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All Journal International Journal of Electrical and Computer Engineering 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 PIKSEL : Penelitian Ilmu Komputer Sistem Embedded and Logic 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 Journal of Consumer Science 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 RESTI (Rekayasa Sistem dan Teknologi Informasi) Journal of Consumer Sciences 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 CYBERNETICS Petir Kwangsan: Jurnal Teknologi Pendidikan Jesya (Jurnal Ekonomi dan Ekonomi Syariah) Komputasi: Jurnal Ilmiah Ilmu Komputer dan Matematika Jurnal Sistem Cerdas EDUMATIC: Jurnal Pendidikan Informatika 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 Information Technology and Its Utilization 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 Jurnal Pustakawan Indonesia Jurnal Sistem Informasi Al-Kharaj: Jurnal Ekonomi, Keuangan & Bisnis Syariah Jurnal Sistem Informasi dan Aplikasi Journal of Information Technology and its Utilization
Irman Hermadi
Computer Science Study Program, IPB University, IPB Darmaga Campus, Bogor, 16680, Indonesia
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 Physics Public Health Social Sciences Transportation Other

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Grade Classification of Agarwood Sapwood Using Deep Learning Hatta, Heliza Rahmania; Nurdiati, Sri; Hermadi, Irman; Turjaman, Maman
JOIV : International Journal on Informatics Visualization Vol 8, No 4 (2024)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/joiv.8.4.2257

Abstract

The agarwood tree (Aquilaria sp.) is a tree that produces agarwood, which is a black resin that has a distinctive fragrant smell. In Indonesia, one that is commonly traded is sapwood agarwood. Agarwood sapwood is black or brownish-black wood obtained from the parts of the agarwood-producing tree containing a strong aromatic mastic. Based on the Indonesian National Standard (SNI) 7631:2018, agarwood sapwood has three classes: Super Double, Super A, and Super B. However, many agarwood farmers need to learn to differentiate and classify the agarwood sapwood classes, and traders exploit this to buy cheap. So, deep learning can be used to classify the agarwood sapwood class. One of the uses of deep learning is in image processing. Image processing is used to help humans recognize or classify objects quickly and precisely and can process many data simultaneously. One of the deep learning algorithms used in image processing is the Convolutional Neural Network (CNN). In this study, it is proposed that the deep learning model used is CNN with batch normalization. The dataset used is 72 agarwood sapwood images with a white background, each consisting of 24 Super A, 24 Super B data, and 24 Super Double data. The dataset is divided into 80% training and 20% testing data. The evaluation results of the proposed method at 100 epochs show an accuracy of 87.5%. The research implications will help agarwood tree farmers differentiate and classify agarwood sapwood so that farmers get the right price from buyers.
Implementasi Pengujian Otomatis dan Pengukuran Kualitas Website Employee Self-Service PT Asta Protek Jiarsi Aprilianti, Dhila; Hermadi, Irman
Journal Cerita: Creative Education of Research in Information Technology and Artificial Informatics Vol 11 No 1 (2025): Journal CERITA : Creative Education of Research in Information Technology and Ar
Publisher : UNIVERSITAS RAHARJA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/cerita.v11i1.3420

Abstract

Pengujian perangkat lunak menjadi sangat penting untuk memastikan operasi yang benar, sehingga memahami prinsip-prinsip dasar pengujian perangkat lunak serta teknik yang efektif sangat penting untuk menghasilkan perangkat lunak berkualitas tinggi. Otomatisasi pengujian membantu meningkatkan efisiensi, terutama dalam proyek yang kompleks dan memerlukan pemeliharaan serta pengujian yang berulang. Selain meningkatkan efisiensi, pengujian juga perlu dilakukan untuk mengukur kualitas perangkat lunak guna mencapai perangkat lunak yang berkualitas tinggi. PT Asta Protek Jiarsi telah membangun website Employee Self Service untuk memudahkan karyawan melakukan presensi, klaim medis, reimbursement, klaim lembur, dan menu lainnya. Metode McCall telah banyak digunakan untuk mengukur kualitas perangkat lunak. Beberapa penelitian sebelumnya menunjukkan bahwa penggunaan McCall dalam pengukuran kualitas perangkat lunak menghasilkan rekomendasi perbaikan yang berharga. Implementasi otomatisasi pada web Employee Self Service dan penerapan metode McCall dapat merinci karakteristik kualitas perangkat lunak seperti keandalan, efisiensi, dan pemeliharaan. Penerapan kriteria keberhasilan perangkat lunak McCall dengan pengujian otomatisasi memungkinkan identifikasi kelemahan dan kekuatan website Employee Self Service dengan lebih jelas, serta memungkinkan pengambilan tindakan yang diperlukan untuk perbaikan.
Long Short Term Memory-Based Marine Data Prediction with Pearson Correlation Mukhlis, Mukhlis; Jaya, Indra; Nurdiati, Sri; Priandana, Karlisa; Hermadi, Irman
PIKSEL : Penelitian Ilmu Komputer Sistem Embedded and Logic Vol. 13 No. 1 (2025): Maret 2025
Publisher : LPPM Universitas Islam 45 Bekasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33558/piksel.v13i1.10731

