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All Journal International Journal of Electrical and Computer Engineering IAES International Journal of Artificial Intelligence (IJ-AI) IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Economic Journal of Emerging Markets Jurnal Ilmiah Poli Rekayasa Proceedings of KNASTIK Bulletin of Electrical Engineering and Informatics CommIT (Communication & Information Technology) Indonesian Journal of Electrical Engineering and Informatics (IJEEI) SITEKIN: Jurnal Sains, Teknologi dan Industri Jurnal NERS Scientific Journal of Informatics Proceeding of the Electrical Engineering Computer Science and Informatics Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) POLYGLOT Emerging Science Journal Syntax Literate: Jurnal Ilmiah Indonesia JITK (Jurnal Ilmu Pengetahuan dan Komputer) Jurnal Komtika (Komputasi dan Informatika) International Journal of New Media Technology Jurnal Teknoinfo Jurnal Sisfokom (Sistem Informasi dan Komputer) International Journal of Supply Chain Management Poltekita : Jurnal Ilmu Kesehatan Jutisi: Jurnal Ilmiah Teknik Informatika dan Sistem Informasi Informatika Jurnal Sistem Informasi dan Informatika (SIMIKA) Jurnal Informatika Ekonomi Bisnis Jurnal Informatika dan Rekayasa Perangkat Lunak International Journal of Advances in Data and Information Systems Jurnal Sistem Komputer dan Informatika (JSON) Journal of Applied Data Sciences Walisongo Journal of Information Technology Jurnal Informatika dan Teknologi Komputer ( J-ICOM) Action Research Literate (ARL) Jurnal Algoritma Jurnal Indonesia Sosial Teknologi Eduvest - Journal of Universal Studies Jurnal Informatika Ekonomi Bisnis Jurnal Sistem Informasi International Journal of Education, Language, Literature, Arts, Culture, and Social Humanities The Indonesian Journal of Computer Science Malahayati International Journal of Nursing and Health Science JHSS (Journal of Humanities and Social Studies) Jurnal Komtika (Komputasi dan Informatika) Sosio e-kons
Achmad Nizar Hidayanto
Fakultas Ilmu Komputer, Universitas Indonesia
Aerospace Engineering Arts Humanities Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Medicine & Pharmacology Neuroscience Nursing Public Health Social Sciences Transportation Other

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Faktor-Faktor yang Mempengaruhi Literasi Digital Remaja dalam Game Online: Sebuah Systematic Literature Review Syanandi, Muhammad Destara; Hidayanto, Achmad Nizar
The Indonesian Journal of Computer Science Vol. 14 No. 6 (2025): The Indonesian Journal of Computer Science
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v14i6.5049

Abstract

The growing prominence of online games as spaces for intensive digital interaction has encouraged adolescents to engage more actively in gaming activities, while simultaneously increasing their exposure to various online opportunities and risks. This condition requires adolescents to possess adequate digital literacy skills, enabling them to navigate information, interact safely, and understand the social implications of their behaviour in virtual environments. This study aims to identify individual, social, and platform-level factors that influence adolescents’ digital literacy within the context of online games, and to explain how the relationships among these factors are discussed in prior empirical research. Using a Systematic Literature Review method based on PRISMA 2020, this study analyses 26 articles selected through a process of identification, screening, quality appraisal, and data extraction. The results demonstrate that adolescents’ digital literacy is influenced by individual competencies, such as digital skills, self-efficacy, critical thinking, and psychological conditions; social factors, including parental mediation, peer support, and socioeconomic conditions; and platform factors, including game feature design, interaction mechanisms, and characteristics of metaverse environments. The relationships among these factors are mutually reinforcing, in which digital literacy develops when a responsive social environment and safe platform design support individual competencies. This study highlights the importance of an ecological approach to understanding and enhancing adolescents’ digital literacy in online games. It encourages further research to explore more specific cultural contexts and game mechanics.
Identification Of Factors Influencing Customer’s Continuance Inten-tion In The Post-Adoption Phase Of A Cloud-Based Human Resource Management System Alfatianisa, Kirana; Hidayanto, Achmad Nizar
Syntax Literate Jurnal Ilmiah Indonesia
Publisher : Syntax Corporation

