nurlaila Suci Rahayu Rais NURUL AZIZAH Oleh Soleh, Oleh Padeli Padeli Panjaitan, Paris Pertiwi, Komala Dwi Po Abas Sunarya Pokkali, Krishna Chaitanya Pongky Arie Wijaya Pratama, A. A. Priyadi, Agung Purnomo, Yunianto Putra Wahyudi, Otniel Feliks Qurotul Aini Rafika, Ageng Setiani Rahman, Nor Farahwahidah Abdul Ramadhan, Rezki Ramadita, Salsabil Fardha Ramli, Ahmad Rani Irma Handayani Rani Lestari Reza Dani Pramudya Rifky Adinanta Fauzanie Rijal, M. S. Risca Lusiana Pratiwi Riswan Jaenudin Rivai Sungkowo Riya Widayanti Rizky Kurniawan Robifahmi, N. Rodriguez, Marta Roma Ito, Yulia Romadi Romadi Ronal Aprianto Rosdiana Rosdiana Rosyid, Adhe Muhammad Rosyifa Rosyifa Saepudin, Andri Sairi, Muhammad Salampessy, Randi B.S Sanurdi Sanurdi Sardianto Markos Siahaan Sari, Meri Mayang Sayuti, Mohammad Sekar Ayu Aryani Shalahuddin, Shalahuddin Shofiyul Millah Siahaan, Kelvin Sihotang, Sondang Visiana Sinta Puspita Dewi Siti Fauziah Siti Rochmani Sitorus, Novandrik Yeriko SRI RAHAYU Sri Wahyani, Sri Sri Yulianto Joko Prasetyo Sugiarto, Gerry Suhaepi, Muhamad Iip Suhendi Suhendi Sukmawati, Eva Sunengsih, Meriyana Supriyati . Supriyatman, Supriyatman Suratmi Suryani, N. Lilis Suryari Purnama Susan Oktaviani Susanto Rahardja Sutarman, Asep Sutarto Wijono Syamsiar, Syamsiar Syamsul Arifin Syauqi Naufal, Romzi Takrim, Muhammad Taqwa Hariguna Taqwa Hariguna Tarisya Ramadhan Taufiq Taufiq Theopillus J. H. Wellem Tjiptosumirat, T. Triana, Desilawati Tuasikal, B. J. Turki Salim Untung Rahardja Uzma, Wishnu Waston Wibowo, Shesilia Wijil Nugroho Yeni, Alfitri Yulia Putri Ayu Sanjaya Yuliani, Opie Oktavia Yulianto Yulianto Yulika Ayu Rantama Yunita Kartika Sari Yusuf Abdurachman Zebua, Selamat Zulkardi