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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) RABIT: Jurnal Teknologi dan Sistem Informasi Univrab Journal Of Vocational Health Studies Jurnal Penelitian Pendidikan IPA (JPPIPA) Syntax Literate: Jurnal Ilmiah Indonesia Jurnal Teknoinfo Journal of Physics and Its Applications 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 Informatika dan Rekayasa Perangkat Lunak 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 Journal of Computing Theories and Applications International Journal Of Health And Social Behavior International Journal of Health and Medicine

Kusworo Adi

Jurusan Fisika, Fakultas Sains Dan Matematika, Universitas Diponegoro Jl. Prof. Soedharto, SH., Tembalang, Semarang, Jawa Tengah

Author-ID : 219451

Religion Agriculture, Biological Sciences & Forestry Arts Humanities Astronomy 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 Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Nursing Physics Public Health Social Sciences Veterinary Other

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Systematic Literature Review on Information Technology Governance in Government Wicaksono, Januar Agung; Widodo, Aris Puji; Adi, Kusworo
Telematika Vol 20 No 2 (2023): Edisi Juni 2023
Publisher : Jurusan Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31315/telematika.v20i2.9642

Purpose: This article aims to assist the government in developing better, more efficient, and sustainable public governance by utilizing information technology and artificial intelligence. The article provides insights on how information technology and artificial intelligence can be applied in public governance to improve the efficiency, effectiveness, and sustainability of public services, as well as to enhance public trust in the government.Design/Method/Approach: The method used in this article is a Systematic Literature Review (SLR), which is a systematic and methodological research method for collecting, evaluating, and synthesizing evidence from previous studies in the field under investigation, through search terms and searching for information in online databases and creating inclusion and exclusion criteria.Results: This article is expected to achieve more efficient, effective, and sustainable public governance and improve the quality of public services and public trust. The article also shows that information technology and artificial intelligence have become an integral part of public governance in various countries, with many countries taking a holistic and sustainable approach.Originality/State of the art: The state-of-the-art of this article is that information technology and artificial intelligence can be effectively used to improve public governance to achieve better, more efficient, and sustainable goals. The article also emphasizes the importance of considering data privacy, cyber security, and unwanted environmental impacts, as well as considering ethical and human rights aspects in the development of artificial intelligence. This will help the government to develop and implement information technology and artificial intelligence in public governance in a responsible and sustainable manner.

Optimasi Convolutional Neural Network Menggunakan Differential Evolution dalam Identifikasi Kematangan Buah Kelapa Sawit Budiman, Naufal; Adi, Kusworo; Wibowo, Adi
Jurnal Teknologi Informasi dan Ilmu Komputer Vol 13 No 1: Februari 2026
Publisher : Fakultas Ilmu Komputer, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25126/jtiik.2026131

Deteksi kematangan buah kelapa sawit merupakan salah satu langkah penting dalam meningkatkan efisiensi dan produktivitas di sektor pertanian di Indonesia. Dalam era perkembangan teknologi, penerapan metode berbasis kecerdasan buatan, seperti Convolutional Neural Network (CNN), sering digunakan dalam pengenalan dan klasifikasi citra. Dalam proses pengembangan model Deep Learning, optimasi untuk meningkatkan akurasi dan efisiensi komputasi menjadi langkah penting. Proses ini melibatkan penyesuaian arsitektur dan hyperparameter untuk memastikan model dapat mempelajari fitur yang relevan secara efektif. Melalui optimasi, model dapat disesuaikan untuk menangani karakteristik dataset tertentu, meningkatkan kemampuan generalisasi, dan memaksimalkan kinerja pada tugas klasifikasi. Penelitian ini mengoptimasi model CNN melalui penyesuaian arsitektur dan hyperparameter menggunakan salah satu algoritma evolusi, yaitu Differential Evolution (DE), dalam mengidentifikasi tingkat kematangan buah kelapa sawit. Dataset yang digunakan dalam penelitian ini berupa gambar buah kelapa sawit dengan tiga tingkat kematangan, yaitu: matang, mentah, dan busuk. Sebagai pembanding, penelitian ini juga menggunakan metode CNN tanpa DE. Hasil dari penelitian menunjukkan bahwa metode CNN yang dioptimasi menggunakan DE dalam mengidentifikasi tingkat kematangan buah kelapa sawit memberikan akurasi sebesar 0,98 serta nilai presisi, sensitivitas, dan F1-score di atas 0,97 untuk semua kelas. Abstract The detection of oil palm fruit ripeness is a crucial step in improving efficiency and productivity in Indonesia's agricultural sector. In the era of technological advancement, artificial intelligence-based methods, such as Convolutional Neural Networks (CNN), are frequently applied in image recognition and classification. In developing Deep Learning models, optimization plays a vital role in enhancing accuracy and computational efficiency. This process involves adjusting the architecture and hyperparameters to ensure the model can effectively learn relevant features. Through optimization, the model can be tailored to handle specific dataset characteristics, improve generalization, and maximize performance in classification tasks. This study optimizes a CNN model by adjusting its architecture and hyperparameters using an evolutionary algorithm known as Differential Evolution (DE) to identify the ripeness levels of oil palm fruits. The dataset used in this study consists of images of oil palm fruits categorized into three ripeness levels: ripe, unripe, and rotten. For comparison, a baseline CNN model without DE optimization was also employed. The results show that the CNN model optimized using DE achieved an accuracy of 0,98 with precision, sensitivity, and F1-score values exceeding 0.97 for all classes.

