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Aji Prasetya Wibawa

Univeristas Negeri Malang

Author-ID : 2489010

Aerospace Engineering Agriculture, Biological Sciences & Forestry Arts Humanities Astronomy Automotive Engineering 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 Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Neuroscience Physics Public Health Social Sciences Transportation Other

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Prediksi Tingkat Inflasi Dengan Menggunakan Metode Backpropagation Neural Network Kelvin Wong; Aji Prasetya Wibawa; Herman Santoso Pakpahan; Anton Prafanto; Hario Jati Setyadi
Sains, Aplikasi, Komputasi dan Teknologi Informasi Vol 1, No 2 (2019): Sains, Aplikasi, Komputasi dan Teknologi Informasi
Publisher : Universitas Mulawarman

Artikel ini bertujuan untuk memprediksi tingkat inflasi di Kota Samarinda, Kalimantan Timur dengan mengimplementasikan algoritma cerdas, Backpropagation Neural Network (BPNN). Data tingkat inflasi diperoleh dari Biro Pusat Statistik Provinsi (BPS) Kota Samarinda https://samarindakota.bps.go.id/ periode Januari 2012 hingga Januari 2017. Pengukuran akurasi prediksi algoritma BPNN menggunakan metode mean square error (MSE). Berdasarkan hasil percobaan, metode BPNN dengan parameter arsitektur 5-5-5-1; fungsi pembelajaran adalah trainlm; fungsi aktivasi adalah logsig dan purelin; laju pembelajaran adalah 0.1 mampu menghasilkan tingkat kesalahan prediksi yang baik dengan nilai MSE sebesar 0.00000424. Hasil penelitian menunjukkan bahwa algoritma BPNN ini dapat digunakan sebagai alternatif metode dalam memprediksi tingkat inflasi dalam rangka mendukung pertumbuhan ekonomi yang berkesinambungan sehingga dapat meningkatkan kesejahteraan masyarakat di Kota Samarinda, Kalimantan Timur.

ANALISIS PENERAPAN APLIKASI MUSEUM VIRTUAL INDONESIA (SIMVONI) Tri Lathif Mardi Suryanto; Nur Cahyo Wibowo; Aji Prasetya Wibawa; Baitun Nadhiroh
Jurnal Sistem Informasi dan Bisnis Cerdas Vol 15 No 1 (2022): Februari 2022
Publisher : Program Studi Sistem Informasi, Fakultas Ilmu Komputer, UPN Veteran Jawa Timur

Penelitian ini mengggunakan metode deskriptif analisis dengan tujuan untuk mengetahui peran SIMVONI sebagai sistem informasi baru yang dapat mempermudah pengunjung museum dalam melakukan kunjungan sehingga dapat menjaga eksistensi kunjungan museum itu sendiri di tengah pandemi Covid-19. Teknologi tersebut dinamakan virtual tour, di tengah pandemic virtual tour menjadi primadona di berbagai sektor termasuk sektor pariwista. Pengembangan SIMVONI digunakan untuk menjaga eksistensi kunjungan museum ditengah segala keterbatasan yang ada. Dengan hasil kuesioner yang didapatkan menunjukkan terdapat gap yang sangat jauh terhadap minat pengguna, dimana pengunjung memiliki niat yang cukup besar untuk berkunjung secara langsung ke museum setelah melakukan tur di SIMVONI. Dari hasil tersebut menunjukkan bahwa saat atau setelah menerapkan SIMVONI di museum memberikan dampak yang positif.