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36418/syntax-literate.v11i2.63545

Abstract

The advancements in information technology during the digital transformation era have encouraged organizations to adopt cloud-based systems to improve their operational efficiency, including in human resource management area. Human Resource Management Systems (HRMS) have become a critical component in enabling integrated automation of HR processes. PT XYZ, as a vendor providing cloud-based HRMS through its product HRTechIndo, has supported the digitalization of HR processes for various organizations in a Business-to-Business (B2B) setting. However, the stagnant customer retention rate that has always been below the target indicates system utilization that is not optimal. This condition requires attention, because low retention may hinder PT XYZ’s business sustainability, which relies on loyalty and long-term relationships with clients. This study aims to identify the factors influencing continuance intention in PT XYZ. The research model was developed by integrating the Expectation Confirmation Model (ECM) and the Technology-Organization-Environment (TOE) framework. PLS-SEM was employed to analyze data from 184 respondents representing 36 client organizations, supported by literature review and qualitative validation through interviews. The results show that confirmation, perceived usefulness, satisfaction, vendor service quality, and organizational fit significantly influence continuance intention. Meanwhile, cloud system quality indirectly affects continuance intention through satisfaction, and perceived value does not influence it significantly. These findings highlight that the continuance intention of HRTechIndo’s usage by clients is primarily driven by perceived benefits, post-adoption experience, vendor service quality, and alignment between the system and organizational processes.
Information and Technology Governance Capability Analysis: Case Study of CV Wirelessindo Reihan Putra Oktavio; Achmad Nizar Hidayanto
Jurnal Indonesia Sosial Teknologi Vol. 5 No. 8 (2024): Jurnal Indonesia Sosial Teknologi
Publisher : Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59141/jist.v5i8.1324

Abstract

The implementation of information and technology (IT) supports company sustainability. Large companies use IT as an integral part of their business model. Digital strategies must align with business strategies to achieve sustainability. Wirelessindo, established in 2007, provides IT solutions such as equipment, site surveys, network design and security, and tower installations. Its mission is to increase company productivity to win the competition in the era of Industry 4.0. It is used to enhance customer service and internal business process efficiency. Initial investigations found issues with IT function mismatches, financial losses due to data loss, IT equipment installation and configuration errors, and business process incidents caused by emerging risks. Identified root problems include employee knowledge gaps, risk management disparities, errors in defining business needs, and change management gaps. Based on these findings, IT governance eval_uation was chosen as the research focus. This study aims to provide an overview of CV Wirelessindo IT capability levels and recommend improvements to meet expected levels. A mixed-method approach and COBIT 2019 were used in this study. The General Manager, IT Division Manager, Software Development Team, Network Monitoring Team, Project Manager, and HR Manager were selected as respondents based on the RACI chart guidelines. Of the nine selected objectives, BAI08 showed level 0. APO12, BAI02, BAI06, BAI07, and DSS01 showed level 1. APO07, BAI10, and DSS03 showed capability level 2. Therefore, 61 recommendations were provided to raise the IT governance capability level to level 3 for all objectives.
Case Study of Claim Data and Participant Data in Indonesian Insurance Companies Chris Solontio; Achmad Nizar Hidayanto
Jurnal Indonesia Sosial Teknologi Vol. 5 No. 12 (2024): Jurnal Indonesia Sosial Teknologi
Publisher : Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59141/jist.v5i12.7043

Abstract

Data has become an asset for insurance companies that has many benefits, especially health insurance, so that management needs to realize the importance of good data quality in order to avoid the impact of poor data quality. In this study, data quality measurement will be carried out by observation to see the total amount of invalid data from the data dimensions, namely, accuracy, completeness and consistency of the relationship between claim data and customer data as well as the findings of the overall data of each case study site. In addition to the data analysis, interviews were conducted with the IT, Customer Retention, Operations, and Actuarial teams who are directly related to data flow and data processing to create an analysis that helps management in making decisions. From the results of the analysis and interviews that have been conducted, there are still data that do not match and obstacles faced by users in dealing with poor data quality. From the results of this analysis, management needs to form a data govenance team that has the responsibility of the entire data flow and maintaining data quality. Later, the managed data set will have a positive impact on other teams in terms of analyzing trends or fraud in a faster time, assisting in the creation of a data warehouse, implementing artificial intelligence (AI) and digital transformation as a form of company improvement to insurance policyholders.
Evaluation and Selection of Robotic Process Automation Platforms Using the AHP–Topsis Method: A Case Study in the Banking Industry Kumalasari, Diah; Nizar Hidayanto, Achmad
Syntax Literate Jurnal Ilmiah Indonesia
Publisher : Syntax Corporation

