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All Journal ComEngApp : Computer Engineering and Applications Journal Seminar Nasional Aplikasi Teknologi Informasi (SNATI) JIK Jurnal Ilmu Komputer Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI) JUTI: Jurnal Ilmiah Teknologi Informasi Jurnal Ilmu Komputer dan Agri-Informatika INFOKAM Jurnal Teknologi Informasi dan Ilmu Komputer JUSIFO : Jurnal Sistem Informasi Jurnas Nasional Teknologi dan Sistem Informasi Journal of Information Systems Engineering and Business Intelligence Jurnal Kajian Informasi & Perpustakaan Jurnal IPTEK-KOM (Jurnal Ilmu Pengetahuan dan Teknologi Komunikasi) Proceeding of the Electrical Engineering Computer Science and Informatics JOIV : International Journal on Informatics Visualization Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) International Journal of Artificial Intelligence Research Paradigma Jurnal Ilmiah FIFO Journal of Government and Civil Society Emerging Science Journal Jurnal Pilar Nusa Mandiri Jurnal Sains Dan Teknologi (SAINTEKBU) Faktor Exacta Jurnal Teknik Informatika STMIK Antar Bangsa JITK (Jurnal Ilmu Pengetahuan dan Komputer) Masyarakat Telematika Dan Informasi : Jurnal Penelitian Teknologi Informasi dan Komunikasi JURNAL TEKNIK INFORMATIKA DAN SISTEM INFORMASI Jurnal Teknoinfo Jurnal Sisfokom (Sistem Informasi dan Komputer) RESEARCH : Computer, Information System & Technology Management Voice Of Informatics Jurnal Nasional Pendidikan Teknik Informatika (JANAPATI) Kilat Jambura Journal of Informatics Jurnal Informatika Global Jurnal Teknologi Terpadu Jurnal ICT : Information Communication & Technology MULTINETICS Jurnal Mantik Journal of Information Systems and Informatics Syntax Idea Jurnal Teknologi Dan Sistem Informasi Bisnis Jurnal Informatika Ekonomi Bisnis Journal of Applied Engineering and Technological Science (JAETS) Unistek: Jurnal Pendidikan dan Aplikasi Industri Indonesian Journal of Electrical Engineering and Computer Science International Journal of Advances in Data and Information Systems Infotek : Jurnal Informatika dan Teknologi Budapest International Research and Critics Institute-Journal (BIRCI-Journal): Humanities and Social Sciences Jurnal Teknik Informatika (JUTIF) Jurnal Restikom : Riset Teknik Informatika dan Komputer Journal of Applied Data Sciences INSERT: Information System and Emerging Technology Journal Journal La Multiapp International Journal of Social Service and Research Asian Management and Business Review Jurnal Impresi Indonesia Makara Journal of Technology Jurnal Indonesia Sosial Sains Proceeding of International Conference Health, Science And Technology (ICOHETECH) Journal of Business, Social and Technology Eduvest - Journal of Universal Studies Telematika MKOM Ranah Research : Journal of Multidisciplinary Research and Development Jurnal Informatika Ekonomi Bisnis Jurnal Sistem Informasi PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON DATA SCIENCE AND OFFICIAL STATISTICS Proceeding of International Conference on Information Science and Technology Innovation (ICoSTEC) The Indonesian Journal of Computer Science Scientific Journal of Informatics Jurnal Ragam Pengabdian JuTISI (Jurnal Teknik Informatika dan Sistem Informasi)
Dana Indra Sensuse
Universitas Indonesia
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A Systematic Literature Review of Supporting Factors for Big Data Analytics (BDA) in Public Sector Auditing Retisa Heryati Siwi; Gesi Deta Hendika Wardani; Dana Indra Sensuse; Sofian Lusa; Nurcholis Ramlan
Eduvest - Journal of Universal Studies Vol. 6 No. 7 (2026): Eduvest - Journal of Universal Studies
Publisher : Green Publisher Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59188/eduvest.v6i7.52986

