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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) International Journal of Advances in Applied Sciences Media Kesehatan Masyarakat Indonesia BERKALA FISIKA MATEMATIKA SAINS DAN MATEMATIKA JURNAL SISTEM INFORMASI BISNIS YOUNGSTER PHYSICS JOURNAL Jurnal Sistem Komputer Telematika : Jurnal Informatika dan Teknologi Informasi Speed - Sentra Penelitian Engineering dan Edukasi Jurnal Teknologi Informasi dan Ilmu Komputer Jurnas Nasional Teknologi dan Sistem Informasi Jurnal Imejing Diagnostik Register: Jurnal Ilmiah Teknologi Sistem Informasi Jurnal Manajemen Kesehatan Indonesia Jurnal Teknologi dan Sistem Komputer Informatika Mulawarman: Jurnal Ilmiah Ilmu Komputer Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Journal Of Vocational Health Studies Jurnal Penelitian Pendidikan IPA (JPPIPA) Syntax Literate: Jurnal Ilmiah Indonesia Jurnal Teknoinfo Journal of Physics and Its Applications Jurnal Sisfokom (Sistem Informasi dan Komputer) JURTEKSI Unnes Journal of Public Health Jurnal Komunika : Jurnal Komunikasi, Media dan Informatika JARES (Journal of Academic Research and Sciences) Jurnal Manajemen Informasi Kesehatan Indonesia (JMIKI) Journal of Electronics, Electromedical Engineering, and Medical Informatics Journal of Information Systems and Informatics Jurnal Teknik Elektro dan Komputasi (ELKOM) Indonesian Journal of Electrical Engineering and Computer Science Jurnal Aisyah : Jurnal Ilmu Kesehatan Budapest International Research and Critics Institute-Journal (BIRCI-Journal): Humanities and Social Sciences Media Publikasi Promosi Kesehatan Indonesia (MPPKI) Jurnal Multidisiplin Madani (MUDIMA) East Asian Journal of Multidisciplinary Research (EAJMR) Jurnal Nasional Teknik Elektro dan Teknologi Informasi Prisma Sains: Jurnal Pengkajian Ilmu dan Pembelajaran Matematika dan IPA IKIP Mataram Makara Journal of Technology International Journal Of Health And Social Behavior
Kusworo Adi
Jurusan Fisika, Fakultas Sains Dan Matematika, Universitas Diponegoro Jl. Prof. Soedharto, SH., Tembalang, Semarang, Jawa Tengah
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Implementasi Metode Gray Level Co-occurrence Matrix dalam Identifikasi Jenis Daun Tengkawang Rahmat Robi Waliyansyah; Kusworo Adi; Jatmiko Endor Suseno
Jurnal Nasional Teknik Elektro dan Teknologi Informasi Vol 7 No 1: Februari 2018
Publisher : Departemen Teknik Elektro dan Teknologi Informasi, Fakultas Teknik, Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1139.589 KB)

Abstract

Tengkawang or known as Borneo tallow nut is now difficult to find due to unsustainable forestry practices and high levels of forest destruction. The method used in this research was pattern recognition. The process of identifying Tengkawang plants was carried out through this process: image acquisition, image cutting and background removal of tengkawang leaf image, RGB image conversion of tengkawang leaf into gray scale, threshold limit determination with certain value, feature extraction with GLCM method (spatial distance 1, 2, and 3 pixels), and morphology, so the pattern of Tengkawang leaf image could be obtained. The image pattern was classified using Back Propagation Neural Network algorithm. The output is a software for identifying the types of tengkawang leaf. The results of identification testing of non-tengkawang leaf species show that using a total of 16 random samples of test images, an accuracy of 87.5% is obtained. The identification rate of tengkawang leaf image with spatial distance of 1, 2, and 3 pixels from total 24 random sample of test image shows 100% accuracy level. Training with 2 pixel spatial spacing has the lowest iteration, i.e. 10 iterations. The result of identifying damaged tengkawang leaf image on the edge has an effect on the extraction of morphological characteristics.
Chicken tracking for location mapping of lameness chickens using YOLOv8 and deep learning-based tracking algorithm Wiwit Agus Triyanto; Kusworo Adi; Jatmiko Endro Suseno
Indonesian Journal of Electrical Engineering and Computer Science Vol 34, No 1: April 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v34.i1.pp407-418