Abstract

Marine data prediction plays a vital role in supporting decision-making in the field of marine environment and resources. However, the complexity of marine data, which is nonlinear and dynamic, is a significant challenge in producing accurate predictions. This study aims to explore the role of Long Short-Term Memory (LSTM) models in computer systems to predict marine data, focusing on Pearson Correlation analysis. The methods applied include collecting historical marine data, implementing LSTM models for prediction, and evaluating performance using metrics such as Mean Absolute Error (MAE). In addition, Pearson Correlation analysis is used to understand the relationship between variables in marine data. The results show that the LSTM model is able to produce predictions with a low error rate with a composition of training data and testing data of 80:20, resulting in Sea Surface Temperature (SST) = 0.0053, Sea Surface Salinity (SSS) = 0.0026, sea Surface Height (SSH) = 0.0061 and CHL-a = 0.0002 and shows a significant relationship between variables through Multivariate correlation analysis. This research contributes to the development of marine data-based prediction systems and provides implications for the world of marine resource research and management.
Pemodelan Prediksi Perdagangan Satwa Liar Menggunakan Algoritma k-Nearest Neighbor Hermadi, Irman; Hardhienata, Medria; Primasari, Angela
Jurnal Ilmu Komputer dan Agri-Informatika Vol. 12 No. 1 (2025)
Publisher : Sekolah Sains Data, Matematika, dan Informatika. Institut Pertanian Bogor

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29244/jika.12.1.91-101

Abstract

Perdagangan satwa liar dengan pengawasan yang tidak optimal dapat merupakan salah satu ancaman yang mampu memberikan dampak signifikan bagi keberlangsungan keanekaragaman hayati. Beberapa spesies hewan seperti mamalia dan reptil saat ini terancam punah dengan adanya perdagangan satwa liar yang tidak terpantau dengan baik. Praktik perdagangan satwa liar kerap ditemukan di berbagai media, termasuk situs internet, karena kemudahan akses yang ditawarkan kepada masyarakat luas. Namun jika data tersebut diolah secara manual maka dibutuhkan waktu, tenaga, dan upaya yang cukup besar. Oleh sebab itu, dibutuhkan sebuah pendekatan berbasis kecerdasan buatan untuk mengidentifikasi wilayah dengan aktivitas perdangan satwa liar yang tinggi dan berpotensi melampai batas perdagangan satwa liar yang diizinkan. Penelitian ini bertujuan untuk membangun sebuah model yang dapat melakukan prediksi area yang rawan perdagangan satwa liar. Algoritma yang digunakan dalam penelitian ini adalah algoritma clustering K-Means untuk mengelompokkan wilayah berdasarkan tingkat kerawanan aktivitas perdagangan satwa liar, serta algoritma k-Nearest Neighbor untuk melakukan prediksi tingkat kerawanan wilayah perdagangan satwa liar. Selain itu, metode Market Basket Analysis digunakan untuk mengidentifikasi pola asosiasi dalam perdagangan satwa liar antar negara. Data yang digunakan merupakan data perdagangan satwa liar dari berbagai negara pada tahun 2018 hingga 2020. Dengan menggunakan pendekatan clustering, dalam penelitian ini diklasifikasikan tiga wilayah dengan potensi kerawanan perdagangan satwa liar, yaitu wilayah dengan resiko rendah, sedang, dan tinggi. Hasil penelitian menunjukkan bahwa model prediksi yang dibangun mampu memprediksi wilayah rawan perdagangan satwa liar dengan tingkat akurasi model training sebesar 99% dengan data impor dan 100% dengan data ekspor. Setelah dievaluasi dengan 3-cross fold validation, akurasi model yang diperoleh adalah sebesar 97% untuk data impor dan 98% untuk data ekspor. Hasil akurasi model testing dalam penelitian ini adalah sebesar 100% dengan data impor maupun ekspor. Melalui pendekatan metode market basket analysis, penelitian ini menyimpulkan dengan data yang dipertimbangkan belum ditemukan pola asosiasi yang kuat dalam aktivitas perdagangan satwa liar antara satu negara spesifik dengan negara lainnya.
Pengembangan Modul Front-End KMS Desa Digital untuk meningkatkan adopsi Inovasi Digital pada Desa di Indonesia Nuryantika, Fitria; Hermadi, Irman; Ahmad, Hafidlotul Fatimah; Nurhadryani, Yani
Jurnal Ilmu Komputer dan Agri-Informatika Vol. 12 No. 1 (2025)
Publisher : Sekolah Sains Data, Matematika, dan Informatika. Institut Pertanian Bogor

