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All Journal International Journal of Electrical and Computer Engineering Jurnal Rekayasa Proses Pixel : Jurnal Ilmiah Komputer Grafis Jurnal Pekommas Indonesian Journal of Educational Review (IJER) Journal of Environmental Engineering and Sustainable Technology Jurnal Teknologi Informasi dan Ilmu Komputer Jurnal Informatika dan Teknik Elektro Terapan Indonesian Journal on Computing (Indo-JC) Jurnal Inspiration JOIN (Jurnal Online Informatika) Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Creative Information Technology Journal JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING JFMR (Journal of Fisheries and Marine Research) JIKO (Jurnal Informatika dan Komputer) Insect (Informatics and Security) : Jurnal Teknik Informatika JITK (Jurnal Ilmu Pengetahuan dan Komputer) JURNAL TEKNIK INFORMATIKA DAN SISTEM INFORMASI Applied Information System and Management Jurnal Rekayasa Proses JURNAL EDUCATION AND DEVELOPMENT MATRIK : Jurnal Manajemen, Teknik Informatika, dan Rekayasa Komputer J-SAKTI (Jurnal Sains Komputer dan Informatika) Indonesian Journal of Applied Informatics JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) CSRID (Computer Science Research and Its Development Journal) Informasi Interaktif Building of Informatics, Technology and Science Progresif: Jurnal Ilmiah Komputer Journal of Sustainable Engineering: Proceedings Series SENSITEK E-JURNAL JUSITI : Jurnal Sistem Informasi dan Teknologi Informasi Jurnal Teknologi Informasi dan Multimedia bit-Tech Jurnal Teknologi Informasi : Jurnal Keilmuan dan Aplikasi Bidang Teknik Informatika Dielektrika : Jurnal Ilmiah Kajian Teori dan Aplikasi Teknik Elektro Respati Journal Cerita: Creative Education of Research in Information Technology and Artificial Informatics G-Tech : Jurnal Teknologi Terapan JIKA (Jurnal Informatika) Jurnal Informa: Jurnal Penelitian dan Pengabdian Masyarakat Infotek : Jurnal Informatika dan Teknologi jurnal syntax admiration Jurnal TIKOMSIN (Teknologi Informasi dan Komunikasi Sinar Nusantara) Jurnal Ilmiah Publika Jurnal Teknimedia: Teknologi Informasi dan Multimedia Journal of Electrical Engineering and Computer (JEECOM) Information System Journal (INFOS) Buletin Poltanesa Jurnal Senopati : Sustainability, Ergonomics, Optimization, and Application of Industrial Engineering INFOSYS (INFORMATION SYSTEM) JOURNAL J-SAKTI (Jurnal Sains Komputer dan Informatika) Research Fair Unisri Jurnal Ilmiah IT CIDA : Diseminasi Teknologi Informasi Jurnal Dinamika Informatika (JDI) Jurnal Nasional Teknik Elektro dan Teknologi Informasi Jurnal Teknik Informatika Journal of Comprehensive Science Jurnal Indonesia Sosial Teknologi Ceddi Journal of Information System and Technology (JST) SmartComp Teknomatika: Jurnal Informatika dan Komputer JURNAL MULTIDISIPLIN BHATARA Jurnal Pengabdian Indonesia
Arief Setyanto
Universitas Amikom Yogyakarta
Religion Aerospace Engineering Agriculture, Biological Sciences & Forestry Arts Humanities Astronomy Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Nursing Social Sciences Other

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Peningkatan Akurasi Pada Slowfast Network Menggunakan Multi-Head Self Attention Layer Reza, Muhammad; Setyanto, Arief
Journal Cerita: Creative Education of Research in Information Technology and Artificial Informatics Vol 11 No 2 (2025): Journal CERITA : Creative Education of Research in Information Technology and Ar
Publisher : UNIVERSITAS RAHARJA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/cerita.v11i2.3870

