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All Journal International Journal of Electrical and Computer Engineering IAES International Journal of Artificial Intelligence (IJ-AI) Jurnal Teknologi Industri Pertanian Jurnal Komunikasi Pembangunan Jurnal Manajemen dan Organisasi Jurnal Manajemen dan Agribisnis Jurnal Pustakawan Indonesia Jurnal Reviu Akuntansi dan Keuangan JPTK: Jurnal Pendidikan Teknologi dan Kejuruan Jurnal Ilmu Komputer dan Informasi Jurnal Manajemen Teknologi Techno.Com: Jurnal Teknologi Informasi TELKOMNIKA (Telecommunication Computing Electronics and Control) Bulletin of Electrical Engineering and Informatics Jurnal Ilmu Komputer dan Agri-Informatika JAM : Jurnal Aplikasi Manajemen Indonesian Journal of Business and Entrepreneurship (IJBE) SITEKIN: Jurnal Sains, Teknologi dan Industri Jurnal Teknologi Informasi dan Ilmu Komputer Jurnal Edukasi dan Penelitian Informatika (JEPIN) Jurnal Pengelolaan Sumberdaya Alam dan Lingkungan (Journal of Natural Resources and Environmental Management) Jurnal Aplikasi Bisnis dan Manajemen (JABM) E-Journal Scientific Journal of Informatics Edulib Jurnal Manajemen Teori dan Terapan Lentera Pustaka Sosio Konsepsia Proceeding of the Electrical Engineering Computer Science and Informatics JOIV : International Journal on Informatics Visualization Jurnal Pendidikan Informatika dan Sains JURNAL SIMETRIK Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Informatika Pertanian Syntax Literate: Jurnal Ilmiah Indonesia Jurnal Penjaminan Mutu Jurnal Gizi dan Pangan Soedirman (JGPS) Communications in Science and Technology Jurnal Informatika Universitas Pamulang Applied Information System and Management Jurnal Teknoinfo JAS-PT Jurnal Analisis Sistem Pendidikan Tinggi Zero : Jurnal Sains, Matematika, dan Terapan CYBERNETICS Petir Informatik : Jurnal Ilmu Komputer Kwangsan: Jurnal Teknologi Pendidikan Jesya (Jurnal Ekonomi dan Ekonomi Syariah) Komputasi: Jurnal Ilmiah Ilmu Komputer dan Matematika Jurnal Sistem Cerdas EDUMATIC: Jurnal Pendidikan Informatika Journal of Information Systems and Informatics Systematics Jurnal MEBIS (Manajemen dan Bisnis) JGISE-Journal of Geospatial Information Science and Engineering Journal Cerita: Creative Education of Research in Information Technology and Artificial Informatics Indonesian Journal of Electrical Engineering and Computer Science Journal of Applied Data Sciences Business Review and Case Studies International Journal of Engineering, Science and Information Technology International Journal of Social Service and Research Media Publikasi Promosi Kesehatan Indonesia (MPPKI) Jurnal Pustakawan Indonesia Jurnal Ilmiah Ilmu Terapan Universitas Jambi Eduvest - Journal of Universal Studies Jurnal Teknik Indonesia Jurnal Sistem Informasi Al-Kharaj: Jurnal Ekonomi, Keuangan & Bisnis Syariah Jurnal Sistem Informasi dan Aplikasi Journal of Information Technology and its Utilization Biodiversitas Journal of Biological Diversity
Irman Hermadi
School Of Data Science, Mathematics And Informatics, IPB University, Bogor, West Java, Indonesia, 16680
Aerospace Engineering Agriculture, Biological Sciences & Forestry 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 Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Neuroscience Physics Public Health Social Sciences Transportation Other

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Dynamic optimization using long short-term memory and genetic algorithms for predicting marine data Mukhlis Mukhlis; Indra Jaya; Sri Nurdiati; Karlisa Priandana; Irman Hermadi
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 15, No 3: June 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v15.i3.pp2826-2837

