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Facemask Detection using the YOLO-v5 Algorithm: Assessing Dataset Variation and R esolutions Kurniawan, Fachrul; Astawa, I Nyoman Gede Arya; Atmaja, I Made Ari Dwi Suta; Wibawa, Aji Prasetya
Register: Jurnal Ilmiah Teknologi Sistem Informasi Vol 9 No 2 (2023): July
Publisher : Information Systems - Universitas Pesantren Tinggi Darul Ulum

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26594/register.v9i2.3249

Abstract

The Covid-19 pandemic has made it imperative to prioritize health standards in companies and public areas with a large number of people. Typically, officers oversee the usage of masks in public spaces; however, computer vision can be employed to facilitate this process. This study focuses on the detection of facemask usage utilizing the YOLO-v5 algorithm across various datasets and resolutions. Three datasets were employed: the face with mask dataset (M dataset), the synthetic dataset (S dataset), and the combined dataset (G dataset), with image resolutions of 320 pixels and 640 pixels, respectively. The objective of this study is to assess the accuracy of the YOLO-v5 algorithm in detecting whether an individual is wearing a mask or not. In addition, the algorithm was tested on a dataset comprising individuals wearing masks and a synthetic dataset. The training results indicate that higher resolutions lead to longer training times, but yield excellent prediction outcomes. The system test results demonstrate that face image detection using the YOLO-v5 method performs exceptionally well at a resolution of 640 pixels, achieving a detection rate of 99.2 percent for the G dataset, 98.5 percent for the S dataset, and 98.9 percent for the M dataset. These test results provide evidence that the YOLO-v5 algorithm is highly recommended for accurate detection of facemask usage.
Pengembangan Sistem Informasi Pengelolaan Konferensi Internasional Universitas Negeri Malang dengan Menggunakan Metode Waterfall Wibawa, Aji Prasetya; Diantoro, Markus; Idris, Idris; Purnomo, Agus; Kurniawan, Novian Candra
Jurnal Teknologi Sistem Informasi dan Aplikasi Vol. 7 No. 1 (2024): Jurnal Teknologi Sistem Informasi dan Aplikasi
Publisher : Program Studi Teknik Informatika Universitas Pamulang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32493/jtsi.v7i1.34974

Abstract

An international conference is an event that involves researchers from around the world. This will certainly provide a broader view of the knowledge gained. Problems with the information system managed by the organizer. This problem will certainly hamper the productivity of the organizers. Therefore, the focus of this development is to provide convenience for organizers in conducting conference management that is being held. The method used in this research is waterfall using 4 stages, namely analysis, design, coding, and testing.  The selection of the waterfall method is because the stages in the waterfall are systematic in sequence. This certainly makes it easy for developers to create information systems. The results of this development resulted in an application entitled International Conference State University of Malang "ICON-UM". Based on the results of black-box testing, it is interpreted that all functions developed run optimally. This system can be a recommendation for international conference organizers.
Implementasi Mesin Pencacah Rumput Otomatis Menggunakan Panel Surya sebagai Solusi Efektif untuk Ternak Sapi Aripriharta, Aripriharta; Wibawa, Aji Prasetya; Sujito, Sujito; Mizar, Alfian; Faidzin, Ilham; Rahmadhani, Nur Aini Syafrina; Bagaskoro, Muhammad Cahyo
Abditeknika Jurnal Pengabdian Masyarakat Vol. 4 No. 2 (2024): Oktober
Publisher : LPPM Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/abditeknika.v4i2.4919

