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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Seminar Nasional Aplikasi Teknologi Informasi (SNATI) Edutech: Jurnal Teknologi Pendidikan Techno.Com: Jurnal Teknologi Informasi Syntax Jurnal Informatika TELKOMNIKA (Telecommunication Computing Electronics and Control) JDM (Jurnal Dinamika Manajemen) Jurnal Teknik Elektro Jurnal Informatika Jurnal Penelitian Ekonomi dan Bisnis Jurnal Edukasi dan Penelitian Informatika (JEPIN) Journal of Educational Science and Technology Scientific Journal of Informatics POSITIF ANDHARUPA CESS (Journal of Computer Engineering, System and Science) InfoTekJar : Jurnal Nasional Informatika dan Teknologi Jaringan Jurnal Informatika Upgris JOIN (Jurnal Online Informatika) Informatika Mulawarman: Jurnal Ilmiah Ilmu Komputer International Journal of Artificial Intelligence Research Creative Information Technology Journal SISFOTENIKA Jurnal Administrasi Publik : Public Administration Journal Emerging Science Journal JURNAL MEDIA INFORMATIKA BUDIDARMA CogITo Smart Journal Jurnal Teknoinfo Technomedia Journal ILKOM Jurnal Ilmiah Journal of Education Technology Aptisi Transactions on Management Aptisi Transactions on Technopreneurship (ATT) CSRID (Computer Science Research and Its Development Journal) CCIT (Creative Communication and Innovative Technology) Journal SENSITEK ADI Journal on Recent Innovation (AJRI) Journal of Innovation and Future Technology (IFTECH) ICIT (Innovative Creative and Information Technology) Journal Journal Sensi: Strategic of Education in Information System CICES (Cyberpreneurship Innovative and Creative Exact and Social Science) Computer Science and Information Technologies International Journal of Marine Engineering Innovation and Research Journal of Innovation in Educational and Cultural Research ADI Bisnis Digital Interdisiplin (ABDI Jurnal) Journal of Applied Data Sciences IAIC Transactions on Sustainable Digital Innovation (ITSDI) International Journal of Engineering, Science and Information Technology Jurnal Manajemen Retail Indonesia (JMARI) ADI Pengabdian kepada Masyarakat Jurnal (ADIMAS Jurnal) MAVIB Journal : Jurnal Multimedia Audio Visual and Broadcasting ProBisnis : Jurnal Manajemen International journal of education and learning Jurnal Dinamika Informatika (JDI) International Journal of Cyber and IT Service Management (IJCITSM) Startupreneur Business Digital (SABDA Journal) Media Riset Akuntansi Auditing & Informasi Universal Raharja Community (URNITY Journal) Jurnal MENTARI: Manajemen, Pendidikan dan Teknologi Informasi SATIN - Sains dan Teknologi Informasi Jurnal Sistem Informasi International Transactions on Education Technology (ITEE) Nusantara Journal of Computers and its Applications Blockchain Frontier Technology (BFRONT) International Transactions on Artificial Intelligence (ITALIC) Jurnal Pendidikan IPA Indonesia Jurnal ilmiah teknologi informasi Asia Journal of Computer Science and Technology Application International Journal Research on Metaverse Lontar Komputer: Jurnal Ilmiah Teknologi Informasi JOT
Untung Rahardja
Universitas Raharja
Religion Arts Humanities Astronomy 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 Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Physics Social Sciences Transportation Other

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A Framework for Mining Customer Data in Management Information Systems Untung Rahardja; Ninda Lutfiani; Agung Rizky; Yul Ifda Tanjung; Richard Evans
CORISINTA Vol 3 No 1 (2026): February
Publisher : Pandawan Sejahtera Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/m5qymx32

