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All Journal International Conference on Law, Business and Governance (ICon-LBG) International Conference on Education and Language (ICEL) International Conference on Engineering and Technology Development (ICETD) Jurnal English Education: Jurnal Tadris Bahasa Inggris Explore: Jurnal Sistem Informasi dan Telematika (Telekomunikasi, Multimedia dan Informatika) EXPERT: Jurnal Manajemen Sistem Informasi dan Teknologi Jurnal Informatika Jurnal Informatika International Multidiciplinary Conference on Social Sciences (IMCoSS) Prosiding Seminar Nasional Darmajaya Jurnal Informasi dan Teknologi International Journal of Health, Economics, and Social Sciences (IJHESS) Jurnal Kolaboratif Sains Journal Of Human And Education (JAHE) Digital Transformation Technology (Digitech) Sanskara Hukum dan HAM Innovative: Journal Of Social Science Research Sahabat Sosial: Jurnal Pengabdian Masyarakat West Science Business and Management Jurnal Ekonomi dan Kewirausahaan West Science West Science Interdisciplinary Studies Jurnal ICT : Information and Communication Technologies West Science Accounting and Finance West Science Interdisciplinary Studies West Science Social and Humanities Studies The Eastasouth Journal of Information System and Computer Science Science Information System and Technology West Science Nature and Technology Journal of Innovative and Creativity Journal of Artificial Intelligence and Development Marsialapari: Jurnal Pengabdian Kepada Masyarakat Journal of Engineering and Science Application Jurnal Ekonomi, Manajemen, Akuntansi Journal of Moeslim Research Technik Research of Scientia Naturalis Jurnal Sipakatau Indonesian Journal of Enterprise Architecture ZAHRA (JOURNAL OF HEALTH AND MEDICAL RESEARCH) Indonesian Journal of Education (INJOE) Jurnal Ilmu Pendidikan dan Kearifan Lokal (JIPKL) Jurnal Ekonomi dan Bisnis (Jebi) Journal of World Future Medicine, Health and Nursing
Arnes Yuli Vandika
Universitas Bandar Lampung
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USING NEURAL COLLABORATIVE FILTERING TO PERSONALIZE ONLINE LEARNING CONTENT Novianty Djafri; Kasmudin Mustapa; Arnes Yuli Vandika
Indonesian Journal of Education (INJOE) Vol. 3 No. 1 (2023): Indonesian Journal of Education (INJOE)
Publisher : CV. ADIBA AISHA AMIRA

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Abstract

Personalization of learning is a strategy used to determine the characteristics of learners so they can learn effectively. There are many approaches that can be taken to personalize learning. This system for personalizing learning content in the form of recommendations for online learning content was built using the Neural Collaborative Filtering method and utilizes a collection of implicit feedback data taken from student activity records when interacting with online learning content as reference data to produce recommendations. The design of a learning content personalization system in the form of recommendations on online learning content for students using the Neural Collaborative Filtering method has been successfully built and can run well in online learning content. The literature study approach was used to conduct the research. Data and relevant information were gathered through a review of the literature using Neural Collaborative Filtering to personalize online learning content. This research discusses traditional methods in personalizing online learning content, Neural Collaborative Filtering, relevant previous research, and the implementation of Neural Collaborative Filtering in online learning content
KECERDASAN BUATAN SEBAGAI MITRA DALAM PENILAIAN DAN EVALUASI PENDIDIKAN Alim Hardiansyah; Rosmawati Harahap; Arnes Yuli Vandika
Jurnal Ilmu Pendidikan dan Kearifan Lokal Vol. 2 No. 5 (2024): Jurnal Ilmu Pendidikan dan Kearifan Lokal (JIPKL)
Publisher : CV. ADIBA ASIHA AMIRA

