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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) Jurnal Masyarakat Informatika Bulletin of Electrical Engineering and Informatics Kreano, Jurnal Matematika Kreatif-Inovatif Sainteknol : Jurnal Sains dan Teknologi International Journal of Advances in Intelligent Informatics Scientific Journal of Informatics Journal of Information Systems Engineering and Business Intelligence Jurnal Nasional Pendidikan Teknik Informatika (JANAPATI) Jurnal Abdimas PHB : Jurnal Pengabdian Masyarakat Progresif Humanis Brainstorming Abdimasku : Jurnal Pengabdian Masyarakat Unnes Journal of Mathematics Education Unnes Journal of Mathematics Journal of Community Empowerment Proceeding ISETH (International Summit on Science, Technology, and Humanity) Jurnal Inovasi Pengabdian dan Pemberdayaan Masyarakat Recursive Journal of Informatics Kreano, Jurnal Matematika Kreatif Inovatif Jurnal Penelitian Pendidikan Jurnal Dharma Indonesia Jurnal Abdi Negeri Recursive Journal of Informatics

Riza Arifudin

Unknown Affiliation

Author-ID : 232768

Humanities Automotive Engineering Computer Science & IT Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Health Professions Industrial & Manufacturing Engineering Mathematics Mechanical Engineering Medicine & Pharmacology Public Health Social Sciences Other

Published : 93 Documents Claim Missing Document

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Optimizing Support Vector Machine Performance for Parkinson's Disease Diagnosis Using GridSearchCV and PCA-Based Feature Extraction Jumanto, Jumanto; Rofik, Rofik; Sugiharti, Endang; Alamsyah, Alamsyah; Arifudin, Riza; Prasetiyo, Budi; Muslim, Much Aziz
Journal of Information Systems Engineering and Business Intelligence Vol. 10 No. 1 (2024): February
Publisher : Universitas Airlangga

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20473/jisebi.10.1.38-50

Background: Parkinson's disease (PD) is a critical neurodegenerative disorder affecting the central nervous system and often causing impaired movement and cognitive function in patients. In addition, its diagnosis in the early stages requires a complex and time-consuming process because all existing tests such as electroencephalography or blood examinations lack effectiveness and accuracy. Several studies explored PD prediction using sound, with a specific focus on the development of classification models to enhance accuracy. The majority of these neglected crucial aspects including feature extraction and proper parameter tuning, leading to low accuracy. Objective: This study aims to optimize performance of voice-based PD prediction through feature extraction, with the goal of reducing data dimensions and improving model computational efficiency. Additionally, appropriate parameters will be selected for enhancement of the ability of the model to identify both PD cases and healthy individuals. Methods: The proposed new model applied an OpenML dataset comprising voice recordings from 31 individuals, namely 23 PD patients and 8 healthy participants. The experimental process included the initial use of the SVM algorithm, followed by implementing PCA for feature extraction to enhance machine learning accuracy. Subsequently, data balancing with SMOTE was conducted, and GridSearchCV was used to identify the best parameter combination based on the predicted model characteristics. Result: Evaluation of the proposed model showed an impressive accuracy of 97.44%, sensitivity of 100%, and specificity of 85.71%. This excellent result was achieved with a limited dataset and a 10-fold cross-validation tuning, rendering the model sensitive to the training data. Conclusion: This study successfully enhanced the prediction model accuracy through the SVM+PCA+GridSearchCV+CV method. However, future investigations should consider an appropriate number of folds for a small dataset, explore alternative cross-validation methods, and expand the dataset to enhance model generalizability. Keywords: GridSearchCV, Parkinson Disaese, SVM, PCA, SMOTE, Voice/Speech

STEM Trails: Enhancing STEM Education through Math Trails with Digital Technology Cahyono, Adi Nur; Dewi, Nuriana Rachmani; Asih, Tri Sri Noor; Arifudin, Riza; Aditya, Rozak Ilham; Maulana, Bagus Surya; Nugroho, Muhammad Andi
Kreano, Jurnal Matematika Kreatif-Inovatif Vol. 15 No. 1 (2024): Kreano, Jurnal Matematika Kreatif-Inovatif
Publisher : UNNES JOURNAL