Abstract

Peternakan Lembu Ndeso yang berlokasi di Desa Kedungrejo, Kecamatan Pakis, Kabupaten Malang, Jawa Timur 65154 dan berfokus pada perkembangbiakan sapi. Peternakan ini menghadapi kesulitan signifikan dalam memproses pakan ternak secara efisien dan dalam jumlah yang memadai. Proses pencacahan pakan secara manual tidak hanya memakan waktu dan tenaga yang besar, tetapi juga menghasilkan hasil yang tidak seragam dan tidak efisien, yang menyebabkan pemborosan sumber daya. Dampaknya, produktivitas peternakan sapi terhambat dan pendapatan peternak menurun. Solusi yang diusulkan adalah penggunaan teknologi tepat guna (TTG) berupa mesin pencacah rumput yang didukung oleh Pembangkit Listrik Tenaga Surya (PLTS). Mesin ini dirancang untuk mempercepat dan meningkatkan efisiensi proses pencacahan pakan ternak. Manfaatnya termasuk peningkatan efisiensi dan efektivitas pencacahan pakan, proses yang lebih ramah lingkungan dengan memanfaatkan energi surya, serta kemudahan dalam pengendalian dan pemantauan operasional mesin. Proses perencanaan dan perancangan teknologi ini melibatkan observasi langsung, pencatatan detail, dan wawancara dengan mitra usaha, dengan tujuan menghasilkan solusi TTG yang berkelanjutan dan memberikan manfaat jangka panjang bagi para peternak Lembu Ndeso. Dengan demikian, teknologi ini diharapkan dapat membantu peternak dalam mengelola pakan ternak mereka secara lebih efisien dan meningkatkan kesejahteraan peternak. Hasil implementasi menunjukkan bahwa mesin pencacah rumput yang didukung PLTS berhasil meningkatkan efisiensi proses pencacahan pakan, dengan panel surya menghasilkan daya optimal pada cuaca cerah dan tetap berfungsi meskipun ada variasi cuaca. Pelatihan penggunaan mesin kepada warga Desa Kedungrejo mendapat antusiasme tinggi, dan serah terima teknologi kepada mitra berjalan lancar, menandakan potensi keberlanjutan penggunaan teknologi ini untuk meningkatkan produktivitas peternakan Lembu Ndeso.   Lembu Ndeso Farm, located in Kedungrejo Village, Pakis District, Malang Regency, East Java 65154, focuses on cattle breeding. The farm faced significant difficulties in processing animal feed efficiently and in sufficient quantities. The manual process of chopping feed is not only time-consuming and labor-intensive, but also produces non-uniform and inefficient results, leading to a waste of resources. As a result, cattle farming productivity is hampered and farmers' income decreases. The proposed solution is the use of appropriate technology (TTG) in the form of a grass chopping machine powered by a Solar Power Plant (PLTS). The machine is designed to speed up and improve the efficiency of the fodder chopping process. The benefits include increased efficiency and effectiveness of feed chopping, a more environmentally friendly process by utilizing solar energy, and ease in controlling and monitoring machine operations. The process of planning and designing this technology involved direct observation, detailed note-taking and interviews with business partners, aiming to produce a sustainable TTG solution that provides long-term benefits to Lembu Ndeso farmers. Thus, this technology is expected to help farmers manage their animal feed more efficiently and improve the welfare of farmers.
Comparison of Adam Optimization and RMS prop in Minangkabau-Indonesian Bidirectional Translation with Neural Machine Translation Ahda, Fadhli Almu'iini; Wibawa, Aji Prasetya; Dwi Prasetya, Didik; Arbian Sulistyo, Danang
JOIV : International Journal on Informatics Visualization Vol 8, No 1 (2024)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/joiv.8.1.1818

Abstract

Language is a tool humans use to establish communication. Still, the language used is one language and between regions or nations with their languages. Indonesia is a country that has a diversity of second languages and is the fourth most populous country in the world. It is recorded that Indonesia has nearly 800 regional languages, but research activities in natural language processing are still lacking. Minangkabau is an endangered language spoken by the Minangkabau people in Indonesia's West Sumatra province. According to UNESCO, the Minangkabau language is listed as a language that is "definitely endangered," with only around 5 million speakers worldwide. This study uses neural machine translation (NMT) to create a formula based on this information. Neural machine translation, in contrast to conventional statistical machine translation, intends to build a single neural network that can be built up to achieve the best performance. Because it can simultaneously hold memory for a long time, comprehend complicated relationships in data, and provide information that is very important in determining the outcome of translation, LSTM is one of the most powerful machine-learning techniques for translating languages. The BLUE score is utilized in the NMT evaluation. The test results use 520 Minangkabau sentences, conducting tests based on the number of epochs ranging from 100-1000, resulting in optimization using Adam being better than optimization RMSprop. This is evidenced by the results of the best BLUE-1 score of 0.997816 using 1000 epochs.
Attention-Enhanced Convolutional Neural Network for Context Extraction in Andersen's Fairy Tales Daniati, Erna; Wibawa, Aji Prasetya; Irianto, Wahyu Sakti Gunawan; Nafalski, Andrew
JOIV : International Journal on Informatics Visualization Vol 9, No 6 (2025)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/joiv.9.6.4056