Abstract

The application of Big Data Analytics (BDA) in auditing offers significant benefits, including increased accountability and transparency, as well as reduced operational costs. BDA is also expected to improve the quality and reliability of audit results used for decision-making. The role of BDA in public sector auditing is crucial, as it helps detect anomalies or fraud, enhance oversight, and evaluate implemented policies. Despite its benefits, the application of BDA in public sector auditing still faces various challenges that need to be addressed. This study aims to analyze the factors that support the implementation of BDA in public sector auditing and identify the challenges encountered during its implementation. This research uses a systematic literature review (SLR) approach with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) framework. The study also employs the Content Validity Index (CVI) to validate the relevance of the identified factors and their classification. The results reveal eight factors that support the use of BDA in public sector auditing: perceived organizational benefits; process management; data privacy, security, and governance; data quality; people aspects; auditor aspects; organizational aspects; and systems, tools, and technologies. Public sector auditing needs to consider these factors when implementing BDA to improve audit effectiveness, efficiency, and the quality of oversight. Proper implementation of BDA can strengthen transparency and accountability in public financial management and policy oversight.
Enhancing Master Data Management Maturity: A Case Study of Institution XYZ Gesi Deta Hendika Wardani; Retisa Heryati Siwi; Dana Indra Sensuse; Sofian Lusa; Nurcholis Ramlan
Eduvest - Journal of Universal Studies Vol. 6 No. 7 (2026): Eduvest - Journal of Universal Studies
Publisher : Green Publisher Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59188/eduvest.v6i7.53117

Abstract

Data has become a strategic asset that supports decision-making in the digital era. Master Data Management (MDM) is used to assure quality, accuracy, and consistency of master data. However, government electronic certification services face challenges related to data inconsistencies due to the use of two applications with separate databases. This study assessed the MDM maturity level in government electronic certification services (Institution XYZ) using the Spruit & Pietzka Master Data Management Maturity Model (MD3M). It then provided improvement recommendations aligned with the Data Management Body of Knowledge (DMBOK). The research applied five domains: data model, data quality, use and ownership, data protection, and maintenance, encompassing 62 required capabilities. Data were collected through interviews with the data management team. The results indicated that 69.36% of the capabilities in the MD3M model had been implemented.This study identified areas for improvement in master data management within government electronic certification services and provided strategic recommendations to enhance data management effectiveness. This approach is expected to support more effective, secure, and standardized data management in accordance with organizational and regulatory requirements.
Evaluation of Electronic Health Record Data Quality: A Case Study of a Government General Hospital in Jakarta Iindra Iriyanti; Isnina Eva Hidayati; Nur Indrawati; Dana Indra Sensuse
Eduvest - Journal of Universal Studies Vol. 6 No. 7 (2026): Eduvest - Journal of Universal Studies
Publisher : Green Publisher Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59188/eduvest.v6i7.53118

Abstract

The digital transformation of healthcare is a global priority for improving service efficiency, information system integration, and data-driven decision-making. In Indonesia, government hospitals are pioneering the implementation of digital transformation policies through the SATUSEHAT program, which aligns with the Health Level Seven International (HL7) initiative to implement global health data interoperability standards. This program requires the hourly submission of Electronic Health Record (EHR) data to the Ministry of Health of the Republic of Indonesia’s SATUSEHAT platform, with the requirement that the data meet the dimensions of completeness, accuracy, timeliness, and consistency. This study aims to evaluate the quality of EHR data at a central government general hospital in Jakarta using the Total Data Quality Management (TDQM) framework and linking it to the principles of HL7 Fast Healthcare Interoperability Resources (FHIR). This study involved in-depth interviews with the EHR development team and a quantitative analysis of data from the hospital’s Health Information System (HIS) and data warehouse for outpatients during the period of December 1–31, 2025. The results showed that the quality of EHR data did not fully meet the four main dimensions of data quality. A total of 13.16% of EHR data was rejected by the SATUSEHAT platform. Key recommendations include synchronizing population data with the Directorate General of Population and Civil Registration and improving data quality governance capabilities within government hospitals. This research provides a strategic contribution to national efforts to build an integrated, interoperable, and globally standardized digital health system.
Faktor-Faktor yang Mempengaruhi Proses Manajemen Pengetahuan: Studi Kasus STMIK XYZ Fithri Selva Jumeilah; Dana Indra Sensuse
JUSIFO : Jurnal Sistem Informasi Vol 4 No 2 (2018): December
Publisher : Program Studi Sistem Informasi, Fakultas Sains dan Teknologi, Universitas Islam Negeri Raden Fatah Palembang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19109/jusifo.v4i2.4108