Abstract

Keselamatan berkendara merupakan aspek krusial dalam sistem transportasi modern, di mana perilaku pengemudi seperti kantuk dan kehilangan fokus menjadi faktor utama penyebab kecelakaan. Penelitian ini mengusulkan sistem deteksi perilaku pengemudi berbasis video dengan menggunakan arsitektur SlowFast Network yang dikombinasikan dengan mekanisme Self-Attention. SlowFast Network memungkinkan pemrosesan dua jalur informasi temporal secara paralel, yaitu gerakan cepat dan lambat, untuk menangkap pola ekspresi dan dinamika visual pengemudi. Mekanisme Self-Attention ditambahkan untuk memperkuat kemampuan model dalam mengenali fitur penting secara kontekstual. Dataset yang digunakan adalah SUST Driver Drowsiness Dataset, yang telah melalui proses segmentasi dan normalisasi. Model dilatih menggunakan pembagian data pelatihan, validasi, dan pengujian, serta dievaluasi dengan metrik akurasi, presisi, recall, dan F1-score. Hasil pengujian menunjukkan bahwa penambahan Self-Attention meningkatkan performa model secara signifikan, dengan akurasi mencapai 96% pada data uji seimbang. Visualisasi attention map dan filter Conv3D mendukung interpretasi bahwa model mampu menangkap pola perilaku tanpa memerlukan deteksi eksplisit bagian wajah. Sistem ini menunjukkan potensi untuk diterapkan dalam sistem peringatan dini berbasis video guna meningkatkan keselamatan berkendara secara real-time.
BIODIVERSITAS LOBSTER DI TELUK PRIGI, TRENGGALEK JAWA TIMUR Setyanto, Arief; Halimah, Siti
JFMR (Journal of Fisheries and Marine Research) Vol. 3 No. 3 (2019): JFMR
Publisher : Faculty of Fisheries and Marine Science, Brawijaya University, Malang, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21776/ub.jfmr.2019.003.03.9

Abstract

Pengelolaan perikanan lobster perlu dengan studi tentang sebaran atau dispersal spesies lobster pada tiap fase hidup. Metode yang dipakai bisa menggunakan identifikasi spesies pada masing-masing fase hidup (larva, juvenile, dewasa) pada waktu dan tempat yang berbeda. Studi ini dilakukan untuk menginditifikasi spesies lobster dewasa yang hidup di Teluk Prigi, Watulimo, Trenggalek, Jawa Timur. Sampling dilakukan dengan mengidentifikasi morlogi lobster yang tertangkap oleh nelayan lobster. Ditemukan 5 spesies lobster yang tertangkap dengan menggunakan 3 alat tangkap yang berbeda. Spesies lobster yang tertangkap yaitu lobster pasir (Panulirus homarus), lobster mutiara (P. ornatus), lobster bambu (P. versicolor), lobster batu (P. penicillatus), lobster batik (P. longipes). Ketiga alat tangkap tersebut adalah: gill net, krendet dan ditangkap dengan tangan (menyelam). Gill net banyak menangkap jenis pasir dibandingkan jenis lainnya. Krendet banyak mendapat pasir bersama dengan bamboo, mutiara, batik, kemudian batu lebih sedikit tertangkap krendet dibandingkan alat tangkap lainnya. Hand picking banyak menangkap pasir, mutiara, batu, dan batik kemudian sedikit menangkap jenis bambu.
BIOLOGI REPRODUKSI TONGKOL LISONG, Auxis rochei rochei (Risso, 1810) DI PERAIRAN SENDANG BIRU, KABUPATEN MALANG, JAWA TIMUR Setyanto, Arief; Raka Wiadnya, Dewa Gede; Publikasi), (Menunda
JFMR (Journal of Fisheries and Marine Research) Vol. 1 No. 1 (2017): JFMR
Publisher : Faculty of Fisheries and Marine Science, Brawijaya University, Malang, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