Abstract

The chicken farming industry is one of the biggest food industries that supports the achievement of food security internationally. Farmers need an independent tool that can monitor the welfare conditions of chickens in cages. Using their tools, farmers can ideally detect the condition of chickens. Lameness chickens, can be known for activity and dredging of their location in the cage. Occlusion, and background in the cage are interesting challenges. By observing behavior, image handling practices can be used to identify tainted chicks and provide an early warning of sickness in chickens. In this study, you only look once, version 8 (YOLOv8) which is a convolutional neural network (CNN) network model was chosen to perform the detection, tracking, and mapping of chicken locations. YOLOv8 was combined with various algorithm optimizers to improve training performance, such as root mean square (RMS) Prop, stochastic gradient descent (SGD), ADAM, and ADAMW. Multi-object tracking algorithms such as BOT-sort and ByteTrack are also used to improve tracking performance. Based on the results, YOLOv8 with combinations of optimizer algorithms ADAMW has the best mAP, support, precision and F1-score values compared to the others, with 0.936, 0.993, 0.990, 0.991. Meanwhile, for multi object tracking, ByteTrack is faster in inference time(s) values compared to the others, with 0.2.
Management Information Systems in Decision Making: Narrative Review Natalia Kristiani; Kusworo Adi; Apoina Kartini
Jurnal Aisyah : Jurnal Ilmu Kesehatan Vol 6, No 3: September 2021
Publisher : Universitas Aisyah Pringsewu

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (654.33 KB) | DOI: 10.30604/jika.v6i3.989

Abstract

Management has a role in generating information, which requires the use of information systems capable of producing relevant and better data. Systematic decision-making procedures are also needed to produce more focused data. In making decisions for hospital development, hospital management considers several factors, including health programs by looking at facilities and specialist doctors who can provide excellent service, as well as efforts with good numbers and services to introduce or convince the public of our services. general, company, and insurance This research uses a narrative review approach, with many articles on the same problem. Articles are taken from a database from Scopus, Science Direct, ProQuest, SpringerLink, Google Scholar, Nature, JSTOR, and Emerald Insight with a total of 29 articles used. The purpose of this study is to determine whether management has a significant influence in decision making. decisions in hospitals with strategic support systems such as human resource development, program selection, marketing, and facility growth.  Abstrak: Manajemen memiliki peranan dalam menghasilkan informasi, yang mengharuskan penggunaan sistem informasi yang mampu menghasilkan data yang relevan dan lebih baik. Prosedur pengambilan keputusan yang sistematis juga diperlukan untuk menghasilkan data yang lebih terfokus. Dalam mengambil keputusan untuk pengembangan rumah sakit, manajemen rumah sakit mempertimbangkan beberapa faktor, antara lain program kesehatan dengan melihat fasilitas dan dokter spesialis yang dapat memberikan pelayanan prima, serta usaha dengan jumlah dan pelayanan yang baik untuk memperkenalkan atau meyakinkan masyarakat akan pelayanan kami. umum, perusahaan, dan asuransi Penelitian ini menggunakan pendekatan narrative review, dengan banyak artikel tentang masalah yang sama. Artikel diambil dari data base yang berasal dari scopus, science direct, ProQuest, SpringerLink, Google Scholar, Nature, JSTOR, dan Emerald Insight dengan total artikel yang digunakan sebanyak 29. Tujuan dari penelitian ini adalah untuk mengetahui apakah manajemen memiliki pengaruh yang signifikan dalam pengambilan keputusan di rumah sakit dengan sistem pendukung strategis seperti pengembangan sumber daya manusia, pemilihan program, pemasaran, dan pertumbuhan fasilitas.
Evaluasi Sistem Informasi Manajemen Puskesmas menggunakan Model HOT-Fit Delfia, Fila; Adi, Kusworo; Purnami, Cahya Tri
Jurnal Teknologi dan Sistem Komputer Volume 10, Issue 2, Year 2022 (April 2022)
Publisher : Department of Computer Engineering, Engineering Faculty, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/jtsiskom.2022.14418

