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All Journal International Journal of Electrical and Computer Engineering Jurnal Rekayasa Proses Pixel : Jurnal Ilmiah Komputer Grafis TELKOMNIKA (Telecommunication Computing Electronics and Control) 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) INTENSIF: Jurnal Ilmiah Penelitian dan Penerapan Teknologi Sistem Informasi JIKO (Jurnal Informatika dan Komputer) Journal of Electrical Technology Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control CogITo Smart Journal 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) 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) Journal of Innovation Information Technology and Application (JINITA) 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 Teknik Informatika (JUTIF) 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 Advance Sustainable Science, Engineering and Technology (ASSET) 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 Chemistry 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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PELATIHAN PEMBUATAN NUGGET IKAN NILA UNTUK PEMBERDAYAAN UMKM DAN GENERASI MUDA DI DESA WINONGAN LOR Isdianto, Andik; Atminenggar, Alinda Najma; Nisrina, Aliyya; Sucianingsih, Ni Komang Diah; Septiansyah, Moch. Rafli; Ginting, Meliani Ananda Br.; Yumna, Orryza Nayla; Arbiansyah, Moh Junit; Wijaya, Sony; Aliyah, Nada Rahma; Hamdallah, Dika Puja; Sari, Yeni Kartika; Ammara, Laya; Hamzah, Hamzah; Setyanto, Arief
Jurnal Pengabdian Indonesia (JPI) Vol. 1 No. 2 (2025): Vol. 1 No. 2 Edisi Juli 2025
Publisher : PT. Jurnal Center Indonesia Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62567/jpi.v1i2.1140

Abstract

Pelatihan pembuatan nugget ikan nila merupakan upaya pemberdayaan pelaku UMKM dan generasi muda di Desa Winongan Lor untuk meningkatkan keterampilan pengolahan hasil perikanan menjadi produk bernilai tambah. Kegiatan ini dilaksanakan melalui sosialisasi, praktik langsung, sesi tanya jawab, dan uji hedonik yang melibatkan masyarakat setempat. Hasil pelatihan menunjukkan peningkatan signifikan pada kemampuan teknis peserta dalam pengolahan, kebersihan, dan keamanan pangan, serta kemampuan praktis menghasilkan nugget dengan cita rasa dan tekstur yang diminati konsumen. Uji hedonik mengonfirmasi bahwa produk nugget ikan nila diterima baik oleh ibu-ibu dan anak-anak, menandakan potensi pasar yang menjanjikan. Meskipun terdapat tantangan seperti keterbatasan alat dan bahan, pelatihan ini berhasil membangkitkan motivasi kewirausahaan dan membuka peluang usaha baru yang berkelanjutan. Disarankan pelatihan lanjutan dengan fokus pada peningkatan mutu produk, teknik pengemasan inovatif, dan strategi pemasaran digital untuk meningkatkan daya saing produk olahan ikan nila. Program ini memberikan kontribusi nyata dalam pemberdayaan UMKM serta pengembangan ekonomi berbasis inovasi produk hasil perikanan.
Optimization of Parallel Neural Network Layer Configuration in English Text Sentiment Analysis Nugroho, Agung; Arief Setyanto
Jurnal Nasional Teknik Elektro dan Teknologi Informasi Vol 14 No 4: November 2025
Publisher : This journal is published by the Department of Electrical and Information Engineering, Faculty of Engineering, Universitas Gadjah Mada.