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Abstract

Artificial Intelligence (AI) has emerged as a transformative technology in various fields, including education. AI offers significant capabilities in analysing large-scale data, providing real-time feedback, and tailoring assessments to students' individual needs. The research method used literature. The results showed that the integration of AI in educational assessment requires a balanced approach that blends the analytical power of AI with human judgement. In conclusion, AI has the potential to increase the effectiveness and personalisation of educational assessment, but its implementation must be done with careful ethical considerations and focus on enhancing, not replacing, the role of educators in the evaluation process
PENGGUNAAN KECERDASAN BUATAN UNTUK PERSONALISASI PENGALAMAN BELAJAR Arnadi Arnadi; Aslan Aslan; Arnes Yuli Vandika
Jurnal Ilmu Pendidikan dan Kearifan Lokal Vol. 3 No. 1 (2024): Jurnal Ilmu Pendidikan dan Kearifan Lokal (JIPKL)
Publisher : CV. ADIBA ASIHA AMIRA

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Abstract

Using Artificial Intelligence (AI) to Personalise Learning Experiences refers to the application of AI technology and machine learning algorithms in an educational context to create individually tailored learning experiences for each learner. This approach leverages AI's ability to analyse big data about each student's learning paterns, strengths, weaknesses and preferences, then uses that information to adjust content, pace and teaching methods in real-time. The aim is to optimise the learning process by providing the most relevant and effective material for each individual. In practice, these AI-based systems can recommend appropriate learning resources, adjust task difficulty levels, provide personalised feedback, and even predict areas where a student may struggle in the future. This approach not only includes customisation of academic content, but can also take into account factors such as a student's learning style, motivation, and socio-emotional context. Thus, the use of AI to personalise learning experiences aims to create an educational environment that is more inclusive, effective, and responsive to the individual needs of each learner.
THE ROLE OF ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING IN PRECISION TARGETING: REVOLUTIONIZING MARKETING STRATEGIES Silvia Ekasari; Loso Judijanto; Arnes Yuli Vandika
Jurnal Ekonomi dan Bisnis Vol. 2 No. 1 (2024): JEBI: Jurnal Ekonomi dan Bisnis
Publisher : CV. Adiba Aisha Amira

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Abstract

Digital marketing has undergone rapid evolution in recent years. The development of machine learning and artificial intelligence (AI) is one of the major shifts affecting the marketing environment (ML). This technology has completely changed how businesses engage with their clientele and maximize their advertising budgets. Artificial intelligence refers to the ability of a computer or system to imitate human intelligence. In the context of digital marketing, AI can be used to quickly and efficiently analyze data, identify patterns and provide valuable insights. With artificial intelligence, companies can make smarter decisions and optimize their marketing campaigns based on deeply analyzed data. The method used in this article is the study method. Literature studies can be obtained from various sources, including journals, books, documentation, the internet and libraries. This research discusses the definition of AI and ML, the transformation of the marketing sector by digital platforms and data analytics, the exploration of precision marketing and its increasing relevance in the digital era, the role of AI and ML in data mining for precision targeting, the contribution of AI in creating more granular customer segments, and the study of ML in predictive analytics to anticipate customer behavior.
Pemberdayaan Kader Kesehatan dalam Meningkatkan Perilaku Hidup Sehat Masyarakat Abdullah Abdullah; Abdul Rahim; Arnes Yuli Vandika; Lorensius Lonik
Sahabat Sosial: Jurnal Pengabdian Masyarakat Vol. 4 No. 3 (2026): Sahabat Sosial: Jurnal Pengabdian Masyarakat (Juni)
Publisher : Asosiasi Guru dan Dosen Seluruh Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59585/sosisabdimas.v4i3.1168