Abstract

Penelitian ini mengevaluasi salah satu sistem informasi di bidang kesehatan yaitu sistem informasi manajemen Puskesmas dengan menggunakan model HOT-Fit. Metode HOT-Fit dipilih karena memberikan interpretasi penilaian yang komprehensif melalui pendekatan terhadap komponen inti suatu sistem informasi. Metode HOT-Fit mencakup: Manusia (Pengguna Sistem dan Kepuasan Pengguna), Organisasi (Struktur Organisasi dan Lingkungan Organisasi), Teknologi (Kualitas Sistem, Kualitas Informasi, dan Kualitas Layanan), serta Manfaat. Hasil penelitian menunjukkan bahwa terdapat pengaruh yang signifikan antara faktor Manusia dengan Manfaat (Sig. 0,014; Odds ratio 11,075 yang berarti faktor Manusia akan meningkatkan faktor Manfaat SIMPUS sebanyak 11,075 kali lebih tinggi). Tidak ada pengaruh yang signifikan antara Organisasi dengan Manfaat (Sig. 0,267). Tidak ada pengaruh yang signifikan antara Teknologi dengan Manfaat (Sig. 0,753).
Enhanced you only look once approach for automatic phytoplankton identification Wisnu Ardhi, Ovide Decroly; Retnaningsih Soeprobowati, Tri; Adi, Kusworo; Prakasa, Esa; Rachman, Arief
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 13, No 3: September 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v13.i3.pp3426-3436

Abstract

Conventionally, identifying phytoplankton species is challenging due to human taxonomical knowledge limitations. Advanced technology can overcome this problem. A novel model that accurately enhances phytoplankton detection and identification classification by combining asymmetric convolution and vision transformers (ACVIT) within the YOLOv8m framework is promoted with ACVIT-YOLO. The performance of this model surpasses the original YOLOv8m model, exhibiting a notable 2.4% enhancement in precision, 5.5% improvement in recall, and 1.1% gain in mAP 50 score. The enhanced effectiveness of ACVIT-YOLO compared to the YOLOv8m model, further demonstrated by the decreased giga floating-point operations (GFLOP), decreased parameter count, and compact dimensions, significantly improves the automation of phytoplankton species identification. This suggests that the ACVIT-YOLO model could produce a better prediction system for identifying phytoplankton with similar accuracy to the original YOLOv8m model but with lower computational power and resource usage.
Development of a Surveilens System as a Means for Collection and Reporting of Infectious Diseases in Puskodono Health Center, Sragen Sari, Kiki Puspita; Adi, Kusworo; Agushybana, Farid
Journal of Electronics, Electromedical Engineering, and Medical Informatics Vol 5 No 4 (2023): October
Publisher : Department of Electromedical Engineering, POLTEKKES KEMENKES SURABAYA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35882/jeeemi.v5i4.317