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36418/syntax-literate.v11i2.63606

Abstract

Robotic Process Automation (RPA) has become a key technology for improving efficiency and accuracy in operational processes within the banking sector. However, increasing organizational complexity and regulatory demands make the selection of an appropriate RPA platform a challenging decision. This study aims to identify the most suitable RPA platform using a Multi-Criteria Decision-Making (MCDM) approach by integrating the Analytical Hierarchy Process (AHP) and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). The evaluation framework is developed based on a hierarchical structure consisting of six main criteria and sixteen sub-criteria, including technology, cost efficiency, compliance, user experience, vendor and implementation support, as well as analytics and monitoring. Four alternatives were compared: UiPath, Automation Anywhere, Power Automate, and Kofax. The AHP weighting results indicate that compliance, technology, and cost efficiency are the most influential criteria in RPA platform selection. The TOPSIS analysis shows that Power Automate achieves the highest relative closeness value (Ci = 0.7344), followed by UiPath (Ci = 0.4604). Based on these findings, Power Automate is identified as the most suitable RPA platform for supporting banking process automation. The study recommends a hybrid RPA implementation strategy whereby Power Automate is adopted as the primary solution and UiPath is used as a complementary platform for complex automation scenarios. The results of this research are expected to serve as a basis for strategic decision-making to support the bank’s ongoing digital transformation.
Data Analytics Capability Maturity and Governance Gaps in PT ABC: A Diagnostic Case Study Simanjuntak, Almon Junior; Hidayanto, Achmad Nizar; Trimanadi, Raden
International Journal of Advances in Data and Information Systems Vol. 7 No. 1 (2026): April 2026 - International Journal of Advances in Data and Information Systems
Publisher : Indonesian Scientific Journal

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59395/ijadis.v7i1.1503

Abstract

This study provides a within-case diagnosis of data analytics capability maturity in PT ABC to inform refinement of its 2025 to 2026 governance roadmap. Using a qualitative-first mixed-method diagnostic case design (QUALQUAN), this study conducted five semi-structured key-informant interviews first, followed by a cross-sectional survey of 76 purposively selected analytics-involved employees, analyzed using the Shortened TDWI Data Analytics Maturity Model (STDAMM). The overall maturity mean was 3.31 on a 5-point scale (bootstrap 95% confidence interval: 3.15 to 3.46), classifying the assessed respondent pool as Level 3 (Established). Dimension means were tightly clustered (3.27 to 3.35) with substantial confidence-interval overlap, suggesting that respondents perceive maturity as a coupled system rather than sharply separated capability domains. A small descriptive pattern places analytics use and infrastructure marginally above data management and organizational enablement, consistent with interview accounts of definition inconsistency, limited socialization of dictionary and stewardship practices, and recurring manual reconciliation of figures across systems. The findings support a governance-first refinement of the roadmap that prioritizes standardization and ownership mechanisms to improve the comparability and decision-readiness of analytics outputs, while treating subgroup comparisons cautiously where measurement comparability is not supported.
Klasifikasi Ulkus Kaki Diabetik Berbasis Transfer Learning: Studi Komparatif Arsitektur CNN Nafiiyah, Nur; Rifqi Firdaus Al Jauhari; Agus Harjoko; Achmad Nizar Hidayanto
Jurnal Sistem Komputer dan Informatika (JSON) Vol. 7 No. 3 (2026): Maret 2026
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/json.v7i3.9580