Abstract

This study aims to develop an accurate and efficient ocean data prediction model to tackle the challenges posed by climate change and complex oceanographic dynamics. The main goal is to use long short-term memory (LSTM) networks along with genetic algorithms (GA) to predict four key ocean factors at once: sea surface temperature (SST), sea surface height (SSH), sea surface salinity (SSS), and chlorophyll-a (Chl-a). An experimental quantitative approach is employed, utilizing satellite data from the Banda Sea region. This approach involves time series modeling using LSTM, which is optimized by GA for hyperparameters such as the number of neurons and batch size. The results show that the combined LSTM-GA model greatly improves prediction accuracy and successfully identifies seasonal trends and irregular changes in all variables, even when there is a lot of noise. Tests reveal that the optimal configuration varies for each variable, and the GA optimization process can expedite model convergence by as little as 10 epochs. These findings underscore the effectiveness of integrating evolutionary techniques in training deep learning (DL) models for ocean data. The implications of this research include potential applications in adaptive ocean monitoring systems, early warning initiatives, and data-driven planning in marine resource management.
A Conceptual Consortium Blockchain Model to Enhance Integrity and Auditability in Indonesia’s Election Result Recapitulation Muhammad Hadi Pranowo; Yani Nurhadryani; Irman Hermadi
ZERO: Jurnal Sains, Matematika dan Terapan Vol 10, No 1 (2026): Zero: Jurnal Sains Matematika dan Terapan
Publisher : UIN Sumatera Utara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30829/zero.v10i1.27710

Abstract

Election results recapitulation requires stakeholder participation, data integrity, and auditability. However, electronic systems remain largely centralized and provide limited support for multi-stakeholder involvement, traceable audit trails, and verifiable record integrity. This study formalizes the recapitulation process as a rule-based state-transition model and proposes a consortium Blockchain architecture as a parallel recapitulation channel. Built on Hyperledger Fabric, the network comprises peer nodes representing election officials, supervisors, and witnesses, and is governed by smart contracts with policy-driven endorsement. The model encodes stakeholder roles, cryptographic document binding through IPFS content identifiers and hash verification, and rule-based state validation, with emphasis on arithmetic consistency and plenary time-window constraints. The artifact is evaluated through regulatory compliance mapping and computational testing. The results show that the model enables multiparty verification, preserves auditable transaction history, and maintains verifiable linkage between recapitulation records and supporting documents, while constraining accepted state transitions to defined arithmetic and procedural rules.
Conceptual Design of a Permissioned Blockchain-Based Asset Management System in Higher Education using Hyperledger Fabric Ichwan Subekti; Irman Hermadi; Yani Nurhadryani
Journal of Information System and Informatics Vol 8 No 3 (2026): June
Publisher : Asosiasi Doktor Sistem Informasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63158/journalisi.v8i3.1618

Abstract

Effective asset management is a fundamental pillar of higher education operations and strategic sustainability. However, existing conventional systems are often hampered by systemic challenges, including operational inefficiencies, lack of transparency, and chronic data integrity issues resulting from fragmented information silos. This study proposes a conceptual design for a higher education asset management system utilizing blockchain technology to address these governance weaknesses. Based on a comprehensive literature review and system architecture modeling, this study synthesizes concepts from asset management, blockchain principles, and enterprise platforms without deploying a functional prototype. The proposed conceptual framework is built on a permissioned blockchain platform, specifically Hyperledger Fabric, and adopts a multi-layered system architecture for modularity. To balance data integrity with storage efficiency, the system conceptually applies a hybrid data storage pattern combining on-chain ledger records and off-chain databases. Furthermore, the business logic is modeled into smart contracts (chaincode) to automate and secure all stages of the asset lifecycle, from procurement to disposal. The study proposes a theoretical blueprint designed to provide a single, immutable source of truth and enforce multi-level digital approvals. The impact of this research offers a conceptual architectural blueprint that aims to shift academic asset management from a reactive administrative task to an automated, transparent governance ecosystem, paving the way for future validation tasks including performance, scalability, usability, and organizational feasibility.
Government Resource Planning-Based Transformation Strategy for Budget Planning System in Planning Division Directorate General of Sea Transportation Hari Ryanto Wiyono; Dikky Indrawan; Irman Hermadi
Eduvest - Journal of Universal Studies Vol. 5 No. 12 (2025): Eduvest - Journal of Universal Studies
Publisher : Green Publisher Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59188/eduvest.v5i12.51843