Abstract

Surveillance is an important activity in the context of disease data collection. The results of these surveillance activities can also be used as a consideration for making decisions related to disease management, especially infectious diseases. The aim of the research was to develop an information system for surveillance of infectious diseases for data collection and reporting to support management decision making at the Sukodono Health Center, Sragen.This research method is qualitative and quantitative. Prototype model research development. The research population is all parties involved in the development of an Infectious Disease Management Information System at the Sukodono Health Center, Sragen. The subjects of this study were the Head of the Community Health Center, the Head of the Infectious Diseases Program and the four Communicable Diseases Program Holders. the research object is the Communicable Disease Health Center Management Information System. This research method is qualitative and quantitative. Prototype model research development. The subjects of this study were one head of the health center, one head of the infectious disease program and four holders of the infectious disease program. the research object is the Communicable Disease Health Center Management Information System. Data analysis in this study was carried out by means of content analysis for qualitative and descriptive analysis methods for quantitative. The acquisition of the evaluation results from the total average percentage is Accurate at (62.19%), Complete at (83.89%), timeliness (84.44%), and Relevant at (95.20%). Meanwhile, in terms of data accuracy (accuracy) and completeness of content or data availability (content), information system users are very satisfied, as indicated by the results of the total average percentage of both 80.36 and 99.36% indicating that the user is very confident in the completeness and correctness of the examination data that has been inputted into the information system by paramedics. The results of the evaluation of the information system as a whole are 81.43%, meaning that the Information System for Surveillance of Communicable Diseases can be received and used by users of the information system very well
COMPARISON MEASUREMENT AND CALCULATION OF BRAIN TUMOR IN MRI MODALITIES UTILISING SPIN-ECHO PULSE SEQUENCE T1-WEIGHTED CONTRAST AND DIGITAL IMAGE PROCESSING APPLICATIONS Putri, Maizza Nadia; Kusworo Adi; M.Irwan Katili; Sidin Hariyanto; Dwi Rochmayanti
Journal of Vocational Health Studies Vol. 6 No. 2 (2022): November 2022 | JOURNAL OF VOCATIONAL HEALTH STUDIES
Publisher : Faculty of Vocational Studies, Universitas Airlangga

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20473/jvhs.V6.I2.2022.151-157

Abstract

Background: Evaluation of brain tumor MRI image results performed by radiologists employing the linear measurement method has several weaknesses and is sensitive to subjectivity. Purpose: To compare the results of measurements and calculations of brain tumors utilizing the linear measurement method on the Siemens 1.5 Tesla MRI modality employing pulse sequence spin echo with T1 contrast weighting compared with the results of measurements and calculations of brain tumors utilizing the active contour segmentation method. Method: An experimental study was conducted on 32 MRI images. Result: The study's findings indicated that the linear measurement was more significant than the active contour segmentation method (p-value<0,05). The results were obtained by calculating the sensitivity and specificity values of the diagnostic test, which were calculated to be 87.5%. Conclusion: The active contour segmentation method applied to pulse sequence spin-echo T1-weighted contrast can be utilized as an alternative measurement and calculation of brain tumors with a sensitivity and specificity value of 87.5%. Further research suggests developing a Matlab application to compare the results of measurements and calculations of brain tumors on acquiring 3D image magnetic resonance imaging data.
Electronic document management systems implementation across industries: systematic analysis Anggraini, Dian; Adi, Kusworo; Suseno, Jatmiko Endro
Indonesian Journal of Electrical Engineering and Computer Science Vol 36, No 1: October 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v36.i1.pp264-273

Abstract

The construction sector’s pivotal role in the global economy faces challenges due to its dynamic nature. Inaccurate documentation impacts project cost management, underscoring the need for effective document management systems (DMS), including electronic document management systems (EDMS). This study conducts a systematic literature review to comprehensively examine EDMS implementation, utilization, and effectiveness across sectors. Analyzing peer-reviewed articles and scholarly sources reveals key themes, trends, and findings, providing insights into successful EDMS adoption and best practices. The review contributes evidence-based insights for practitioners, researchers, and policymakers, addressing gaps in knowledge and advancing understanding of EDMS in modern information management. Additionally, it presents a detailed breakdown of publication distribution across sectors, highlighting significant research areas like companies and businesses, education, and information technology and software. Furthermore, analysis of factors influencing employee behavior, including technical factors, employee’s personal characteristics, organizational factors, and trust, offers valuable insights into workplace dynamics. Overall, the study offers comprehensive insights into EDMS implementation, guiding future research, and organizational strategies.
IDENTIFICATION OF CAPABILITY LEVELS OF MEDIS CARE INFORMATION SYSTEM USING COBIT 2019 Pamungkas, Ardian; Fardana, Nouvel Izza; Widodo, Aris Puji; Adi, Kusworo
JURTEKSI (Jurnal Teknologi dan Sistem Informasi) Vol 10, No 4 (2024): September 2024
Publisher : STMIK Royal