Abstract

ABSTRACT Healthy living behaviors are a crucial factor in improving public health. However, many people still have not optimally implemented healthy living behaviors in their daily lives. Health cadres, as part of the community, play a crucial role in assisting health workers in health promotion at the community level. This community service activity aims to improve the knowledge and skills of health cadres in educating the public about healthy living behaviors. Implementation methods include health cadre training, health education, interactive discussions, and pre- and post-activity knowledge assessments. The results of the activity indicate an increase in the knowledge and skills of health cadres in educating the public about healthy living behaviors. Empowering health cadres has proven effective in increasing community participation in implementing healthy living behaviors. Keywords: Health Cadres, Community Empowerment, Healthy Living Behavior, Health Promotion ABSTRAK Perilaku hidup sehat merupakan salah satu faktor penting dalam meningkatkan derajat kesehatan masyarakat. Namun, masih banyak masyarakat yang belum menerapkan perilaku hidup sehat secara optimal dalam kehidupan sehari-hari. Kader kesehatan sebagai bagian dari masyarakat memiliki peran penting dalam membantu tenaga kesehatan dalam melakukan promosi kesehatan di tingkat komunitas. Kegiatan pengabdian kepada masyarakat ini bertujuan untuk meningkatkan pengetahuan dan keterampilan kader kesehatan dalam mengedukasi masyarakat mengenai perilaku hidup sehat. Metode pelaksanaan meliputi pelatihan kader kesehatan, penyuluhan kesehatan, diskusi interaktif, serta evaluasi tingkat pengetahuan sebelum dan sesudah kegiatan. Hasil kegiatan menunjukkan adanya peningkatan pengetahuan dan keterampilan kader kesehatan dalam memberikan edukasi kepada masyarakat mengenai perilaku hidup sehat. Pemberdayaan kader kesehatan terbukti efektif dalam meningkatkan partisipasi masyarakat dalam menerapkan perilaku hidup sehat. Kata Kunci: Kader Kesehatan, Pemberdayaan Masyarakat, Perilaku Hidup Sehat, Promosi Kesehatan.
Application of Artificial Intelligence in Medical Diagnostics: Applications and Implications in the Healthcare Sector Arnes Yuli Vandika; Dadang Muhammad Hasyim; Devi Rahmah Sope; Legito; Novycha Auliafendri
Jurnal Informasi dan Teknologi 2025, Vol. 7, No. 3
Publisher : SEULANGA SYSTEM PUBLISHER

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60083/jidt.vi0.674

Abstract

Artificial Intelligence (AI) has emerged as a transformative innovation in the medical diagnostic sector. This study explores the application and implications of AI in healthcare services at RSUD Dr. H. Abdul Moeloek, Bandar Lampung. Using a qualitative case study method, data were obtained through in-depth interviews and participatory observation. The results show that AI contributes significantly to improving diagnostic accuracy and speed, particularly in radiological imaging. However, limitations in technological infrastructure and system integration were found to hinder its optimal use. Furthermore, the readiness of human resources remains a critical factor. Although there is optimism among medical staff, a lack of technical training has led to gaps in understanding and utilization. Ethical and legal concerns also emerged, especially regarding responsibility in case of misdiagnosis and the protection of patient data. The absence of specific regulations and digital ethics protocols presents a major barrier to AI adoption. This research concludes that while the implementation of AI in medical diagnostics shows promising outcomes, it still faces institutional and regulatory challenges. Strengthening digital literacy among healthcare workers, developing standard operating procedures, and building a secure infrastructure are essential. Collaboration between hospitals, academic institutions, and government bodies is needed to create an inclusive and ethical AI-based healthcare ecosystem.
Pemberdayaan Masyarakat melalui Program Bank Sampah untuk Meningkatkan Kesehatan Lingkungan Muslimin B; Arnes Yuli Vandika; M.Khalid Fredy Saputra
Sahabat Sosial: Jurnal Pengabdian Masyarakat Vol. 4 No. 3 (2026): Sahabat Sosial: Jurnal Pengabdian Masyarakat (Juni)
Publisher : Asosiasi Guru dan Dosen Seluruh Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59585/sosisabdimas.v4i3.1167