Abstract

Proses klasifikasi citra medis secara otomatis sangat penting untuk membantu proses diagnosis yang cepat dan objektif. Deep learning, terutama Convolutional Neural Network (CNN), telah menunjukkan kemampuan yang lebih baik untuk mengidentifikasi dan mengklasifikasikan gambar. Namun, model yang tepat masih sulit dipilih karena perbedaan dalam desain arsitektur CNN dapat berdampak besar pada kinerja. Tujuan dari penelitian ini adalah untuk mengevaluasi dan membandingkan kinerja lima arsitektur CNN (VGG16, VGG19, ResNet101, InceptionV3, dan DenseNet121) ketika menggunakan dataset Ulkus Kaki Diabetes (Diabetic Foot Ulcer/DFU) untuk mengklasifikasikan gambar medis kelas normal dan abnormal. Metode berbasis dataset digunakan untuk menjalankan semua eksperimen. Akurasi, ketepatan, recall, dan F1-score digunakan untuk menilai model. Hasil eksperimen menunjukkan bahwa ResNet101 adalah yang terbaik dengan akurasi dan F1-score sebesar 99,87%, diikuti oleh VGG19 dan VGG16, masing-masing dengan F1-score di atas 99%. DenseNet121 dan InceptionV3 juga menunjukkan kinerja yang kompetitif, meskipun sedikit di bawah model berbasis residual dan VGG. Hasil ini menunjukkan betapa pentingnya melakukan analisis komparatif saat memilih arsitektur CNN untuk klasifikasi citra medis berbasis deep learning.
Integrating Tacit Knowledge into Employee Profiles to Improve Talent Review Accuracy: A Case Study of Oil and Gas Industry Hari Prasetyo Tri Wicaksono; Achmad Nizar Hidayanto; Geri Yesa Ermawan
Eduvest - Journal of Universal Studies Vol. 6 No. 5 (2026): Eduvest - Journal of Universal Studies
Publisher : Green Publisher Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59188/eduvest.v6i5.52684

Abstract

The success of an organization in managing human resources is significantly influenced by the accuracy of its talent review processes, including promotions, rotations, and employee placements. However, these processes often rely solely on explicit data, such as job history and administrative evaluations, which do not fully capture contextual competencies. Tacit knowledge—encompassing field experience, intuition, and problem-solving abilities—plays a crucial role in work effectiveness yet remains largely undocumented in a systematic manner. This study aims to design a system that integrates tacit knowledge into employee profiles using the STAR (Situation, Task, Action, Result) narrative framework to support decision-making in talent reviews. The research adopts a Design Science Research Methodology (DSRM) approach, comprising problem identification, system design, prototype development, and evaluation. A case study was conducted within an operational unit of the oil and gas industry, with data collected through interviews and observations. The findings indicate that integrating STAR narratives into employee profiles enriches the available decision-making data and enhances the precision of talent placement and development. This study provides practical contributions for organizations seeking to build more contextual and knowledge-based human resource management systems, offering a structured approach to capturing tacit knowledge and improving strategic HR decisions.
DEVELOPING A MICRO-ENTERPRISE E-READINESS FRAMEWORK: A CASE STUDY FROM INDONESIA Nori Wilantika; Fitri Kartiasih; Ernawati Pasaribu; Aisha Arthamevia; Yunarso Anang; Achmad Nizar Hidayanto
JITK (Jurnal Ilmu Pengetahuan dan Teknologi Komputer) Vol. 11 No. 3 (2026): JITK Issue February 2026
Publisher : LPPM Nusa Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33480/jitk.v11i3.7189