Abstract

Event extraction in classic literature and fairy tales remains highly challenging due to their non-linear plot structures, archaic linguistic expressions, and intricate character interactions, while advances in modern NLP still show limitations in capturing subtle narrative cues in historical texts. This study aims to address these gaps by developing an event extraction model tailored to the narrative characteristics of Hans Christian Andersen’s fairy tales. We propose a BERT-enhanced Context-aware Convolutional Neural Network (CNN) that integrates an attention mechanism to overcome the limited contextual range of traditional CNNs. The model leverages BERT’s contextual embeddings enriched with an attention layer to detect event triggers, character relations, and narrative transitions across nonlinear storylines. A hybrid dataset was constructed through system-generated annotations refined via manual verification and combined with AN/an cartoon-based representations for model training and final testing. Experimental results show that the proposed model surpasses both the CNN-only baseline and a rule-based approach, achieving precision of 0.92, recall of 0.89, F1-score of 0.90, and accuracy of 0.91, outperforming the CNN baseline (0.85/0.82/0.83/0.84) and rule-based system (0.78/0.75/0.76/0.77). These findings highlight the effectiveness of context-aware representations for processing literary narratives and demonstrate interdisciplinary relevance to digital humanities and AI-based storytelling, with future extensions envisioned for multilingual settings and genre-specific adaptations.
Geographic-Origin Music Classification from Numerical Audio Features: Integrating Unsupervised Clustering with Supervised Models Pranolo, Andri; Sularso, Sularso; Anwar, Nuril; Putra, Agung Bella Utama; Wibawa, Aji Prasetya; Saifullah, Shoffan; Dreżewski, Rafał; Nuryana, Zalik; Andi, Tri
Buletin Ilmiah Sarjana Teknik Elektro Vol. 7 No. 4 (2025): December
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/biste.v7i4.13400

Abstract

Classifying the geographic origin of music is a relevant task in music information retrieval, yet most studies have focused on genre or style recognition rather than regional origin. This study evaluates Support Vector Machine (SVM) and Convolutional Neural Network (CNN) models on the UCI Geographical Origin of Music dataset (1,059 tracks from 33 non-Western regions) using numerical audio features. To incorporate latent structure, we first applied K-means clustering with the optimal number of clusters (k=2) determined by the Elbow and Silhouette methods. The cluster assignments were used as auxiliary signals for training, while evaluation relied on the true region labels. Classification performance was assessed with Accuracy, Precision, Recall, and F1-score. Results show that SVM achieved 99.53% accuracy (95% CI: 97.38–99.92%), while CNN reached 98.58% accuracy (95% CI: 95.92–99.52%); Precision, Recall, and F1 mirrored these values. The differences confirm SVM’s superior performance on this dataset, though the near-perfect scores also suggest strong separability in the feature space and potential risks of overfitting. Learning-curve analysis indicated stable training, and cluster supervision provided small but consistent benefits. Overall, SVM remains a reliable baseline for tabular music features, while CNNs may require spectro-temporal representations to leverage their full potential. Future work should validate these findings across multiple datasets, apply cross-validation with statistical significance testing, and explore hybrid deep models for broader generalization.
A hermeneutic inquiry into musical meaning in AI-generated music: a case study of Suno AI’s text-to-music system Ratnasari, Novia; Wibawa, Aji Prasetya; Patmanthara, Syaad
Gelar: Jurnal Seni Budaya Vol. 23 No. 2 (2025)
Publisher : Institut Seni Indonesia Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33153/glr.v23i2.7763