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/jtknv202

This study aims to explore the development of STEM Trails to improve STEM Education through the integration of Math Trails activity with Digital Technology. An exploratory study initiative engaged researchers, teachers, students, and programmers. Data was collected through discussions and observations and then evaluated to create STEM Education through Math Trails utilizing Digital Technology. The study demonstrated the successful development of STEM Trails, comprising the STEM Trails platform and the creation of STEM Education activities utilizing Math Trails on the platform. STEM Trailblazers create paths with goals focused on science, technology, engineering, and mathematics using elements found in the surroundings. The trail and tasks are posted on a website for STEM Trail walkers to access and investigate via an application. STEM Trails enable the comprehensive exploration of science, technology, engineering, and mathematics through physical or virtual means. The study suggests that STEM Trails can serve as a mathematics learning approach that mixes outdoor activities with digital technologies and incorporates other subjects. Math Trails is a traditional concept that has been innovatively combined with digital technologies and diverse activities. This method must be broadened and refined by adjusting to the specific circumstances, conditions, and requirements, and then executed in different settings. Penelitian ini bertujuan untuk mengeksplorasi pengembangan STEM Trails untuk meningkatkan STEM Education melalui integrasi aktivitas Math Trails dengan Digital Technology. Sebuah inisiatif penelitian eksploratif melibatkan peneliti, guru, siswa, dan programmer. Data dikumpulkan melalui diskusi dan pengamatan dan kemudian dievaluasi untuk menciptakan STEM Education melalui Math Trails menggunakan Teknologi Digital. Studi ini menunjukkan keberhasilan pengembangan STEM Trails, yang terdiri dari platform Stem Trails dan penciptaan kegiatan STEM Education menggunakan Math Trails di platform tersebut. STEM Trailblazers menciptakan jalur dengan tujuan yang berfokus pada ilmu pengetahuan, teknologi, teknik, dan matematika menggunakan elemen yang ditemukan di sekitarnya. Trail dan tugas diposting di situs web untuk STEM Trail walker untuk mengakses dan menyelidiki melalui aplikasi. STEM Trails memungkinkan eksplorasi komprehensif ilmu pengetahuan, teknologi, teknik, dan matematika melalui sarana fisik atau virtual. Studi ini menyarankan bahwa STEM Trails dapat berfungsi sebagai pendekatan pembelajaran matematika yang menggabungkan kegiatan outdoor dengan teknologi digital dan mengintegrasikan mata pelajaran lainnya. Math Trails adalah konsep tradisional yang telah digabungkan secara inovatif dengan teknologi digital dan berbagai kegiatan. Metode ini harus diperluas dan disempurnakan dengan menyesuaikan dengan keadaan, kondisi, dan persyaratan tertentu, dan dijalankan dalam pengaturan yang berbeda.

Implementation of NXT 2.0 Mindstorm Robot Sensors on Mobile Education for Students Kuncoro, Rizki Danang Kartiko; Arifudin, Riza; Sugiharti, Endang
Proceeding ISETH (International Summit on Science, Technology, and Humanity) 2018: Proceeding ISETH (International Summit on Science, Technology, and Humanity)
Publisher : Universitas Muhammadiyah Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23917/iseth.2289

In the current 4.0 industry era, technological development is very fast and fast. In the world of education the lessons about technology should have been introduced to students since elementary school. Do not have to use complex technology, enough to use robotics technology from the NXT 2.0 LEGO minstorm robot which is lego-based to play and learn algorithms in composing technology. Using this tool can also be controlled by the smartphone application. Using a mobile application that we designed will make it easier for students to use and play this educational media. In this media, each sensor in the robot will be interrelated to the mobile control, we have tested this control with 83.33% detection accuracy. So that it can effectively become an interactive and fun technology-based learning media for students. The purpose of this educational media is to improve the quality of education in Indonesia so that it can be technology-based and enjoyable for students. Because the application of technology to education is very important to hone the power of creative thinking in composing programming algorithms using robots. Students will be very interested and have good enthusiasm in learning robotics based on this mobile application.