Manakah yang Lebih Diminati Masyarakat?: Bukalapak, Tokopedia atau Shopee Dhani Wahyu Wijaya; Aji Prasetya Wibawa
Performance: Jurnal Personalia, Financial, Operasional, Marketing dan Sistem Informasi Vol 27 No 2 (2020): Performance
Publisher : Faculty of Economics and Business Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32424/1.jp.2020.27.2.2581

One of the drivers of technological advances is the Internet, which led to the occurrence of shifting trading patterns from offline to online. But the problem is that some users of e-marketplace services, such as Bukalapak, Tokopedia, and Shopee do not know what is most interested by the community. Therefore we need to do the research which one is most interested by the community. In this research conducted observations and analyses of Website features, featured Website features, promotions what is done and by using Google Trend, in a way by comparing the three e-marketplace. The results of this study are used to find out which people are most interested in and for reference in choosing e-marketplace for the perpetrators of small and medium enterprises (SMES) or the public.

Applied of Analytical Hierarchy Process and Fuzzy Time Series in Hybrid for Optimizing Smart Vertical Farming with Multi-Variety Plants Danang Arengga Wibowo; Siti Sendari; Aji Prasetya Wibawa; Fauzy Satrio Wibowo
International Journal of Artificial Intelligence Research Vol 7, No 1 (2023): June 2023
Publisher : STMIK Dharma Wacana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29099/ijair.v7i1.402

Vertical Farming is a kind of modern agricultural methods, where the structure of growing racks are arranged upwards. This method aims to optimize the use of agricultural space. There are many plants, which are suitable to be planted for vertical farming, such as Strawberry, Tomatoes, Celery, Chili, Mint, Chives, Kuchay, Spinach, and Water spinach. The problem, which is studied in this paper, is how to control the environments of vertical farming with multi-variety plants. This paper proposed a hybrid method of Analytical Hierarchy Process and Fuzzy Time Series AHP-FTS, that is, plants with similar characteristics are placed at the same block area determined by the method of Analytical Hierarchy Process (AHP). Furthermore, controlling the environments regarding the needs of appropriate growing parameters for multi-variety plants, the Fuzzy Time Series (FTS) method is used. Then, time variable for activating actuators could be adjusted as a multi-control system. The effectiveness of the proposed method was evaluated with 365 record data in 12 months. The result shows that the AHP was successful to determine the multi-criteria to determine the zone and priority of plants. The second stage is that the FTS predicts the temperature to determine time variable for activating actuators, and the third stage is the implemented AHP-FTS as a hybrid system to evaluate the vertical Farming system. The results show that the proposed system works well as hybrid system of AHP-FTS

Combination of Feature Extractions for Classification of Coral Reef Fish Types Using Backpropagation Neural Network Luther Alexander Latumakulita; I Nyoman Gede Arya Astawa; Vitrail Gloria Mairi; Fajar Purnama; Aji Prasetya Wibawa; Nida Jabari; Noorul Islam
JOIV : International Journal on Informatics Visualization Vol 6, No 3 (2022)
Publisher : Politeknik Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30630/joiv.6.3.1082

Feature extraction is important to obtain information in digital images, where feature extraction results are used in the classification process. The success of a study to classify digital images is highly dependent on the selection of the feature extraction method used, from several studies providing a combination of feature extraction solutions to produce a more accurate classification. Classifying the types of marine fish is done by identifying fish based on special characteristics, and it can be through a description of the shape, fish body pattern, color, or other characteristics. This study aimed to classify coral reef fish species based on the characteristics contained in fish images using Backpropagation Neural Network (BPNN) method. Data used in this research was collected directly from Bunaken National Marine Park (BNMP) in Indonesia. The first stage was to extract shape features using the Geometric Invariant Moment (GIM) method, texture features using Gray Level Co-occurrence Matrix (GLCM) method, and color feature extraction using Hue Saturation Value (HSV) method. The third value of feature extraction was used as input for the next stage, namely the classification process using the BPNN method. The test results using 5-fold cross-validation found that the lowest test accuracy was 85%, the highest was 100%, and the average was 96%. This means that the intelligent model derived from the combination of the three feature extraction methods implemented in the BPNN training algorithm is very good for classifying coral reef fish.