Abstract

ABSTRACT Waste is an environmental problem that can impact public health. Improper waste management can lead to environmental pollution and increase the risk of various environmental-based diseases. One effort that can be made to address the waste problem is through a waste bank program that involves active community participation in waste management. This community service activity aims to increase public awareness and participation in waste management through the waste bank program as an effort to improve environmental health. Implementation methods include environmental health education, waste management training, the formation of waste bank groups, and activity evaluation. The results of the activity indicate an increase in public knowledge and participation in waste management, as well as increased public awareness of the importance of maintaining a clean environment. The waste bank program has proven effective in improving environmental health and community empowerment. Keywords: Waste Bank, Community Empowerment, Environmental Health, Waste Management ABSTRAK Permasalahan sampah merupakan salah satu masalah lingkungan yang dapat berdampak pada kesehatan masyarakat. Pengelolaan sampah yang tidak tepat dapat menyebabkan pencemaran lingkungan serta meningkatkan risiko berbagai penyakit berbasis lingkungan. Salah satu upaya yang dapat dilakukan untuk mengatasi permasalahan sampah adalah melalui program bank sampah yang melibatkan partisipasi aktif masyarakat dalam pengelolaan sampah. Kegiatan pengabdian kepada masyarakat ini bertujuan untuk meningkatkan kesadaran dan partisipasi masyarakat dalam pengelolaan sampah melalui program bank sampah sebagai upaya meningkatkan kesehatan lingkungan. Metode pelaksanaan meliputi penyuluhan kesehatan lingkungan, pelatihan pengelolaan sampah, pembentukan kelompok bank sampah, serta evaluasi kegiatan. Hasil kegiatan menunjukkan adanya peningkatan pengetahuan dan partisipasi masyarakat dalam pengelolaan sampah serta meningkatnya kesadaran masyarakat terhadap pentingnya menjaga kebersihan lingkungan. Program bank sampah terbukti efektif dalam meningkatkan kesehatan lingkungan dan pemberdayaan masyarakat. Kata Kunci: Bank Sampah, Pemberdayaan Masyarakat, Kesehatan Lingkungan, Pengelolaan Sampah
Development of Machine Learning Algorithms for Anomaly Detection in Internet of Things (IoT) Networks Vicheka Rith; Vann Sok; Arnes Yuli Vandika
Journal of Moeslim Research Technik Vol. 1 No. 5 (2024)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/technik.v1i5.1560

Abstract

The proliferation of Internet of Things (IoT) devices has increased the vulnerability of networks to security threats, making anomaly detection essential for maintaining system integrity. Traditional security measures often fall short in identifying and mitigating complex attack patterns that can jeopardize IoT networks. This research aims to develop a machine learning algorithm specifically designed for anomaly detection in IoT environments. The goal is to enhance the ability to identify unusual behavior indicative of potential security breaches while minimizing false positives. A dataset comprising network traffic from various IoT devices was collected and preprocessed to extract relevant features. Several machine learning algorithms, including decision trees, support vector machines, and neural networks, were implemented and evaluated. Performance metrics such as accuracy, precision, recall, and F1-score were used to assess the effectiveness of each model. The results indicated that the proposed machine learning algorithm outperformed traditional methods, achieving an accuracy of 95% in detecting anomalies. The model demonstrated a significant reduction in false positives compared to existing techniques, thereby enhancing the reliability of anomaly detection in IoT networks. The research concludes that the developed machine learning algorithm is a robust solution for detecting anomalies in IoT environments. This advancement contributes to the field by providing an effective tool for improving security measures in the rapidly evolving landscape of IoT. Future work should focus on real-time implementation and further optimization of the algorithm to adapt to dynamic network conditions.
Effectiveness of Deep Learning Models in Cybercrime Prediction Muhammad Mustofa; Shazia Akhtar; Arnes Yuli Vandika
Journal of Moeslim Research Technik Vol. 1 No. 5 (2024)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/technik.v1i5.1561