Implementasi E-Ujian Sebagai Sistem Penilaian Pembelajaran Daring di SMP Islam Roudlotus Saidiyyah Semarang Hakim, M. Faris Al; Sugiharti, Endang; Alamsyah, Alamsyah; Arifudin, Riza; Abidin, Zaenal; Putra, Anggyi Trisnawan
Jurnal Abdi Negeri Vol 2 No 1 (2024): Januari 2024
Publisher : Informa Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63350/jan.v2i1.18

The presence of the COVID-19 outbreak has led to the implementation of online learning from the location of each home. SMP Islam Roudlotus Saidiyyah Semarang has transformed learning by utilizing various applications. However, for the purposes of final semester assessment or integrated assessment, an online exam application is needed that is easy to use and able to provide data on student learning outcomes accurately and quickly. The implementation method consists of preparation, training, and evaluation. The results of the training showed that the E-Ujian application as an application for online assessment has the potential to be applied at SMP Islam Roudlotus Saidiyyah Semarang. The utilization of the E-Ujian Application in learning activities in the partner environment is an effort to maintain the quality of learning.

OPTIMASI PENJADWALAN PROYEK DENGAN PENYEIMBANGAN BIAYA MENGGUNAKAN KOMBINASI CPM DAN ALGORITMA GENETIKA Riza Arifudin
Jurnal Masyarakat Informatika Vol 2, No 4 (2011): Jurnal Masyarakat Informatika
Publisher : Department of Informatics, Universitas Diponegoro

The project scheduling must be prepared systematically by using resources effectively and efficiently so that project objectives can be achieved optimally. This research aimed to examine the application of combinaton CPM and genetic algorithms to solved optimization problems in a project scheduling with the leveling of costs and designing a software. CPM is one of method to schedule the project that produce the shortest time. In this study of CPM combined with genetic algorithm to perform scheduling. Genetic algorithms are search methods that mimic the process of solution of natural selection and genetics. The allocation of activities is determined based on the earliest start time and latest start time by taking into account the cost of resources in each period of the project. Project scheduling and optimal criterion used is minimizing the cost of deviations from the average total project cost. Results obtained in this research is that the cost of scheduling with deviations smaller than the scheduling with CPM alone thus generated a shorter project schedules and project cost per day is also more equitable. This Scheduling method can be alternative decisions for the contractor in project implementation.

Peningkatan Kompetensi Guru MGMP Matematika dalam Pembuatan Modul Ajar melalui Pelatihan Generative Artificial Intelligence Arifudin, Riza; Abidin, Zaenal; Sugiharti, Endang; Arini, Florentina Yuni; Setiawan, Abas
Jurnal Pengabdian Masyarakat Progresif Humanis Brainstorming Vol 9, No 1 (2026): Jurnal Abdimas PHB : Jurnal Pengabdian Masyarakat Progresif Humanis Brainstormin
Publisher : Politeknik Harapan Bersama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30591/japhb.v9i1.9854

Kegiatan pengabdian masyarakat ini dilatarbelakangi oleh permasalahan utama yang dihadapi oleh mitra, yaitu MGMP Matematika Kota Semarang, yakni rendahnya literasi digital dan pemahaman guru dalam memanfaatkan Generative Artificial Intelligence (Gen-AI) untuk pengembangan modul ajar. Hal ini mengakibatkan ketergantungan pada media konvensional, modul yang monoton, serta proses penyusunan yang tidak efisien. Topik ini dipilih karena integrasi Gen-AI dalam pendidikan merupakan kebutuhan mendesak di era digital untuk meningkatkan efisiensi dan kualitas pembelajaran. Tujuan pengabdian adalah untuk meningkatkan kompetensi guru dalam memanfaatkan Gen-AI (seperti ChatGPT dan DeepSeek) untuk pembuatan modul dan rubrik ajar. Metode pelaksanaan terdiri dari lima tahap: identifikasi kebutuhan, pengenalan Gen-AI, praktik pembuatan modul, evaluasi, serta pendampingan dan monitoring. Kegiatan ini melibatkan 20 guru MGMP Matematika SMP Kota Semarang. Hasil evaluasi menunjukkan peningkatan keterampilan (hardskill) yang signifikan, yaitu kemampuan membuat modul ajar (40,6%) dan rubrik ajar (41,9%), serta peningkatan pemahaman konsep Gen-AI (23,7%) dan kemampuan menggunakan prompt (31,4%). Kegiatan ini berhasil memberdayakan guru dengan keterampilan digital yang aplikatif, sehingga sangat penting untuk keberlanjutan inovasi pembelajaran dan efisiensi kerja guru dalam mendukung Kurikulum Merdeka.