Abstract

Micro-enterprises play a vital role in Indonesia’s economy but continue to face persistent barriers in adopting information and communication technology (ICT). Understanding E-Readiness is essential for implementing effective digital interventions, especially for micro-enterprises. To address the lack of validated frameworks for assessing digital readiness at the micro-enterprise level, this study develops and empirically tests a novel E-Readiness Assessment Framework specifically designed for micro-enterprises. The proposed conceptual model consists of four dimensions: Technology, Organization, External Environment, and Human Resources, which are derived from established E-Readiness models. This study also proposed the measurement indicators that have been adapted to the characteristics of micro enterprises. Using quantitative data from 641 food and beverage (F&B) micro-enterprises in Batu City, Indonesia, exploratory factor analysis (EFA) was applied to evaluate construct validity. Despite the elimination of five indicators due to insufficient communality value, the overall model structure remained statistically valid. Subsequently, factor analysis was succeeded by the calculation of E-Readiness index using weighted aggregation and normalisation methods.  The resulting E-Readiness Index for Batu City was 46.47, with 57.10% of enterprises classified as “Not Ready,” primarily due to technological and infrastructural limitations.  The proposed model in this study efficiently assesses E-Readiness at the micro-enterprise level and is adaptable for application in different regions or business sectors.  This model also provides valuable insights for policymakers in formulating targeted digital support initiatives.  Future research may consider expanding the scope of indicators and validating the model using confirmatory analysis.
A Hybrid YOLO–CNN Model for Automatic Detection and Severity Assessment of Atopic Dermatitis in Infant Images Debi Setiawan; Ramalia Noratama Putri; Sara Herlina; Achmad Nizar Hidayanto; Yuda Irawan; Naohiro Hohashi
Journal of Applied Data Sciences Vol 7, No 2: May 2026
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v7i2.1212