Abstract

The exponential growth of customer data within Management Information Systems (MIS) has generated an urgent need for structured analytical approaches capable of transforming raw information into valuable insights that support decision-making across various organizational processes. This study aims to develop a comprehensive and systematic framework for mining customer data in MIS by integrating preprocessing procedures, machine learning algorithms, and model evaluation techniques into a unified analytical workflow. Using the Design Science Research methodology, the framework was designed based on existing data mining standards, developed through iterative refinement, and demonstrated using a customer-behavior dataset processed with clustering, classification, and association rule mining techniques. The findings reveal that the proposed framework improves data quality, enhances segmentation accuracy, and strengthens predictive capability, enabling MIS to deliver deeper insights into customer behavior, purchasing tendencies, and potential churn risks. Experimental results show that combining K-Means, Random Forest, and Apriori algorithms yields more comprehensive and reliable patterns compared to using a single analytical technique. The outcomes of this research highlight the practical significance of applying an integrated data mining approach in MIS, allowing organizations to optimize marketing strategies, personalize services, and make more informed managerial decisions. Overall, this study contributes to the field by offering a scalable, adaptable, and effective framework for implementing customer data mining within real-world MIS environments.
Leveraging IPFS to Build Secure and Decentralized Websites in the Web 3.0 Era Imam Ryan Maulana; Untung Rahardja; Nur Azizah; Mohamad Rakhmansyah; Maulana Arif Komara
IAIC Transactions on Sustainable Digital Innovation (ITSDI) Vol 7 No 1 (2025): October
Publisher : Pandawan Sejahtera Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34306/itsdi.v7i1.700

Abstract

In recent years, Web 3.0 has gained significant attention due to its potential to create a more secure and decentralized internet. The background of this research lies in the growing demand for data privacy and security, which traditional Web 2.0 platforms fail to provide.The objective of this study is to explore how IPFS (InterPlanetary File System) can be leveraged to build decentralized websites that prioritize security and user privacy in the Web 3.0 ecosystem. The method involves a qualitative approach, including a case study where IPFS is utilized to develop a decentralized website, followed by a series of performance and security tests. The performance tests revealed that IPFS-based websites achieved a 99.2% uptime compared to 96.5% in traditional websites, and reduced server failure rates by approximately 35%. These quantitative results confirm that IPFS provides higher resilience against data breaches and server failures while reducing reliance on single points of failure. The conclusion drawn from this research indicates that IPFS is a promising technology for developing secure, decentralized websites in the Web 3.0 era, offering an enhanced user experience with improved privacy, data security, and scalability. The findings suggest that adopting IPFS for web development could pave the way for the next generation of decentralized applications, contributing to the ongoing transformation of the internet.
A Qualitative Case Study on Fintech-Driven Modernization of Capital Market Infrastructure Untung Rahardja; Ratna Utami Wijayanti; Yunita Christy; Gabriel Fransiso
IAIC Transactions on Sustainable Digital Innovation (ITSDI) Vol 7 No 2 (2026): April
Publisher : Pandawan Sejahtera Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34306/itsdi.v7i2.725

Abstract

By addressing inefficiencies, high operating costs, and transparency constraints in conventional systems, this study investigates the role of Financial Technology (fintech) in modernizing capital market infrastructure. The study examines the impact of cloud computing, Artificial Intelligence (AI), machine learning, and Distributed Ledger Technology (DLT) on pre-trade, trade, and post-trade processes using a qualitative case study approach and thematic analysis of secondary data from exchanges, fintech companies, industry reports, and regulatory documents. Unlike previous studies that mainly focus on fintech adoption in general financial services or individual technologies, this study provides an integrated analysis of multiple fintech technologies within capital market infrastructure modernization. The findings show that fintech significantly improves post-trade efficiency by reducing operational risks, accelerating settlement processes, and minimizing reliance on intermediaries. Cloud-based infrastructure enhances scalable data analytics and market accessibility, while AI and machine learning strengthen market surveillance and risk management through real-time monitoring and early detection of anomalous trading activities. Despite these benefits, implementation remains constrained by institutional readiness, cybersecurity risks, and regulatory complexity. The study highlights the importance of collaboration among regulators, traditional financial institutions, and fintech firms to ensure sustainable integration and effective risk mitigation. Taken together, the findings indicate that fintech plays a crucial role in creating a more efficient, transparent, and resilient capital market infrastructure.
Business Intelligence-Based Risk Analysis Approach to Prevent Accidents in Overhead Crane Operations Ridwan Kurniaji; Nur Azizah; Mohamad Rakhmansyah; Untung Rahardja; Alfajri Ismail
IAIC Transactions on Sustainable Digital Innovation (ITSDI) Vol 8 No 1 (2026): October
Publisher : Pandawan Sejahtera Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34306/itsdi.v8i1.731

