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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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Analysis of the quality of broccoli leaf powder treated by blanching and drying Hamid, Mansoor Abdul; Chong , Wan Ni; Hong, Yeap Chi; Mantony, Oslida; Devi, Mazarina; Soekopitojo, Soenar; Pratikto, Heri; Wibawa, Aji Prasetya; Sugiyanto, Sugiyanto
Anjoro: International Journal of Agriculture and Business Vol 4 No 1 (2023): Anjoro
Publisher : Agribusiness Department, Agriculture and Forestry Faculty, Universitas Sulawesi Barat, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31605/anjoro.v4i1.2350

Brassica oleracea L. italica, the scientific name for broccoli, is a vegetable that is frequently consumed for its florets, which have a number of health benefits. However, other portions of the plant, including the leaves, are almost always discarded despite being good for human health. The study was carried out with the purpose of investigating how the physicochemical characteristics of powdered broccoli leaves were affected by blanching and various drying techniques applied. Broccoli leaves were first blanched in hot water before being dried, which included sun drying, oven drying, cabinet drying, and vacuum drying. The findings demonstrated that blanching enhanced the powder's physical attributes while maintaining its phenolic and flavonoid contents. Blanching also reduced the breakdown of the chlorophyll content in all drying techniques, although this process made it harder to keep the goods' antioxidant function. In conclusion, vacuum drying method of blanched broccoli leaf powder showed the highest retention of physicochemical properties, phytochemical content, and antioxidant activity.

Mean-Median Smoothing Backpropagation Neural Network to Forecast Unique Visitors Time Series of Electronic Journal Wibawa, Aji Prasetya; Utama, Agung Bella Putra; Lestari, Widya; Saputra, Irzan Tri; Izdihar, Zahra Nabila; Pujianto, Utomo; Haviluddin, Haviluddin; Nafalski, Andrew
Journal of Applied Data Sciences Vol 4, No 3: SEPTEMBER 2023
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v4i3.97

Sessions or unique visitors is the number of visitors from one IP who accessed a journal portal for the first time in a certain period of time. The large number of unique daily average subscriber visits to electronic journal pages indicates that this scientific periodical is in high demand. Hence, the number of unique visitors is an important indicator of the accomplishment of an electronic journal as a measure of the dissemination in accelerating the journal accreditation system. Numerous methods can be used for forecasting, one of which is the backpropagation neural network (BPNN). Data quality is very important in building a good BPNN model, because the success of modeling at BPNN is very dependent on input data. One way that can be carried out to improve data quality is by smoothing the data. In this study, the forecasting method for predicting time series data for unique visitors to electronic journals employed three models, respectively BPNN, BPNN with mean smoothing, and BPNN with median smoothing. Based on the findings, the results of the smallest error were obtained by the BPNN model with a mean smoothing with MSE 0.00129 and RMSE 0.03518 with a learning rate of 0.4 on 1-2-1 architecture which can be used as a forecast for unique visitors of electronic journals.

Exploring Visitor Sentiments: A Study of Nusantara Temple Reviews on TripAdvisor Using Machine Learning Hariyono, Hariyono; Wibawa, Aji Prasetya; Noviani, Erina Fika; Lauretta, Giovanny Cyntia; Citra, Hana Rachma; Utama, Agung Bella Putra; Dwiyanto, Felix Andika
Journal of Applied Data Sciences Vol 5, No 2: MAY 2024
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v5i2.208

This study examines the mood of tourist evaluations for the Nusantara Temples, such as Borobudur, Prambanan, Ijo, Plaosan, and Mendut Temples, on TripAdvisor using Stochastic Gradient Descent (SGD), Logistic Regression (LR), and Support Vector Machine (SVM) classification techniques. The study examines the viewpoints and encounters of tourists from different nations on Indonesia's cultural legacy through English-language evaluations. The evaluation findings show that LR achieves the highest performance in sentiment classification, with an accuracy rate of 91.66%. The research offers valuable insights but has limits in portraying local visitors and relies heavily on the English language. Future studies might focus on doing sentiment analysis on more historical tourism sites in Indonesia, integrating multilingual data, and experimenting with novel categorization methods. This study significantly enhances our understanding of how technology and social media impact tourists' impressions of cultural heritage in the digital age via strengthening analytical methodologies and investigating alternative destinations.

