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All Journal International Journal of Electrical and Computer Engineering IAES International Journal of Artificial Intelligence (IJ-AI) IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Jurnal Ilmu Komputer MATICS : Jurnal Ilmu Komputer dan Teknologi Informasi (Journal of Computer Science and Information Technology) TELKOMNIKA (Telecommunication Computing Electronics and Control) Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Jurnal Ilmiah Kursor Journal of Innovation and Applied Technology International Journal of Local Economic Governance Journal of Environmental Engineering and Sustainable Technology Jurnal Pembangunan dan Alam Lestari Jurnal Teknologi Informasi dan Ilmu Komputer The International Journal of Accounting and Business Society Jurnal Edukasi dan Penelitian Informatika (JEPIN) International Journal of Advances in Intelligent Informatics Scientific Journal of Informatics Journal of Information Systems Engineering and Business Intelligence KLIK (Kumpulan jurnaL Ilmu Komputer) (e-Journal) JOIV : International Journal on Informatics Visualization Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Journal of Information Technology and Computer Science Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Knowledge Engineering and Data Science Jambura Law Review Advances in Food Science, Sustainable Agriculture and Agroindustrial Engineering (AFSSAAE) Indonesian Journal of Electrical Engineering and Computer Science International Journal of Engineering, Science and Information Technology Indexia Prosiding Seminar Nasional Teknik Elektro, Sistem Informasi, dan Teknik Informatika (SNESTIK) Bulletin of Culinary Art and Hospitality Bulletin of Social Informatics Theory and Application Jurnal ilmiah teknologi informasi Asia Signal and Image Processing Letters Jurnal Pengabdian Masyarakat Teknologi Informasi dan Informatika
Wayan Firdaus Mahmudy
Brawijaya University
Agriculture, Biological Sciences & Forestry 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 Immunology & microbiology Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Physics Social Sciences Transportation

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High Dimensional Data Clustering using Self-Organized Map Febrita, Ruth Ema; Mahmudy, Wayan Firdaus; Wibawa, Aji Prasetya
Knowledge Engineering and Data Science
Publisher : citeus

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Abstract

As the population grows and e economic development, houses could be one of basic needs of every family. Therefore, housing investment has promising value in the future. This research implements the Self-Organized Map (SOM) algorithm to cluster house data for providing several house groups based on the various features. K-means is used as the baseline of the proposed approach. SOM has higher silhouette coefficient (0.4367) compared to its comparison (0.236). Thus, this method outperforms k-means in terms of visualizing high-dimensional data cluster. It is also better in the cluster formation and regulating the data distribution.
Optimisation of Rice Fertiliser Composition using Genetic Algorithms Anissa, Retno Dewi; Mahmudy, Wayan Firdaus; Widodo, Agus Wahyu
Knowledge Engineering and Data Science
Publisher : citeus

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There are so many problems with food scarcity. One of them is not too good rice quality. So, an enhancement in rice production through an optimal fertiliser composition. Genetic algorithm is used to optimise the composition for a more affordable price. The process of genetic algorithm is done by using a representation of a real code chromosome. The reproduction process using a one-cut point crossover and random mutation, while for the selection using binary tournament selection process for each chromosome. The test results showed the optimum results are obtained on the size of the population of 10, the crossover rate of 0.9 and the mutation rate of 0.1. The amount of generation is 10 with the best fitness value is generated is equal to 1,603.
Earthquake Magnitude and Grid-Based Location Prediction using Backpropagation Neural Network Priambodo, Bagus; Mahmudy, Wayan Firdaus; Rahman, Muh Arif
Knowledge Engineering and Data Science
Publisher : citeus

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Earthquakes, a type of inevitable natural disaster, is responsible for the highest average death toll per year compared to other types of a natural disaster. Even though it is inevitable, but it can be anticipated to minimize damage and casualties, such as predicting the earthquake‘s magnitude using a neural network. In this study, a backpropagation algorithm is used to train the multilayer neural network to weekly predict the average magnitude of earthquakes in grid-based locations in Indonesia. Based on the findings in this research, the neural network is able to predict the magnitude of earthquakes in grid-based locations across Indonesia with a minimum error rate of 0.094 in 34.475 seconds. This best result is achieved when the neural network is trained for 210 epochs, with 16 neurons used in the input and output layer, one hidden layer consisted of 5 neurons and a learning rate of 0.1. This result showed backpropagation has pretty good generalization capability in order to map the relations between variables when mathematical function is not explicitly available.
Efficient Scheduling of Plantation Company Workers using Genetic Algorithm Mahmudy, Wayan Firdaus; Pardede, Andreas; Widodo, Agus Wahyu; Rahman, Muh Arif
Knowledge Engineering and Data Science
Publisher : citeus