Abstract

The fragmentation of planning and budgeting systems in government institutions poses significant challenges to operational efficiency and strategic decision-making. This research develops a comprehensive transformation strategy for the budget planning system at the Directorate General of Sea Transportation, Ministry of Transportation, Indonesia. Using As-Is Analysis and Soft System Methodology (SSM), the study examines current system conditions and identifies transformation requirements. The analysis reveals critical challenges including the operation of three separate systems (E-Planning, KRISNA, and SAKTI) without integration protocols, dominance of manual processes in budget calculations for 302 work units, and absence of standardized digital infrastructure. Through SSM implementation, two conceptual models were developed addressing digital transformation and system integration requirements. Gap analysis between conceptual models and reality identified deficiencies across six dimensions: stakeholder engagement, system architecture, performance management, technical design, implementation strategy, and risk management. The research proposes Government Resource Planning (GRP) implementation through four integrated strategies: developing integrated system architecture with modular design principles, implementing organizational change management addressing human and institutional factors, establishing interoperability protocols for seamless data exchange, and creating comprehensive evaluation and risk mitigation frameworks. A phased implementation roadmap spanning 18 months provides a pragmatic approach to transformation. This research contributes to digital government literature by demonstrating the effectiveness of combining As-Is Analysis with SSM in addressing complex socio-technical challenges, while offering practical frameworks for government agencies pursuing similar transformations. The findings have significant implications for Indonesia's digital government initiatives and public sector modernization efforts.
Plant species identification based on leaf venation features using SVM Agus Ambarwari; Qadhli Jafar Adrian; Yeni Herdiyeni; Irman Hermadi
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 18, No 2: April 2020
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v18i2.14062

Abstract

The purpose of this study is to identify plant species using leaf venation features. Leaf venation features were obtained through the extraction of leaf venation features. The leaf image segmentation was performed to obtain the binary image of the leaf venation which is then determined the branching point and ending point. From these points, the extraction of leaf venation feature was performed by calculating the value of straightness, a different angle, length ratio, scale projection, skeleton length, number of segments, total skeleton length, number of branching points and number of ending points. So that from the extraction of leaf venation features 19 features were obtained. Identification of plant species was carried out using Support Vector Machine (SVM) with RBF kernel. The learning model was built using 75% of the training data. The testing results using 25% of the data on the training model, obtained an accuracy of 82.67%, with an average of precision of 84% and recall of 83%. 
Leadership Communication and Implications For Acceptance of The Go-Biz Application By MSMEs Employees (Case Study: Bogor District) Nadia Nur Soraya; Sarwititi Sarwoprasodjo; Irman Hermadi
Jurnal Aplikasi Bisnis dan Manajemen Vol. 10 No. 2 (2024): JABM, Vol. 10 No. 2, May 2024
Publisher : School of Business, Bogor Agricultural University (SB-IPB)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17358/jabm.10.2.423

Abstract

Background: Leaders of micro, small, and medium enterprises (MSMEs) have a role in the continuity of a business. Purpose: This research aims to examine the influence of leadership communication on the acceptance of the Go-Biz application by MSME employees in Bogor Regency. Design/methodology/approach: Research on acceptance of the Go-Biz application by MSME employees in Bogor Regency uses the Technology Acceptance Model theory modified by the Motivating Language Theory. This type of research is quantitative, using primary data. Research data was collected through structured interviews using questionnaires and direct field observations. The sampling technique is accidental sampling. The research population is 100 MSME employees who use the GoBiz application and are located in the Bogor Regency area. Inferential data analysis used PLS SEM 3 analysis.Findings/Result: The research results showed that the influence of leadership communication on the acceptance of Bogor Regency MSME employees in the Go-Biz application consisted of language giving direction, language making meaning, perception of usefulness, perception of ease, attitude of use, and actual use. Direction-giving language, namely explaining the benefits of the application, application instructions, and information on the achievements obtained, and meaning-making language consisting of telling the importance of the application and suggestions for use, are factors that influence the acceptance of the Go -Biz application by Bogor district MSME employees.Conclusion: Effective leadership in communication will help articulate the MSME vision and strategy regarding the development and implementation of application technology. This helps the entire team understand the direction the MSME is taking in terms of technology. Additionally, strong leadership through communication can motivate teams to accept new technologies and actively contribute to their development or use.Originality/value (State of the art): There has been no research that examines the influence of the three motivational languages (motivating language theory) that leaders can use to communicate more effectively in the workplace regrading employee acceptance of an application using the Technology Acceptance Model (TAM) theory. Keywords: leadership communication, motivational language theory, technology acceptance model, MSMEs (Micro, Small, and Medium Enterprises)
Development and Usability Testing of HemoGirl, an Android-Based Application for Anemia Education among Adolescent Girls Annisa Rizkiriani; Hadi Riyadi; Dodik Briawan; Irman Hermadi
Media Publikasi Promosi Kesehatan Indonesia Vol. 9 No. 7 (2026)
Publisher : Fakultas Kesehatan Masyarakat, Universitas Muhammadiyah Palu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56338/mppki.v9i7.10312