The aims of this study are to know some biological  reproductive aspects of bullet tuna. Information of its biological reproductive aspects will be useful for managing the bullet tuna fishery. Determining about gonadal maturity level in fish can be completed by macroscopic and microscopic (histology) observation. The study about gonadal matuity level determination of bullet tuna has been done through histological observation. Sampling was done by taken sample from UPT P2SKP Pondokdadap Sendangbiru, from January until March 2018. Species identification follows the FAO standard procedure (species identification sheet) published 2001. A specimen was deposited at Depository Ichtyologicum Brawijaya with code DIB.FISH.11111 002 03. Forklength of the sampled 82 fish  range from 20,10 – 27,20. Gonadal samples were cut with microtome machine at 5 mm thickness. The preparates were then analyzed using biological binocular microscope at 40x magnification. The result showed that maturity stage of bullet tuna dominated by TKG IV with  34 %, followed by TKG III (31 %), TKG 1 (28 %), TKG II (5 %) and  TKG V (1 %). Lenght at first maturity occured at 23.88 cm and egg diameter were 20,92–367,65 µm.
KOMPOSISI SPESIES LARVA LOBSTER YANG TERKUMPUL PADA ATRAKTOR LAMPU BAWAH AIR Setyanto, Arief; Kamila, Firda Nikmatul; Bintoro, Gatut
JFMR (Journal of Fisheries and Marine Research) Vol. 4 No. 2 (2020): JFMR
Publisher : Faculty of Fisheries and Marine Science, Brawijaya University, Malang, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21776/ub.jfmr.2020.004.02.12

Abstract

Lobster (Panulirus sp.) merupakan hewan avertebrata anggota Filum Arthropoda. Di Indonesia terdapat 6 spesies lobster dari genus Panulirus yaitu P. homarus, P. longipes, P. ornatus, P. penicillatus, P. polyphagus dan P. versicolor. Keenam spesies lobster ini memiliki distribusi yang berbeda-beda. Fase hidup lobster sangat komplek. Fase larva adalah relative lama dan mempunyai beberapa tahap yangmana kelulushidupan dalam fase ini sangat menentukan populasi alaminya. Fase larva lobster termasuk dalam plankton yang makanannya tergantung pada jenis mikroorganisme lainnya. Mikroorganisme umumnya adalah phototaksis positive. Studi tentang pengaruh cahaya terhadap komposisi spesies larva lobster menarik dilakukan karena dapat memberikan informasi bagi upaya budidaya dan peningkatan jumlah populasi melalui penurunan kematian alaminya. Penelitian ini di laksanakan di perairan Pantai Lampon, Banyuwangi, Jawa Timur tahun 2019. Pada penelitian ini analisis yang digunakan adalah analisis Chi-Square, uji F (ANOVA), dan uji lanjutan.Hasil dari penelitian ini adalah spesies larva lobster yang terkumpul pada atraktor lampu dan tanpa atraktor ada empat speseis yaitu P. ornatus, P. homarus, P. penicillatus, dan P. versicolor. Spesies yang dominan terkumpul adalah P. homarus. Pada penelitian ini penggunaan atraktor lampu celup bawah air lebih berpengaruh terhadap jumlah larva lobster untuk mendekat kearah atraktor. Keberhasilan pengelolaan sumberdaya perikanan lobster akan sangat ditentukan oleh hasil kajian yang mencakup seluruh siklus hidupnya.
OPTIMIZATION OF SOFTWARE DEFECT PREDICTION USING CNN AND ADABOOST: ANALYSIS AND EVALUATION Basit, Muhammad Abdul; Setyanto, Arief; Hidayat, Tonny
JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Vol 10, No 3 (2025)
Publisher : STKIP PGRI Tulungagung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29100/jipi.v10i3.6405