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Abstract

Workers at large plantation companies have various activities. These activities include caring for plants, regularly applying fertilizers according to schedule, and crop harvesting activities. The density of worker activities must be balanced with efficient and fair work scheduling. A good schedule will minimize worker dissatisfaction while also maintaining their physical health. This study aims to optimize workers' schedules using a genetic algorithm. An efficient chromosome representation is designed to produce a good schedule in a reasonable amount of time. The mutation method is used in combination with reciprocal mutation and exchange mutation, while the type of crossover used is one cut point, and the selection method is elitism selection. A set of computational experiments is carried out to determine the best parameters’ value of the genetic algorithm. The final result is a better 30 days worker schedule compare to the previous schedule that was produced manually.
Detection of Disease and Pest of Kenaf Plant Based on Image Recognition with VGGNet19 Fajri, Diny Melsye Nurul; Mahmudy, Wayan Firdaus; Yulianti, Titiek
Knowledge Engineering and Data Science
Publisher : citeus

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One of the advantages of Kenaf fiber as an environmental management product that is currently in the center of attention is the use of Kenaf fiber for luxury car interiors with environmentally friendly plastic materials. The opportunity to export Kenaf fiber raw material will provide significant benefits, especially in the agricultural sector in Indonesia. However, there are problems in several areas of Kenaf's garden, namely plants that are attacked by diseases and pests, which cause reduced yields and even death. This problem is caused by the lack of expertise and working hours of extension workers as well as farmers' knowledge about Kenaf plants which have a terrible effect on Kenaf plants. The development of information technology can be overcome by imparting knowledge into machines known as artificial intelligence. In this study, the Convolutional Neural Network method was applied, which aims to identify symptoms and provide information about disease symptoms in Kenaf plants based on images so that early control of plant diseases can be carried out. Data processing trained directly from kenaf plantations obtained an accuracy of 57.56% for the first two classes of introduction to the VGGNet19 architecture and 25.37% for the four classes of the second introduction to the VGGNet19 architecture. The 5×5 block matrix input feature has been added in training to get maximum results.
Fish Image Classification using Transfer Learning Method withAdaptive Learning Rate Suhana, Rizka; Mahmudy, Wayan Firdaus; Budi, Agung Setia
Knowledge Engineering and Data Science
Publisher : citeus

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The diversity of fish species in coral reef ecosystems is one of the indications in determining health in coral reef ecosystems. Many Indonesian Fisheries and Marine Research and Development Agency experts carefully classify fish images. A reliable technique for performing image classification is Convolutional Neural Network (CNN). Transfer learning appears and adopts part of CNN, namely the modified convolution layer. The paper aims to solve the fish classification problem using the pre-trained model of Mobilenet V2. The model has a low computational process and does not use too many memory resources when training image data. The research image data used is 49,281 data of various sizes and 18 types of fish. The image is entered into the transformation process (random rotation, random resize crop, random horizontal flip) on the training and test data to produce varied data. After the transformation process, the image data is entered into the training process using the Mobilenet V2 architecture. Testing the Mobilenet V2 architectural model obtained an accuracy score of 99.54%, which is reliable in classifying fish images.
Hybrid Artificial Bee Colony and Improved SimulatedAnnealing for the Capacitated Vehicle Routing Problem Mar'i, Farhanna; Ubaidillah, Hafidz; Mahmudy, Wayan Firdaus; Supianto, Ahmad Afif
Knowledge Engineering and Data Science
Publisher : citeus