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/jnteti.v14i4.21069

Abstract

Accuracy in analyst sentiment classification is very important so that the trained model can be implemented well to make business decisions. Researchers proposed a method for configuring neural network models arranged in parallel to improve classification accuracy. The results of the first stage, a bidirectional long short-term memory (Bi-LSTM) algorithm with Keras embedding with a sequential layer configuration, produced the best accuracy of 80.20%. The results of this first stage served as the baseline to be used as a reference for the combination in the second stage of the experiment. In the second stage of the experiment, a combination of the Bi-LSTM algorithm with other algorithms was carried out in parallel, such as gated recurrent unit (GRU), recurrent neural network (RNN), and Simple RNN with Keras embedding. It was found that the combination of three parallel layers of GRU-BiLSTM-RNN with Keras Embedding produced the highest accuracy for sentiment analysis of three classes, with a value of 88%. A statistical test of the t-test method was carried out with a critical p-value of 0.05 to prove the accuracy that has been produced between the sequential and the parallel configuration. The results of the t-test between the sequential configuration and the parallel configuration obtained a p-value of 0.5e-9 which is much smaller than the critical p-value of 0.05 so that in statistical testing the average accuracy produced from the two configurations is significantly different.
Analisis Aplikasi Marbel Huruf Versi Mobile Terhadap Pembelajaran Membaca di Desa Semanding Ponorogo Karaman, Jamilah; Setyanto, Arief; Sofyan, Amir Fatah
INTENSIF: Jurnal Ilmiah Penelitian dan Penerapan Teknologi Sistem Informasi Vol 2 No 2 (2018): Vol. 2 No. 2 Agustus 2018
Publisher : Universitas Nusantara PGRI Kediri

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (176.797 KB) | DOI: 10.29407/intensif.v2i2.11878

Abstract

The development of technology, especially information and communication technology offers many ease-ease in learning, which allows the shift of learning orientation from the process of presenting various knowledge into the process of guidance in individual exploration of science. Interactive learning media for children who rampant today is a game-based learning pedia is "MARBEL". Marbel is an abbreviation of "Let's Learn", marbel application is an educational application (mobile learning) for children aged 2 to 8 years so that made mobile-based applications aims to facilitate children in the learning process.
Analisis Metode CNN menggunakan Arsitektur Facenet dan VGG16 dalam Mengenali Wajah Penyandang Tunanetra Agung Budi Prastyo; Arief Setyanto
G-Tech: Jurnal Teknologi Terapan Vol 9 No 2 (2025): G-Tech, Vol. 9 No. 2 April 2025
Publisher : Universitas Islam Raden Rahmat, Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70609/gtech.v9i2.6573

Abstract

Face recognition is a rapidly growing biometric technology, especially with the application of Convolutional Neural Networks (CNN) such as FaceNet and VGG16. This research aims to evaluate the effectiveness of both CNN models in recognizing the faces of visually impaired people, who face the challenge of limited vision in image retrieval. The research uses two face detection methods, namely MTCNN and HaarCascade, to analyze the effect of face detection on recognition accuracy. The experimental method was conducted by collecting facial data of visually impaired people under various lighting conditions and expressions. The results show that accurate face detection greatly affects the performance of face recognition models, with MTCNN providing better face detection results (93.75% detection accuracy) than HaarCascade (83.75% detection accuracy). Both models, FaceNet and VGG16, show excellent face recognition accuracy (100%) if the face image is correctly detected by MTCNN. Therefore, for face recognition of visually impaired people, it is recommended to use MTCNN as the face detection method, followed by FaceNet or VGG16 for face recognition.
Forecasting the Highest and Lowest Prices in Financial Markets Using a VMD-LSTM Hybrid Model Purwantara, I Made Adi; Kusrini, Kusrini; Setyanto, Arief; Utami, Ema
CogITo Smart Journal Vol. 11 No. 2 (2025): Cogito Smart Journal
Publisher : Fakultas Ilmu Komputer, Universitas Klabat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31154/cogito.v11i2.963.295-310