Abstract

This study focuses on enhancing software defect prediction (SDP) by integrating Convolutional Neural Networks (CNN) with the AdaBoost algorithm. The PROMISE dataset was employed in this research, and data balancing was achieved using the SMOTE Tomek technique. With the help of AdaBoost, we were able to increase the prediction accuracy after building a complex CNN model to extract features from the da-taset. The AdaBoost model's hyperparameters were fine-tuned using GridSearch to find the best values for enhanced model performance. For the studies, we used StandardScaler to normalize the data after splitting it into training and testing groups with an 80:20 ratio. The ex-perimental results show that compared to the baseline method, SDP's accuracy is significantly improved when CNN, AdaBoost, and GridSearch hyperparameter tweaking are used together. Accuracy, pre-cision, recall, F1 score, MCC, and AUC were some of the measures used to assess the model's performance.
Evaluation of E-Learning Usability Based on ISO 25010 with Hofstede's Cultural Dimensions as Moderation: A PLS-SEM Study in Higher Education Januhari, Ni Nyoman Utami; Setyanto, Arief; Kusrini, Kusrini; Utami, Ema; Béjar, Rodrigo Martínez
Applied Information System and Management (AISM) Vol. 8 No. 1 (2025): Applied Information System and Management (AISM)
Publisher : Depart. of Information Systems, FST, UIN Syarif Hidayatullah Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15408/aism.v8i1.45738

Abstract

Although e-learning has rapidly advanced in higher education, many platforms still fall short of meeting user needs due to a lack of integration between usability and cultural dimensions. This study explores how usability influences user satisfaction with e-learning platforms, with cultural dimensions based on Hofstede’s model examined as moderating variables. Usability Quality (QiU) is assessed using the ISO/IEC 25010 framework, which includes five key elements: effectiveness, efficiency, user satisfaction, risk avoidance, and contextual relevance. A total of 384 students from private universities in Bali participated in the study, representing a diverse range of academic disciplines. Using SmartPLS and Partial Least Squares Structural Equation Modeling (PLS-SEM), the analysis revealed that usability has a significant effect on user satisfaction (T=7.528, β=0.270), and cultural variables also play a substantial role (T=21.094, β=0.704). Although the moderating effect of culture was statistically significant (T=2.379, β=0.042), its impact was relatively modest compared to the direct effect of usability. Among the usability components, efficiency emerged as the most influential factor. Regarding cultural dimensions, individualism versus collectivism was found to have the strongest effect. These findings emphasize the importance of designing e-learning systems that are both usability-driven and culturally sensitive, ensuring alignment with user expectations and the educational context.  
Web Pembuatan Website Klub Sepatu Roda Black Pegasus Inline Skate untuk Peningkatan Efektifitas Komunikasi Setyanto, Arief; Puspitasari, Nila Feby; Seniwati, Erni; Gibran, Ibrahim El; Shahruri, Rifandi Annas
BHATARA: Jurnal Multidisiplin Ilmu Vol 2 No 1 (2025): January
Publisher : Hemispheres Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59095/jmb.v2i1.186

Abstract

Peningkatan efektivitas komunikasi antar anggota komunitas merupakan tantangan yang signifikan, terutama dalam sebuah klub olahraga dengan anggota yang terus bertambah. Klub Sepatu Roda Black Pegasus Inline Skate menghadapi kebutuhan untuk menyempurnakan sistem komunikasi dan koordinasi kegiatan antar anggotanya. Untuk menjawab tantangan ini, telah dikembangkan sebuah website resmi yang dirancang sebagai platform digital terpusat bagi klub. Website ini mencakup fitur-fitur penting seperti Home, About, Pelatihan dan Pemanduan, Pendaftaran, Galery Foto, Video, Buku Tamu dan Contact dan lainnya yang memungkinkan anggota klub untuk mengakses informasi dengan mudah, berbagi pengalaman, serta meningkatkan keterlibatan mereka dalam aktivitas klub. Hasil pelaksanaan kegiatan ini menghasilkan website yang memiliki alamat domain https://pegasusjogja.org. Secara keseluruhan, pembuatan website ini berhasil memenuhi tujuan utama untuk meningkatkan efektivitas komunikasi dalam Klub Sepatu Roda Black Pegasus Inline Skate, serta mendukung pertumbuhan dan penguatan komunitas klub secara keseluruhan.
Klasifikasi Radio Siaran FM Berdasarkan Data IQ Menggunakan Convolutional Neural Networks Sukarno, Agus; Setyanto, Arief; Nasiri, Asro
JURNAL INFORMATIKA DAN KOMPUTER Vol 9, No 3 (2025): Oktober 2025
Publisher : Lembaga Penelitian dan Pengabdian Masyarakat - Universitas Teknologi Digital Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26798/jiko.v9i3.1978