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Capacitated Vehicle Routing Problem (CVRP) is a type of NP-Hard combinatorial problem that requires a high computational process. In the case of CVRP, there is an additional constraint in the form of a capacity limit owned by the vehicle, so the complexity of the problem from CVRP is to find the optimum route pattern for minimizing travel costs which are also adjusted to customer demand and vehicle capacity for distribution. One method of solving CVRP can be done by implementing a meta-heuristic algorithm. In this research, two meta-heuristic algorithms have been hybridized: Artificial Bee Colony (ABC) with Improved Simulated Annealing (SA). The motivation behind this idea is to complete the excess and the lack of two algorithms when exploring and exploiting the optimal solution. Hybridization is done by running the ABC algorithm, and then the output solution at this stage will be used as an initial solution for the Improved SA method. Parameter testing for both methods has been carried out to produce an optimal solution. In this study, the test was carried out using the CVRP benchmark dataset generated by Augerat (Dataset 1) and the recent CVRP dataset from Uchoa (Dataset 2). The result shows that hybridizing the ABC algorithm and Improved SA could provide a better solution than the basic ABC without hybridization.
Peningkatan Produktivitas Kader Posyandu dalam Pemanfaatan Digital Melalui Google Workspace Zulvarina, Prima; Kurnianingtyas, Diva; Mahmudy, Wayan Firdaus
DIMASLOKA: Jurnal Pengabdian Masyarakat Teknologi Informasi dan Informatika Vol 5 No 2 (2026): Juli 2026
Publisher : Fakultas Ilmu Komputer Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25126/dimasloka.v5i2.67