Enhanced U-Net models with encoder and augmentation for phytoplankton segmentation Ovide Decroly Wisnu Ardhi; Tri Retnaningsih Soeprobowati; Kusworo Adi; Esa Prakasa; Arief Rachman
International Journal of Advances in Applied Sciences Vol 13, No 4: December 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijaas.v13.i4.pp1013-1022

This study comprehensively analyzes U-Net models for semantic segmentation in phytoplankton image recognition, leveraging encoders such as EfficientNet-B5, MobileNetV2, ResNet50, and ResNeXt50 and employing the Adam optimizer. The research highlights the U-Net MobileNetV2 model with optical distortion, which achieves notable test scores with 93.69% Dice, 88.14% intersection over union (IoU), 99.89% Precision, and 100% Recall, underscoring the efficacy of the applied augmentation strategies, including geometric and distortion transforms, and color and blur techniques. The U-Net ResNet50 model with mix transform consistently demonstrates high accuracy in critical metrics, outperforming others, while EfficientNet-B5 with blur suggests increased model sensitivity with improved recall. These results underscore the crucial role of encoder-augmentation synergy in model performance. Training and testing times across models have remained under 250 seconds, reflecting methodological efficiency. Overall, these results demonstrate the model's excellent performance for the semantic segmentation task.

Modeling Student Learning Profiles from LMS Behavioral Traces Using Big Data Analytics Arief Hidayat; Kusworo Adi; Bayu Surarso
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.v8i3.1588

Digital learning environments and Learning Management Systems (LMSs) generate large volumes of time-stamped behavioral traces that can be used to examine how students access resources, navigate course structures, communicate, and approach assessments. Traditional learning-style models often depend on static self-report categories and may not reflect how students actually study in digital courses. This study develops a learning analytics framework for modeling student learning profiles from authentic LMS behavioral traces. The study used a quantitative, non-experimental, longitudinal design based on Canvas LMS interaction data from 15,342 undergraduate students enrolled in 150 large-enrollment courses during the 2023–2024 academic year. More than 500 million raw interaction logs were processed into 24 engineered behavioral features representing temporal engagement, resource access, navigation behavior, interaction activity, and assessment timing. After feature normalization, K-Means clustering was applied, and the optimal cluster solution was selected using the elbow method and average silhouette score. Cluster distinctiveness was examined using one-way analysis of variance, and the association between cluster membership and academic performance category was evaluated using a Chi-squared test. The analysis supported a four-cluster solution. Assessment procrastination and navigation sequentially were the strongest differentiating features.

