Article Per Year (5 Year)
p-Index From 2021 - 2026
7.258
P-Index
This Author published in this journals
All Journal IJCCS (Indonesian Journal of Computing and Cybernetics Systems) TELKOMNIKA (Telecommunication Computing Electronics and Control) JUITA : Jurnal Informatika Majalah Kedokteran Gigi Indonesia Scientific Journal of Informatics EXPOSURE JOURNAL Indonesian Journal of Science and Technology JEES (Journal of English Educators Society) JOIN (Jurnal Online Informatika) Sistemasi: Jurnal Sistem Informasi Jurnal ELTIKOM : Jurnal Teknik Elektro, Teknologi Informasi dan Komputer Jurnal Taman Vokasi UICELL Conference Proceeding SELAPARANG: Jurnal Pengabdian Masyarakat Berkemajuan IJEMS (Indonesian Journal of Environmental Management and Sustainability) ILKOM Jurnal Ilmiah Jiko (Jurnal Informatika dan komputer) MATRIK : Jurnal Manajemen, Teknik Informatika, dan Rekayasa Komputer PeTeKa NUSANTARA : Jurnal Ilmu Pengetahuan Sosial JURNAL PENDIDIKAN TAMBUSAI Jurnal Basicedu Journal on Education JURTEKSI Jurnal Pemberdayaan: Publikasi Hasil Pengabdian Kepada Masyarakat RESISTOR (Elektronika Kendali Telekomunikasi Tenaga Listrik Komputer) Indonesian Journal on Learning and Advanced Education (IJOLAE) JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Jurnal Pendidikan dan Konseling Jurnal Informatika dan Rekayasa Perangkat Lunak Jurnal Pengabdian Masyarakat Bumi Raflesia JATI (Jurnal Mahasiswa Teknik Informatika) Journal of Vocational Education Studies Jurnal Abdi Insani G-Tech : Jurnal Teknologi Terapan International Journal of Advances in Data and Information Systems Indonesian Journal of Computing, Engineering, and Design English Teaching and Linguistics Journal (ETLiJ) Indonesia Berdaya Journal Social Science And Technology For Community Service Sawala : Jurnal pengabdian Masyarakat Pembangunan Sosial, Desa dan Masyarakat Jurnal Pengabdian Masyarakat Indonesia Vocational : Jurnal Inovasi Pendidikan Kejuruan Jurnal Abdi Masyarakat Indonesia Mechanical Engineering for Society and Industry METAL : Jurnal Sistem Mekanik dan Termal Prosiding Seminar Nasional Pengabdian Kepada Masyarakat Jurnal Basicedu Scientific Journal of Informatics KUNKUN Journal of Multidisciplinary Research Scientific Journal of Engineering Research
Muhammad Kunta Biddinika
Universitas Ahmad Dahlan
Religion Aerospace Engineering Agriculture, Biological Sciences & Forestry Arts Humanities Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry 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 Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Nursing Public Health Social Sciences Transportation Veterinary Other

Published : 61 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 61 Documents
Search

 2   3   4   5   6 
LEARNING SPEAKING USING GOOGLE SITES-BASED EPORTFOLIO: INDONESIAN STUDENT’S EXPERIENCE Ali, Raden Muhammad; Hastuti, Dwi; Ananda, Anisa Rizki; Biddinika, Muhammad Kunta
EXPOSURE : JURNAL PENDIDIKAN BAHASA INGGRIS Vol 13, No 1 (2024): Exposure
Publisher : Universitas Muhammadiyah Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26618/exposure.v13i1.14384