Abstract

The rise of cybercrime poses significant challenges to security agencies and organizations worldwide. Traditional methods of crime prediction often fall short in accurately identifying potential threats. As a result, there is a growing interest in leveraging advanced technologies, such as deep learning, to enhance predictive capabilities in cybersecurity. This research aims to evaluate the effectiveness of deep learning models in predicting cybercrime incidents. The study investigates how these models can improve accuracy and reliability compared to conventional prediction techniques. A dataset comprising historical cybercrime incidents was collected and preprocessed to extract relevant features. Various deep learning architectures, including convolutional neural networks (CNNs) and recurrent neural networks (RNNs), were implemented. The models were trained and validated using a portion of the data, while performance metrics such as accuracy, precision, recall, and F1-score were used to assess their predictive capabilities. The findings indicate that deep learning models significantly outperform traditional methods in predicting cybercrime incidents. The best-performing model achieved an accuracy of 92%, showcasing its ability to identify complex patterns in the data. Additionally, deep learning models demonstrated lower false positive rates, enhancing their reliability in real-world applications. The research concludes that deep learning is a powerful tool for predicting cybercrime, offering enhanced accuracy and efficiency. These findings contribute to the field by highlighting the potential of advanced machine learning techniques in improving cybersecurity measures. Future work should focus on refining these models and exploring their applicability in real-time cyber threat detection.
Performance Analysis of Cloud Computing Systems in Collaborative Software Development Environments Zhang Li; Yang Xiang; Arnes Yuli Vandika
Journal of Moeslim Research Technik Vol. 1 No. 6 (2024)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/technik.v1i6.1562