Optimized Three Deep Learning Models Based-PSO Hyperparameters for Beijing PM2.5 Prediction Andri Pranolo; Yingchi Mao; Aji Prasetya Wibawa; Agung Bella Putra Utama; Felix Andika Dwiyanto
Knowledge Engineering and Data Science Vol 5, No 1 (2022)
Publisher : Universitas Negeri Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17977/um018v5i12022p53-66

Deep learning is a machine learning approach that produces excellent performance in various applications, including natural language processing, image identification, and forecasting. Deep learning network performance depends on the hyperparameter settings. This research attempts to optimize the deep learning architecture of Long short term memory (LSTM), Convolutional neural network (CNN), and Multilayer perceptron (MLP) for forecasting tasks using Particle swarm optimization (PSO), a swarm intelligence-based metaheuristic optimization methodology: Proposed M-1 (PSO-LSTM), M-2 (PSO-CNN), and M-3 (PSO-MLP). Beijing PM2.5 datasets was analyzed to measure the performance of the proposed models. PM2.5 as a target variable was affected by dew point, pressure, temperature, cumulated wind speed, hours of snow, and hours of rain. The deep learning network inputs consist of three different scenarios: daily, weekly, and monthly. The results show that the proposed M-1 with three hidden layers produces the best results of RMSE and MAPE compared to the proposed M-2, M-3, and all the baselines. A recommendation for air pollution management could be generated by using these optimized models.

PSO based Hyperparameter tuning of CNN Multivariate Time- Series Analysis Agung Bella Putra Utama; Aji Prasetya Wibawa; Muladi Muladi; Andrew Nafalski
JOIN (Jurnal Online Informatika) Vol 7 No 2 (2022)
Publisher : Department of Informatics, UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15575/join.v7i2.858

Convolutional Neural Network (CNN) is an effective Deep Learning (DL) algorithm that solves various image identification problems. The use of CNN for time-series data analysis is emerging. CNN learns filters, representations of repeated patterns in the series, and uses them to forecast future values. The network performance may depend on hyperparameter settings. This study optimizes the CNN architecture based on hyperparameter tuning using Particle Swarm Optimization (PSO), PSO-CNN. The proposed method was evaluated using multivariate time-series data of electronic journal visitor datasets. The CNN equation in image and time-series problems is the input given to the model for processing numbers. The proposed method generated the lowest RMSE (1.386) with 178 neurons in the fully connected and 2 hidden layers. The experimental results show that the PSO-CNN generates an architecture with better performance than ordinary CNN.

Indonesian education: A future promise Roni Herdianto; Punaji Setyosari; Dedi Kuswandi; Aji Prasetya Wibawa; Andrew Nafalski; Ilham Mulya Putra Pradana
International Journal of Education and Learning Vol 4, No 3: December 2022
Publisher : Association for Scientific Computing Electrical and Engineering(ASCEE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/ijele.v4i3.733

Technological, social, and environmental changes are occurring globally. The disruption of technology will impact all sectors of human life. Sociocultural changes occur in the demographics and socioeconomics of the world population. During this chaotic condition, the Indonesian nation, with a large population and natural resources, must inevitably adapt to the global environment. Statistics Center Agency and World Bank data show that Indonesian student enrollment rates are rising, but preschool and tertiary gaps remain. Despite rising student enrollment, Indonesian education remains in crisis. One of the backbones of the nation's civilization to face global competition is good and mature planning in the education sector that adapts to global demands. This paper reviews the future of Indonesian education based on the mapping between Ki Hadjar Dewantara’s education model, the Indonesian education roadmap 2020-2015, the disrupted education model in 2020, The WEF Education 4.0 Framework, and the Future of the classroom model. This paper results in a future Indonesian education model framework to realize Indonesia's education vision for 2035.