Abstract

The purpose of this study is to offer insights into Indonesian students' experiences with using Google Sites-based ePortfolios to learn public speaking, particularly concerning setting objectives, selecting platforms, selecting content, and uploading their ePortfolio. This qualitative research data was gathered from twenty-two students who joined public speaking lesson at an English Language Education Study Program of a university in Yogyakarta, Indonesia, through interviews, observations, and documentation. In-depth interviews were conducted with six selected students of the class and a lecturer who supervised the course. Data analysis is carried out through the process data preparation, reduction and categorization, representation, and conclusion. The study's findings are as follows: first, while creating an ePortfolio, students desire to have a personal website that serves as a repository for all of their resources, assignments, and completed projects that are structured thoroughly, neatly, and conveniently online. Second, students use Google-Sites, as per the guidelines provided in class, to choose the platform. Students first faced several challenges. Students successfully developed their ePortfolio after learning from friends and instructions from various social media platforms.. Third, students get experience producing and publishing a variety of artifacts, including text, photos, audio, and video, while selecting content.. Four, students gain practice presenting their ePortfolio to instructors and fellow students and engaging in discussion about it when they publish one.
JAVANESE SCRIPT HANACARAKA CHARACTER PREDICTION WITH RESNET-18 ARCHITECTURE Sudewo, Egi Dio Bagus; Biddinika, Muhammad Kunta; Fadlil, Abdul
JURTEKSI (Jurnal Teknologi dan Sistem Informasi) Vol 10, No 2 (2024): Maret 2024
Publisher : STMIK Royal

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33330/jurteksi.v10i2.3017

Abstract

Abstract: This study aims to train computers to recognize Javanese script characters known as Hanacaraka. The evaluation was conducted on the use of Convolutional Neural Network (CNN) with the ResNet-18 architecture in recognizing these characters. The research objective is to overcome traditional character recognition barriers and improve accuracy. The method employed includes building a CNN model with the ResNet-18 architecture and using diverse datasets. The results show a training accuracy of 100%, validation accuracy of 98.01%, and accuracy, precision, recall, and F1-score each at 100%. This study concludes that the developed model successfully achieves a high level of accuracy and contributes positively to the development of Javanese Hanacaraka character recognition technology. Keywords: convolution neural network (CNN); javanese hanacaraka script; resnet-18           Abstrak: Penelitian ini bertujuan melatih komputer untuk mengenali huruf aksara Jawa Hanacaraka. Evaluasi dilakukan terhadap penggunaan Convolutional Neural Network (CNN) dengan arsitektur ResNet-18 dalam pengenalan karakter tersebut. Tujuan penelitian adalah mengatasi hambatan pengenalan karakter tradisional dan meningkatkan akurasi. Metode yang digunakan mencakup pembuatan model CNN dengan arsitektur ResNet-18 dan penggunaan dataset yang beragam. Hasilnya menunjukkan akurasi pelatihan 100%, validasi 98.01%, dan akurasi, presisi, recall, dan F1-score masing-masing sebesar 100%. Simpulan penelitian ini adalah bahwa model yang dikembangkan berhasil mencapai tingkat akurasi yang tinggi dan memberikan kontribusi positif pada pengembangan teknologi pengenalan karakter Hanacaraka Jawa.Kata kunci: convolution neural network (CNN); huruf aksara jawa hanacaraka; resnet-18 
Recalcitrant Industrial Wastewater Treatment Using Fenton and Photo-Fenton Oxidation: A Comparison Study Wijayanti, Karima Anggita; Hakika, Dhias Cahya; Setyawan, Martomo; Suhendra; Amal, Ikhlasul; Biddinika, Muhammad Kunta
Indonesian Journal of Environmental Management and Sustainability Vol. 8 No. 3 (2024): September
Publisher : Magister Program of Material Science, Graduate School of Universitas Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26554/ijems.2024.8.3.100-109