Abstract

Saat ini, aset organisasi bukan hanya yang berwujud saja tetapi juga yang tidak berwujud, seperti pengetahuan. Banyak sekali organisasi yang menyadari pentingnya manajemen pengetahuan salah satunya adalah STMIK XYZ. Namun proses manajemen pengetahuan di STMIK XYZ belum terlaksana dengan baik, maka perlu diketahui faktor-faktor apa saja yang mempengaruhi proses manajemen pengetahuan di STMIK XYZ. Dalam penelitian ini, faktor-faktor yang diduga mempengaruhi proses manajemen pengetahuan adalah faktor kepercayaan, kolaborasi, pembelajaran, strategi organisasi, penghargaan, sentralisasi, formalisasi, IT support, T-shape skill, effort expectancy dan performance expectancy. Proses manajemen pengetahuan diukur dengan menggunakan pendekatan Socialization, Externalization, Combination, dan Internalization. Penelitian ini menggunakan pendekatan kuantitatif melalui kuesioner dimana respondennya adalah semua karyawan di STMIK XYZ dengan menggunakan skala likert 5 poin. Hasil kuesioner dianalisis menggunakan pendekatan Partial Least Square (PLS). Hasil dari penelitian ini adalah faktor kepercayaan, faktor strategi organisasi dan penghargaan terbukti signifikan memberikan pengaruh kuat terhadap proses manajemen pengetahuan.
Sentiment Analysis of Tweets Before the 2024 Elections in Indonesia Using Bert Language Models Lenggo Geni; Evi Yulianti; Dana Indra Sensuse
Jurnal Ilmiah Teknik Elektro Komputer dan Informatika Vol. 9 No. 3 (2023): September
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/jiteki.v9i3.26490

Abstract

General election is one of the crucial moments for a democratic country, e.g., Indonesia. Good election preparation can increase people's participation in the general election. In this study, we conduct a sentiment analysis of Indonesian public opinion on the upcoming 2024 election using Twitter data and IndoBERT model. This study is aimed at helping the government and related institutions to understand public perception. Therefore, they could obtain valuable insights to better prepare for elections, including evaluating the election policies, developing campaign strategies, increasing voter engagement, addressing issues and conflicts, and increasing transparency and public trust. The main contribution of this study is threefold: (i) the application of state-of-the-art transformer-based model IndoBERT for sentiment analysis on political domain; (ii) the empirical evaluation of IndoBERT model against machine learning and lexicon-based models; and (iii) the new dataset creation for sentiment analysis in political domain. Our Twitter data shows that Indonesian public mostly reacts neutrally (83.7%) towards the upcoming 2024 election. Then, the experimental results demonstrate that IndoBERT large-p1 is the best-performing model that achieves an accuracy of 83.5%. It improves our baseline systems by 48.5% and 46.49% for TextBlob, 2.5% and 14.49% for Multinomial Naïve Bayes, and 3.5% and 13.49% for Support Vector Machine in terms of accuracy and F-1 score, respectively.
Adoption of Artificial Intelligence in Chatbot Recommendation Systems for Complex Customer Preferences: A Case Study of Shopee E-Commerce Apriyanti Sijabat; Dana Indra Sensuse
Scientific Journal of Informatics Vol. 13 No. 2: May 2026
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v11i2.48989

Abstract

Purpose: This study identifies and analyzes factors influencing AI chatbot recommendation system adoption and proposes optimization strategies based on user perceptions and organizational decisions. Methods: A qualitative case study was conducted with Shopee as the unit of analysis. Nine participants three internal Shopee personnel and six active users were interviewed and selected via purposive sampling. Thematic analysis followed three stages (open, axial, and selective coding) guided by the TOE–TAM framework. Trustworthiness was ensured through member checking, peer debriefing, and four criteria: credibility, transferability, dependability, and confirmability. Result: Shopee's AI chatbot delivers personalized recommendations but users frequently experience information overload from irrelevant results. Three TOE dimensions technology readiness, organizational readiness, and external pressure, were found to drive adoption, while four TAM factors perceived usefulness, ease of use, trust, and satisfaction, shape user acceptance. Five strategic recommendations are proposed: algorithm enhancement, data quality improvement, adaptive personalization, deeper customer profiling, and information overload reduction. Novelty: Prior studies examine organizational adoption (TOE) or user acceptance (TAM) of AI chatbots in isolation, leaving a gap in understanding how macro-level institutional readiness interacts with micro-level user cognitive barriers. This study addresses that gap by integrating TOE and TAM as a dual-perspective lens, explaining how institutional readiness spanning technology, organization, and environment directly reduces cognitive barriers during automated recommendations. The study further foregrounds the "Complex Customer Preferences vs. Information Overload" paradox as a central challenge: AI chatbots deployed to manage complex preferences often generate overload that undermines user trust and satisfaction, a tension prior TOE–TAM integrations have not addressed.
Utilization of Artificial Intelligence in Government Hospital Information Systems: A Systematic Review Isnina Eva Hidayati; Sofian Lusa; Iindra Iriyanti; Nurcholis Ramlan; Dana Indra Sensuse
Jurnal Impresi Indonesia Vol. 5 No. 2 (2026): Jurnal Impresi Indonesia
Publisher : Riviera Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58344/jii.v5i2.7588