Cognition-Based Document Matching Within the Chatbot Modeling Framework Jatmika, Sunu; Patmanthara, Syaad; Wibawa, Aji Prasetya; Kurniawan, Fachrul
Journal of Applied Data Sciences Vol 5, No 2: MAY 2024
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v5i2.209

The aim of the study is to examine cognitive methods for document matching in a chatbot modeling framework by utilizing Euclidean Distance, Cosine Similarity, and BERT methodologies. Five primary indications are used to carry out evaluation in testing: document matching accuracy, document matching execution time, document search efficiency, consistency of document matching results, and the quality of the document representation in the matrix. Document matching accuracy is evaluated by precision; document matching execution time is measured from the beginning to the end of the document matching process; document search efficiency is measured through evaluation of execution time and matching accuracy; the consistency of document matching results is assessed by comparing method results when tested against the same or similar queries and the quality of document representation is assessed based on the method's ability to represent documents in a matrix or vector. The test findings offer a comprehensive understanding of how well the three approaches operate and exhibit their capacity to address the unique requirements of chatbot users. These results may contribute to the advancement of language technology applications, making it possible for chatbots to deliver pertinent information more rapidly and precisely. There are 1,755 labeled question samples in the dataset, which were split up into two sets: 60% for training (1,053 pieces), and 40% for testing (702 samples) to evaluate the model's performance. The test results show the accuracy of the three methods based on five measured evaluation indications, namely Euclidean Distance 0,45%, Cosine similarity 0,59%, and BERT 0,91%. By comprehending the benefits and drawbacks of each approach, this research strengthens contributions to the growth of chatbot systems to better serve user demands and opens the door for the creation of more complex human-machine interaction solutions.

LSTM-Based Machine Translation for Madurese-Indonesian Sulistyo, Danang Arbian; Wibawa, Aji Prasetya; Prasetya, Didik Dwi; Ahda, Fadhli Almu'iini
Journal of Applied Data Sciences Vol 4, No 3: SEPTEMBER 2023
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v4i3.113

Madurese is one of the regional languages in Indonesia, which dominates East Java and Madura Island in particular. The use of Madurese as a daily language has declined significantly due to a language shift in children and adolescents, some of which are caused by a sense of prestige and difficulty in learning Madurese. The scarcity of research or scientific titles that raises the Madurese language also helps reduce literacy in the language. Our research focuses on creating a translation machine for Madurese to Indonesian to maintain and preserve the existence of the Madurese language so that learning can be done through digital media. This study use the latest dataset for the Madurese-Indonesian language by using a corpus of 30,000 Madura-Indonesian sentence pairs from the online Bible. This study scrapped online Bible pages to organize the corpus based on the Indonesian and Madurese bilingual Bible. Then This study manually process text to match the two languages' scrapping results, normalization, and tokenization to remove non-printable characters and punctuation from the corpus. To perform neural machine translation (NMT), This study connected the RNN encoder with the RNN decoder of the language model, while for training and testing, This study used a sequential model with LSTM, while the BLEU measure was used to assess the accuracy of the translation results. This study used the SoftMax optimization function with Adam Optimizer and added some settings, including using 128 layers in the training process and adding a Dropout layer so that This study got the average evaluation result for BLEU-1 is 0.798068, BLEU-2 is 0.680932, BLEU-3 is 0.623489, and for BLEU-4 is 0.523546 from five tests conducted. Given the language differences between Madurese and Indonesian, this can be the best approach for machine translation of Indonesian to Madurese.

Decision tree based algorithms for Indonesian Language Sign System (SIBI) recognition Nugraha, Agil Zaidan; Salsabila, Reni Fatrisna; Handayani, Anik Nur; Wibawa, Aji Prasetya; Hitipeuw, Emanuel; Arai, Kohei
Applied Engineering and Technology Vol 3, No 2 (2024): August 2024
Publisher : ASCEE

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/aet.v3i2.1536

Indonesian Sign Language System (SIBI) recognition plays a crucial role in improving effective communication for individuals with hearing loss in Indonesia. To support automatic SIBI recognition, this research presents a performance analysis of two main algorithms, namely Decision Tree and C4.5, in the context of the SIBI recognition task. This research utilizes a rich SIBI dataset that includes a variety of SIBI signs used in everyday communication. Data pre-processing, model construction with both algorithms, and model performance evaluation using accuracy, precision, recall, and F1-score metrics are all part of the study. Regarding SIBI recognition accuracy, the experimental results demonstrate that the Decision Tree performs better than Decision Tree. The Decision Tree also makes models that are easier to understand, which is important for making communication systems based on SIBI.