Abstract

The growth rate in agro-industrial sectors has both positive and negative effects on technological, social, and economic development. Agro-industry production generates substantial volumes of wastewater, primarily from the aqueous discharges of its manufacturing processes. Some of this wastewater contains harmful pollutants that endanger human life, health, and the sustainability of the environment and ecosystem. For example, wastewater from the bioethanol industry contains high concentrations of organic pollutants and recalcitrant compounds, with COD and BOD values exceeding 50,000 mg/L and 30,000 mg/L, respectively. The Fenton process is an oxidation method that generates hydroxyl radicals through the reaction between H2O2 and Fe2+ ions. These hydroxyl radicals are highly effective at breaking down recalcitrant compounds. In this study, a comparative analysis of recalcitrant wastewater treatment using Fenton and photo-Fenton oxidation processes was conducted. The effects of dilution factors, or initial concentrations of recalcitrant wastewater (1:25, 1:50, and 1:75), were examined. Higher dilution ratios enhanced the degradation of COD and BOD levels in wastewater, with the optimal dilution factor for both processes being 1:75. Under optimal conditions, the removal efficiencies for COD, BOD, potassium, and phenol were in the range of 72.29-99.99%. The photo-Fenton process demonstrated higher removal efficiency compared to the Fenton process. The conclusion from this study suggests that the photo-Fenton process could be successfully employed as an advanced treatment method for effectively breaking down recalcitrant wastewater. These findings could be useful for adapting these processes to field-scale applications.
Radial Basis Function Model for Obesity Classification Based on Lifestyle and Physical Condition Razak, Farhan Radhiansyah; Biddinika, Muhammad Kunta; Yuliansyah, Herman
Jurnal ELTIKOM : Jurnal Teknik Elektro, Teknologi Informasi dan Komputer Vol. 8 No. 2 (2024)
Publisher : P3M Politeknik Negeri Banjarmasin

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31961/eltikom.v8i2.1347

Abstract

Obesity is a chronic condition affecting millions worldwide, influenced by genetic predispositions, environmental factors, lifestyle habits, and excessive caloric intake surpassing energy expenditure. widespread prevalence, existing studies lack a comprehensive exploration of classification models that effectively address the complex interplay between lifestyle and physical attributes. This study tackles the absence of an optimal machine learning model for accurately classifying obesity based on these multifaceted factors. To address this gap, the study evaluates the performance of three machine learning algorithms: Support Vector Machine (SVM) with a Radial Basis Function (RBF) kernel, Naïve Bayes, and K-Nearest Neighbor (KNN). The primary objectives are to identify the most accurate classification approach, analyze the strengths of these algorithms, and highlight the importance of lifestyle and physical attributes in obesity prediction. Experimental findings show that SVM with RBF kernel achieves the highest accuracy at 89%, surpassing the performance of the other models. This study advances the field of obesity classification by offering a detailed comparative analysis of machine learning algorithms and underscoring the critical role of integrating lifestyle and physical factors into predictive modeling.
Electronic portfolio-based learning development training for Teachers of SMP Muhammadiyah 3 Yogyakarta Ali, Raden Muhammad; Hastuti, Dwi; Biddinika, Muhammad Kunta; Pamungkas , Rani Rahmawati; Alfaridhi, Dio Fahmi; Syahputra, Derly; Putri, Anggista Malya; Mbuo, Wilda; Nadia, Hafizhatu
Jurnal Pemberdayaan: Publikasi Hasil Pengabdian Kepada Masyarakat Vol. 8 No. 3 (2024)
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/jpm.v8i3.11611

Abstract

The world of education needs to keep up with the development of information technology in providing learning services for students. One of the tools that is currently widely known for its advantages and widely used in developed countries is the electronic portfolio. The background of this program is a problem that is often faced by schools, namely the lack of teacher competence in developing learning by utilizing electronic portfolios in teaching. SMP Muhammadiyah 3 Yogyakarta (SMP Muhammadiyah 3 Yogyakarta), as one of the private schools in Yogyakarta that has a high concern for the application of information technology in learning, in collaboration with the Community Service Team of Ahmad Dahlan University carried out an electronic portfolio-based learning development training which was attended by teachers of various subjects and education staff who served in various school service units. The objective of this activity is to improve teachers' understanding and skills by using electronic portfolios to support the realization of quality learning. The methods used are training and mentoring for teachers to develop electronic portfolio- based learning, improving internet infrastructure, and monitoring and evaluation. This training has resulted in an increase in the trainees' understanding of the concept of electronic portfolios and the improvement of participants' skills as shown by a total of 43 participants who have been able to develop their electronic portfolios. To ensure the implementation of electronic portfolios in schools, the Principal has decided that six classes with IT (Information Technology) specialization consisting of two learning groups from Grade 7, Grade 8, and Grade 9 will implement electronic portfolio-based learning. The impact of this training is that teachers have a positive mindset towards the use of information technology so that it further increases the opportunity for schools to improve the quality of learning in accordance with technological developments.
Special Job Exchange Strategies for Enhancing Graduate Employability in Vocational High Schools Center of Excellence in Yogyakarta and Central Java Suprap, Suprap; Sayuti, Muhammad; Santosa, Budi; Biddinika, Muhammad Kunta; Susanto, Harry Agus; Hasanah , Noviatun
Journal of Vocational Education Studies Vol. 7 No. 2 (2024): Vol.7 No.2 (2024)
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/joves.v7i2.11649