Abstract

The rise of cloud computing has transformed software development, enabling collaborative environments that enhance productivity and efficiency. However, the performance of cloud computing systems in supporting collaborative software development remains an area of active research, with various factors influencing effectiveness. This study aims to analyze the performance of cloud computing systems in collaborative software development environments. The focus is on identifying key performance metrics and their impact on team productivity and project outcomes. A mixed-methods approach was employed, combining quantitative performance metrics and qualitative surveys from development teams using cloud-based tools. Key metrics analyzed included system uptime, response time, and resource utilization. Surveys gathered insights on user satisfaction and perceived efficiency improvements. The findings reveal that cloud computing systems significantly enhance collaboration among software development teams. Metrics indicated an average system uptime of 99.5%, with response times averaging under 200 milliseconds. Survey results showed that 85% of participants reported increased productivity when using cloud-based tools compared to traditional methods. The research concludes that cloud computing systems provide substantial performance advantages in collaborative software development environments. These systems facilitate better communication, resource sharing, and project management, ultimately leading to improved project outcomes. Future research should explore the long-term effects of cloud computing on software development practices and its implications for team dynamics.
Co-Authors Abdul Muid Fabanyo Abdul Rahim Abdullah Abdullah Achmad Choerudin Ade Kurniawan Ade Kurniawan Ade Suhara Adnan, Ahmad Zaelani Afen Prana Utama Sembiring Afrizal Afrizal Agus Mukholid Ahmad Cucus Ahmad Nur Budi Utama Ahmad Zaelani Adnan Ainun Jariyah Aldo, Novian Aldo, Novian Alim Hardiansyah Alim Hardiansyah Ambarwati, Rini Amelia S. Sarungallo Ana Uzla Batubara Andi Arfah Andi Naila Quin Azisah Aliasyahbana Andi Naila Quin Azisah Alisyahbana andrew shandy utama, andrew shandy Anggeraeni, Anggeraeni Anggit Wasesa Praja Anggun Nugroho Anggun Nugroho, Anggun Annisa Paramaswary Aslam Ansar Ansar Archristhea Amahoru, Archristhea Ardiana Batubara Ardiyanto Saleh Modjo Ari Kurniawan Saputra ARIEF BUDI PRATOMO Arief Yanto Rukmana Arif Mudi Priyatno Aris Triwiyatno Aris Triwiyatno Arnadi Arnadi Arnadi Arnadi Asfahani Asfahani Aslam, Annisa Paramaswary Aslan Aslan Aslan Aslan Astutik, Wahyuni Sri Bambang Prihantoro Nugroho Bambang Prihantoro Nugroho Bambang Prihantoro Nugroho Bambang Winardi Bambang Winardi Baso Intang Sappaile Basri, T Saiful Basri, T. Saiful Bekti Setiadi Bekti Utomo Belinda Arbitya Dewi Benny Novico Zani Bilal Aslam Bilondato, Nikma Chevy Herli Sumerli Dadang Muhammad Hasyim Debi Herlina Meilani Debi Herlina Meilani Devi Rahmah Sope Dewantara, Rizki Dewantara, Rizki Dewi Endah Fajariana, Dewi Endah Dian Resha Agustina Dina Ika Wahyuningsih Dina Rasmita Dora, Mechi Silvia Dunggio, Abdul Rivai Saleh Dwi Aris Nurohman Effendy, Femmy Eka Imama Novita Sari Eka Imama Novita Sari Eka Imama Novita Sari Eka Imama Novita Sari Eka Imama Novitasari Eko Sudarmanto Eko Sudarmanto Endrianto , Endrixs Endrixs Endrianto Ethan Tan Fadhilah, St. Annisa Nurul Fahrijal, Rival Faiz Muqorrir Kaaffah Farida Arinie Soelistianto Faridah Faridah Faridah Faridah Faridah Fenty Ariani Feriyanti, Yang Gusti Fildansyah, Rully Fitriani.K Fitriani.K Frans Sudirjo Frans Sudirjo Gilang Pranajasakti Guntur Arie Wibowo Guntur Arie Wibowo Gusma Afriani Guterres, Juvinal Ximenes Hakim, Nur Hamzah, Abd Natsir Hamzali, Said Handy Widjaya Hanifah Nurul Muthmainah Hannan Fadlurahman Hannan Fadlurahman Harsya, Rabith Madah Khulaili Hazmi, Muhammad