Performance analysis of random forest on quartile classification journal Sucahyo, Cornaldo Beliarding; Rizqini, Fajriwati Qoyyum; Naufal, Ayyub; Yandratama, Hengky; Shiddiqy, Jabar Ash; Utama, Agung Bella Putra; Putri, Nastiti Susetyo Fanany; Wibawa, Aji Prasetya
Applied Engineering and Technology Vol 3, No 1 (2024): April 2024
Publisher : ASCEE

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/aet.v3i1.1189

Journals play a pivotal role in disseminating scientific knowledge, housing a multitude of valuable research articles. In this digital age, the evaluation of journals and their quality is essential. The SCImago Journal Rank (SJR) stands as one of the prominent platforms for ranking journals, categorizing them into five index classes: Q1, Q2, Q3, Q4, and NQ. Determining these index classes often relies on classification methodologies. This research, drawing inspiration from the Cross-Industry Standard Process for Data Mining (CRISP-DM), seeks to employ the Random Forest method to classify journals, thus contributing to the refinement of journal ranking processes. Random Forest stands out as a robust choice due to its remarkable ability to mitigate overfitting, a common challenge in machine learning classification tasks. In the context of approximating SJR index classes, Random Forest, when utilizing the Gini index, exhibits promise, albeit with an initial accuracy rate of 62.12%. The Gini index, an impurity measure, enables Random Forest to make informed decisions while classifying journals into their respective SJR index classes. However, it is worth noting that this accuracy rate represents a starting point, and further refinement and feature engineering may enhance the model's performance. This research underscores the significance of machine learning techniques in the domain of journal classification and journal-ranking systems. By harnessing the power of Random Forest, this study aims to facilitate more accurate and efficient categorization of journals, thereby aiding researchers, academics, and institutions in identifying and accessing high-quality scientific literature.

[AET Volume 2 Nomor 3] Environmental, medical, and educational research sustainability in the age of technology: An editorial review Pranolo, Andri; Hernandez, Leonel; Wibawa, Aji Prasetya
Applied Engineering and Technology Vol 2, No 3 (2023): December 2023
Publisher : ASCEE

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/aet.v2i3.1363

The six articles on Applied Engineering and Technology Volume 2 No 3 December 2023 have significant relevance in current engineering and technological developments to the three sectors: Environmental sustainability, Medical, and Education. First, in an era that increasingly pays attention to environmental sustainability, as reflected in efforts to mitigate the environmental impact of the oil and gas industry, Effiom's research on developing bio-based drilling fluid becomes relevant and reflects the industry's efforts to adopt environmentally friendly solutions in the oil and gas exploration process [1]. This research develops and optimizes local pear seed-based biocyte fluid. Throughout the world, oil exploration and exploitation have had severe environmental impacts. So, it is very important to develop drilling fluid for oil exploration. This research optimizes drilling fluids by using biodegradable materials. The optimized drilling fluid contains environmentally friendly and cost-effective characteristics and is expected to be widely used in oil exploration, reducing adverse environmental impacts. Princewill et al. [2] conducted a safety and economic evaluation of boil-off gas (BOG) in global petroleum (LPG) storage tanks. BOG production impacts safety and economic profitability in the liquefied petroleum gas supply chain. This research evaluates BOG production due to heat leaks in storage tanks by analyzing thermodynamic properties and heat transfer equations. The research results show that maintaining isolation and external factors minimizes BOG formation. Therefore, this research provides essential guidance and suggestions for the safety and economic benefits of the liquefied petroleum gas supply chain. Finally, Yudanto et al. [3] used computational fluid dynamics (CFD) and Taguchi methods to calculate the CPU cooling system. The performance and stability of electronic devices are significant for users in today's rapid development of information technology. This study analyzes the impact of different cooling system configurations on CPU temperatures and provides practical insights into electronic thermite design. Through numerical simulations, the research results provide an essential reference for developing computer hardware design. Second, Agughasi and Srinivasiah [4] developed a semisupervised method for characterizing multiple chest X-ray images in the medical field. Accurate marker images are critical for training supervised learning models in medical image handling. However, manually tagging a large number of images requires time and effort. Therefore, this study suggests using unsupervised cluster technology-based K-Means and Self-Organizing Maps to produce reliable images. In this way, medical imaging processing costs can be reduced significantly, speeding up the research and application process. Meanwhile, in the education sector, Mariscal et al. [5] developed the mobile application MobILcaps to improve information literacy for social science students in higher education as a relevant instrument to facilitate teaching. Information literacy is crucial for developing individuals and society in today's information era. Based on cognitive, constructivist, and connectivity theories, this application has provided multimedia resources for students to facilitate independent learning. By working with teachers and students, this application provides practical tools and avenues for increasing students' information literacy levels. In addition, Riva et al. [6] developed AdPisika as an electronic learning system tailored to improve student academic achievement. In today's educational environment, personalized learning is critical to increasing the impact of learning for students. This research, based on learning style models and machine learning algorithms, personally optimizes learning materials, thereby improving students' learning performance. This system has significantly improved students' academic performance through experimental verification, providing practical ways to align education. In conclusion, these studies make essential contributions and provide valuable references and guidance for applying engineering and technology research and practice in the fields of Environmental sustainability, Medical, and Education. Future research could investigate the depth and breadth of these areas and test the feasibility and effectiveness of such research through practical applications and experimental testing. In the context of environmental sustainability potential research includes exploration in the development of bio-based drilling fluid using alternative materials that are more environmentally friendly, research on green technology to reduce the impact of boil-off gas (BOG) in the LPG industry, and research on processor types and system configurations as well as the development of more efficient materials and more innovative cooling technology to improve the performance of the CPU cooling system. In the medical field, deepen semi-supervised labeling methods for medical image processing can focus on developing more sophisticated algorithms and further validation of various medical datasets. Meanwhile, in the educational context, developing broader mobile applications could increase information literacy. It could be useful if it adapted to various disciplines and research on integrating more advanced AI technology for adaptive e-learning systems more effectively.