Abstract

Pengawasan spektrum siaran FM secara real-time memerlukan teknik canggih, pendekatan berbasis klasifikasi sinyal telah terbukti meningkatkan ketepatan deteksi dibandingkan metode manual. Penelitian ini mengembangkan dan membandingkan tiga arsitektur deep learning - CNN 5-Layers, CNN-BiLSTM, dan CNN-Transformer - untuk mengklasifikasikan pengguna siaran radio FM berdasarkan data IQ. Data sinyal dikumpulkan dari 16 pemancar FM menggunakan SDR dan diolah menjadi 80.000 sampel seimbang. Model-model ini dievaluasi berdasarkan akurasi klasifikasi dan waktu inferensi. Hasil eksperimen menunjukkan bahwa CNN-BiLSTM memberikan akurasi tertinggi sebesar 98,96% namun dengan waktu inferensi relatif lama sekitar 62 detik. Sementara itu, CNN 5-Layers memiliki waktu klasifikasi tercepat sekitar 10 detik dengan akurasi tinggi sebesar 98,18%, dan CNN-Transformer paling lambat sekitar 120 detik dengan akurasi sebesar 97,72%. Mengingat waktu klasifikasi per batch harus lebih pendek daripada laju pengambilan data sekitar 2 ms per sampel, hanya CNN 5-Layers yang memenuhi persyaratan pemantauan spektrum secara real-time.
Characterizing Hardware Utilization on Edge Devices when Inferring Compressed Deep Learning Models Nabhaan, Ahmad Naufal Labiib; Rachmanto, Rakandhiya Daanii; Setyanto, Arief
MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer Vol. 24 No. 1 (2024)
Publisher : Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/matrik.v24i1.3938

Abstract

Implementing edge AI involves running AI algorithms near the sensors. Deep Learning (DL) Model has successfully tackled image classification tasks with remarkable performance. However, their requirements for huge computing resources hinder the implementation of edge devices. Compressing the model is an essential task to allow the implementation of the DL model on edge devices. Post-training quantization (PTQ) is a compression technique that reduces the bit representation of the model weight parameters. This study looks at the impact of memory allocation on the latency of compressed DL models on Raspberry Pi 4 Model B (RPi4B) and NVIDIA Jetson Nano (J. Nano). This research aims to understand hardware utilization in central processing units (CPU), graphics processing units (GPU),and memory. This study focused on the quantitative method, which controls memory allocation and measures warm-up time, latency, CPU, and GPU utilization. Speed comparison among inference of DL models on RPi4B and J. Nano. This paper observes the correlation between hardware utilization versus the various DL inference latencies. According to our experiment, we concluded that smaller memory allocation led to high latency on both RPi4B and J. Nano. CPU utilization on RPi4B. CPU utilization in RPi4B increases along with the memory allocation; however, the opposite is shown on J. Nano since the GPU carries out the main computation on the device. Regarding computation, thesmaller DL Size and smaller bit representation lead to faster inference (low latency), while bigger bit representation on the same DL model leads to higher latency.
Deep Learning Model Compression Techniques Performance on Edge Devices Rachmanto, Rakandhiya Daanii; Nabhaan, Ahmad Naufal Labiib; Setyanto, Arief
MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer Vol. 23 No. 3 (2024)
Publisher : Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/matrik.v23i3.3961