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29244/jika.12.1.72-78

Abstract

Indonesia memiliki jumlah desa yang sangat besar, yaitu sebanyak 83.794 desa, sehingga transformasi digital memegang peranan penting dalam meningkatkan kesejahteraan masyarakat pedesaan. Desa digital adalah desa yang menerapkan teknologi informasi untuk mendorong efisiensi pelayanan publik, penguatan ekonomi masyarakat desa, serta peningkatan kualitas hidup masyarakat desa. Namun, rendahnya literasi digital dan terbatasnya kapasitas sumber daya manusia masih menjadi kendala dalam implementasi desa digital. Penelitian sebelumnya yang bekerja sama dengan FAO pada program Digital Village Initiative (2023) telah menghimpun data melalui pendekatan etnografi terhadap 160 desa digital dan 100 inovasi digital yang dikategorikan dalam 10 kelompok, seperti Agri-Food Marketing and E-commerce, E-Government, Smart Farming, dan Social Service. Sayangnya, informasi desa digital saat ini tersebar secara tidak terstruktur sehingga sulit diakses dan dimanfaatkan oleh desa lain. Penelitian ini bertujuan mengembangkan platform Knowledge Management System (KMS) desa digital menggunakan pendekatan Prototyping melalui tahapan komunikasi, perencanaan cepat, desain, pembuatan prototipe, dan evaluasi. KMS ini ditujukan bagi inovator, perangkat desa, dan masyarakat desa, serta dapat diakses secara publik. Modul yang dikembangkan memuat informasi inovasi digital dalam 10 kategori beserta deskripsinya, profil inovator, profil desa digital, serta fitur asesmen kesiapan digital desa. Hasil ini diharapkan dapat mempercepat diseminasi pengetahuan dan adopsi inovasi digital antar desa di Indonesia.
Price Prediction of Aglaonema Ornamental Plants Using the Long Short-Term Memory (LSTM) Algorithm Sugiarti, Yuni; Suroso, Arif Imam; Hermadi, Irman; Sunarti, Euis; Yamin, Fadhilah Bt Mat
Journal of Applied Data Sciences Vol 6, No 2: MAY 2025
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v6i2.640

Abstract

The Aglaonema ornamental plant is a horticultural commodity with high economic value and promising prospects. It is well known for its attractive leaf variations, earning it the nickname "Queen of Leaves." However, unpredictable price fluctuations make investing in Aglaonema speculative and high-risk. This research aims to predict the price of Aglaonema over the next five years using the Long Short-Term Memory (LSTM) algorithm. LSTM is considered superior to other algorithms in handling time series data. The model's performance was evaluated using Mean Squared Error (MSE), Root Mean Squared Error (RMSE), and Mean Absolute Error (MAE) on a weekly Aglaonema price dataset covering the period from January 2012 to December 2023. The results demonstrate that the LSTM algorithm can predict Aglaonema prices with high accuracy, as indicated by the following metrics: MSE: 0.005 – Represents the average squared difference between predicted and actual prices. A lower MSE indicates higher model accuracy. RMSE: 0.07-RMSE provides a more interpretable error measurement as it retains the same units as the original data. A low RMSE signifies that the model's predictions closely align with actual values. MAE: 0.04 – Measures the absolute average difference between predicted and actual prices. A lower MAE value reflects a smaller prediction error. Thus, this research makes a significant contribution to the development of a machine learning-based price prediction system for the ornamental plant industry.
Challenges of Implementing Knowledge Management Systems in Agribusiness for Aglaonema Farmers Sugiarti, Yuni; Suroso, Arif Imam; Hermadi, Irman; Sunarti, Euis; Yamin, Fadhilah Bt Mat
Applied Information System and Management (AISM) Vol 8, No 1 (2025): Applied Information System and Management (AISM)
Publisher : Depart. of Information Systems, FST, UIN Syarif Hidayatullah Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15408/aism.v8i1.44074