Abstract

The use of Artificial Intelligence (AI) in healthcare continues to expand. Hospital Information Systems (HIS) play a crucial role in managing clinical and operational data within hospitals. With advancements in technology, the integration of AI into HIS is gaining increasing attention due to its potential to enhance efficiency, accuracy, and the overall quality of healthcare services. Currently, government hospitals face various challenges in delivering public health services, including lengthy administrative processes, limited medical personnel, and the growing need for faster, data-driven clinical decision-making. This study focuses on analyzing the role of AI in supporting HIS development in government hospitals, with the objective of improving efficiency, accuracy, and service quality. Using a Systematic Literature Review (SLR) approach, the study collects, evaluates, and analyzes recent literature on the application of AI within HIS in government hospitals, particularly in areas such as patient registration, diagnostic support, electronic medical record management, and digital triage systems. The expected outcome of this study is a more comprehensive understanding of how AI can improve hospital operational efficiency while enhancing the quality of patient experiences, especially within public healthcare contexts. In addition, the study identifies key challenges in implementing AI within HIS, including limited system interoperability, the need for stronger health data security and regulatory frameworks, and insufficient human resource readiness. Therefore, this research is expected to provide meaningful contributions to policymakers, system developers, and government hospitals in designing digital transformation strategies for public health services that are smarter, safer, and more patient-oriented.
Factors Influencing Generative AI Adoption in Government: A Case Study in BPS-Statistics of Indonesia Mutia Sayyidah; Sofian Lusa; Muhammad Rizki; Nurcholis Ramlan; Dana Indra Sensuse
Jurnal Impresi Indonesia Vol. 5 No. 4 (2026): Jurnal Impresi Indonesia
Publisher : Riviera Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58344/jii.v5i4.7666

Abstract

Rapid technological developments hold great potential, one of which is generative AI. Technology that is easily accessible and user-friendly tends to spread quickly, and BPS-Statistics of Indonesia is no exception. The challenges currently faced by BPS-Statistics of Indonesia, such as rapid data growth, high data demand, and data analysis and representation, encourage the institution to be adaptive to new technologies that can accelerate work processes. This research aims to determine the factors influencing the acceptance and use of generative AI (GenAI), such as ChatGPT, Gemini, and others, among BPS-Statistics of Indonesia employees, using Behavioral Intention as the central mediating variable that bridges the influence of these predictor factors on Use Behavior. The model also examines the relationships between external factors, such as Social Influence and Trust, and Perceived Usefulness and Perceived Ease of Use, as well as their effects on Attitude. Additionally, it evaluates the influence of Hedonic Motivation, Facilitating Conditions, Perceived Severity, and Perceived Vulnerability on Behavioral Intention. Based on a survey of 166 respondents at BPS-Statistics of Indonesia, the results reveal that Attitude has a significant influence on Behavioral Intention, while Perceived Severity has a significant negative influence on Behavioral Intention. Furthermore, Behavioral Intention is also shown to have a significant positive influence on Use Behavior. These findings contribute theoretically to the development of technology adoption models in the public sector and have practical implications for BPS-Statistics of Indonesia in formulating AI usage policies.
Analysis of Public Sentiment Indonesia’s Personal Data Protection Law: A Comparison of SVM and IndoBERT on X Platform Kurniawati, Yulia; Hamid, Ricky Bahari; Sensuse, Dana Indra; Lusa, Sofian; Putro, Prasetyo Adi Wibowo; Indriasari, Sofiyanti
Jurnal Teknik Informatika (Jutif) Vol. 7 No. 2 (2026): JUTIF Volume 7, Number 2, April 2026
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2026.7.2.5415