Cracking the code: Understanding lecturer performance and student success Tri Kuncoro; Marji Marji; Mazarina Devi; Aji Prasetya Wibawa; Ming F. Teng
International Journal of Education and Learning Vol 4, No 3: December 2022
Publisher : Association for Scientific Computing Electrical and Engineering(ASCEE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/ijele.v4i3.958

One of the essential factors in a learning process, especially in higher education, is lecturer performance. This study aims to discover the impact of a lecturer's performance on students learning outcomes in the online learning environment. Lecturer performance is represented by four aspects which are the lecturer's performance on learning technology (X1), the lecturer's performance on learning pedagogy (X2), the lecturer's performance on supporting learners (X3), and the lecturer's performance on supporting educators (X4). This quantitative research approach aims to discover one variable's cause-and-effect relationship to another. The subject of this study is 37 lecturers and 146 students. The result shows that the lecturer's performance contributes 43.1% to students' learning outcomes. It is known that learning technology and pedagogy aspects have a significant effect on students' learning outcomes. However, supporting learners and educators does not significantly impact students' learning outcomes. Therefore, the lecturer's performance positively impacts learning outcomes and is valuable for further online learning development. A potential research contribution could be to investigate further the relationship between specific aspects of a lecturer's performance and students' learning outcomes in an online learning environment. this study's findings have significant implications for higher education institutions seeking to improve online learning experiences for students. By identifying the specific aspects of lecturer performance that most impact learning outcomes, institutions can provide targeted support and training to their lecturers, ultimately leading to improved learning outcomes for students in online learning environments.

Performance of Ensemble Classification for Agricultural and Biological Science Journals with Scopus Index Nastiti Susetyo Fanany Putri; Aji Prasetya Wibawa; Harits Ar Rosyid; Agung Bella Putra Utama; Wako Uriu
Knowledge Engineering and Data Science Vol 5, No 2 (2022)
Publisher : Universitas Negeri Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17977/um018v5i22022p137-142

The ensemble method is considered an advanced method in both prediction and classification. The application of this method is estimated to have a more optimal output than the previous classification method. This article aims to determine the ensemble's performance to classify journal quartiles. The subject of agriculture was chosen because Indonesia is an agricultural country, and the interest of researchers in this field shows a positive response. The data is downloaded through the Scimago Journal and Country Rank with the accumulation in 2020. Labels have four classes: Q1, Q2, Q3, and Q4. The ensemble applied is Boosting and Bagging with Decision Tree (DT) and Gaussian Naïve Bayes (GNB) algorithms compiled from 2144 instances. The Boosting meta-ensembles used are Adaboost and XGBoost. From this study, the Bagging Decision Tree has the highest accuracy score at 71.36, followed by XGBoost Decision Tree with 69.51. The third is XGBoost Gaussian Naïve Bayes with 68.82, Adaboost Decision Tree with 60.42, Adaboost Gaussian Naïve Bayes with 58.2, and Bagging Gaussian Naïve Bayes with 56.12 results. This paper shows that the Bagging Decision Tree is the ensemble method that works optimally in this subject classification. This result suggests that the ensemble method can still fail to produce an ideal outcome that approaches the SJR system.