Application of Fuzzy Logic in Visual Novel Evaluation System Using Unity 3D Epafraditus Memoriano; Riza Arifudin
Recursive Journal of Informatics Vol. 3 No. 1 (2025): March 2025
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/rji.v3i1.1158

Purpose: Visual novels, narrative-driven games focused on character interaction, commonly employ point-based evaluation systems that struggle to represent the inherent complexity and uncertainty of player choices. This research introduces a novel approach: integrating fuzzy logic into visual novel evaluation systems using Unity 3D. Fuzzy logic addresses the limitations of point-based systems by accounting for the "fuzzy" nature of player choice and its varied impact on story progression and character relationships. Methods/Study design/approach: A visual novel game was developed in Unity 3D, incorporating a fuzzy logic evaluation system for scoring player choices and assessing route progress. Fuzzy sets and membership functions were defined for key aspects like emotional response, character alignment, and plot development. These aspects were dynamically evaluated based on player dialogue selection, and individual scores were aggregated to generate a final route evaluation. Result/Findings: Testing demonstrated seamless integration of the fuzzy logic system within the game engine. Evaluation of conversation choices and route progression yielded accurate and nuanced scores, reflecting the varying weight of each decision based on narrative context and character interaction. Fuzzy logic facilitated the interpretation of "fuzzy" player choices, translating them into meaningful information for story progression and character relationships. Novelty/Originality/Value: This research presents a novel and promising approach to visual novel evaluation by leveraging the strengths of fuzzy logic. It overcomes the limitations of traditional point-based systems, capturing the complexity and dynamism of player choices within the narrative. The dynamic and responsive evaluation results enhance player engagement and provide a more immersive gaming experience.

Implementation of the Term Frequency-Inverse Document Frequency Method for Mental Health Classification Using Algorithm Support Vector Machine Ilfa Minatika; Riza Arifudin
Recursive Journal of Informatics Vol. 3 No. 2 (2025): September 2025
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/rji.v3i2.1921

Abstract. Mental health is a person's emotional, social and psychological condition. A person's mental health level can be influenced by emotional experiences, behavior, environment and family educational background. A person's psychological well-being can be influenced by a person's behavior, where they live, the education they receive, and their emotional experiences. It is important not to underestimate the existence of mental health disorders because the number of cases is currently increasing. Purpose: Using SVM algorithm and TF-IDF method can produce good accuracy for classification text. Therefore this research aims to determine the implementation of the use of the TF-IDF method and the SVM algorithm in mental health classification and to determine the accuracy results of using these methods. Study Method/Design/Approach: The methods used in the research this for the mental health classification is Term Frequency-Inverse Document Frequency used in the vectorization process to convert text into a numerical representation, as well as using the Support Vector Machine algorithm in modeling. The dataset used is the Mental Health Corpus dataset obtained from the Kaggle website. This dataset consists of two classes containing text and labels totaling 27,977 data. Before applying the model, preprocessing is carried out first, namely cleaning the text using stopword removal and stemming. After cleaning the text, the next process is vectorization using CountVectorizer and TF-IDF. Results/Findings: In this study the SVM algorithm was used four kernels, namely the linear kernel, the RBF kernel, the polynomial kernel, and the later sigmoid kernel get the best accuracy results on the RBF kernel if compared to with other kernels. Accuracy results obtained _ of 92.62%, value precision of 92.64%, value recall 92.62%, and value f1-score 92.62%. Novelty/Originality/Value: So, it can be concluded that the application of the SVM algorithm and the TF-IDF method is possible used for classification mental health results mark high accuracy.