Abstract

Artificial intelligence at the edge can help solve complex tasks faced by various sectors such as automotive, healthcare and surveillance. However, challenged by the lack of computational power from the edge devices, artificial intelligence models are forced to adapt. Many have developed and quantified model compres-sion approaches over the years to tackle this problem. However, not many have considered the overhead of on-device model compression, even though model compression can take a considerable amount of time. With the added metric, we provide a more complete view on the efficiency of model compression on the edge. The objective of this research is identifying the benefit of compression methods and it’s tradeoff between size and latency reduction versus the accuracy loss as well as compression time in edge devices. In this work, quantitative method is used to analyze and rank three common ways of model compression: post-training quantization, unstructured pruning and knowledge distillation on the basis of accuracy, latency, model size and time to compress overhead. We concluded that knowledge distillation is the best, with potential of up to 11.4x model size reduction, and 78.67% latency speed up, with moderate loss of accura-cy and compression time.
Co-Authors (Menunda Publikasi) Abdillah, M A Agastya, I Made Artha Agung, Kris Agus Sukarno Agus Tumulyadi Agustina Rahmawati Ahmad Afief Amrullah Ahmad Afief Amrullah Ahmad Naufal Labiib Nabhaan Ahmad Tantoni Ainul Yaqin Akhmad Fadjeri Al Maky, Nuril Huda Aliyah, Nada Rahma Amanda Rifan Fathoni Amir Fatah Sofyan Amiruddin Khairul Huda Ammara, Laya Amrullah, Ahmad Afief Anam, M. Choirul Anang Anang Andi Kriswantono Andik Isdianto Anggit Dwi Hartanto Anggit Hartanto annisa gatri zakinah Annisa Gatri Zakinah Anthon Andrimida, Anthon Anton, Tri Arbiansyah, Moh Junit Ariefandi, Muhammad Fikri Asadi, M. Arif Askar, Muhammad Ichfan Asmirijal, Amrey Syahnur Asro Nasiri Asro Nasiri Asro Nasiri Astika Wulansari Astuti , Septiana Sri Atmaja, Albertus Aldo Danar Atminenggar, Alinda Najma Aulia Lanudia Fathah Basit, Muhammad Abdul Bawan, Sarah Bunda Desi Béjar, Rodrigo Martínez Berlania Mahardika Putri Constantin Menteng Daduk Setyohadi Darmawan Ockto Sutjipto Dedi Tri Hermanto Dewa Gede Raka Wiadnya Dewa Gede Raka Wiadnya Dewa Gede Raka Wiadnya, Dewa Gede DHANI ARIATMANTO Dhea, Luthfia Ayu Dhiana Puspitawati Diah, M. Dian Rusvinasari Dinar Mustofa Dwi Satrio Anurogo Eko Pramono Eko Pramono Eko Pramono Ema Utami Emha Emha Luthfi Emha Taufiq Luthfi Emha Taufiq Luthfi Emha Taufiq Luthfi Emha Taufiq Luthfi F Purwanto Fathah, Aulia Lanudia Fazlul Rahman Ferry Wahyu Wibowo Ferry Wahyu Wibowo Ferry Wahyu Wibowo Fiqih Akbari Gatut Bintoro Gibran, Ibrahim El Gibran, Khalil Ginting, Meliani Ananda Br. Gunawan Wicahyono Hadiyah, Lisa Nur Hafidz Sanjaya, Hafidz Hamdallah, Dika Puja Hamdikatama, Bimantyoso Hamka Suyuti Hamzah Hamzah