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33330/jurteksi.v10i4.3257

Abstract

Abstract: In the health sector, information technology was initially used for exchanging information between patients and doctors, health services, and exchanging health documents. The aim of applying information technology to the health sector is to increase the effectiveness and efficiency of the performance of doctors and clinic staff. This research uses COBIT 2019 as a framework for evaluating information technology governance. Primary data is collected directly from the research subjects through observation and interviews, while secondary data is sourced from other materials, such as documents or websites related to the research subject. This research focuses on Risk Profile and I&T Related Issues, with domains: APO11 – Managed Quality, and APO13 – Managed Security. Through interviews and evaluation, each priority objective was found to be at capability level 2 with ratings of 100% and 86% respectively. There are no significant gaps between the current capability levels; both are at level 2. Keywords: auditing; COBIT 2019; telemedicine  Abstrak: Di sektor kesehatan, teknologi informasi awalnya digunakan untuk pertukaran informasi antara pasien dan dokter, layanan kesehatan, dan pertukaran dokumen kesehatan. Tujuan penerapan teknologi informasi di sektor kesehatan adalah untuk meningkatkan efektivitas dan efisiensi kinerja dokter dan staf klinik. Penelitian ini menggunakan COBIT 2019 sebagai kerangka kerja untuk mengevaluasi tata kelola teknologi informasi. Data primer dikumpulkan langsung dari subjek penelitian dengan melakukan pengamatan dan interaksi langsung, sementara data sekunder diperoleh dari sumber lain. didapatkan dari jurnal atau situs website yang berkaitan dengan subjek penelitian. Penelitian ini berfokus pada Risk Profile dan I&T Related Issues, dengan domain : APO11 – Managed Quality, dan APO13 – Managed Security. Melalui wawancara dan evaluasi, setiap tujuan prioritas ditemukan berada pada level kapabilitas 2 dengan nilai masing-masing 100% dan 86%. Tidak ada kesenjangan signifikan antara tingkat kapabilitas saat ini; keduanya berada pada level 2. Kata kunci: audit; COBIT 2019; telemedis
Utilization of convolutional neural network in image interpretation techniques for detecting kidney disease Sulaksono, Nanang; Adi, Kusworo; Isnanto, Rizal
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 14, No 1: February 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v14.i1.pp602-613