Abstract

Overhead crane operations remain a high-risk activity in heavy manufacturing, yet safety management often relies on static assessments that fail to capture real-time operational dynamics. In developing economies such as Indonesia, a significant digital gap hinders the adoption of high-cost IoT solutions, leaving safety data fragmented and reactive. This study aims to bridge this gap by developing and validating a Business Intelligence (BI) Safety Dashboard that utilizes bridge technologies, defined as cost-effective digital solutions that leverage existing administrative and operational data instead of dedicated IoT infrastructure, to provide real-time predictive risk insights. Following a Design Science Research (DSR) framework, a three-year longitudinal study (2024–2026) was conducted at a metal fabrication facility in West Java. A Weighted Dynamic Risk Score (WDRS) was formulated using Data Analysis Expressions (DAX), integrating incident logs, maintenance records, and operator certification data into a unified star schema model. The results demonstrate a 95% reduction in data processing time and a 30% increase in near-miss reporting. The proposed artifact successfully identified critical risk outliers, such as Crane 08 (WDRS = 8.3), and generated spatiotemporal heatmaps that pinpointed specific risk hotspots within the facility. These findings confirm that the BI Dashboard is a feasible and highly practical solution for resource-constrained environments, providing a scalable blueprint for Indonesian SMEs to achieve Industry 4.0 safety standards by leveraging existing administrative data for predictive maintenance and proactive safety interventions.
Deep Learning-Based Biology Learning with Ethnopedagogy and Local Wisdom to Support Sustainable Development Goals Mia Nurkanti; Untung Rahardja; Maesaroh Lubis; Ahmad Adnan Mohd Shukri
Jurnal Pendidikan IPA Indonesia Vol. 15 No. 1 (2026): March 2026
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/jpii.v15i1.32341

Abstract

This study aims to implement a deep learning-based Biology learning model that integrates ethnopedagogical approaches and local wisdom values ​​to support the achievement of the Sustainable Development Goals (SDGs), specifically SDG 4 (quality education), SDG 13 (climate change), and SDG 15 (preservation of terrestrial ecosystems). The research method uses a quantitative approach with a pre-experimental design (one-group pretest-posttest) because the data are preliminary and the study is still in the research and development stage. The study subjects were students from a private high school in Bandung City, which has a rich local culture and high biodiversity. Data collection instruments included cognitive tests, affective and psychomotor observation sheets, and an ecological awareness questionnaire. The study found a significant increase in students' cognitive, affective, and psychomotor skills following the implementation of the learning model. In addition, culture-based learning succeeded in fostering meaningful connections between Biology concepts and traditional community practices. This study concludes that the implementation of the learning model shows great potential to shape students who are ecologically aware and rooted in cultural values. The integration of immersive learning and ethnopedagogy offers an innovative alternative in biology education that is locally relevant yet globally impactful. This research is still in its developmental stage and therefore uses pre-experimental methods.
Orange Technology for Humanistic Innovation in Higher Education Shesilia Wibowo; Irene Apriani Widjaya; Jihan Zanubiya; Richard Evans; Untung Rahardja
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.v4i2.899