Abstract

This study examines how generative artificial intelligence participates in the creation and interpretation of musical meaning, using Suno AI’s text-to-music system as a focused case. The research explores how machine-generated sound can be understood hermeneutically, particularly how linguistic prompts, probabilistic modeling, and audio generation processes shape meaning, emotion, and musical intention. The study aims to determine the extent to which generative AI functions as an epistemic collaborator rather than a passive tool and how its outputs align with or diverge from human interpretive expectations. Using a digital epistemological hermeneutic framework operationalized through prompt-based observation, semantic interpretation, and comparative listening, the study conducted controlled experiments varying genre, instrument, mood, and tempo. Each output was evaluated in terms of expressive quality, emotional valence, stylistic coherence, and prompt response fidelity. The findings indicate that generative AI constructs musical meaning through representational inference, producing sonic forms that partially reflect the semantic cues embedded in linguistic prompts. Although the system does not exhibit human-like intentionality, its probabilistic structures generate patterns that resonate with human affective and interpretive frameworks, creating a co-creative space where human prompts and machine inference jointly shape musical expression. These insights demonstrate the usefulness of hermeneutics as a methodological lens for understanding AI-mediated creativity and highlight the importance of prompt design, model transparency, and human-machine interpretive dynamics in future computational musicology and creative AI research.
Combination of Feature Extractions for Classification of Coral Reef Fish Types Using Backpropagation Neural Network Latumakulita, Luther Alexander; Arya Astawa, I Nyoman Gede; Mairi, Vitrail Gloria; Purnama, Fajar; Wibawa, Aji Prasetya; Jabari, Nida; Islam, Noorul
JOIV : International Journal on Informatics Visualization Vol 6, No 3 (2022)
Publisher : Society of Visual Informatics

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

Abstract

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.
Neural Machine Translation of Spanish-English Food Recipes Using LSTM Dedes, Khen; Putra Utama, Agung Bella; Wibawa, Aji Prasetya; Afandi, Arif Nur; Handayani, Anik Nur; Hernandez, Leonel
JOIV : International Journal on Informatics Visualization Vol 6, No 2 (2022)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30630/joiv.6.2.804

Abstract

Nowadays, food is one of the things that has been globalized, and everyone from different parts of the world has been able to cook food from other countries through existing online recipes. Based on that, this study developed a translation formula using a neural machine translation (NMT). NMT is a recently proposed approach to machine translation. Unlike the traditional statistical machine translation, the neural machine translation aims at building a single neural network that can be jointly tuned to maximize the translation performance. The models proposed recently for neural machine translation often belong to a family of encoder–decoders. Our experiment led to novel insights and practical advice for building and extending NMT with the applied long short-term memory (LSTM) method to 47 bilingual food recipes between Spanish-English and English-Spanish. LSTM is one of the best machine learning methods for translating languages because it can retain memories for an extended period concurrently, grasp complicated connections between data, and provides highly useful information in deciding translation outcomes. The evaluation for this neural machine translation is to use BLEU. The comparing results show that the translation of recipes from Spanish-English has a better BLEU value of 0.998426 than English-Spanish with a data-sharing of 70%:30% during epoch 1000. Researchers can convert the country's popular cuisine recipes into another language for further research, allowing it to become more widely recognized abroad.
Pelatihan Penyusunan Proposal Penelitian dan Pengabdian untuk Dosen STIEBI Syaikhona Kholil Sidogiri Pasuruan ST. Ulfawanti Intan Subadra; Sri Rahmawati; Aji Prasetya Wibawa; RR. Poppy Puspitasari; Nurul Hidayat; Ahmad Taufiq
I-Com: Indonesian Community Journal Vol 5 No 2 (2025): I-Com: Indonesian Community Journal (Juni 2025)
Publisher : Fakultas Sains Dan Teknologi, Universitas Raden Rahmat Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70609/icom.v5i2.6888