Perbandingan Instance Segmentation Image Pada Yolo8 Wulanningrum, Resty; Handayani, Anik Nur; Wibawa, Aji Prasetya
Jurnal Teknologi Informasi dan Ilmu Komputer Vol 11 No 4: Agustus 2024
Publisher : Fakultas Ilmu Komputer, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25126/jtiik.1148288

Seorang pejalan kaki sangat rawan terhadap kecelakaan di jalan. Deteksi pejalan kaki merupakan salah satu cara untuk mengidentifikasi atau megklasifikasikan antara orang, jalan atau yang lainnya. Instance segmentation adalah salah satu proses untuk melakukan segmentasi antara orang dan jalan. Instance segmentation dan penggunaan yolov8 merupakan salah satu implementasi dalam deteksi pejalan kaki. Perbandingan segmentasi pada dataset Penn-Fundan Database menggunakan yolov8 dengan model yolov8n-seg, yolov8s-seg, yolov8m-seg, yolov8l-seg, yolov8x-seg. Penelitian ini menggunakan dataset publik pedestrian atau pejalan kaki dengan objek multi person yang diambil dari dataset Penn-Fudan Database. Dataset mempunyai 2 kelas, yaitu orang dan jalan. Hasil perbandingan penggunaan model yolov8 model segmentasi yang terbaik adalah menggunakan model yolov8l-seg. Hasil penelitian didapatkan Instance segmentation valid box pada data orang, mAP50 tertinggi pada yolov8l-seg dengan nilai 0,828 dan mAP50-95 adalah 0,723. Instance segmentation valid mask pada orang nilai mAP50 tertinggi pada yolov8l-seg dengan nilai 0,825 dan mAP50-95 adalah 0,645. Pada penelitian ini, yolov8l-seg menjadi nilai terbaik dibandingkan versi yang lain, karena berdasarkan nilai mAP tertinggi pada valid mask sebesar 0,825. Abstract A pedestrian is very vulnerable to road accidents. Pedestrian detection is one way to identify or classify between people, roads or others. Instance segmentation is one of the processes to segment people and roads. Instance segmentation and the use of yolov8 is one of the implementations in pedestrian detection. Comparison of segmentation on Penn-Fundan Database dataset using yolov8 with yolov8n-seg, yolov8s-seg, yolov8m-seg, yolov8l-seg, yolov8x-seg models. This research uses a public pedestrian dataset with multi-person objects taken from the Penn-Fudan Database dataset. The dataset has 2 classes, namely people and roads. The results of the comparison using the yolov8 model, the best segmentation model is using the yolov8l-seg model. The results obtained Instance segmentation valid box on people data, the highest mAP50 on yolov8l-seg with a value of 0.828 and mAP50-95 is 0.723. Instance segmentation valid mask on people the highest mAP50 value on yolov8l-seg with a value of 0.825 and mAP50-95 is 0.645. In his study, yolov8l-seg is the best value compared to other versions, because based on the highest mAP value on the valid mask of 0.825.