Abstract

Posyandu sebagai pilar pelayanan kesehatan masyarakat masih menghadapi tantangan, terutama dalam pencatatan manual, koordinasi Kader, serta keterbatasan literasi digital. Kondisi ini berdampak pada rendahnya efisiensi kerja dan akurasi data. Penelitian ini bertujuan mendeskripsikan praktik pelatihan keterampilan digital bagi Kader Posyandu melalui pemanfaatan Google Workspace sebagai upaya peningkatan produktivitas dan transformasi digital layanan publik. Metode yang digunakan adalah Service Learning, metode kegiatan pembelajaran atau pelatihan kepada masyarakat. Menggabungkan pelayanan kepada masyarakat dengan proses pembelajaran melalui pelatihan kepada Kader Posyandu di Desa Dono, Kabupaten Tulungagung[FASM1] . Kegiatan dilakukan dalam tiga tahap: persiapan, pelaksanaan, dan evaluasi, meliputi pengenalan Google Workspace (Docs, Sheets, Form, Drive, Calendar, dan Meet), praktik pencatatan data, pelaporan, serta simulasi koordinasi daring. Hasil menunjukkan peningkatan signifikan pemahaman dan keterampilan Kader, dari hanya tiga Kader yang memahami Google Workspace pada pre-test menjadi 17 Kader pada hasil post-test. Penerapan produk digital terbukti mempercepat pencatatan, meningkatkan akurasi pelaporan, dan memperluas metode edukasi masyarakat melalui media daring. Pelatihan ini juga mendorong Kader lebih adaptif terhadap perkembangan teknologi, sejalan dengan arah transformasi digital kesehatan nasional. Dengan demikian, pemanfaatan Google Workspace mampu menjadi strategi efektif dalam meningkatkan produktivitas Kader Posyandu dan memperkuat kualitas layanan kesehatan masyarakat secara berkelanjutan.   Abstract Posyandu, as a cornerstone of community health services, continues to face challenges, particularly in manual data recording, cadre coordination, and limited digital literacy. These issues contribute to low work efficiency and data accuracy. This study aims to describe the practice of digital skills training for Posyandu cadres through the utilization of Google Workspace as an effort to enhance productivity and support the digital transformation of public services. A qualitative descriptive method was employed, involving training sessions for Posyandu cadres in Dono Village, Tulungagung Regency. The activities were conducted in three phases: preparation, implementation, and evaluation. The training covered the introduction to Google Workspace tools (Docs, Sheets, Forms, Drive, Calendar, and Meet), hands-on practice in data recording and reporting, and simulations of online coordination. The results showed a significant improvement in cadre understanding and skills, from only three cadres familiar with Google Workspace during the pre-test to 17 cadres in the post-test. The adoption of digital tools proved effective in accelerating data entry, improving reporting accuracy, and expanding community education methods through online media. The training also encouraged cadres to become more adaptive to technological developments, aligning with the national agenda for digital health transformation. Thus, the use of Google Workspace presents an effective strategy for improving Posyandu cadre productivity and strengthening the quality of community health services in a sustainable manner.
Analisis Variasi Operator Genetika pada Optimasi Rute dan Jadwal Wisata Ihsan Akram, Faiz; Firdaus Mahmudy, Wayan; Wahyu Widodo, Agus
Jurnal Pengembangan Teknologi dan Ilmu Komputer Vol 10 No 6 (2026): Juni 2026
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Perencanaan perjalanan wisata harian merupakan permasalahan optimasi kombinatorial yang kompleks karena harus mempertimbangkan time window, preferensi wisata, jadwal makan, dan waktu tempuh antar lokasi. Permasalahan ini termasuk dalam Travelling Salesman Problem with Time Windows (TSP-TW) dapat diselesaikan menggunakan Algoritma Genetika. Namun, penelitian terdahulu umumnya hanya berfokus pada satu operator genetika tanpa mengevaluasi secara komprehensif kombinasi teknik crossover, mutasi, seleksi, dan repair. Penelitian ini bertujuan menganalisis pengaruh variasi operator genetika terhadap