Abstract

Amidst the rapid adoption of technology in education, a crucial challenge arises regarding the risk of dehumanizing learning. This study examines Orange Technology as a humanistic innovation approach that seeks to balance digital advancement with human values. Using a qualitative descriptive approach, this research analyzes literature from academic journals and technology education reports, which are then evaluated through a SWOT framework. The analysis results indicate that while Orange Technology holds significant potential to enhance students’ mental well being, digital empathy, and emotional engagement, its implementation faces significant challenges, including limited human resources and inadequate ethical regulations. Therefore, it is concluded that the success of this implementation requires a holistic strategy encompassing investment in human resource training, policy development, and interdisciplinary collaboration. This innovation model has strategic relevance to the Sustainable Development Goals (SDGs), particularly Goal 4 (Quality Education). By focusing on character development and mental well-being, this research contributes to creating an education system that is not only efficient but also inclusive, equitable, and relevant to the holistic needs of future generations.
Digital Transformation in Public Administration through Digital Leadership to Improve Government Efficiency Muhtarom Muhtarom; Untung Rahardja; Po Abas Sunarya; Arthur Freeman
Technomedia Journal Vol 11 No 1 (2026): June
Publisher : Pandawan Incorporation, Alphabet Incubator Universitas Raharja

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/tmj.v11i1.2641

Abstract

This study examines the role of digital leadership in accelerating digital transformation within public administration to improve governmental efficiency. The objective of this research is to analyze how digital leadership influences the effectiveness, transparency, and service quality of public sector institutions in the digital era. This study employs a quantitative approach using survey data collected from 125 public sector employees, complemented by Structural Equation Modeling-Partial Least Squares (SEM-PLS) to test the relationships between variables. The results indicate that digital leadership has a significant positive effect on the success of digital transformation initiatives, which in turn enhances operational efficiency, decision-making speed, and public service delivery quality additionally, organizational readiness and technological infrastructure are identified as supporting factors that strengthen these relationships. In conclusion, the study highlights that effective digital leadership is a critical driver in ensuring successful digital transformation in public administration, thereby improving overall government performance, and it is recommended that policymakers invest in leadership development and digital capability enhancement to sustain long-term efficiency gains.
Utilization of Machine Learning for Stunting Prediction: Case Study and Implications for Pre-Matrical and Pre-Conceptive Midwifery Services Qurotul Aini; Untung Rahardja; Indrajani Sutedja; Harco Leslie Hendric Spits Warnar; Nanda Septiani
International Journal of Engineering, Science and Information Technology Vol 5, No 1 (2025)
Publisher : Malikussaleh University, Aceh, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52088/ijesty.v5i1.1488

Abstract

Stunting, a global health challenge, affects millions of children, particularly in low- and middle-income countries, and has lasting consequences on cognitive development, physical growth, and overall well-being. Early prediction and intervention are crucial for reducing stunting, especially before conception and during early pregnancy. This paper explores the utilisation of machine learning (ML) for predicting stunting risk in the context of pre-maternal and pre-conceptive midwifery services. By analysing a case study, the research assesses the effectiveness of various machine learning algorithms in identifying stunting risk factors, including maternal health, nutrition, socioeconomic status, and environmental conditions. Using healthcare and demographic data, the study develops predictive models to assist midwives in assessing stunting risks during pre-conception and prenatal phases. The findings demonstrate that ML models, particularly random forest and support vector machine algorithms, outperform traditional risk assessment methods, providing higher accuracy and earlier detection of stunting risk. These models enable midwives to deliver personalised care and targeted interventions, optimising maternal and child health outcomes. The study also highlights the broader implications of integrating machine learning into midwifery services, including improved decision-making, resource allocation, and healthcare efficiency. In conclusion, this research underscores the transformative potential of machine learning in predicting stunting risk and enhancing the effectiveness of pre-maternal and pre-conceptive midwifery services, offering a promising approach to mitigating the global burden of stunting.
Machine Learning-Based Heart Failure Worsening Prediction Model to Build Self-Monitoring Prototype as an Effort to Prevent Readmissions and Maintain Quality of Life Untung Rahardja; Kristoko Dwi Hartomo; Indrajani Sutedja; Ardi Kho; Muhammad Farhan Kamil
International Journal of Engineering, Science and Information Technology Vol 5, No 1 (2025)
Publisher : Malikussaleh University, Aceh, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52088/ijesty.v5i1.1467