Abstract

Aglaonema plants have become an important element in people's lives, serving as home decorations and sources of income. Aglaonema cultivation is increasingly popular, opening up business opportunities for farmers. This plant is not just a hobby but a horticultural commodity with high economic value. This research aims to analyze the difficulties faced by Aglaonema farmers, from seedling to marketing. This research uses a constructivist paradigm and qualitative methods, involving 20 informants from among farmers, traders, buyers, extension workers, and farmer organizations. Data were collected through interviews, focus group discussions, and observations, with triangulation to validate the information. Data analysis was conducted using the NVivo application. The research results show that the main difficulties faced by Aglaonema farmers include unpredictable price fluctuations, limited varieties, weak communication among farmers, traditional seedling methods, and a lack of information about seed supply. These findings emphasize the need for information sharing between farmers and stakeholders to improve productivity and quality in agribusiness, in line with consumer demands and technological advancements, which can be implemented through a knowledge management system platform in the Aglaonema agribusiness supply chain.
ENTERPRISE ARCHITECTURE APPROACHMENT FOR DESIGNING IT MASTER PLAN BASED ON ERP FOR WATER UTILITY COMPANY Fatimah, Hilmi Azmi; Hermadi, Irman; Nurhadryani, Yani
Jurnal Aplikasi Manajemen Vol. 17 No. 2 (2019)
Publisher : Universitas Brawijaya, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21776/ub.jam.2019.017.02.17

Abstract

A comprehensive planning document that is written in the IT Master Plan has the purpose of addressing the company's need and guiding the implementation process to minimize failure. But many IT master plan was not based on integrated and best practice adoption using ERP. The development of the IT master plan also does not use the proper enterprise architecture (EA) method. This research designed an IT master plan based on ERP using Enterprise Architecture approachment for water utility companies and adopt ERP best practice references model. The Enterprise Architecture's method was TOGAF ADM from a prelim phase, requirement management phase, vision architecture phase, business architecture phase, and information system architecture phase. This research gave the results of 23 system recommendations named IT Integrated Solution for water utility companies which consist of 10 integrated applications, 8 ERP modules, and 5 ERP Industry Solution-Utility (IS-U) modules. To get a comprehensive IT Master Plan based on ERP, the water company needs to pay attention to other stages of TOGAF ADM. There needs to be a study to be able to validate the IT Master Plan, which has been developed.
Comparative Study on the Implementation of Knowledge Management Systems for Aglaonema Farmers: A Structured Method and UML Object Approach Sugiarti, Yuni; Suroso, Arif Imam; Hermadi, Irman; Sunarti, Euis
International Journal of Engineering, Science and Information Technology Vol 5, No 3 (2025)
Publisher : Malikussaleh University, Aceh, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52088/ijesty.v5i3.953

Abstract

Aglaonema farming holds significant economic potential, but challenges in knowledge management often hinder farmers' productivity. Knowledge Management Systems (KMS) provide effective solutions for managing knowledge efficiently. This study aims to conduct a comparative analysis of KMS implementation for aglaonema farmers using a structured method and an object-oriented method with the Unified Modeling Language (UML). The research methodology includes identifying farmers' needs, developing systems using both approaches, conducting functionality testing, and performing a comparative analysis based on effectiveness, efficiency, and ease of use. The study's results indicate that the object-oriented approach with UML offers greater flexibility in development and adaptation to changing user needs. At the same time, the structured method provides stability within a well-defined system. User evaluations reveal a preference for UML-based systems, particularly in supporting dynamic knowledge access and integrating market price prediction features. The study concludes that the object-oriented approach with UML is more suitable for KMS development in agribusiness, where an adaptive and responsive system is essential.
Optimasi Kinerja Operasional Terminal Petikemas Berdasarkan Handling Capacity (Studi Kasus Terminal Petikemas Koja Tanjung Priok) Cahyandaru, Paulus; Iskandar, Budhi Hascaryo; Hermadi, Irman; Safuan, Safuan
Jesya (Jurnal Ekonomi dan Ekonomi Syariah) Vol 8 No 2 (2025): Artikel Riset Juli 2025
Publisher : LPPM Sekolah Tinggi Ilmu Ekonomi Al-Washliyah Sibolga