Abstract

This study aims to examine the strategy of the Special Job Exchange (BKK) of the Central Vocational Education Center of Excellence (SMK PK) in Yogyakarta and Central Java in increasing the absorption of graduates in the world of work. The research method used is qualitative descriptive with data collection techniques through interviews with the Principal and Chairman of BKK from 10 PK Vocational education selected through purposive sampling. Data analysis uses Miles and Huberman's interactive model with the help of NVIVO version 12 Plus software. The results of the study show that BKK's main strategy includes cooperation with industry, development of job preparation programs, strengthening students' soft skills and mentality, and the implementation of tracer studies. The challenges faced include students' interests and mentality that need to be improved, limited resources, data and communication management, program synchronization, expansion of industry networks, parental support, and improvement of the quality of graduates. This study concludes that BKK has an important role in increasing the absorption of vocational school graduates, but still faces various challenges that require a comprehensive and collaborative approach to overcome them.
Empowering Indonesian Vocational Students with Artificial Intelligence Awareness: Challenges and Career Opportunities Suyahman, Suyahman; Prayitno, Kintung; Pratama, Genta; Biddinika, Muhammad Kunta; Yudhana, Anton
Journal of Social Sciences and Technology for Community Service (JSSTCS) Vol 5, No 2 (2024): Volume 5, Nomor 2, September 2024
Publisher : Universitas Teknokrat Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33365/jsstcs.v5i2.4478

Abstract

Artificial intelligence (AI) has emerged as one of the most transformative and influential technological advancements, significantly impacting sectors like healthcare, finance, and education in the rapidly evolving digital era. However, vocational high school students often have limited knowledge about AI, primarily due to the superficial coverage of AI in their curriculum and the lack of resources and trained educators. This study aimed to assess the effectiveness of an intervention designed to enhance AI awareness and understanding among vocational high school students. A comprehensive program was implemented, involving initial assessments, interactive face-to-face training sessions, and facilitated group discussions. Descriptive analysis using statistical methods was employed to compare pretest and posttest data, revealing significant improvements in students' knowledge and attitudes towards AI. For example, the average score for the question "I know what Artificial Intelligence is" increased from 1.77 to 2.93, while "I can name an example of an AI application" rose from 1.76 to 2.85. Additionally, students showed increased awareness of AI's impact on future careers and a greater interest in learning more about AI, with scores rising from 2.20 to 2.85 and 2.48 to 2.96, respectively. The intervention proved effective in significantly enhancing students' understanding and attitudes towards AI, highlighting the value of targeted educational programs. By addressing gaps in AI education and fostering a proactive learning environment, the approach equips students with the knowledge and skills necessary to thrive in an AI-driven job market. This comprehensive strategy not only prepares students for future career challenges but also empowers them to leverage AI technology for career advancement.
Manajemen Kemitraan Sekolah dengan Dunia Industri pada Kompetensi Keahlian Teknik Instalasi Tenaga Listrik di Sekolah Menengah Kejuruan Muhammadiyah 1 Klaten Utara Gilang Isa Baskara; Tri Kuat; Muhammad Kunta Biddinika
Journal on Education Vol 7 No 1 (2024): Journal on Education: Volume 7 Nomor 1 Tahun 2024
Publisher : Departement of Mathematics Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/joe.v7i1.6962