Abstract

Heart failure is a long-term condition of great concern which calls for health care services in cycles. This significantly hampers quality of life for patients and increases costs for the healthcare systems. If the worsening of heart failure could be detected early, the intervention to prevent readmission could be employed, such that readmission would be avoided, enhancing the quality of life for the patient. Accordingly, the paper explains how such a model to predict the worsening of heart failure in patients who are at high risk of this condition has been developed. The model uses information gathered from the Electronic Health Records (EHRs) (Clinical Variables, Vitals, Test Results, and Demographics) to make accurate predictions on patients. As an effective and efficient approach towards achieving this goal, comparison of different algorithms such as random forests, support vector machines and gradient boosting has been employed towards the building of the final model. At this stage, the model is embedded into a user-friendly self-monitoring device, allowing the chronic heart failure patients to assess health indices on the fly with the help of the mobile app and wearable devices. This secondary prevention strategy makes patients more responsible for their health and decreases the number of patients readmitted to the hospital by increasing their functioning and well-being. The paper further projects the future development of other forms of treatment for chronic heart failure, especially at the first line, focusing primarily on the timing and succession.
The Effect of Technology Training on Increasing MSME Productivity: Case Analysis of Digital Training Programs for Local Craftsmen Chandra Lukita; Ika Yuni Purnama; Untung Rahardja; Ersa Aura Natasya; Yulia Putri Ayu Sanjaya
International Journal of Engineering, Science and Information Technology Vol 5, No 1 (2025)
Publisher : Malikussaleh University, Aceh, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52088/ijesty.v5i1.1087