Co-Authors A.N. Afandi Abd. Rasyid Syamsuri Abdur Rohman Achmad Fanany Onnilita Gaffar Adaby, Resnu Wahyu Ade Kurnia Ganesh Akbari Aderyan Reynaldi Fahrezza Dewandra Aditya Wahyu Setiawan Adjie Rosyidin Adnan, Adam Agung Bella Putra Utama Agung Bella Putra Utama Agung Bella Putra Utama Agung Bella Putra Utama Agung Bella Putra Utama Agung Bella Putra Utama Agung Bella Putra Utama Agus Purnomo Ahmad Munjin Nasih Ahmad Naim Che Pee Ahmad Taufiq Aindra, Alifah Diantebes Aji, Bayu Kuncoro Akbari, Ade Kurnia Ganesh Akhimullah Akmal Fattah Akhmad Fanny Fadhilla Akrom Tegar Khomeiny Alfiansyah Putra Pertama Triono Ali, Martina Alifah Diantebes Aindra Amro, Manar Y Anak Agung Istri Sri Wiadnyani Andien Khansa’a Iffat Paramarta Andika Dwiyanto, Felix Andini, Nurul Fajriah Andrew Nafalski Andrew Nafalski Andrew Nafalski Andrew Nafalski Andrew Nafalski Andrew Nafalski Andri Pranolo Andriansyah, Muhammad Rizal Angeline, Grace Anggreani, Desi Anik Nur Handayani Anton Prafanto Anusua Ghosh Anusua Ghosh, Anusua Ardiansyah, Mohammad Iqbal Firman Aripriharta - Arya Tandy Hermawan Ashar, Muhammad Astuti, Wistiani Atmaja, I Made Ari Dwi Suta Atmaja, Nimas Hadi Ba, Abdoul Fatakhou Bagaskoro, Muhammad Cahyo Bahalwan, Lugas Anegah Baitun Nadhiroh Bambang Widi Pratolo Bella Putra Utama, Agung Betty Masruroh Bety Masruroh Bin Abdul Hadi, Abdul Razak Bin Haji Jait, Adam Cahyo Prayogo, Cahyo Cengiz, Korhan Cholisah Erman Hasihi Chong , Wan Ni Chuttur, Mohammad Yasser Citra Suardi Citra, Hana Rachma Collante, Leonel Hernandez Danang Arengga Wibowo Daniar Wahyu Darwis, Herdianti Dedi Kuswandi Dedy Kuswandi Denis Eka Cahyani Denna Delawanti Chrisyarani, Denna Delawanti Desi Anggreani Dewi, Popy Maulida Dhani Wahyu Wijaya Dhani Wahyu Wijaya Dhaniyar Dhaniyar Didik Dwi Prasetya Didik Nurhadi Didik Suprayogo Dika Fikri L Dityo Kreshna Argeshwara Dityo Kreshna Argeshwara Dwi Jaelani, Mardian dwi yasa, arnelia Dwieb, Mohamed Dwiyanto, Felix Andika Dwiyanto, Felix Andika Dyah Lestari Edinar Valiant Hawali Eka Nurcahya Ningsih Elta Sonalitha Endah Setyo Wardani Erna Daniati Esther Irawati Setiawan Fachrul Kurniawan Fachrul Kurniawan Fachrul Kurniawan Fadhilah, Farhan Fadhilla, Akhmad Fanny Fadhli Almu’iini Ahda Faidzin, Ilham Fajar Purnama Fajarwati, Erliana Faller, Erwin Faradini Usha Setyaputri Farid Miftahuddin Farida Nur Kumala Fauzan Cahya Arifin Fauzy Satrio Wibowo Felix Andika Dwiyanto Felix Andika Dwiyanto Felix Andika Dwiyanto Felix Andika Dwiyanto Ferdinand, Miftakhul Anggita Bima Ferina Ayu Pusparani Filby , Brilliant Filby, Brilliant Fitria, Nimas Dian Fitriana Kurniawati Gianika Roman Sosa Graciello, Manuel Tanbica Gülsün Kurubacak Gunawan Gunawan Gwinny Tirza Rarastri Hammad, Jehad A. H. Hammad, Jehad A.H Hari