Abstract

Partnerships between Vocational High Schools (SMK) and the industrial world are vital in improving the quality of education and competency of graduates, however the existence of school partnership management should be paid attention to by educational institutions. This research aims to describe partnership management, including planning, organizing, implementing, and evaluating partnerships between SMK Muhammadiyah 1 North Klaten with competency in electrical power installation engineering expertise and the industrial world. This research uses a qualitative approach, data is obtained by observation, interviews, and documentation. The research results show that overall the management of school partnerships with industry has gone well, including (1) partnership planning, the school has carried out situation analysis and problem identification by paying attention to school goals so that several strategies for achieving goals are obtained, one of which is the implementation of the guest teacher program; (2) organizing partnerships is carried out by determining resources and activities to achieve school goals, namely by determining priority programs (guest teacher program), distributing tasks and authority, and coordinating with partners; (3) the implementation of partnerships between schools and industry is carried out through several activities in the form of curriculum alignment, internships, guest teacher programs, entrepreneurship training, and workforce recruitment; (4) partnership evaluation is carried out by measuring the implementation or results achieved compared to standards, improving competencies in the curriculum, both internally and externally by involving the industrial world.
Human Digital Twin Modeling for Cardiovascular System Herman, Herman; Annafii, Moch. Nasheh; Kunta Biddinika, Muhammad; Fitriah, Fitriah
Scientific Journal of Informatics Vol. 12 No. 1: February 2025
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v11i4.16012

Abstract

Purpose: The cardiovascular system is a vital system responsible for the distribution of oxygen and nutrients throughout the body. The complexity of interactions between the heart and blood vessels often presents challenges in monitoring and analyzing health conditions. The research proposes the development of a Human Digital Twin (HDT) for the cardiovascular system through application of two different modelling approaches geometric modeling and physic-based modeling. Through this model physical conditions can be represented and real time data integrated to offer insights into the dynamics of the cardiovascular system. Methods: This model development is based on two major components: a geometric modeling and a physic-based modeling. The geometric model is done in 3D to show the structure of the heart in detail, while the physical-based model is tabulated with different measurable physical parameters in the cardiovascular system, such as blood pressure and flow rate. This information is integrated into the Five Dimension Digital Twin model, including physical, virtual, data, connection, and service dimensions for the accurate simulation of cardiovascular conditions. Result: Results confirm that the Five-Dimensional Digital Twin (DT) could give further development to how the dynamics of the cardiovascular system behave, possibly in real-time updates on conditions and a supply of data that is far more detailed in view of analyzing risk and further representation of specific cardiovascular disorders while providing personalized medical support. Novelty: The Five-Dimensional Human Digital Twin Model (HDTM) developed in this research introduces novel innovations in the monitoring and simulation of the cardiovascular system through the application of geometric and physic-based modeling techniques. This approach offers a higher level of detail, compared to previous models, and added value for the advancement of health technology by integrating real time data into the simulations. This model serves not only as an advanced analytical tool but also as a reference for further research on DT technology in the medical field.
Machine Learning Techniques for Heart Disease Prediction Using a Multi-Algorithm Approach Biddinika, Muhammad Kunta; Masitha, Alya; Herman, Herman; Fatimah, Vita Arfiana Nurul
JUITA: Jurnal Informatika JUITA Vol. 12 No. 2, November 2024
Publisher : Department of Informatics Engineering, Universitas Muhammadiyah Purwokerto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30595/juita.v12i2.24153