Abstract

This research aims to explore the impact of technology training on increasing the productivity of micro, small and medium enterprises (MSMEs), focusing on local artisans. The Partial Least Squares structural analysis method (PLS-SEM) tests the proposed hypothesis based on survey data from MSMEs participating in digital training programs. The research results show that active participation in technology training programs significantly increases the application of technology in MSME business operations. Applying this technology will then have a positive impact on improving the productivity of MSMEs. Additionally, consistency in construct measurement, such as reliability and validity, is vital in explaining variation in the dependent variable. These findings provide an essential contribution to understanding the role of technology in increasing the productivity of MSMEs and highlight the importance of consistency in construct measurement in the context of this research.
Co-Authors AA Sudharmawan, AA Abas Sunarya Abas Sunarya, Po Abdul Hamid Arribathi Abdul Hayat Abdul Rahman, Abdul Wahab Achani Rahmania Az Zahra Achmad Benny Mutiara Achmad Nizar Hidayanto Adam Faturahman Ade Iriani Adele Valerry Adi Setiawan Aditiya Lityanian Al Nasir Adiyarta, Krisna Aghnia Sabila Agung Rizky Agung Rizky Ahmad Adnan Mohd Shukri Al Hafiz, Mohammad Aditya Alexander Williams Alfajri Ismail Alfian Dimas Ahsanul Rizki Ahmad Alwiyah Alwiyah Amelia, Sindy Amsyar, Izwan Ana Nurmaliana Anderson, James Andhika Dwi Putra Andriyani, Fitri Andriyansah . Anggun Aditya Ningrum Anggun Oktariyani Anggy Fatillah Anggy Giri Prawiyogi Ani Wulandari Anil Ram Anjani, Sheila Aulia Ankur Singh Bist Anoesyirwan Moeins Anoesyirwan Moeins Anwar, Aang Solahudin Apriliasari, Dwi Ardi Kho Ari Asmawati Arini Dwi Lestari Arini Dwi Lestari Aristo, Nabila Cynthia Ariya Panndhitthana Candra Arko Djajadi Aroha Patel Arthur Freeman Ary Budi Warsito Asep Saefullah Asep Sutarman Asif Khan Asif Khan Asri asri Athapol Ruangkanjanases Augury El Rayeb Aulia Edliyanti Ayi Rakhmat Ramdani Ayu Martha Wardani Ayu Sanjaya, Yulia Putri Ayu Wanda Azz, Istajib Kulla Himmy Bayu Pramono Bennet, Daniel Bhupesh Rawat Bist, Ankur Singh Budiarto, Mukti budiarty, frizca Bunga Pertiwi Chairun Nas Chalifatullah, Siti Chandra Lukita Charlotte Pasha Chen, Shih Chih Christianto, Dennies Dwi Chua Toh Hua Chung-Hao Hsu Chung-Wen Hung Citra Destianty Clara Pasha Lim Cristhopher, Ethan Daelami Ahmad Daeli, Marda Leni Danny Manongga Darmawan, Muhammad Diky Darmawan, Muhammad Diky Davies, Mary Deddy Pratama Desi Sartika Desrianti, Dewi Immaniar Desy Apriani Devi, Lakshmi Dewi Immaniar Dewi Mariana Apriani Dewi, Yustin Novita Dhita Rukmianti Diah Aryani, Diah Dian Maharani Damanik Dian Mustika Putri Dina Fitria Murad Dina Fitria Murad Dini Intan Pratiwi Dini Intan Pratiwi Dini Nurul Suvianti Dwi Andayani, Dwi Dwi Anjani Dwi Apriliasari Dwi Apriliasari DWI CAHYONO Dwi Julianingsih Dwi Maya Suhainingsih Dwi Nur Ramadhan Dwi Safarina Edward Boris P Manurung Edward Boris P Manurung Edward Guustaaf Efa Ayu Nabila Efendy, Rifan Eka Dian Astuti Eko