Abstract

The high number of data misuses, thefts, and leaks led to the enactment of the PDP Law, which regulates the rights and obligations of data owners and electronic system providers. The purpose of this study is to examine the public’s response to the implementation of the law through the X platform, using tweet harvest as a scraping tool, and to evaluate model performance through a comparative approach between SVM and BERT. The feature extraction used in this study is TF-IDF for SVM and BERT with IndoBERT. The accuracy results indicate that BERT is better with an accuracy of 86% compared to SVM with a training and test data ratio of 85:15. This advantage is because BERT can understand linguistic context that SVM cannot. On the other hand, SVM has advantages in computational efficiency and faster processing, making it a suitable choice in situations with limited computational resources. The sentiment analysis result revealed that data protection,  digital footprint and the institution's role were the most frequently discussed topics. Furthermore, periodic or real-time evaluations can be conducted on the public's response to the PDP Law to ensure it remains aligned and relevant to technological developments and societal needs.
Identifying Key Components of Knowledge Management Strategy in Government: A Systematic Literature Review Sabrina Editha Putri; Irni Irmayani; Dana Indra Sensuse; Sofian Lusa; Nadya Safitri
Journal of Business, Social and Technology Vol. 7 No. 1 (2026): Journal of Business, Social and Technology
Publisher : Politeknik Siber Cerdika Internasional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59261/jbt.v7i1.579