Abstract

This analysis explores the efficiency of machine learning systems for heart disease identification through a multi-algorithm approach. The main objective is to identify the best performing algorithm for accurate disease prediction, improving clinical decision making. Using criteria including accuracy, precision, recall, F1 score, and recall, the study assessed four algorithms: Random Forest (RF), Naïve Bayes (NB), Support Vector Machine (SVM), and Decision Tree (DT). The results show that Random Forest outperforms the others, achieving 86.23% precision, 93.76% recall, 89.84% F1 score, and 88.41% accuracy. Random Forest gets an AUC ROC result of 0.94, so Random Forest is considered a superior model in this scenario, especially because it has higher accuracy. The algorithms showed a strong balance between sensitivity and specificity. Decision Tree showed reasonable performance with a precision of 84.18% and a recall of 90.27%, while Naïve Bayes recorded a precision of 87.68% and a recall of 87.03%. SVM showed a precision of 87.40% and a recall of 84.78%, indicating some limitations in capturing positive cases. The novelty of this study lies in the comparative analysis of several algorithms to optimize the heart disease prediction model for clinical use. The random forest algorithm is one of the choices, but there is still a medical standard for classifying people as either indicating or not experiencing heart failure, according to the study.
Co-Authors Abdul Fadlil Abrar Ridwan Aditya Kolakoti Affan, Dhava Chairul Agus Aktawan, Agus Ahmad Azhari Ahmad Kafrawi Nasution Al Baqir, Mufaddal Aldri Frinaldi Alfaridhi, Dio Fahmi Alghiffari, Eka Kevin Ali, Raden Muhammad Aliyah Rasyid Baswedan Alper Calam Amalia, Nabilah Aminuyati Amrullah, Abdullathif Karim Ananda, Anisa Rizki Annafii, Moch. Nasheh Anton Yudhana Areeprasert, Chinnathan Asep Bayu Dani Nandiyanto Asep Setyaji Asih, Hayati Mukti Azwan, Hasnul B. A. Budiman Bakhtiyor Nakhshiniev Bambang Hariyadi Bella Okta Sari Miranda Budi Santosa Budi Santosa Caesar Irjayana, Rizky Dahlan, Bakrun Damayanti, Nunung Desi Lestari Dewi Soyusiawaty Dhias Cahya Hakika Dhias Cahya Hakika Diyah Puspitarini Dori Yuvenda Dwi Hastuti Edhy Susatya Edhy Susatya, Edhy Egi Dio Bagus Sudewo F. Triawan Fadliondi Fatimah, Vita Arfiana Nurul Febriyanto, Bayu Fitri Nur Mahmudah Fitri Nur Mahmudah Fitriah Fitriah Fitriah Fitriah Fumitake Takahashi Gilang Isa Baskara Hasanah , Noviatun Hasanah, Noviatun Herman Herman Herman Herman Herman Herman Yuliansyah, Herman Husna, Jannatul Ikhlasul Amal Imam Riadi Indryanto, Mokhamad Arif Iqwan Sanjani, Muhammad Irhash Ainur Rafiq Jogo Samodro, Maulana Muhamammad Junedi Haryanto Kamis, Arasinah Karima Anggita Wijayanti Kariyamin, Kariyamin Khaerati Syam, Ummi Khoirul Anam Dahlan Kintung Prayitno, Kintung Kurniasih, Indri Kusnadi, Andre Martomo Setyawan Martomo Setyawan Maulana Muhammad Jogo Samudro Maulana, Irvan Mbuo, Wilda Mochamad Syamsiro Muhajir Yunus Muhamad Agus Sriyono Muhamad Alwi Talib Muhammad Ali, Raden Muhammad Aziz Muhammad Eko Agung Nugroho Muhammad Fahmi Mubarok Nahdli Muhammad Sayuti Muji Setiyo Murinto Musfirah Nadia, Hafizhatu Narpaduita, Pamastu Nofikusumawati Peni, Nur Robiah Nor Azwadi Che Sidik Nur Mahmudah, Fitri Nur Makkie Perdana Kusuma Olusegun David Samuel Opwora, Meshack Pamungkas , Rani Rahmawati Peni, Nur Robiah Nofi Kusumawati Pratama, Genta Putri, Anggista Malya Putri, Vinanga Dentia Rahayu, Aster Razak, Farhan Radhiansyah Ridwan Abdurrahman Rofiah, Nurul Hidayati Rokhmah, Na'ilir S. Hanaoka Safitri, Anggi Satriya Dwi Putra Sayuti, Muhammad Setiawati, Nelly Setyawati, Nelly Sholihah, Mona Shun-ichiro Ohmi Sonny Abriantoro Wicaksono Srikandi Novianti Subekti, Dewi Ani Sugeng Santoso Sugianti, Ardina Fitri Suhendra Sunardi, Sunardi Suprap, Suprap Susanto, Harry Agus Suwanti Suwanti Syahputra, Derly Syahrani Lonang Syamsiar, Syamsiar Tri Kuat Tri Kuat, Tri Triawan, Farid Tristanti, Novi Tuessi Ari Purnomo Wadiyo Wadiyo Wijayanti, Karima Anggita Wiwik Handayani Yulianto, Dinan Yunisa, Fahmi Yuwantina, Anissa Zein, Wahid Alfaridsi Achmad