Prasetiyani Eko Prasetiyani Eko Sediyono Elinda, Bella Dhea Elinda, Bella Dhea Elisa Ananda Natalia Elmanda, Vonda Endah Nirmala Dewi Erick Alfons Lisangan Erick Febriyanto Erika Erika Erni Astuti Ersa Aura Natasya Erviani, Maya Ima Ester Ananda Natalia Ethan Aptman Ethan Harris Euis Sitinur Aisyah Evi Maria Faisal Rizki Azhari Farida Agustin, Farida Faturahman, Adam Fauziah, Zaleha Febiani, Dyah Ayu Febiansyah, Hidayat Femi Allamiah Femi Allamiah Fernanda Setyobudi Armansyah, Fernanda Setyobudi Firman Hanafi Fitra Putri Oganda Fitra Putri Oganda Fitri Faradilla Fitri Faradilla Fitri Lisnawati Fresandy, Gilang Fuad, Azharul Gabriel Fransiso Galih Putra Cesna Giandari Maulani Girinzio, Iqbal Desam Guustaaf, Edward Hakiki, Salman Handayani, Indri Handayani, Indri Hani Dewi Ariessanti Hani Dewi Ariessanti Harahap, Eka Purnama Harahap, Eka Purnama Harco Leslie Hendric Spits Warnar Harries Madiistriyatno Harries Madiistriyatno, Harries Henderi . Hendriyati, Penny Hendry Heriyanto Heriyanto Hidayati * Hidayati Hidayati Hikam, Ihsan Nuril Hikmal Baedowi Hindriyanto Dwi Purnomo Ignatius Joko Dewanto, Ignatius Joko Ika Yuni Purnama Imam Prayogi Imam Ryan Maulana Imam Ryan Maulana Indrajani Sutedja Indri Handayani Indri Handayani Indri Handayani Indri Handayani Indri Handayani Indri Handayani, Indri Ira Geraldina Irene Apriani Widjaya Irwan Nurdin Irwan Sembiring Isabella Yaumil Annisa Iswara Gandhi Iwan Setyawan Jazi Eko Istiyanto Jelita Bagaskara Jetty Susanti Jihan Zanubiya Joko Siswanto Jonathan Parker Jonathan Parker Julianingsih, Dwi Juniar, Hega Lutfilah Kamal, ⁠Abdullah Arif Kanivia, Aan Kenita Zelina Kgomotso Moyo Khairunisa, Alfiah Khanna Tiara Khanna Tiara, Khanna Khasanah, Kartika Trissanti Khoirunisa, Alfiah Khoirunisa, Alfiah Khoirunisa, Alfiah Kristoko Dwi Hartomo Lachlan, Nicholas Lalita Tri Adila Lalu Darmawan Bakti, Lalu Darmawan Latifah, Haznah Lestari Santoso, Nuke Puji Lic, Yung-Ming Lidya Wijayanti Lilik Agustin Lilis Setiani Lily Maria Evans Lod Sulistyo Lusyani Sunarya Lutfiyah, Konita M. Ramdani Made Bunga Thalia Maesaroh Lubis Maharani, Herliana Wahyu Maimunah Maimunah Manik, Ita Sari Perbina Mardiana Mardiana Mardiana Mardiana Mardiansyah, Aditya Marviola Hardini Maulana Arif Komara Maulana Arif Komara Maulana, Sabda Md Asri Ngadi Melani Rapina Tangkaw Meri Mayang Sari Meri Mayang Sari Meria, Lista Meriyana Sunengsih Mertayasa, I Komang Meta Amalya Dewi Meylda Sarah Parwati Meytasari, Rista Mia Novalia Mia Nurkanti Michael Surya Gunawan Michael Surya Gunawan Miftah, Mohammad Millah, Shofiyul Mitra Terima Des Sincer Putri Moch Sandi Alpansuri Mochamad Heru Riza Chakim Mochamad Sandi Alpansuri Mochamad Sukrisno Mardiyanto Mohamad Rakhmansyah Mohammed Iftequar Ali Much Alvin Aldiya Muchlishina Madani Muhamad Alfi Duwi Juliansah Muhamad Hendri Muhamad Rapidan Kusuma Muhamad Stabil Tanwin Saputra Muhamad Yusup Muhammad Diky Darmawan Muhammad Farhan Kamil Muhammad Ghifari Ilham Muhammad Iqbal Muhammad Iqbal Muhammad Salamuddin Muhtarom Mukti Budiarto Muktiyanto, Ali Mulyati Mulyati Mulyati Mustofa Kamil, Mustofa Mustofa, Kenny Ilyas Nanda Septiani