kualitas dan efisiensi penjadwalan rute wisata. Data destinasi wisata dan tempat makan diperoleh dari Google Maps, OpenStreetMap, dan sumber daring lainnya. Eksperimen dilakukan terhadap 80 kombinasi operator, masing-masing sebanyak 20 kali menggunakan seed berbeda, dengan ukuran populasi 100, probabilitas crossover 0,8, probabilitas mutasi 0,01, Tournament Selection berukuran 3, dan maksimum 750 generasi. Kinerja setiap kombinasi dievaluasi menggunakan rata-rata nilai fitness, waktu komputasi, dan overall score. Hasil menunjukkan bahwa kombinasi Insertion Mutation–Partially Matched Crossover (PMX)–Roulette Wheel Selection tanpa repair menghasilkan performa terbaik dengan rata-rata overall score sebesar 0,7576. Selain itu, seluruh 10 kombinasi terbaik tidak menggunakan repair, sedangkan crossover PMX dan mutasi Insertion secara konsisten muncul pada kombinasi berperforma tinggi. Penelitian ini menyimpulkan bahwa pemilihan kombinasi operator genetika yang tepat berpengaruh signifikan terhadap kualitas dan efisiensi penjadwalan rute wisata.
Optimasi Komposisi Pakan Ternak Kambing Perah Menggunakan Algoritma Genetika Tanjung, Lutfi Mitra; Mahmudy, Wayan Firdaus
Jurnal Pengembangan Teknologi dan Ilmu Komputer Vol 10 No 7 (2026): Juli 2026
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Kambing merupakan salah satu ternak dengan populasi terbesar di Indonesia dan berperan penting bagi perekonomian serta kehidupan masyarakat, termasuk kambing perah yang dimanfaatkan produksi susunya. Penentuan komposisi pakan yang tepat menjadi salah satu faktor penting agar kambing perah dapat menghasilkan susu secara optimal dengan biaya yang efisien. Selama ini, penyusunan komposisi pakan pada peternak umumnya masih dilakukan berdasarkan kebiasaan tanpa perhitungan kebutuhan nutrisi secara pasti, sehingga hasil yang diperoleh belum tentu optimal. Penelitian ini bertujuan untuk menemukan komposisi pakan ternak kambing perah yang optimal menggunakan Algoritma Genetika serta mengetahui tingkat kualitas solusi yang dihasilkan. Penyelesaian masalah dilakukan dengan merepresentasikan komposisi pakan ke dalam kromosom berbasis real code, dimana setiap gen mewakili bobot (kg) dari salah satu jenis bahan pakan. Sistem dibangun melalui tahapan studi literatur, analisis kebutuhan, perancangan sistem, implementasi menggunakan bahasa pemrograman Python, serta pengujian dan analisis. Pengujian dilakukan terhadap parameter batas atas interval gen, crossover rate, mutation rate, ukuran populasi, dan jumlah generasi untuk memperoleh kombinasi parameter yang menghasilkan nilai fitness terbaik. Hasil pengujian parameter menunjukkan kombinasi terbaik diperoleh pada batas atas interval gen 10 kg, ukuran populasi 70, jumlah generasi 50, crossover rate 0,9, dan mutation rate 0,4. Evaluasi hasil optimasi dilakukan dengan membandingkan komposisi pakan yang selama ini digunakan peternak dengan komposisi hasil sistem. Komposisi hasil optimasi sistem menghasilkan estimasi total produksi susu sebesar 7,96 liter dengan biaya pakan Rp110.000, meningkat lebih dari dua kali lipat dibandingkan komposisi peternak yang hanya menghasilkan estimasi 3,73 liter dengan biaya Rp43.250. Meskipun biaya pakan hasil sistem lebih besar secara nominal, biaya yang dikeluarkan untuk setiap liter tambahan produksi susu justru lebih rendah, yaitu sekitar Rp18.469 dibandingkan Rp24.971 pada praktik peternak. Hasil ini membuktikan bahwa Algoritma Genetika mampu menghasilkan komposisi pakan kambing perah yang secara proporsional lebih efisien dibandingkan praktik yang selama ini diterapkan oleh peternak.