Optimization of Residual Network 50 using Boosted Anisotropic Diffusion Filter and Contrast Limited Adaptive Histogram Equalization for Fingerprint Classification Ahmad Syafii; Riza Arifudin
Recursive Journal of Informatics Vol. 4 No. 1 (2026): March 2026
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/rji.v4i1.13398

Abstract. Biometrics itself can be interpreted as a computerized method that uses aspects of biology, especially unique characteristics possessed by humans. Unique characteristics that can be used include fingerprints, geometric shapes of the hand, sound frequency keys, iris patterns, and retinas that generally differ from one individual to another. Fingerprints are the result of reproduction of the palm of the finger, either intentionally taken, stamped with ink, or marks left on objects because they have been touched by the skin of the palms of the hands or feet. Fingerprints are used as identification and verification as a means for security. So, there is a tool used to carry out this task, namely AFIS (Automatic Fingerprint Identification System). The purpose of this system is to strive for strong and fast detection. So, a fingerprint grouping or classification is needed, so that the identification process takes place faster. The algorithm used to classify fingerprints is ResNet-50. The data used came from the National Institute of Standards and Technology in 2000 (NIST-DB4 in 2000). In this dataset, there are 4000 data with each number per class is 800 data. There are five classes in this dataset including arch. right loop, left loop, tended arch, and whorl. In the training process, data processing is carried out first. This is done to optimize the accuracy produced during the training process. This research used preprocessing Boosted Anisotropic Diffusion Filter (BADF) and Contrast Limited Adaptive Histogram Equalization (CLAHE). The BADF method is used to reduce the noise present in the image. Whereas, CLAHE is used to adjust the contrast of the image. The accuracy produced using the two preprocessing was 94.5%. Purpose: This research aims to optimize fingerprint classification using ResNet-50 combined with Boosted Anisotropic Diffusion Filter (BADF) and Contrast Limited Adaptive Equalization (CLAHE) methods. Methods: This research uses the ResNet-50 method combined with the Boosted Anisotropic Diffusion Filter (BADF) and Contrast Limited Adaptive Histogram Equalization techniques CLAHE) methods. Result: This research has four experiments, including an experiment using the ResNet-50 model without using preprocessing to obtain an accuracy of 92.5%. When BADF preprocessing was applied in the data training process, the accuracy increased to 93.5%. Meanwhile, the experiment using the ResNet-50 model using preprocessing obtained an accuracy of 94%. This accuracy can still be improved by combining BADF and CLAHE preprocessing which gets an accuracy of 94.5%. Novelty: This research uses the ResNet-50 model with a preprocessing method that is combined to obtain higher accuracy. The update in this research is to apply the BADF and CLAHE methods as image preprocessing. The BADF method aims to reduce the noise present in the scattered image, while the CLAHE method is used to adjust the contrast in the image itself.

Implementation of Raita Algorithm in Manado-Indonesia Translation Application with Text Suggestion Using Levenshtein Distance Algorithm Novanka Agnes Sekartaji; Riza Arifudin
Recursive Journal of Informatics Vol. 2 No. 2 (2024): September 2024
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/pkvgtg90

Abstract. Manado City is one of the multidimensional and multicultural cities, possessing assets that are considered highly potential for development into tourism and development attractions. The current tourism assets being developed by the Manado City government are cultural tourism, as they hold a charm and allure for tourists. Hence, a communication tool in the form of a translation application is necessary for facilitating communication between visiting tourists and the native community of North Sulawesi, even for newcomers who intend to reside in North Sulawesi, given that the Manado language serves as the primary communication tool within the community. This research employs a combination of the Raita algorithm and the Levenshtein distance algorithm in its creation process, along with the confusion matrix method to calculate the accuracy of translation results using the Levenshtein distance algorithm with a text suggestion feature. The research begins by collecting a dataset consisting of Manado language vocabulary and their translations in Indonesia language, sourced from literature studies and original respondents from North Sulawesi, which have been validated by a validator to prevent translation data errors. The subsequent stage involves preprocessing the dataset, converting the entire content of the dataset to lowercase using the case folding process, and removing spaces at the start and end of texts using the trim function. Next, both algorithms are implemented, with the Raita algorithm serving for translation and the Levenshtein distance algorithm providing text suggestions for typing errors during the translation process. The accuracy results derived from the confusion matrix calculations during the translation process of 100 vocabulary words, accounting for typing errors, indicate that the Levenshtein distance algorithm is capable of effectively translating vocabulary accurately and correctly, even in the presence of typing errors, resulting in a high accuracy rate of 94,17%. Purpose: To determine the implementation of the Levenshtein distance and Raita algorithms in the process of using the Manado-Indonesian translation application, as well as the resulting accuracy level. Methods/Study design/approach: In this study, a combination of the Raita and Levenshtein distance algorithms is utilized in the translation application system, along with the confusion matrix method to calculate accuracy. Result/Findings: The accuracy achieved in the translation process using text suggestions from the Levenshtein distance algorithm is 94.17%. Novelty/Originality/Value: This research demonstrates that the combination of the Raita and Levenshtein distance algorithms yields optimal results in the vocabulary translation process and provides accurate outcomes from the use of effective text suggestions. This is attributed to the fact that nearly all the data used was successfully translated by the system, even in the presence of typographical errors.