Abstract

Introduction: Mobile health applications represent an innovative strategy to strengthen health promotion by improving the accessibility and delivery of nutrition-related information, particularly anemia education among adolescent girls. Adolescence is a critical period characterized by increased nutritional demands and vulnerability to iron deficiency anemia, which can adversely affect growth, cognitive performance, and future reproductive health. Given the limitations of conventional educational approaches in engaging adolescents, interactive digital interventions have emerged as a promising alternative. Therefore, this study aimed to develop the HemoGirl mobile application and evaluate its preliminary usability and user acceptance among adolescent girls. Methods: This study employed a Research and Development design using the Waterfall model, encompassing requirement analysis, system design, development, testing, and maintenance. Usability testing was conducted among 61 first-year adolescent girls aged 17–19 years recruited through convenience sampling. Participants attended a supervised usability testing session lasting approximately 60 minutes, during which they used the HemoGirl application and completed predefined tasks before evaluating the system using the System Usability Scale (SUS). The SUS consists of 10 standardized items rated on a five-point Likert scale and assesses usability, ease of use, and user satisfaction. Results: The usability evaluation yielded a mean SUS score of 78 ± 12.7, indicating good usability and acceptable user satisfaction. Participants generally perceived the application as easy to learn, simple to navigate, and appropriate for accessing anemia-related educational content. These findings suggest that the HemoGirl prototype was well accepted by its intended users and met established usability standards. Conclusion: The HemoGirl mobile application demonstrated good usability and user acceptance among adolescent girls. As a prototype for anemia education and self-monitoring, the application shows promise as a digital health promotion tool. However, further longitudinal and experimental studies are required to evaluate its effectiveness in influencing knowledge, health behaviors, and anemia-related outcomes.
Time Series Forecasting of Environmental Dynamics in Urban Ecotourism Forest Using Deep Learning Ade Rahmat Iskandar; Arif Imam Suroso; Irman Hermadi; Lilik Budi Prasetyo
Journal of Applied Data Sciences Vol 7, No 1: January 2026
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v7i1.1029

Abstract

Time Series Forecasting of Environmental Dynamics in urban forests is quite challenging, unless new approaches such as deep learning and remote sensing are employed. Deep learning-based time series algorithms offer robust scientific capabilities for forecasting and assessing sustainability trends using sequential data. Among these, Long Short-Term Memory (LSTM), Gated Recurrent Unit (GRU), and Bidirectional LSTM (BiLSTM) have gained widespread adoption across various predictive modeling domains. In the present research, these algorithms are employed to analyze urban forest raster data derived from the Srengseng Ecotourism Forest, located in West Jakarta, Indonesia. The present study focuses on predicting the temporal patterns of key spatial indicators: Normalized Difference Vegetation Index (NDVI), Land Surface Temperature (LST), and Forest Cover Density (FCD) in the Srengseng urban ecotourism forest area, spanning the years 2014 to 2024, through the application of LSTM, GRU, and BiLSTM deep learning architectures. The methodology used in this study is a combined approach involving remote sensing and deep learning. Spatial data were acquired through the delineation of a high-precision polygon of Srengseng Urban Forest using Google Earth Pro and Google Earth Engine (GEE). GeoTIFF datasets of NDVI, LST, and FCD for the years 2014–2024 were processed using Python-based modeling scripts. Model performance was evaluated through a comparative analysis of LSTM, GRU, and BiLSTM in predicting temporal trends in these ecological indicators. The results of this study show that the Bidirectional LSTM (BiLSTM) consistently demonstrated superior performance to predict all the data spatially, with scores of 0.94 for NDVI, 0.90 for FCD, and 0.85 for LST. Followed by LSTM that predicts NDVI (0.87), FCD (0.89), LST (0.83), as well as GRU, which can estimate spatial data NDVI (0.86), FCD (0.89), and LST (0.85). These results outperformed the predictive accuracy of both the standard LSTM and GRU models.
Development of a protected birds identification system using a convolutional neural network IRMAN HERMADI; WULANDARI WULANDARI; DHANA DHIRA
Biodiversitas Journal of Biological Diversity Vol. 23 No. 5 (2022)
Publisher : Society for Indonesian Biodiversity