Putranto Haris Anwar Syafrudie Harits Ar Rasyid Harits Ar Rosyid Hariyono Hariyono Hariyono Hariyono Hariyono Hariyono Hartono, Nickolas Hary Suswanto Hasanuddin, Tasrif Hashim, Ummi Raba’ah Haviluddin Haviluddin Haviluddin, - Hendrawan, William Hartanto Herdianti Darwis Heri Pratikto Herman Herman Herman Thuan To Saurik Heru Nurwarsito Heru Wahyu Herwanto Hery Widijanto Hidayah Kariima Fithri Hidayah, Laily Hidayatul Ma'rifah Hitipeuw, Emanuel Hong, Yeap Chi I Made Wirawan I Nyoman Gede Arya Astawa Idris Ilham Mulya Putra Pradana Imansyah, Pranadya Bagus Imro’aturrozaniyah, Imro’aturrozaniyah Inggar Tri Agustin Mawarni Irsyada, Rahmat Islami, Pio Arfianova Fitrizky Islami, Pio Arfianova Fitrizky Islami, Pio Arfianova Fitrizky Ismail, Amelia Ritahani Istiqlal, Adib Izdihar, Zahra Nabila Jehad A. H. Hammad Jehad A.H. Hammad Jevri Tri Ardiansah Junoh, Ahmad Kadri Juwita Annisa Fauzi Juwita Annisa Fauzi Kaki, Gregorius Paulus Mario Laka Kasturi Kanchymalay, Kasturi Kelvin Wong Khafit Badrus Zaman Khen Dedes Khoiruddin Asfanie Khurin Nabila Kirya Mateeke Moses Kohei Arai Kurniawan, Fachrul Kurniawati, Fitriana Kuswandi, Dedy Laily Hidayah Langlang Gumilar Lauretta, Giovanny Cyntia Lazuardi Noorca Rachmadi Leonel Hernandez Leonel Hernandez Leonel Hernandez Leonel Hernandez, Leonel Lestari, Muqodimah Nur Lestari, Muqodimah Nur Lestari, Muqodimah Nur Liang, Yoeh Wen Lisa Ramadhani Harianti Lisa Ramadhani Harianti Ludovikus Boman Wadu Luther Latumakulita M. Alfian Mizar M. Zainal Arifin Mansoor Abdul Hamid Mantony, Oslida Mao, Yingchi Marchena, Piedad Marida, Tyas Agung Cahyaning Marji Marji Markus Diantoro Masruroh, Bety Mazarina Devi Meiga Ayu Ariyanti Mhd. Irvan, Mhd. Irvan Mifta Dewayani Miftahul Qiki Winata Ming F. Teng Ming Foey Teng Ming Foey Teng, Ming Foey Mochamad Hariadi Moh. Zainul Falah Mohamad Rodhi Faiz Mokh Sholihul Hadi Moses, Kirya Mateeke Moses, Kirya Mateeke Moses, Kirya Mateeke Mudakir, Mudakir Muh. Aliyazid Mude Muhamad Arifin Muhammad Busthomi Arviansyah Muhammad Ferdyan Syach Muhammad Firman Aji Saputra Muhammad Iqbal Akbar Muhammad Jauharul Fuadi Muhammad Nu’man Hakim Muhammad, Abdullahi Uwaisu Muladi Munir Munir Muntholib Muqodimah Nur Lestari Mursyit, Mohammad Nabila Izdihar, Zahra Nabila, Khurin Nada, Anita Qotrun Nadhiroh, Baitun Nadia Roosmalita Sari Nadia Roosmalita Sari Nafalski, Andrew Nastiti Susetyo Fanany Putri Naufal, Ayyub Naziro Nedic, Zorica Nida Jabari Ningsih, Eka Nurcahya Ningtyas, Yana Noorul Islam Novia Ratnasari Novian Candra Kurniawan Noviani, Erina Fika Nugraha, Agil Zaidan Nur Cahyo Wibowo Nur Hidayatullah Nurhalifah, Siti Nurroby Wahyu Saputra Nurul Falah Hashim Nurul Hidayat Oakley, Simon Okazaki Yasuhisa Oki Dwi Yuliana Omar, Saodah Osamu Fukuda