Hanif Al Fatta HANIF AL FATTA Hanif Al Fatta Hanif Al Fattah Hanifa Ramadhani Hari Susanto Harlyan, Ledhyane Eka Henderi . Hendi Muhammad, Alva Heri Sismoro Hidayat, Aji Said Wahyudi Hidayat, Kardilah Rohmat Hizbul Izzi I Made Artha Agastya Ilham Mubarog Imam Syafii Imam Syafii Imam Thoib Irianies Cahya Gozali Irwan Jatmiko Ishaq, Syafrial Yanuar Jamilah Karaman Jimmy H Moedjahedy José Ramón Martínez Salio Kamila, Firda Nikmatul Kartikasari, Wahida Khairan marzuki Khasanah, Nabiila Rizqi Kholida Zia Abidin Komang Aryasa Kris Agung Kudrati, Amelinda Vivian Kumara Ari Yuana Kumoro, Danang Tejo Kurniawan, Mei P Kusnawi Kusnawi KUSRINI Kusrini Kusrini Kusrini, Kusrini La Ariandi, Hadin López, Alba Puelles M. Diah M. Rudyanto Arief M. RUDYANTO ARIEF Maehendrayuga, Arief Mardya Hayati Marsela, Kristina Martiani, Evi Martínez-Béjar, Rodrigo Mei P Kurniawan Mei P. Kurniawan Mohamad Syafri Lamato Morita Puspita Sari Muchamad Zainul Muhamad Maksum Hidayat Muhammad Arif Asadi, Muhammad Arif Muhammad Arif Rahman Muhammad Azmi Muhammad Ghozaly Salim Muhammad Javier Irsyad Muhammad Reza Muhammad Reza Riansyah Muhammad Yusuf Munandar, Arief Muqorobin Muqorobin Nabhaan, Ahmad Naufal Labiib Nabilla, Azma Salma Nadea Cipta Laksmita Nasiri, Asro Naufal Hilda Bahtiar nfn Sarip Nggego, Dedy Abdianto Ni Nyoman Utami Januhari, Ni Nyoman Nico Rahman Caesar Nila Feby Puspitasari, Nila Feby Nina Kurnia Hikmawati Nisrina, Aliyya Nizery, Sefhanissa Puspa Retno Nuddin Harahab Nugroho, Agung Nur Khamidah oktiyas muzaky Luthfi, oktiyas muzaky Pahlawan, Muammar Reza Pangestu, Wanda Suryani Pattisahusiwa, Annisa Shafira P. Prastyo, Agung Budi Prayoghi, M. Lukman Publikasi), (Menunda Putra, Muhammad Naufal Eka Putri, Berlania Mahardika Rachmanto, Rakandhiya Daanii Rafif Zul Fahmi Rahmad Arif Setiawan Rahman, Aulia Tegar Rahmat Taufik R.L Bau Rakandhiya Daanii Rachmanto Ramdhani, Mohamad Dhicy Rarasrum Dyah Kasitowati Ratno Kustiawan Ria Andriani Ripto Sudiyarno Rismayani Rismayani Roni Sasongko Rudyanto Arief Sadikin, Moh. Fal Samuel, Pratama Diffi San Sudirman Saputra, Tedy Eko Sarah Bunda Desi Bawan Sarip, nfn Seniwati, Erni Septiansyah, Moch. Rafli Shahruri, Rifandi Annas Simone Martin Marotta Siswo Utomo, Mardi Siti Alvi Sholikhatin Siti Halimah Soejono, Ajie Wibowo Sriyati Sriyati Stephan Adriansyah Hulukati Suardi, Heri Sucianingsih, Ni Komang Diah Sudarmawan Sudarmawan Sudarmawan Sudarmawan Sudarmawan Sudarmawan Sudarmawan, Sudarmawan Sudirman, San Suhardi Aras Sukoco Sunardi Sunardi Supriyadi Supriyadi Supriyadi Supriyadi Suwanto Raharjo Suyadi Suyadi Suyuti, Hamka Syarief, Salsabila Nazmie Putri TONNY HIDAYAT Totok Wahyu Caturiyanto Tri Djoko Lelono Tumulyadi, Agus Tyas, Herlin Widi Aning Utama, Andria Ansri Veithzal Rivai Zainal Wahyu Nugroho Widhiarta, Widhiarta Wijaya, Sony Yasmin, Delviega Aisyah Yeni Kartika Sari, Yeni Kartika Yorarizka, Putri Devi Yuliana Yuliana Yumna, Orryza Nayla Zul Hisyam