Abstract

Research and community service are part of the Tri Dharma of Higher Education that must be carried out by a lecturer. In fact, the Government has provided funds for lecturers to carry out research and community service. However, low motivation, interest, and knowledge in writing are some of the reasons why lecturers do not write proposals. Therefore, the community service team conducted training on writing research and community service proposals for lecturers at the Syaikhona Kholil Islamic Economics and Business College, Pasuruan. The training was conducted using lecture and direct practice methods, and was divided into three sessions. The evaluation results showed that 100% of participants stated that the material presented was in accordance with the needs of the participants and the strategies used in the training were very effective. This activity had a positive impact on lecturers' motivation in writing proposals. In addition, knowledge and ability in using the Zotero reference manager also increased, making it easier for STEIBI Syaikhona Kholil lecturers to write references both in proposals and in scientific articles.
Co-Authors A.N. Afandi Abd. Rasyid Syamsuri Abdullah Sholum Abdur Rohman Achmad Fanany Onnilita Gaffar Adaby, Resnu Wahyu Ade Kurnia Ganesh Akbari Adil Zakaria 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 Agustinus Noertjahyana Ahmad 'Ammar Musyaffa' 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 Alamsyah, David Satria Aldy Rahmat Yulianto Alfiansyah Putra Pertama Triono Ali, Martina Alifah Diantebes Aindra Amro, Manar Y 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 Anik Nur Handayani Anton Prafanto Anusua Ghosh Anusua Ghosh, Anusua Ardha Ardhana Putra Agustavada Ardiansyah, Mohammad Iqbal Firman Aripriharta - Arya Tandy Hermawan Ashar, Muhammad Astuti, Wistiani Atmaja, I Made Ari Dwi Suta Atmaja, Nimas Hadi Azizah, Desi Fatkhi 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 Che Pee, Ahmad Naim Chong , Wan Ni Chuttur, Mohammad Yasser Citra Suardi Citra, Hana Rachma Collante, Leonel Hernandez Dafa Fadhilah Hilmi Danang Arbian Sulistyo Daniar Wahyu Darwis, Herdianti David Satria Alamsyah Dedes, Khen Dedi Kuswandi Dedy Kuswandi Denis Eka Cahyani Denna Delawanti Chrisyarani, Denna Delawanti Desi Anggreani Devi Dwi Purwanto 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 Eva, Nur Fachrul Kurniawan Fachrul Kurniawan Fachrul Kurniawan Fadhilah, Farhan Fadhilla, Akhmad Fanny Fadhli Almu’iini Ahda Fadia Irsania Putri 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 Felix Andika Dwiyanto Ferdinand, Miftakhul Anggita Bima Ferina Ayu Pusparani Filby , Brilliant Filby, Brilliant Fitria, Nimas Dian Fitriana Kurniawati Fukuda, Osamu Gianika Roman Sosa Graciello, Manuel Tanbica Gülsün Kurubacak Gunawan Gunawan Gwinny Tirza Rarastri Hakkun Elmunsyah Hammad, Jehad A. H. Hammad, Jehad A.H Handayani , Anik Nur 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 Hasihi, Cholisah Erman Haviluddin Haviluddin Haviluddin, - Hendrawan, William Hartanto Heri Pratikto Herman Herman Herman Santoso Pakpahan 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 Jehad Hammad Jevri Tri Ardiansah Junoh, Ahmad Kadri Juwita Annisa Fauzi Juwita Annisa Fauzi Kaki, Gregorius Paulus Mario Laka Kartika Candra Kirana 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 Zainal Arifin, M Zainal 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 Miladina Rizka Aziza Ming F. Teng Ming Foey Teng, Ming Foey Mochamad Hariadi Moh. Safii 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 Musyaffa', Ahmad 'Ammar Nabila Izdihar, Zahra Nabila, Khurin Nada, Anita Qotrun Nadhiroh, Baitun Nadia Roosmalita Sari Nafalski, Andrew Nastiti Susetyo Fanany Putri Naufal, Ayyub Naziro Nedic, Zorica Ningsih, Eka Nurcahya Ningtyas, Yana Novia Ratnasari Noviani, Erina Fika Novrindah Alvi Hasanah Nugraha, Agil Zaidan Nur Hidayat, Wahyu 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 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 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 Rully Charitas Indra Prahmana Ruth Ema Febrita Saifullah, Shoffan Salahuddin, Lizawati Salsabila, Reni Fatrisna Santoso, Priyo Aji Saputra, Anggie Wahyu Saputra, Irzan Tri 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 ST. Ulfawanti Intan Subadra Stamen Gadzhanov 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 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 Yuhefizar Yuhefizar Yuliana, Oki Dwi Yulianto, Aldy Rahmat Yuliawati, Pundhi Yuni Rahmawati Yusmanto, Yunan Zaeni, Ilham Ari Elbaith Zakaria, Adil Zhou, Xiaofeng Zulkham Umar Rosyidin Zulkham Umar Rosyidin