Abstract

Atopic dermatitis is one of the most common skin diseases affecting infants and children worldwide and has a particularly high prevalence in tropical countries. Traditional diagnosis methods, which still rely on physical examinations and laboratory tests often face challenges such as delays, high costs, and limited facilities, thereby necessitating an artificial intelligence–based system that is more efficient and accurate. This study aims to develop a hybrid YOLO–CNN model for the automatic detection and severity classification of atopic dermatitis in infants. The dataset comprises 2,000 infant skin images, including lesions categorized as mild, moderate, and severe, obtained from an online repository and field observations conducted in three villages. The labeling process was performed by a specialist doctor to ensure clinical validity. In the first step, YOLO was used to detect the lesion area in real time by generating a bounding box. This produced a region of interest (ROI), which was subsequently analyzed by a CNN model employing transfer learning in the second step to determine the severity level. Experimental results indicate that YOLO achieved high detection performance, with an mAP@0.5 of 91.2% and an F1-score of 90.2%, while the CNN model attained an average accuracy of 85% and a macro-F1 score of 85% in classification. The visualization of predictions indicates that most lesions were detected with confidence levels ≥0.9, confirming the model’s consistency. These findings highlight the potential of the hybrid YOLO–CNN framework as a supportive system for digital clinical diagnosis, applicable to both mobile applications and teledermatology services, particularly in regions with limited medical personnel. Future research should employ larger, multi-center datasets and integrate explainable AI approaches to promote broader clinical adoption.
Co-Authors . Herianto . Herianto . Herianto . Herianto Ade Irma Suryani Adhiawan Soegiharto Agil Angga Saputra Agri Fina Agung Terminanto Agus Harjoko Agus Harjoko Ahmadin, Yudhiansyah Aisha Arthamevia Ajie Tri Hutama Alfatianisa, Kirana Alfiany, Noverina Aniati Murni Arymurthy Anita Muliawati Antia Antia Ardiati Utami Sarjono Asymala, Asymala Permata Sari Atalya Yoseba S. Ayuning Budi, Nur Fitriah Azainil Azainil Barus, Okky Beny Maulana Achsan Bob Hardian Syahbuddin Brian Rizadhani Latuconsina Cahyaningtyas, Astri Camelia Fikrillah Canrakerta Canrakerta Canrakerta, Canrakerta Chris Solontio Dandi Taufiqurrohman Debi Setiawan Debi Setiawan, Debi Devi Fitrianah Dewi Puspa Dewi Puspasari Diah Kumalasari Dian Setia Hartana Dian Setia Hartana Dian Setia Hartana Diane Fitria Dwiza Riana Dyna Marissa Khairina Ejo Imandeka Ernawati Pasaribu Fahmi, Rizki Ali Fajar Budi Utomo Fakhri Mubarak, Muhammad Fatimah Azzahro Febiani, Dyah Ayu Fitri Kartiasih Fitri, Imelda Friendly Nur Shakti Geri Yesa Ermawan Geri Yesa Ermawan Gusmao, Mazarino Neil Araujo Pires Leite Handayani, Putu Wuri Handini Mekkawati Hanny Handiyani Hapsari, Ika Chandra Hari Prasetyo Tri Wicaksono Hari Prasetyo Tri Wicaksono Hartana, Dian Setia Henki Bayu Seta Hisyam Fahmi Hohashi, Naohiro Husni Teja Sukmana I Gusti Ngurah Adi Wicaksana Ihsan Lutfi Ika Chandra Hapsari Ika Chandra Hapsari Ika Chandra Hapsari Ika Chandra Hapsari Ika Chandra Hapsari Ika Chandra Hapsari Imairi Eitiveni Indra Budi Irfandi, Zikri Isal, Yugo Kartono J.W. Saputro J.W. Saputro J.W. Saputro Jwalita Galuh Garini Kamrozi Kemas Khaidar Ali Indrakusuma Kenedi Binowo Kezia Amelia Putri Kongkiti Phusavat Kongkiti Phusavat Kongkiti Phusavat Krishna Yudhakusuma P.M. Lasiyanto Putro, Pamuji M. Ari Zulkarnaen M. Aulia Hafidh M. Lazuardi Elsony Maemonah, Maemonah Mahdi, Askarul Mahmud, Mufti Mediati, Ati Surya Mediawati, Ati Surya Meganingrum Arista Jiwanggi Meganingrum Arista Jiwanggi Meganingrum Arista Jiwanggi Meganingrum Arista Jiwanggi Mohamad Habib Havito Ihzami Mohammed Al Kwarizmi Dwi Anggara Muh. Alviazra Virgananda Muhamad Ikbal Muhamad Raihan Fikriansyah Muhammad Daril Nofriansyah Muhammad Imam Santosa Muhammad Labib Jundillah Muhammad Rizky Anditama Muhammad Rizky Anditama Mutia Maulida Nafiiyah, Nur Naohiro Hohashi Nazar, Rizal Mochamad Nenden C.S. Ningrum Nenny Anggraini Nerissa Arviana Ni Wayan Trisnawaty Nilamsari Putri Utami Ninda Lutfiani Noratama Putri, Ramalia Nori Wilantika Noverina Alfiany Nugroho, Widijanto Satyo Nugroho, Widijanto Satyo Nur Fitriah Ayuning Budi Nur Fitriah Ayuning Budi Nur Nafiiyah Nurul Nadiyatun Sholihah Pamuji Lasiyanto Putro Panca O. Hadi Putra Pang Ning-Tan Pangesti, Dyah Pertiwi, Ratih Putri Prasetya, Roliand Prastiti, Rizdiani Tri Purwandari, Betty Putro, Prasetyo Adi Wibowo Qorib Munajat Qurotul Aini R. Yugo Kartono Isal Rahmad Mulyadi Ramadiani - Ramalia Noratama Putri Rani Fersari Damanik Rania Azzahra Rayhan Anandya Reihan Putra Oktavio Rifqi Firdaus Al Jauhari Rizha Febriyanti Rizki Tri Prasetio, Rizki Tri Robby Hermansyah Rosa Nur Rizky FT Rr Tutik Sri Hariyati Ryan Randy Suryono Samik-Ibrahim, Rahmat Mustafa Saputro, J.W. Sara Herlina Sartika Djamaluddin, Sartika Septian Bagus Wibisono Septian Bagus Wibisono Setiawati, Deni Setyowati , Setyowati Setyowati Setyowati Setyowati Setyowati Sherah Kurnia Sihotang, Jhon Rafles Simanjuntak, Almon Junior Sita Wardhani Solontio, Chris Suryana Setiawan Suryana Setiawan Syafiq Abdillah U. Syafira, Adinda Rizkita Syahrul Alam Suriazdin Syahrul Tuba Syanandi, Muhammad Destara Theresiawati Trimanadi, Raden Untung Rahardja Wachid Yoga Afrida Wahyu Catur Wibowo Widijanto Satyo Nugroho Wisnubroto, Agus Sigit Yova Ruldeviyani Yuda Irawan Yudhiansyah Ahmadin Yudhiansyah Ahmadin Yudhiansyah Ahmadin Yudhianto, Riswan Haryo Yudi Ramdhani Yunarso Anang Yusuf Rahman Zikri Irfandi