Abstract

Background: Amid digital transformation and the demand for adaptive public governance, Knowledge Management (KM) has become a strategic asset for government agencies. Previous studies have examined individual KM success factors—such as leadership, organizational culture, or technology readiness—yet most remain fragmented, case-specific, and lack an integrated strategic framework tailored to public sector governance. Objective: This study aims to identify key components and effective strategies for implementing KM in government organizations through a Systematic Literature Review (SLR) using the PRISMA 2020 framework. Methods: A total of 600 articles were screened from five leading scientific databases, resulting in 20 eligible studies for in-depth analysis. The review addresses two questions: (1) What are the key components of KM in government. (2) What strategies effectively support KM implementation in the public sector. Results: KM success in government rests on two interrelated domains: KM Foundation (leadership, organizational culture, structure, readiness, and technological infrastructure) and KM Solution (knowledge capture, sharing, discovery processes, regulatory mechanisms, and user-friendly systems). Nine strategic implementation areas were identified, including transformational leadership, human capital development, technology integration, performance alignment, and regulatory strengthening. Unlike prior studies that examined KM components separately, this research integrates fragmented findings into a structured and strategic framework combining foundational and operational dimensions. The study contributes theoretically by conceptualizing KM as a strategic governance capability and practically by offering policy-relevant guidance for strengthening adaptive, collaborative, and knowledge-driven public sector reform. Conclusion: An integrated and strategically aligned KM approach is essential for sustainable and effective public governance.
Co-Authors Abdullah, Puja Putri ACHMAD FUAD Ade Fitria Lestari Adhitama, Raihansyah Yoga Adi Pratama, Yoga Adi Suryaputra Paramita Aditya, Silfa Kurnia Afifah Nefiratika Agnes Agnes Ahmad Jurnaidi Wahidin Aji Baskoro Ajie Tri Hutama Akbarsyah Anza, Fikri Alfiani, Husna Altino, Iqbal Caraka Alusi, Fahmi Amastini, Fitria Anditama, Muhammad Rizky Andriansyah, Chandra Ansis, Ronny Aprilia Pratiwi Aprilia, Relaci Apriyana, Yeni Apriyanti Sijabat Ariani, Septi Arief Ramadhan Arief Ramadhan Arif Wahyudi Ariq Naufal Satria Aryanto Aryanto Assaf Arief Assaf Arief Assaf Arief Assaf Arief, Assaf Astrianty, Rani Aprilia Ayu Bintang Nurrachma Gunawan Ayu Bintang Nurrachma Gunawan Ayu Bintang Nurrachma Gunawan Aziz, Riva Abdillah Basnur, Prajna Wira Binsar Tampahan Binsar Tampahan Binsar Tampahan Brillianto, Bramanti Budi, Nur Fitriah Ayuning Cahyaningsih, Elin Cakra Wirabuana Cakra Wirabuana Damayanti Elisabeth Damayanti Elisabeth Damayanti Elisabeth Damayanti Elisabeth Damayanti Elisabeth Darmawan Baginda Napitupulu Darmawan Napitupulu Deden Sumirat Hidayat Deden Sumirat Hidayat Deden Sumirat Hidayat Deden Sumirat Hidayat Deden Sumirat Hidayat, Deden Sumirat Desiana Nurul Maftuhah Destriani, Rahma Dewi Mutiara Nurani Dewi Sartika Dewi, Yesi Puspita Diaz Saputra Dieny Sukmiati Dieny Sukmiati Dieny Sukmiati Dion Lamilga Sudiono Putra Dion Lamilga Sudiono Sudiono Putra Dwi Handoko Dwi Handoko Dwi Handoko Dwi Handoko Edi Abdurachman El Farisi, Salman Elin Cahyaningsih Elin Cahyaningsih Elisabeth, Damayanti Elkaf Fahrezi Soebianto Putra Erisva Hakiki Purwaningsih Erisva Hakiki Purwaningsih Erisva Hakiki Purwaningsih Erni Juraida EVI YULIANTI Fachri Munandar Fahmi Alusi Fahmi Alusi Fahmi Alusi Faiz Rizqullah Pratama Faradillah Faradillah Fathurahman Ma'ruf Hudoarma Fatoumatta Binta Jallow Fauzia Nur, Pita Larasati Ferdian Maulana Akbar Ferry Febrianto Fikri Akbarsyah Anza Firdaus, Aditya Reza Firmansyah Apryadhi Fithri Selva Jumeilah Fitria Amastini Fitria Rahma Sari Fitria Rahma Sari Fitria Rahma Sari Fitriya, Ghina Ford Lumban Gaol Franky Juhar Furqon, Moehammad Arief Galih Reksa Lingga Respati Gesi Deta Hendika Wardani Ghaisani, Amanda Ghina Fitriya Giffari, Rafi Goldie Gunadi Hakim, Mohammad Luqmanul Hamid, Ricky Bahari Hanif Sudira Harjanto Prabowo Harjanto Prabowo Hartanto, Adi Herlambang Permadi Hidayat Akbar Hidayat Akbar