Natalia, Ester Ananda Neng Enay Nesti Anggraini Santoso Nevizond, Reza Filander Nia Haryani niko alnabawi Ninda Lutfiani Ninda Lutfiani Ningrum, Fanani Islamia Noval Jindan Nuke Puji Lestari Santoso Nur Azizah Nur Azizah Nur Silawati NURAENI, RANI Nurani, Dita Lintang Nurmala, Risma Nurul Komaeni Ornlatcha Sivarak P. O. H. Putra Pahad, Baiq Aneji Pangestu, Anggit Panji Paroli Paroli Pasha, Lukita Po Abas Sunarya Po Abbas Sunarya Pramono, Bayu Pratiwi, Sarah Prihandoko Prihandoko Prihastiwi, Wahyu Yustika Purnama Harahap, Eka Putri, Dian Mustika Qory Oktisa Aulia Qurotul Aini Qurotul Aini Qurotul Aini Qurotul Aini Qurotul Aini Qurotul Aini Qurotul Aini Qurotul Aini Qurotul Aini Qurotul Aini Rahardja.,M.T.I.,MM, Dr. Ir. Untung Rahma Rinie Raihan Raihan, Raihan Rakhmansyah, Mohamad Ramadan, Ahmad Ramadhan, Tarisya Ramzi Zainum Ikhsan Rani Nuraeni Ratna Tri Hari Safariningsih Ratna Utami Wijayanti Rawat, Bhupesh Ray Indra Taufik Wijaya Renowati Hardjosubroto Reny Ardyanti Resti Rahmawati Retantyo Retantyo Retantyo Wardoyo Reyhan Algiffary Gunawan RH. Fitri Faradilla Richard Andre Sunarjo Richard Evans Richardus Eko Indrajit Ridhuan Ahsanitaqwim Ridwan Kurniaji Riya Widayanti Riza Chakim, Mochamad Heru Rizki Afri Liani Firmansyah Rizky Sebastian Rizky, Agung Rochmawati Rochmawati Romzi Syauqi Naufal Rosalinda, Iis Ariska Rosyifa Rosyifa Ruey-Hsing Chang Ruli Supriati, Ruli Rusilowati, Umi Sabda Maulana Salamuddin, Muhammad Santika Dewi Santoso, Nesti Anggraini Santoso, Nuke Puji Lestari Sarah Riwanda Shofroh Sari, Herva Emilda SATRIYAS ILYAS Saulina Panjaitan, Aropria Sella Avionita Septian, Rafly Ananda Dwi Septiani, Nanda Shakinah Badar Shakinah Badar Shesilia Wibowo Shih-Chih Chen Shih-Chih Chen Shih-Wen Chien Shofiyul Millah Shylvia Ratna Dewi Shylvia Ratna Dewi Sihotang, Sondang Visiana Silvia, Pita Siti Chalifatullah Siti Maesaroh Siti Maesaroh Siti Mawadah Siti Nurindah Sari Siti Ria Zuliana Solahudin Solahudin Sri Darmayanti Sri Rahayu Sri Watini Sri Yulianto Joko Prasetyo Suciani, Ayu Sudaryono Sudaryono Sudaryono Sudaryono Sugeng Widada Sulastrini, Lily Ratna Sulistio Sulistio Sulthan Taqi Sampoerna Sunar Abdul Wahid Sunardjo, Richard Andre Supriyati, Ruli Suryari Purnama Suryo Guritno1 Susan Oktaviani Sutama Wisnu Dyatmika Sutarman, Asep Sutarto Wijono Suwandi Suwandi Tanaporn Hongsuchon Tangkaw, Melani Rapina Taqwa Hariguna Tejosuwito, Nikita Jova Thomas Sumarsan Goh Tri Kuntoro Priyambodo Tri Purwaningsih Triyono Triyono Tsung-Hao Wu Tuti Nurhaeni Uki Hares Yulianti Utami, Ria Valent Setiatmi Valent Setiatmi Valent Setiatmi, Valent Viktor A Sin, Muhamad Viola Tashya Devana Vivid Kristiani Alfad Zebua Wahyu Yustika Prihastiwi Wahyudi, Otniel Feliks Putra Wardani, Ayu Martha Widhy Setyowati Wijaya, Randy Wijaya, Surta Wijayanti, Lidya Wiliams, Alexander Windy Yestina Winiarti Prastiwi Yanti Yanti Yasir Mustafa Kareem Yessi Frecilia Yoke Dwi Martianda Setiaji Yolandari, Aulia Yoyo Syoifana Yul Ifda Tanjung Yul Ifda Tanjung Yulia Putri Ayu Sanjaya Yundari, Yundari Yunita Christy Yusuf, Natasya Aprila Zainal Arifin Hasibuan Zainarthu, Henry Zanubiya, Jihan Zeze Nanle