Co-Authors A.N. Afandi Abdul Latief Abadi Abdul Latief Abadi Achmad Arwan Achmad Basuki Achmad Ridok Adimoelja, Ariawan Aditama, Gustian Adyan Nur Alfiyatin Agi Putra Kharisma Agung Mustika Rizki Agung Mustika Rizki, Agung Mustika Agung Setia Budi Agung Setia Budi, Agung Setia Agus Naba Agus Wahyu Widodo Agus Wahyu Widodo Agus Wahyu Widodo, Agus Wahyu Ahmad Afif Supianto Ahmad Afif Supianto Ahmad Afif Supianto Aji Prasetya Wibawa Al Khuluqi, Mabafasa Alauddin, Mukhammad Wildan Alfiani Fitri Alfita Rakhmandasari Alfiyatin, Adyan Nur Alqorni, Faiz Amalia Kartika Ariyani Amalia Kartika Ariyani Amalia Kartika Ariyani Anantha Yullian Sukmadewa Andi Kurniawan Andi Maulidinnawati A K Parewe Andi Maulidinnawati A. K. Parewe Andreas Nugroho Sihananto Andreas Pardede Andreas Patuan G. Pardede Andrew Nafalski Angga Vidianto Anissa, Retno Dewi Aprilia Nur Fauziyah Aprilia Nur Fauziyah Arief Andy Soebroto Arinda Hapsari Achnas Armanda, Rifki Setya Arviananda Bahtiar Arya, Putu Bagus Asyrofa Rahmi Asyrofa Rahmi Asyrofa Rahmi Asyrofa Rahmi Asyrofa Rahmi, Asyrofa Aulia, Yudha Alif Bagus Priambodo Bagus Priambodo Bayu Rahayudi Binti Robiyatul Musanah Budi Darma Setiawan Burhan, M.Shochibul Cahya, Reiza Adi Cahyo Prayogo, Cahyo Candra Dewi Candra Fajri Ananda Cleoputri Yusainy Darmawan, Abizard Hashfi Dea Widya Hutami Dhaifullah, Afif Naufal Diah Anggraeni Pitaloka Didik Suprayogo Dinda Novitasari Dinda Novitasari, Dinda Diny Melsye Nurul Fajri Dita Sundarningsih Durrotul Fakhiroh Dyan Putri Mahardika Dzikron, Ahmad Ahdani Edi Satriyanto Edy Santoso Effendi, Mas’ud Eko Widaryanto Elta Sonalitha Ervin Yohannes Evi Nur Azizah Fadhli Almu’iini Ahda Fais Al Huda Fajri, Diny Melsye Nurul Fatchurrochman Fatchurrochman Fatwa Ramdani, Fatwa Fauzi, Muhammad Rifqi Fauziatul Munawaroh Fazlur Ihzanurahman Febriyana, Ria Fendy Yulianto Fitra Abdurrachman Bachtiar Fitri Anggarsari Fitria Dwi Nurhayati Gayatri Dwi Santika Ghozali Maski Grady Davinsyah Gusti Ahmad Fanshuri Alfarisy Gusti Ahmad Fanshuri Alfarisy, Gusti Ahmad Fanshuri Gusti Eka Yuliastuti Hafidz Ubaidillah Hamdianah, Andi Hanggara , Buce Trias Herman Tolle Hernando, Deo Heru Nurwarsito Hidayat, Luthfi Hilman Nuril Hadi Ida Wahyuni Ihsan Akram, Faiz Imada Nur Afifah Imam Cholisoddin Imam Cholissodin Imam Cholissodin Imam Cholissodin Imam Santoso Indriati Indriati Irvi Oktanisa Ishardita Pambudi Tama Ismiarta Aknuranda Jauhari, Farid Khozaimi, Ach. Kukuh Tejomurti, Kukuh Kuncahyo Setyo Nugroho Kuncahyo Setyo Nugroho Kurnianingtyas, Diva Lailil Muflikhah Lily Montarcih Limantara M Chandra Cahyo Utomo M Fadli Ridhani M Shochibul Burhan, M Shochibul M. Shochibul Burhan M. Zainal Arifin Mabafasa Al Khuluqi Mar'i, Farhanna Marji Marji Mayang Anglingsari Putri, Mayang Anglingsari Mochammad Anshori Moh. Khusaini Moh. Sholichin Moh. Zoqi Sarwani Mohammad Zoqi Sarwani Mohammad Zoqi Sarwani, Mohammad Zoqi Mu’asyaroh, Fita Lathifatul Muh Arif Rahman Muh. Arif Rahman Muhammad Ardhian Megatama Muhammad Faris Mas'ud Muhammad Halim Natsir Muhammad Isradi Azhar Muhammad Khaerul Ardi Muhammad Noor Taufiq Muhammad Rivai Muhammad Rofiq Nadia Roosmalita Sari Nadya Oktavia Rahardiani Nashi Widodo Ni Wayan Surya Wardhani Nindynar Rikatsih Novanto Yudistira Novi Nur Putriwijaya Nurizal Dwi Priandani Nurul Hidayat Oakley, Simon Oktanisa, Irvi Pardede, Andreas Philip Faster Eka Adipraja Pratama, Muhammad Fajarivan Prayudi Lestantyo Prima Zulvarina, Prima Purnomo Budi Santoso Putra, Firnanda Al Islama Achyunda Putri Hasan, Vitara Nindya Putu Indah Ciptayani Qoirul Kotimah Rachmansyah, Ghenniy Rachmawati, Christina Rani Kurnia Rayandra Yala Pratama, Rayandra Yala Retno Astuti Retno Dewi Anissa Riani, Garsinia Ely Rifa’i, Muhaimin Rinda Wahyuni Rizal Setya Perdana Rizal Setya Perdana Rizdania, Rizdania Rizki Ramadhan Rody, Rafiuddin Ruth Ema Febrita Ryan Iriany S, M Zaki Samaher . Saputro, Arkaditya Lanang Saragih, Triando Hamonangan Selly Kurnia Sari Setyawan Purnomo Sakti Sudarto Sudarto Suhana, Rizka Sukarmi Sukarmi, Sukarmi Sulistyo, Danang Arbian Sutrisno . Sutrisno Sutrisno Syafrial Syafrial Syafrial Syafrial Syaiful Anam Syandri, Hafrijal Tanjung, Lutfi Mitra Tirana Noor Fatyanosa, Tirana Noor Titiek Yulianti Titiek Yulianti Titiek YULIANTI Tomi Yahya Christyawan Tri Halomoan Simanjuntak Ubaidillah, Hafidz Ullump Pratiwi Utaminingrum, Fitri Utomo, M. Chandra Cahyo Vivi Nur Wijayaningrum Wahyuni, Ida Widdia Lesmawati Windi Artha Setyowati Yeni Herawati Yogi Pinanda Yogie Susdyastama Putra Yudha Alif Aulia Yudha Alif Auliya Yudha Alif Auliya, Yudha Alif Yulia Trianandi Yusuf Priyo Anggodo Yusuf Priyo Anggodo Yusuf Priyo Anggodo Yusuf Priyo Anggodo, Yusuf Priyo