Abstract

This research is conducted with deep learning for kidney stone disease detection including cysts, stones, normal, and tumors using axial computerized tomography (CT) scan images. The author uses augmentation, generative adversarial networks (GANs), original, and synthetic minority over-sampling technique (SMOTE) to classify kidney disease (cyst, stone, normal, and tumor). This study uses the public dataset nazmul0087 and primary data/data from the hospital, using convolutional neural network (CNN) models, namely augmentation, GANs, original, and SMOTE by training and testing. The results of the accuracy value of the training model (dataset nazmul0087) in the detection of kidney cysts, stones, tumors, and normal. The results of augmentation value are 99.93%, GANs 100%, original 100%, and SMOTE 99.93%. In the results of the training model, a very high accuracy value is obtained, with perfect results. The testing model's accuracy value in detecting kidney cysts, stones, tumors, and normal kidney tissue in the original dataset and hospital data. The results of augmentation value are 11.48%, GANs 17.96%, original 21.76%, and SMOTE 20.41%. In the results of the training model, the highest accuracy value is obtained in the original model. For the testing model to automatically diagnose kidney illness and obtain a high accuracy value, which can enhance patient outcomes and save health care costs, we advise using it in conjunction with the original model.
Co-Authors - Magister Sistem Informasi Universitas Diponegoro, Vincencius Gunawan S.K Abdillah Noor Fajrin Achmad Widodo Adi Pamungkas Adian Fatchur Rohim Adila Safitri Agus Atabik Anwar Agustini, Eka Puji Agvion Virsaw Alfajri, Willy Bima Andrian Bayu Suksmono Andriyan B. Suksmono Andriyan Suksmono Andriyan Suksmono, Andriyan Antono Suryo Putro Apoina Kartini Aprilia Ayu Andarinny Ardhi, Ovide Decroly Wisnu Ari Bawono Putranto Arief Rachman Aris P Widodo Aris Puji Widodo Aris Puji Widodo Aris Sugiharto Ary Setyadi Atik Zilziana Muflihati Noor Baital, Muhammad Sawal Basuki Wibowo Beta Noranita Cahya Tri Purnami Carissa Devina Usman Catur Adi Widodo Catur Edi Widodo Chakim Annubaha Choirul Anam Choirul Anam AM Diponegoro Dartini Dartini Dartini Dartini, Dartini Dedi Apriyandi Dedi Sepriana Delfia, Fila Dewi, Adinda Cipta Dian Anggraini Didi Supriyadi Dwi Ely Kurniawan Dwi Rochmayanti Dyah Apriliani Eka Vickraien Dangkua, Eka Vickraien Eko Adi Sarwoko Eko Sediono Elvira Situmorang Esa Prakasa, Esa Evi Setiawati Evita Ayu Suryaningtyas Faikhin . Faisal Rahman Fanny, Nabilatul Fardana, Nouvel Izza Farid Agushybana Farid Farid Agushybana Fatkhurrazi Basyid Figur Humani Fila Delfia Frida Fallo Gatot Murti Wibowo Gatot Murti Wibowo, Gatot Murti Hadyan Arifianto Hariri, Ahmad Harnanto, Rudy Haryati Haryati Hastuti, Dyah Dewi Havez Vazirani Al Kautsar Hendra Gunawan HENDRA GUNAWAN B11211055 Hernowo Danusaputro Ibrahim, Muhammad Rivani Imam Syafii Ircham Ali Isnain Gunadi Isnain Gunadi Jatmiko Endor Suseno Jatmiko Endro Suseno Jatmiko Endro Suseno Jayawarsa, A.A. Ketut Julianto, Dewa Rizki Rahmat Komang Budi Aryasa Laila Rahmawati Linda Nuryanti M.Irwan Katili Mailia Putri Utami Mailia Putri Utami MAIZZA NADIA PUTR Maratullatifah, Yulaikha MARTINI Martini Martini Mengko, Tati L.R. Muhammad Ikhsan Nahdi Saubari Nanang Sulaksono, Nanang Natalia Kristiani Nava Muzdalifah Nelly Mirnasari Neneng Neneng Nina Dwi Astuti Noor Azizah Nugroho Adhi Santoso Nugroho, Irwan Andriyanto Nur Hamid Nurul Firdausi Nuzula, Nurul Firdausi Nurul Huda Prasetyo Oky Dwi Nurhayati Pamungkas, Ardian Prakasa, Fawwaz Bimo Puji Widodo, Aris Purwanto Purwanto Putri Nuriskianti Qoriani Widayati R Rizal Isnanto Rachmat Gernowo Rachmatullah, Robby Rahmat Gernowo Rahmat Gernowo Rasyid Rasyid, Rasyid Retnaningsih Soeprobowati, Tri Ria Amitasari Rima Ayuning Ratri Riris Trima Derita Sari Rizky Ayomi Syifa Rr. Tony Yulianto Saiful Widianto Salsabila Naqiyah Sari, Kiki Puspita Septya Maharani, Septya Setyowati Setyowati Shahmirul Hafizullah Imanuddin Sidin Hariyanto Sifaunajah, Agus Siti A&#039;isyah Siti Nur Endahyani Sri Bintang Pamungkas Suandari P.V.L Suryono Suryono Suseno, Jatmiko Endor Sutopo Patria Jati Tati Mengko Tati Mengko, Tati Tito Rano Pradibto Toni Wijanarko Adi Putra Tri Mulyono Tri Retnaningsih Soeprobowati Tri Sandhika Jaya Tutur Urip Undari Nurkalis Vincencius Gunawan, Vincencius Vincensius Gunawan S.K. Wahyu Setia Budi Wahyudi Setiawan Wahyuni, Wilda Waliyansyah, Rahmat Robi Weirna Yusanti Wicaksono, Januar Agung Widagdo, Krisan Aprian Willy Bima Alfajri Wisnu Ardhi, Ovide Decroly Wiwit Agus Triyanto Yuliani Setyaningsih Zaenal Arifin Zaenul Muhlisin Zainal Bachrudin