TATA KELOLA TI PADA ORGANISASI KESEHATAN: TINJAUAN LITERATUR SISTEMATIS MENGENAI FRAMEWORK, TANTANGAN, DAN MANFAAT : IT GOVERNANCE IN HEALTHCARE ORGANIZATIONS: A SYSTEMATIC LITERATURE REVIEW OF FRAMEWORKS, CHALLENGES, AND BENEFITS Maharani Swastika; Taufik Akbar; Aris Puji Widodo; Kusworo Adi; Bambang Sugeng Suryatna
Rabit : Jurnal Teknologi dan Sistem Informasi Univrab Vol 11 No 1 (2026): Januari
Publisher : LPPM Universitas Abdurrab

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36341/rabit.v11i1.7061

Information Technology (IT) in the healthcare sector has driven the growing need for effective IT governance to ensure the security, efficiency, and quality of healthcare services. This study provides a comprehensive review of Information Technology (IT) Governance used in the healthcare sector, particularly in hospitals, by analyzing frameworks, their implementation challenges, and evaluating their impact on service quality and operational efficiency. The method used is a systematic literature review based on PRISMA guidelines of 34 international articles published between 2020 and 2025. The sources identified that COBIT is the dominant best practice framework used to align IT with organizational goals and ensure regulatory compliance. In addition, TOGAF is relevant for auditing, risk management, and enterprise architecture design. Specialist frameworks such as blockchain are proposed for higher data security and integrity. Although these frameworks support improved patient outcomes, data security, and operational efficiency, their implementation is hampered by leadership challenges, technical (such as poor infrastructure and legacy system integration), and complex data regulatory compliance issues.

SKIN DISEASE CLASSIFICATION USING EFFICIENT TRANSFER LEARNING AND ATTENTION MECHANISM KURNIA ADI CAHYANTO; KUSWORO ADI; CATUR EDI WIDODO
Rabit : Jurnal Teknologi dan Sistem Informasi Univrab Vol 11 No 1 (2026): Januari
Publisher : LPPM Universitas Abdurrab

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36341/rabit.v11i1.7278

Skin diseases are a common health issue that is often underestimated, as most are mild and can be treated with over-the-counter medications. However, some types, such as melanoma, can be cancerous and deadly if not treated properly. Melanoma is caused by excessive exposure to ultraviolet rays and has a recovery rate of 99% if diagnosed on time, but it decreases to 20% in advanced stages. This study developed a multi-category skin disease classification model using transfer learning through a previously trained model such as EfficientNetV2S with Attention Mechanism to overcome overfitting and improve accuracy. The dataset used is ISIC2019 with 8 classes of skin diseases and 25,331 samples, after data augmentation was performed to increase the sample size. The EffCANet model showed a test accuracy of 94.81%, higher than previous studies, indicating a decrease in the overfitting gap and an improvement in test accuracy results.

Development of a Digital Radiation Card Model Using an Android-Based Smartphone for Patients Undergoing External Radiation Therapy Rukmayani Sipahutar; Kusworo Adi; Agung Nugroho Setiawan; Gatot Murti Wibowo; Nanang Sulaksono
International Journal of Health and Medicine Vol. 3 No. 3 (2026): Juli: International Journal of Health and Medicine
Publisher : Asosiasi Riset Ilmu Kesehatan Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/ijhm.v3i3.647

The clinical role of radiotherapy in oncology, where ionising radiation is applied to damage the deoxyribonucleic acid (DNA) structure of tumour target cells in order to halt uncontrolled cell proliferation. The success of radiotherapy is influenced by patient compliance in completing the entire course of treatment according to the prescribed schedule. Consequently, the aim of this study was to develop a digital radiation card model using an Android-based smartphone for patients undergoing external radiation therapy at Murni Teguh General Hospital in Medan, with a view to improving patient compliance and satisfaction. This study employed a Research and Development (R&D) approach to develop an Android-based digital radiation card and assess its feasibility. The R&D method was chosen as it is suitable for research that produces a product whilst simultaneously conducting testing and refinement prior to wider implementation. The ADDIE development model was utilised, comprising five stages: Analysis, Design, Development, Implementation, and Evaluation. Based on the expert validation test, the digital radiotherapy card has been found to be effective in improving patient compliance and satisfaction in the radiotherapy department. The effectiveness of using Android-based digital radiation cards for patients undergoing external radiation therapy in improving patient satisfaction is demonstrated by the results of the Wilcoxon test, which show that all items relating to satisfaction have a p-value < 0.05; this indicates a significant difference between pre-test and post-test scores for satisfaction following the implementation of the Android-based digital radiation cards. The effectiveness of using Android-based digital radiation cards for patients undergoing external radiation therapy in improving patient compliance was demonstrated by the results of the Wilcoxon test, which showed that all items relating to compliance had a p-value < 0.05. Consequently, the use of digital radiation cards can be deemed effective in improving respondents’ compliance.