Co-Authors Abas Setiawan Adha, Nugraha Saputra Adhitiya, Ervan Nur Adi Nur Cahyono Aditya, Rozak Ilham Ahmad Syafii Aji Saputra Al Hakim, M. Faris Alamsyah - Alfatah, Abdul Muis Alfatah, Abdul Muis Amalia Fikri Utami Amin Suyitno Anggita, Anggita Anggyi Trisnawan Putra Ardhi Prabowo Arief Agoestanto Arief Broto Susilo Arif Widiyatmoko, Arif Ariska, Mega Arka Yanitama Arrohman, Ramadhan Ridho Asih, Tri Sri Noor Atikah Ari Pramesti, Atikah Ari Budi Prasetiyo, Budi Chakim, Muhamad Nur Choirunnisa, Rizkiyanti Clarissa Amanda Josaputri, Clarissa Amanda Damayanti, Angreswari Ayu Damayanti, Tiara Desy Fitria Astutianingtyas Devi, Feroza Rosalina Devi, Feroza Rosalina Dewi, Nuriana Rachmani Dian Tri Wiyanti Dwijanto Dwijanto, Dwijanto Endang Sugiharti, Endang Epafraditus Memoriano Faozi, Faozi Farkhan, Feri Fata, Muhamad Nasrul Fata, Muhamad Nasrul Fitriana, Jevita Dwi Florentina Yuni Arini Habaib, Taufik Nur Hakim, M. Faris Al Hani'ah, Ulfatun Hardi Suyitno Hardianti, Ririn Dwi Hariyanto, Abdul Hidayat, Kukuh Triyuliarno Hidayat, Kukuh Triyuliarno Hikmah, Al Hikmawati, Zahra Shofia Hikmawati, Zahra Shofia Ichsan, Nur Ilfa Minatika Irfan Fajar Muttaqin Jumanto Jumanto, Jumanto Jumanto Unjung Kumalasari, Putri Laksita Kuncoro, Rizki Danang Kartiko Larasati, Ukhti Ikhsani Larasati, Ukhti Ikhsani Mashuri Mashuri Masrukan Masrukan Maulana, Bagus Surya Melissa Salma Darmawan Mohammad Asikin Much Aziz Muslim Mudzakir, Amat Muhammad Fariz Muttaqin, Irfan Fajar Novanka Agnes Sekartaji Nugroho, Ari Yulianto Nugroho, Muhammad Andi Nugroho, Prisma Bayu Pramadita, Anjar Aditya Putriaji Hendikawati Rachmawati, Eka Yuni Rachmawati, Eka Yuni Rahmanda, Primana Oky Rahmanda, Primana Oky Ramadhan Ridho Arrohman Ratna Dewi, Novi Rizki Nor Amelia Rochmad - Rofik Rofik, Rofik S.Pd. M Kes I Ketut Sudiana . Safri, Yofi Firdan Safri, Yofi Firdan Sasongko, Andry Scolastika Mariani Sekartaji, Novanka Agnes Septiko Aji Setiawan, Danang Aji Stephani Diah Pamelasari Subarkah, Agus Subhan Subhan Sukmadewanti, Irahayu Sukmadewanti, Irahayu Susanto, Febri Syafa Nabilah Syahputra Trihanto, Wandha Budhi Trihanto, Wandha Budhi Utami, Hamdan Dian Jaya Rozi Hyang Utami, Hamdan Dian Jaya Rozi Hyang Wibowo, Eric Adie Widyawati, Kharisa Yahya Nur Ifriza Yulianto, Muhamad Maulana Yulianto, Muhamad Maulana Zaenal Abidin Zulfikar Adi Nugroho, Zulfikar Adi

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