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.13057/biodiv/d230537

Abstract

Abstract. Hermadi I, Wulandari, Dhira D. 2022. Development of a protected birds identification system using a convolutional neural network. Biodiversitas 23: 2561-2569. The protected animals are the animals having small populations, a sharp decline in the number of individuals in the wild, or endemic. The government has banned owning, keeping, or trading these animals. The first step in conserving these animals is identification. The government of the Republic of Indonesia has defined 564 species of bird as protected. This issue becomes a challenge to bird species identification. This study aims to develop a web application that implements a convolutional neural network (CNN) model for image-based protected bird species identification. This study uses the images of ten protected bird species in Indonesia as the research subject. This study consists of the stages viz. data collection, data preprocessing, data splitting, CNN model development, model evaluation, and web development using the Prototyping method. This study has successfully developed a model that gained 97% accuracy, 98% precision, and 97% recall on testing data. The study utilized HTML, CSS, Javascript, and Tensorflow.js for Web development. The black-box testing result shows that the prototype is acceptable.
CUSTOMER ENGAGEMENT AS THE KEY DRIVER OF PURCHASE INTENTION IN SOCIAL MEDIA MARKETING Imaduddin, Iqbal; Hermadi, Irman; Munandar, Jono M
Jurnal Ilmiah Ilmu Terapan Universitas Jambi Vol. 10 No. 3 (2026): Volume 10, Nomor 3, June 2026
Publisher : LPPM Universitas Jambi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22437/jiituj.v10i3.55366