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36778/jesya.v8i2.2165

Abstract

Pelabuhan merupakan simpul penting dalam sistem logistik nasional. Namun, kinerja operasional pelabuhan di Indonesia masih belum optimal, yang berdampak pada tingginya biaya logistik. Penelitian ini bertujuan untuk mengoptimalkan kinerja operasional Terminal Petikemas Koja di Pelabuhan Tanjung Priok dengan pendekatan handling capacity. Fokus utama penelitian adalah pelayanan kapal, khususnya kecepatan bongkar muat yang dipengaruhi oleh penggunaan alat bongkar muat seperti Quay Container Crane (QCC), Rubber Tyred Gantry Crane (RTG), dan Head Truck(HT). Analisis dilakukan dengan mengumpulkan data operasional dari Terminal Operation System selama periode 2020–2024, dan dilakukan simulasi regresi linear berganda serta optimasi menggunakan metode linear programming untuk menentukan komposisi alat yang paling efisien. Hasil penelitian menunjukkan bahwa komposisi optimal untuk mencapai Vessel Operating Rate (VOR) tertinggi adalah 5 QCC, 17 RTG, dan 42 HT. Model regresi yang dihasilkan menunjukkan bahwa peningkatan VOR berkontribusi signifikan dalam menurunkan waktu kerja dermaga (Berth Working Time/BWT), yang berdampak langsung pada pengurangan biaya tambat kapal. Penelitian ini memberikan rekomendasi strategis untuk pengelolaan fasilitas terminal secara optimal demi mendukung efisiensi logistik nasional.
Co-Authors A.Muh.Yakin Amin Abdul Mufti 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 Saraswati Aprilianti, Dhila 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 Auzi Asfarian Aziz Kustiyo Barlianto, Agus Bayu Dewantoro Budhi Hascaryo Iskandar Cahyandaru, Paulus Chandra, Mohamad Citra, Suryati Oka Daniel RO Monintja Dean Apriana Ramadhan Dodik Briawan Dyah Umiyarni Purnamasari Eddy Prasetyo Nugroho Elfrida Ratnawati Eneng Tita Tosida Erizal , Erliza Hambali Erus Effendi Erydhani, Gama Batara Euis Sunarti Euis Sunarti Fajar Agustian Fajar Delli Wihartiko FAJAR NUGROHO Fatimah, Hilmi Azmi Faza Adhzima Feriadi Feriadi, Feriadi Firman Ardiansyah Guritno, Hanif Bagus Hani Zulfia Zahro Hardhienata, Medria Hardhienata, Medria Kusuma Dewi Hasan Firdaus Hasanah , Nur Hatmoko, Bondan Dwi Heliza Rahmania Hatta, Heliza Rahmania Hendro Sasongko Heru Sukoco HUSNUL KHOTIMAH I Gusti Ngurah Antaryama Ibrahim, Firmansyah Ikeu Tanziha Illah Sailah Imam Ahmad Imam W Sukoco Imas Sukaesih Sitanggang Indah Pratiwi Indah Puji Astuti Indah Yuliasih Indra Jaya 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 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 Mohammad Mukhayadi Muhamad Ramdani, Risma Muhamad Syukur Mukhlis Mukhlis Mulyono, Pudji Mustakim Mustakim Mustakim Mustakim Nasution, Efrida Yanti Nia Kurniati Nimmi Zulbainarni Noorlela Marcheta Novi Murdiyanti Nugraha Edhi Suyatma Nugroho, Arga Agung Nupin, Iswadi Syahrial Nur Arifin Akbar Nurhardryani, Yani 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. Rifa Herdian Raden Asri Ramadhina Fitriani Ramadhan, Jeri Rein Suadamara Rillya Arundaa 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 Septianto, Yudhi Setyadi, Wawan Shelvie Nidya Neyman Sitanggang, Imas S. Siti Zubaidah Soewarto Hardhienata Sony Hartono Wijaya Soraya, Nadia Nur Sri Nurdiati Sri Wahjuni Subhan Deni Hermawan 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 Vidy Nalendra Wahjuni, Sri Widiatmaka Wisnu Ananta K. Wisnu Ananta Kusuma Yamin, Fadhilah Bt Mat Yandra Arkeman Yandra Arkeman Yani Nurhadryani Yanto Hermawan Yessy Yanitasari Yudhi Trisna Atmajaya Yuni Sugiarti Yuni Sugiarti, Yuni Yusmar, Addini Yusra Fernando Zenal Asikin