Evaluasi Sistem Informasi Kesehatan dengan Model HOT-Fit : Literature Review: Evaluation of Health Information Systam with HOT-Fit Model : Literature Review Fila Delfia; Kusworo Adi; Cahya Tri Purnami
Media Publikasi Promosi Kesehatan Indonesia (MPPKI) Vol. 5 No. 6 (2022)
Publisher : Fakultas Kesehatan Masyarakat, Universitas Muhammadiyah Palu

Latar Belakang: Sistem informasi kesehatan bertujuan untuk mendukung informasi untuk pengambilan keputusan dalam setiap aspek manajemen. Ketika sistem diimplementasikan, evaluasi diperlukan untuk mengetahui sejauh mana sistem informasi bermanfaat. Evaluasi dan monitoring sistem yang tidak dilakukan secara berkala akan mengakibatkan keluaran yang dihasilkan tidak sesuai dengan kebutuhan dan tidak dapat mendukung pengambilan keputusan. Tujuan: Penelitian ini bertujuan guna mengetahui evaluasi sistem informasi kesehatan berdasarkan aspek manusia, organisasi, teknologi dan manfaat. Metode: Literature review bersumber dari 15 artikel penelitian yang diterbitkan pada tahun 2017-2021. Hasil: Penelitian membuktikan bahwa ada hubungan antara teknologi dengan manusia dan organisasi. Manusia ingin memanfaatkan teknologi ketika mereka memahami manfaat positif yang diperoleh dari penerapan sistem. Fungsi teknologi informasi adalah tersedianya informasi sesuai kebutuhan. Kesimpulan: evaluasi sistem informasi kesehatan sangat dibutuhkan guna peningkatan sistem tersebut sehingga dapat dimanfaatkan secara maksimal oleh pengguna dan pihak manajemen guna mengambil keputusan. Faktor-faktor yang berhubungan dengan evaluasi implementasi sistem informasi, yaitu: manusia (penguna sistem dan kepuasan pengguna), organisasi (struktur organisasi dan lingkungan organisasi), teknologi (kualitas sistem, kualitas informasi, dan kualitas layanan), dan manfaat.

Comparative Approaches to Clustering for Profiling Students in Educational Data Mining Noor Azizah; Kusworo Adi; Catur Edi Widodo
Jurnal Informatika dan Rekayasa Perangkat Lunak Vol. 8 No. 1 (2026): Maret
Publisher : Universitas Wahid Hasyim

Show Abstract | Download Original | Original Source | Check in Google Scholar

This study aims to compare the performance of five clustering algorithms, a K-Means, K-Medoids, Fuzzy C-Means (FCM), DBSCAN, and Gaussian Mixture Model (GMM) in profiling 239 students using quantitative data. The methodology includes data collection, refinement, transformation, application of clustering algorithms, and evaluation using the Silhouette Score, Davies–Bouldin Index, and execution time. The results indicate that K-Means provides the most balanced performance, achieving the highest Silhouette score with well-defined cluster separation. K-Medoids and GMM demonstrate competitive performance, while DBSCAN excels in detecting outliers but produces an excessive number of clusters, limiting its interpretability for profiling. FCM performs the weakest due to poor cluster separability. Overall, K-Means is recommended as the primary approach for student profiling, while other algorithms may complement specific analytical needs.

Block-wise Authenticated DNA-based Image Encryption with Tamper Localization using HKDF-Derived Keys Bagus Satrio Waluyo Poetro; Kusworo Adi; Aris Puji Widodo
Journal of Computing Theories and Applications Vol. 4 No. 1 (2026): JCTA 4(1) 2026
Publisher : Universitas Dian Nuswantoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62411/jcta.16605