Pakpahan, Herman Santoso Paramarta, Andien Khansa’a Iffat Paul Igunda Machumu Pio Arfianova Fitrizky Islami Piska Dwi Nurfadila Praherdhiono, Hendy Prananda Anugrah Prasojo, Fadillah Pratama, Awanda Setya Sanfajar Puji Santoso Puji Santoso Puji Santoso Punaji Setyosari Pundhi Yuliawati Pundhi Yuliawati Purnawansyah Purnawansyah Purnomo Purnomo Purnomo Purnomo Purwatiningsih, Ayu Putra Utama, Agung Bella Putri Syarifa, Dhea Fanny Putri, Desy Pratiwi Ika Putri, Fadia Irsania Putri, Nastiti Susetyo Fanany Qonita, Adiba Rahiddin, Rahillda Nadhirah Norizzaty Rahmadhani, Nur Aini Syafrina Raja, Roesman Ridwan Ratnasari, Novia Rendy Yani Susanto Resty Wulanningrum Ridho, Faiz Mohammad Ridwan Shalahuddin Ridwan Shalahuddin Riri Nada Devita Riri Nada Devita Rizal Kholif Nurrohman Rizqini, Fajriwati Qoyyum Roni Herdianto Rosmin, Norzanah Rr. Poppy Puspitasari, Rr. Poppy Rully Charitas Indra Prahmana Ruth Ema Febrita Salahuddin, Lizawati Salsabila, Reni Fatrisna Santoso, Priyo Aji Saputra, Irzan Tri Sari, Nadia Roosmalita Sarni Suhaila Rahim Seno Isbiyantoro Setiawan, Ariyono Setyadi, Hario Jati Setyaputri, Faradini Usha Setyawan P. Sakti Shahrul, Azzhan Shalahuddin, Ridwan Shiddiqy, Jabar Ash Shidiqi, Maulana Ahmad As Shili, Hechmi Sias, Quota Alief Simbolon, Triyanti Sisca Rahmadonna Siti Helmyati Siti Sendari Soenar Soekopitojo Soraya Norma Mustika Sri Rahmawati Stamen Gadzhanov Subadra, ST. Ulfawanti Intan Sucahyo, Cornaldo Beliarding Sugiarto Cokrowibowo Sugiyanto - Suhiro Wongso Susilo Sujito Sujito Sulistyo, Danang Arbian Sunu Jatmika, Sunu Supeno Mardi Susiki Nugroho, Supeno Mardi Supriadi Supriadi Supriyono Supriyono Suryani, Ani Wilujeng Susilo, Suhiro Wongso Suyono Suyono Suyono Suyono Syaad Patmantara Syaad Patmanthara Syabani, Muhiban Tantri Hari Mukti Tasrif Hasanuddin Trahutomo, Dinnuhoni Tri Kuncoro Tri Lathif Mardi Suryanto Tri Lathif Mardi Suryanto Tri Saputra, Irzan Tri Sutanti Tri Sutanti, Tri Triono, Alfiansyah Putra Pertama Triyanna Widiyaningtyas Triyanna Widyaningtyas Triyanna Widyaningtyas, Triyanna Tsukasa Hirashima Tuatul Mahfud Ummi Rabaah Hasyim Uriu, Wako Utama , Agung Bella Putra Utama, Agung Bella Putra Utomo Pujianto Vira Setia Ningrum Vira Setia Ningrum Vitrail Gloria Mairi Voliansky, Roman Wadu, Ludovikus Boman Wahyu Arbianda Yudha Pratama Wahyu Sakti Gunawan Irianto Wahyu Tri Handoko Wako Uriu Wardani, Endah Setyo Wayan Firdaus Mahmudy Wibowo, Nur Cahyo Widiharso, Prasetya Widiyanintyas, Triyanna Yandratama, Hengky Yasa, Arnelia Dwi Yingchi Mao Yongen Susman Yosi Kristian Yuliana, Oki Dwi Yuliawati, Pundhi Yuni Rahmawati Yusmanto, Yunan Zaeni, Ilham Ari Elbaith Zhou, Xiaofeng Zulkham Umar Rosyidin Zulkham Umar Rosyidin

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