Hidayat, Ilatifah Nur Hudoarma, Fathurahman Ma'ruf Husain Husain Husna Alfiani I Made Agus Ana Widiatmika I Made Agus Ana Widiatmika I Made Agus Ana Widiatmika I Nyoman Adi Putra Ignatius Adrian Mastan Iindra Iriyanti Iklima Ermis Ismail Imairi Eitiveni Imairi Eitiveni Imanuddin, Kamila Alifia Inayah, Suci - Indra, Muhammad Nadhirsyah Indria, Sofi Indriasari , Sofiyanti Indriasari, Sofianti Irni Irmayani Isnina Eva Hidayati Iwan Juniar Simanjutak Jallow , Fatoumatta Binta Jani Richi R. Siregar Jeffry Adityapriatama Jonathan Sofian Lusa Jonathan Sofian Lusa Jonathan Sofian Lusa Kautsarina Kautsarina Kautsarina Kautsarina Kautsarina Khalid Jasir Krisanto Abilowo Kurniawan, Shabrina Salsabila Lathiful Alamsyah Lenggo Geni Lia Ellyanti Louis Dwysevrey Ompusunggu Lusa, Sofian Lusa, Sofian Lusi Fajarita M. Mushlih Ridho M. Mushlih Ridho Maharani, Nandhita Zefania Mahmud Ali Asykar Mahsa Elvina Rahmawyanet Marwan Wahyudin Masbudi, Handika Maulana, Miftahul Meilinda Puji Pamungkas Mia Agustina Miftahul Maulana Miftahul Maulana Miftahul Maulana Mirza Triyuna Putra Moehammad Arief Furqon Moehammad Arief Furqon Moh. Anshori Aris Widya Monica Ratna Andani Muhamad Adhytia Wana Putra Rahmadhan Muhammad Fadhiel Alie Muhammad Farid Fadhlan Muhammad Rizki Muhammad Rizki Muhammad Saddam Muhammad, Miftah Mutia Sayyidah Nadya Safitri Nadya Safitri Nadya Safitri Nadya Safitri Nadya Safitri Nadya Safitri Nadya Safitri, Nadya Nandhita Zefania Maharani Napitupulu, Darmawan Nashrul Hakiem Nashrul Hakiem Nefiratika, Afifah Ni Wayan Trisnawaty Novia Agusvina Nur Chasanah Nur Chasanah Nur Chasanah Nur Chasanah Nur Fitriah Ayuning Budi Nur Indrawati Nur Indrawati, Nur Nurcholis Ramlan Nurcholis Ramlan Nurul Aulia Larasati Nurzaitun Purwasih Nurzaitun Purwasih Nurzaitun Purwasih Oki Priyadi Permadi, Herlambang Pita Larasati Fauzia Nur Pita Larasati Fauzia Nur Pita Larasati Fauzia Nur Pradipta, Dhea Junestya Prasetyo Adi Prasetyo Adi Prasetyo Adi Wibowo Putra Prasetyo Adi Wibowo Putro Prasetyo Adi Wibowo Putro Prasetyo Adi Wibowo, Prasetyo Adi Prastowo, Rahardito Dio Pratiwi, Aprilia Pratiwi, Maharani Eka Prayoga, Sigit Hadi Prihantara Arif Budi Santosa Prima, Pudy Puji Rahayu Puji Rahayu Purnomo, Dencaswo Purwaningsih, Erisva Hakiki Purwasih, Nurzaitun Putra Tresna Linge Putra, Risma Bayu Putro , Prasetyo Adi Wibowo Putro, Prasetyo Adi Wibowo Putu Raditya Astika Putra Qurrota Ayun Majid R. Sapto Hendri Boedi Soesatyo Rabiah Al Adawiyah Rachmawati, Ummi Azizah Raden Trimanadi Rafi Giffari Rahmat Nurcahyo Rahmat Nurcahyo Rahmawyanet, Mahsa Elvina Ramadhan, Yudistira Rani Aprilia Astrianty Rendra Gustriansyah Retisa Heryati Siwi Rian Rahmanda Putra Rias Kumalasari Devi Richi R. Siregar, Jani Ridwan Afandi Ridwan Marbanie Rina Rahmawati, Rina Ringgi Cahyo Dwiputra Rini Muliahati Risma Bayu Putra Risma Bayu Putra Risma Bayu Putra Rivaldi Rizalul Akhsan Rivaldi Rizalul Akhsan Rivaldi Rizalul Akhsan Rizaldy Septa Amanda Rizaldy Septa Amanda Rizki Kurniawan Rizky, Fajar Robby Hermansyah Romlah, Ummu Habibah Ronny Ansis Rudy Sugiharto Iskandar Ryan Randy Suryono S.Pd. M Kes I Ketut Sudiana . Sabrina Editha Putri Salman Alfarisi Salman El Farisi Salman El Farisi Saputro, Singgih Dwi Sari, Fitria Rahma Sarika Afrizal Sarika Afrizal Sarika Afrizal, Sarika Semlinda Juszandri Bulan Septian Bagus Wibisono Shabrina Salsabila Kurniawan Sigit Hadi Prayoga Sigit Hadi Prayoga Sigit Hadi Prayoga Sihombing , Boy Sandi Kritian Sihombing, Boy Sandi Kristian Silfa Kurnia Aditya Slamet Darmawan Sofian Lusa Sofian Lusa Sofian Lusa Sofian Lusa Sofian Lusa Sofian Lusa Sofian Lusa Sofian Lusa Sofian Lusa Sofianti Indriasari Sofiyanti Indriasari Sofiyanti Indriasari Sri Rosa Anjelia Sudarto, Reska Nugroho Suhaidir, Wiliam Sukmiati, Dieny Sutoyo, Mochammad Arief Hermawan Suwardiman, Suwardiman Suwiyanto, Viktor Syarifah Hanum Tambunan, Ester Marta Tampahan, Binsar Tanjung, Aldiyan Muhammad Tinny D Kaunang Tokuro Matsuo Tommy Putra Pratama Gunawan Trimanadi, Raden Triyono, Gandung Tsaqif Alfatan Nugraha Wahab, Iis Hamsir Ayub Wanda Kinasih Warkim Warkim Warkim Warkim, Warkim Wendy Nur Falaq Wendy Nur Falaq Wibowo Putra, Prasetyo Adi Wibowo, Wahyu Setyawan Widiatmika, I Made Agus Ana Wiliam Suhaidir Wiliam Suhaidir Wiliam Suhaidir Yaziji, Warda Yolanda Yosephine Zebua Yudho Giri Sucahyo Yudho Giri Sucahyo Yulia Kurniawati Yulianingsih Yulianingsih