Helta Anggia Hendri Khuan Heri Aji Setiawan Heri Aji Setiawan Hermansyah Hermansyah Hermansyah Hermansyah Hery Widijanto Hidayat, Deddy Hildawati Hildawati Hildawati, Hildawati Husain Nurisman I Putu Dody Suarnatha I Wayan Adi Pratama I Wayan Karang Utama Ikhwanto Asri Ikhwanto Asri Ilham Ilham Ilham Ilham Jackson Yumame Jamila Kasim Jasmin Jasmin Jasmin, Jasmin Jatmiko Wahyu Nugroho Jauhari, Burhanuddin Johannes Triestanto Joko Santoso Joko Santoso Judijanto, Loso K, Hairuddin Kaito Tanaka Kasim, Jamila Kasmudin Mustapa Khrisna Agung Cendekiawan Khuan, Hendri Kiran Iqbal Kirana, Sukma Ayu Candra Latifah Latifah Le Hoang Nam Legito Legito Lela Nurlela Lesmana, Tera Lestari Wuryanti Lola Yustrisia Lorensius Lonik Loso Judijanto Loso Judijanto Luckhy Natalia Anastasye Lotte Lucky Mahesa Yahya M. Ammar Muhtadi M. Anwar Aini M.Khalid Fredy Saputra Made Susilawati Made Susilawati Madepan Mulia Manalu, Margareta Margareta Manalu Markus Wibowo Marwah Lubis Mayasari, Nanny Mei Rani Amalia Merakati, Indah Miku Fujita Mislan Sihite, Mislan Moeis, Dikwan Mohammad Arifin Noor Much Deiniatur Muh Arnesta Arnanda Muh Arnesta Arnanda Muh Reza Abdillah Muh Reza Abdillah Muhammad Bitrayoga Muhammad Hazmi MUHAMMAD LUTFI Muhammad Mustofa Muhammad Syafri Muhammad Syafri, Muhammad Muhammad Syarif Hartawan Muhammadong Muhammadong Muhtadi, M. Ammar Munazar Munazar Munazar Munazar Muslimin B Nam Peng Nampira, Ardi Azhar Nanny Mayasari Natasya Yunita Sugiastuti Nguyen Minh Tu Ni Desak Made Santi Diwyarthi Ningsih, Yunia Noning Verawati Novianty Djafri Novycha Auliafendri Nukman Nukman Nukman Nunung Suryana Jamin Nur Afiani, Rulan Nur Afifah Harahap Nur Asmah Nur Hakim Nuridayanti Nuridayanti Nurisman, Husain Nurohman, Dwi Aris Nurul Aisyiyah Puspitarini Omar Ahmad Opan Arifudin Palupiningtyas, Dyah Pannyiwi, Rahmat Pasaribu, Daniel Peluw, Zulfikar Pertiwi, Triani Prata Pranajasakti, Gilang Pratama, I Wayan Adi Priyana, Yana Qudratullah, Fyzria Radiah Ilham Rahman Rahmat Pannyiwi Rahmat, Rezqiqah Aulia Rahmi Setiawati Rasmita, Dina Rezki Fitriani Rezqiqah Aulia Rahmat Rifky , Sehan Rima Ruktiari Rina Destiana Rini Ambarwati Rival Fahrijal Rizki Andita Noviar Rizki Wahyudi Rosmawati Harahap Rosmawati Harahap Rosmiati Rosmiati Rovanita Rama Rovanita Rama Rulan Nur Afiani Rully Fildansyah Ruri Koesliandana Ruri Koesliandana Ruri Koesliandana Ruri Koesliandana Ruri Koesliandana Safarudin, Muhamad Sigid Sagena, Unggul Said Hamzali Samsul Arifin Samsul Arifin Santi Diwyarthi, Ni Desak Made Saputra, M. Khalid Fredy Sari, Nidia Wulan Sarungallo, Amelia S. Satria Eureka Nurseskasatmata Satya Arisena Hendrawan Sawaluddin Siregar Sayed Achmady Sehan Rifky Setiadi, Bekti Setiawan, Zunan setiawati, rahmi Setyorini, Dhiana Shazia Akhtar Silvia Ekasari SILVIA EKASARI Simarangkir, Manase Sahat H Soe Thu Zaw Soelistianto, Farida Arinie Sofia Linm Sota Yamamoto Souisa, Wendy Sri Ariyanti Sri Widiastuti sudarmo sudarmo Sudarmo Sudarmo Suhara, Ade Suharni Suharni Suharni Sumerli A., Chevy Herli Supriyanti Supriyanti Supriyanti Supriyanti Susanti Susanti Syafril Barus Syafril Barus Syam Gunawan Syam Gunawan Syawal Aprian Syawal Aprian Tahir, Usman Tanwir Tanwir Tera Lesmana Thalib, Kiki Uniatri Thandar Htwe Thea Marisca Marbun B.N Tia Tanjung Titiek Rachmawati Toalib, Ramli Tran Thi Lan Tri Budi Rahayu Tri Budi Rahayu, Tri Budi Triyugo Winarko Triyugo Winarko, Triyugo Ummu Kalsum Unggul Sagena Upeka Mendis Usman Tahir Usman Tariq Utama Sembiring, Afen Prana Utomo, Bekti Vann Sok Vicheka Rith Wahidyanti Rahayu Hastutiningtyas Wahyuni Anwar Wahyuni Sri Astutik Wardhani, Diky Wifasari, Septi Wijaya, Hamid Wiwin Susanty Wuryanti, Lestari Yana Priyana Yang Xiang Yenny Sima Yoga Dwi Goesty D.S Yulis, Dian Meiliani Yusuf Yusuf Zaenal Arief Zainab Ali Zani, Benny Novico Zhang Li Zohaib Hassan Sain Zulkifli Zulkifli Zulkifli Zulkifli Zunan Setiawan