Abstract

This study examines the influence of Social Media Marketing Activities (SMMA) dimensions on Purchase Intention through Brand Equity and Customer Engagement among premium smartphone consumers. Therefore, this research aims to analyze the effects of Entertainment, Interaction, Trendiness, Electronic Word-of-Mouth (E-WOM), and Advertising on Brand Equity and Customer Engagement, as well as their implications for Purchase Intention. This study employed a quantitative cross-sectional design using purposive sampling. Data were collected from 175 iPhone users in the Greater Jakarta area through structured online questionnaires measured using a five-point Likert scale. Data analysis was conducted using Partial Least Squares Structural Equation Modeling (PLS-SEM) with SmartPLS 4.0. The results indicate that Interaction and E-WOM significantly influence both Brand Equity and Customer Engagement, while Entertainment, Trendiness, and Advertising show limited influence on Brand Equity. Furthermore, Customer Engagement demonstrates the strongest direct effect on Purchase Intention, exceeding the influence of Brand Equity. The mediation analysis also confirms that Customer Engagement acts as the dominant mediating variable in the relationship between SMMA and Purchase Intention.The novelty of this study lies in the introduction of the concept of Interactive Community-Based Brand Valuation, which emphasizes that brand value in digital environments is increasingly shaped through consumer interaction and engagement rather than conventional promotional activities. The findings imply that companies should shift their digital marketing strategies from content-oriented promotion toward engagement-driven communication and community interaction to enhance consumer purchase intention in highly competitive digital markets.
Co-Authors A.Muh.Yakin Amin Abdul Mufti Ade Hikma Tiana Ade Rahmat Iskandar Agus Ambarwari Agus Buono Agus Mulyana Agustian, Fajar Ahmad, Hafidlotul Fatimah Ahmad, Tarmizi Aji Fajar Nugraha Alfiansyah Halomoan Siregar Alfy Sukma Alvian Abdul Jabar Amalia Rahmawati Anak Agung Gede Sugianthara Anak Agung Istri Sri Wiadnyani Andi Irman Patiroi Anggraini Sukmawati Annisa Rizkiriani Annisa Saraswati Aprilianti, Dhila Arafat Febriandirza Arief Daryanto Arief Samad Arif Imam Suroso Arif Imam Suroso Aristi Imka Apniasari Aritonang, Melva Linda Arkeman, Yandra Astuti, Indah Puji Aulia Rahman Nasution Auzi Asfarian Aziz Kustiyo Barlianto, Agus Bayu Dewantoro Budhi Hascaryo Iskandar Cahyandaru, Paulus Chandra, Mohamad Citra, Suryati Oka Dani Saepuloh Daniel RO Monintja DHANA DHIRA Dodik Briawan Dyah Umiyarni Purnamasari Eddy Prasetyo Nugroho Elfrida Ratnawati Eneng Tita Tosida Eng Heru Sukoco Erizal Erliza Hambali Erus Effendi Erydhani, Gama Batara Esa Prakasa Euis Sunarti Euis Sunarti Euis Sunarti Fadhilah Bt Mat Yamin Fajar Agustian Fajar Delli Wihartiko Faqih Udin dan Jono M. Munandar Meivita Amelia Fatimah, Hilmi Azmi Faza Adhzima Feriadi Feriadi, Feriadi Firman Ardiansyah Fitroh Fitroh Guritno, Hanif Bagus Hadi Riyadi Hani Zulfia Zahro Hardhienata, Medria Hardhienata, Medria Kusuma Dewi Hari Agung Adrianto Hari Ryanto Wiyono Hasan Firdaus Hasanah , Nur Hatmoko, Bondan Dwi Heliza Rahmania Hatta, Heliza Rahmania Hendro Sasongko Heru Sukoco HUSNUL KHOTIMAH I Gusti Ngurah Antaryama Ibrahim, Firmansyah Ichwan Subekti Ikeu Tanziha Ikhlasul Amal Illah Sailah Imaduddin, Iqbal Imam Ahmad Imam W Sukoco Imas Sukaesih Sitanggang Indah Pratiwi Indah Puji Astuti Indah Yuliasih Indra Jaya Indra Kusuma Budiyanto , Firgiawan Indrajani Sutedja Intan Purnamasari Irfan Syauqi B. Irma Rosalina Irwansyah Saputra Irzal Effendi Iskandar, Teddy Ivanovich Agusta Jaman, Jajam Haerul Joko Ratono Joko Ratono Kahfi Heryandi Suradiradja Karlisa Priandana Kesuma, I Nyoman Rai Widartha Kikin H Mutaqin Kudang Boro Seminar Kudang Boro Seminar Lilik Budi Prasetyo Lilik Kustiyah Lufebrina Dorma Uli Manalu Luki Abdullah M. Syamsul Maarif M. Syamsul Ma’arif Maman Turjaman Marulitua, Michael Yakub Meidhianto Usman Meidhianto Usman Meuthia Rachmaniah Meuthia Rachmaniah Mochammad Imam Sulistyo Sarjowo Mohammad Mukhayadi Muhamad Ramdani, Risma Muhamad Syukur Muhammad Hadi Pranowo Muhammad Mukhlis Khoirudin Mukhlis Mukhlis Mulyono, Pudji Mustakim Mustakim Mustakim Mustakim Nadia Nur Soraya Nasution, Efrida Yanti Nia Kurniati Nimmi Zulbainarni Niqotaini, Zatin Noorlela Marcheta Novi Murdiyanti Nugraha Edhi Suyatma Nugroho, Arga Agung Nupin, Iswadi Syahrial Nur Arifin Akbar Nuryantika, Fitria Pradana, I Gusti Made Teddy Prasetyo Nugroho, Eddy Prayughi, Pungki Primasari, Angela Pudji Muljono Puput Irfansyah Putri Yuli Utami Qadhli Jafar Adrian R. Dikky Indrawan R. Rifa Herdian Raden Asri Ramadhina Fitriani Ramadhan, Dean Apriana Ramadhan, Jeri Rein Suadamara Rillya Arundaa Rina Trisminingsih Rinova Budiman Riyanto Rizal Broer Bahaweres Robi Priyadi RR. Ella Evrita Hestiandari Rudi Afnan Safuan Safuan Santi Santika Santi Santika, Santi Saputra, Irwansyah Sari, Dewi Intan Sarwititi Sarwoprasodjo Septianto, Yudhi Setyadi, Wawan Shelvie Nidya Neyman Sitanggang, Imas S. Siti Zubaidah Soewarto Hardhienata Sony Hartono Wijaya Sri Nurdiati Sri Wahjuni Subhan Deni Hermawan Sugi Guritman Sukarna Sukarna Suradiradja, Kahfi Heryandi Susy Katarina Sianturi Susy Katarina Sianturi Sutedja, Indrajani Suwanto Sanjaya Suyus Windayana Sylvia Taufik Djatna Teddy Iskandar Tendy Arya Pranata Thoyyibah Tanjung Tiana, Ade Hikma Tiurma Lumban Gaol Toto Haryanto Ufan Alfianto Ujang Sumarwan Usmany, Rendy Vidy Nalendra Wahjuni, Sri Widiatmaka Widiatmaka Wisnu Ananta K. Wisnu Ananta Kusuma WULANDARI WULANDARI Yamin, Fadhilah Bt Mat Yandra Arkeman Yani Nurhadryani Yani Nurhardryani Yanto Hermawan Yessy Yanitasari Yudhi Trisna Atmajaya Yuni Sugiarti Yuni Sugiarti Yuni Sugiarti Yuni Sugiarti, Yuni Yusmar, Addini Yusra Fernando Zenal Asikin