Photovoltaic Energy Anomaly Detection using Transformer Based Machine Learning Wirawan, I Made; Wibawa, Aji Prasetya; Widiyanintyas, Triyanna
International Journal of Robotics and Control Systems Vol 4, No 3 (2024)
Publisher : Association for Scientific Computing Electronics and Engineering (ASCEE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/ijrcs.v4i3.1260

This study uses the Anomaly Transformer model to find anomalies in photovoltaic energy generation in Malang, Indonesia. The main background of this study is the lack of satellite monitoring in this region and the importance of annual data for electricity generation forecasting. Temperature scattered direct solar radiation, and hourly electricity production are all part of the dataset used which is only available since 2019. Anomalies were detected at 05.00 and 16.00 WIB, indicating instability in the energy supply due to high temperatures in the morning and heavy rain in the afternoon. Detection of these anomalies is important to improve the efficiency and reliability of photovoltaic systems, reduce operational costs, and reduce the risk of system failure. Indonesia has many challenges for photovoltaic energy generation due to its unique location, with many islands located close to the equator. The use of the Anomaly Transformer algorithm improves the accuracy of anomaly detection over conventional methods. This algorithm helps to find complex patterns in very large time series. The results show that the anomaly transformer model can effectively detect anomalous patterns. It offers ideas to improve the stability and efficiency of photovoltaic systems in Malang and other areas with comparable environmental conditions. Improved energy efficiency and environmental sustainability are the results of anomaly pattern detection.

Co-Authors A.N. Afandi Abd. Rasyid Syamsuri Abdur Rohman Achmad Fanany Onnilita Gaffar Adaby, Resnu Wahyu Ade Kurnia Ganesh Akbari 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 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 Arbian Sulistyo, Danang 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 Daniar Wahyu Darwis, Herdianti Dedes, Khen Dedi Kuswandi Dedy Kuswandi Denis Eka Cahyani Denna Delawanti Chrisyarani, Denna Delawanti Desi Anggreani Devita, Riri Nada Dewandra, Aderyan Reynaldi Fahrezza 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 Drezewski, Rafał 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 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 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 Idris Ilham Mulya Putra Pradana Imansyah, Pranadya Bagus Imro’aturrozaniyah, Imro’aturrozaniyah Inggar Tri Agustin Mawarni Irsyada, Rahmat Islam, Noorul Islami, Pio Arfianova Fitrizky Islami, Pio Arfianova Fitrizky Islami, Pio Arfianova Fitrizky Ismail, Amelia Ritahani Istiqlal, Adib Izdihar, Zahra Nabila Jabari, Nida 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 Khoiruddin Asfanie Khurin Nabila Kirya Mateeke Moses Kohei Arai Kurniawan, Fachrul Kurniawan, Novian Candra Kurniawati, Fitriana Kuswandi, Dedy Laily Hidayah Langlang Gumilar Lauretta, Giovanny Cyntia Lazuardi Noorca Rachmadi 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 Mairi, Vitrail Gloria 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 Ningsih, Eka Nurcahya Ningtyas, Yana Novia Ratnasari Noviani, Erina Fika Nugraha, Agil Zaidan Nur Cahyo Wibowo Nur Hidayatullah Nurfadila, Piska Dwi Nurhalifah, Siti Nuril Anwar, Nuril Nurroby Wahyu Saputra Nurul Falah Hashim Nurul Hidayat Nuryana, Zalik 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 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 Putra, Agung Bella Utama Putri Syarifa, Dhea Fanny Putri, Desy Pratiwi Ika Putri, Fadia Irsania Putri, Nastiti Susetyo Fanany Qonita, Adiba Raden Mohamad Herdian Bhakti 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 Rizal Kholif Nurrohman Rizqini, Fajriwati Qoyyum Roni Herdianto Rosmin, Norzanah Rr. Poppy Puspitasari, Rr. Poppy Rully Charitas Indra Prahmana Ruth Ema Febrita Saifullah, Shoffan 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 Stamen Gadzhanov Subadra, ST. Ulfawanti Intan Sucahyo, Cornaldo Beliarding Sugiarto Cokrowibowo Sugiyanto - Suhiro Wongso Susilo Sujito Sujito Sularso Sularso, Sularso 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 Andi, Tri 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 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, Danang Arengga Wibowo, Fauzy Satrio 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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