Confidentiality alone cannot establish whether a medical, forensic, cloud-stored, or remotely sensed image has been modified during transmission, while a single global authentication verdict cannot identify the affected region. This paper presents a block-wise authenticated DNA-based image encryption framework that integrates a DNA-chaos confidentiality core with pre-decryption integrity verification and spatial tamper localization. An authenticated ephemeral X25519 key exchange establishes a session secret, which is expanded by HKDF-SHA256 into four transcript-bound, domain-separated subkeys for permutation, DNA operations, diffusion, and authentication. Chaotic seeds are derived from a canonical plaintext hash and block coordinates, preserving strong plaintext differential sensitivity while confining post-encryption modifications to the affected blocks. Ciphertext integrity is enforced using a block-wise encrypt-then-MAC construction with 128-bit truncated HMAC-SHA256 tags that authenticate both the canonical header and each ciphertext block. A reduction-based security argument shows that the authentication layer provides ciphertext integrity and conditionally upgrades an IND-CPA encryption core to IND-CCA security under standard HKDF and HMAC assumptions, while the confidentiality claim remains explicitly conditional on the encryption core. Experiments on 30 tuberculosis chest radiographs across five independent sessions achieved a ciphertext entropy of 7.9972, near-zero adjacent-pixel correlation, 99.61% NPCR, and 33.47% UACI. Across five representative tampering attacks, the proposed framework achieved an observed 100% block-level true-positive rate, 0% false-positive rate, and required only 2.847 ± 0.258 ms for block-wise authentication with 6.25% tag overhead using the default 16×16 block configuration. These results demonstrate that the proposed framework effectively combines statistical confidentiality, modern cryptographic key management, and reliable block-level tamper localization within a unified authenticated image encryption architecture.

Co-Authors - Magister Sistem Informasi Universitas Diponegoro, Vincencius Gunawan S.K Abdillah Noor Fajrin Achmad Widodo Adi Pamungkas Adi Wibowo Adian Fatchur Rohim Adila Safitri Agung Nugroho Setiawan Agus Atabik Anwar Agus Sifaunajah 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 Ari Bawono Putranto Arief Hidayat Arief Rachman Arief Rachman Aris P Widodo Aris Puji Widodo Aris Puji Widodo Aris Sugiharto Ary Setyadi Atik Zilziana Muflihati Noor Baital, Muhammad Sawal Bambang Sugeng Suryatna Basuki Wibowo Bayu Surarso Beta Noranita Budiman, Naufal Cahya Tri Purnami Carissa Devina Usman Catur Adi Widodo Catur Edi Widodo Catur Edi Widodo Chakim Annubaha Choirul Anam Choirul Anam AM Diponegoro 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 Prakasa, Esa Evi Setiawati Evita Ayu Suryaningtyas Faikhin . Faisal Rahman Fardana, Nouvel Izza Farid Agushybana Farid Farid Agushybana Fatkhurrazi Basyid Figur Humani Fila Delfia Frida Fallo Gatot Murti Wibowo 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 KURNIA ADI CAHYANTO Laila Rahmawati Linda Nuryanti M.Irwan Katili Maharani Swastika Mailia Putri Utami Mailia Putri Utami MAIZZA NADIA PUTR Maratullatifah, Yulaikha MARTINI Martini Martini Mengko, Tati L.R. Muhammad Ikhsan Nabilatul Fanny Nahdi Saubari Nanang Sulaksono Natalia Kristiani Nava Muzdalifah Nelly Mirnasari Neneng Neneng Nina Dwi Astuti Noor Azizah Noor Azizah Nugroho Adhi Santoso Nur Hamid Nurul Firdausi Nuzula, Nurul Firdausi Nurul Huda Prasetyo Oky Dwi Nurhayati Ovide Decroly Wisnu Ardhi Pamungkas, Ardian Poetro, Bagus Satrio Waluyo 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 Rukmayani Sipahutar Saiful Widianto Salsabila Naqiyah Sari, Kiki Puspita Septya Maharani, Septya Setyowati Setyowati Shahmirul Hafizullah Imanuddin Sidin Hariyanto Siti A'isyah Siti Nur Endahyani Sri Bintang Pamungkas Suandari P.V.L Suryono Suryono Suseno, Jatmiko Endor Sutopo Patria Jati Tati Mengko Tati Mengko, Tati Taufik Akbar 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 Wisnu Ardhi, Ovide Decroly Wiwit Agus Triyanto Yuliani Setyaningsih Zaenal Arifin Zaenul Muhlisin Zainal Bachrudin

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