Abstract

Accurate forecasting of the lowest and highest prices in financial markets poses a considerable challenge due to the inherent nonlinear behaviour, non-stationarity, and high noise levels of financial time series data. Most prior studies focus only on closing prices, with limited attention to the simultaneous prediction of high and low prices. Yet, predicting the lowest and highest prices is essential for investors to make informed trading decisions. To address this gap, this study proposes a hybrid DL framework that integrates VMD and LSTM networks for predicting daily high and low prices simultaneously. This study used 12 years of daily data from three diverse assets: AUD/USD, TLKM, and XAU/USD. The data underwent preprocessing, VMD-based decomposition, and were input into the LSTM. The dataset was split 80% for training and 20% for testing. Experiments varied the number of decomposition modes (K = 7, 10, 12) and sliding window sizes (5, 15, 30, 45, 60, 90). Results show that the VMD-LSTM model exhibits improved performance in most of the tested scenarios compared to traditional LSTM. These findings underscore that the use of VMD decomposition can help enhance the accuracy of forecasting the highest and lowest prices in the financial market.
Deep Learning Model Compression Techniques Performance on Edge Devices Rakandhiya Daanii Rachmanto; Ahmad Naufal Labiib Nabhaan; Arief Setyanto
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.
Optimasi Konfigurasi Lapisan Jaringan Saraf Tiruan Paralel dalam Analisis Sentimen Teks Berbahasa Inggris Agung Nugroho; Arief Setyanto
Jurnal Nasional Teknik Elektro dan Teknologi Informasi Vol 14 No 4: November 2025
Publisher : This journal is published by the Department of Electrical and Information Engineering, Faculty of Engineering, Universitas Gadjah Mada.

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/jnteti.v14i4.21069

Abstract

Accuracy in analyst sentiment classification is very important so that the trained model can be implemented well to make business decisions. Researchers proposed a method for configuring neural network models arranged in parallel to improve classification accuracy. The results of the first stage, a bidirectional long short-term memory (Bi-LSTM) algorithm with Keras embedding with a sequential layer configuration, produced the best accuracy of 80.20%. The results of this first stage served as the baseline to be used as a reference for the combination in the second stage of the experiment. In the second stage of the experiment, a combination of the Bi-LSTM algorithm with other algorithms was carried out in parallel, such as gated recurrent unit (GRU), recurrent neural network (RNN), and Simple RNN with Keras embedding. It was found that the combination of three parallel layers of GRU-BiLSTM-RNN with Keras Embedding produced the highest accuracy for sentiment analysis of three classes, with a value of 88%. A statistical test of the t-test method was carried out with a critical p-value of 0.05 to prove the accuracy that has been produced between the sequential and the parallel configuration. The results of the t-test between the sequential configuration and the parallel configuration obtained a p-value of 0.5e-9 which is much smaller than the critical p-value of 0.05 so that in statistical testing the average accuracy produced from the two configurations is significantly different.
Analisis Efisiensi Sistem Smart Charging Eksternal untuk Laptop Amrullah, Ahmad Afief; Setyanto, Arief; Sudarmawan, Sudarmawan
Smart Comp :Jurnalnya Orang Pintar Komputer Vol 12, No 3 (2023): Smart Comp: Jurnalnya Orang Pintar Komputer
Publisher : Politeknik Harapan Bersama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30591/smartcomp.v12i3.5044

Abstract

Smart charging dalam penelitian-penelitian terdahulu terkait dengan piranti seperti laptop lebih banyak fokus pada persoalan usia baterai dan kerusakannya. Di sisi lain, terdapat penelitian yang memperlebar konteks smart charging kepada kendali berdasarkan kondisi kelistrikan dengan indikator berupa frekuensi. Akan tetapi, efisiensi belum jelas antara model sistem per piranti dibandingkan terpusat. Oleh karena itu penulis hendak menginvestigasi dan fokus pada efisiensi tersebut. Dalam penelitian berjudul “Analisis Efisiensi Sistem Smart Charging Eksternal untuk Laptop” ini penulis menggunakan perangkat dan data-data yang relatif serupa dengan penelitian terdahulu, namun dengan pendekatan dan teknologi yang relatif berbeda. Data diolah dengan beberapa filter sehingga data cukup optimal dipergunakan, khususnya terkait dengan persentase, waktu dan laju pengisian. Data kemudian dipergunakan untuk menghitung nilai efisiensi yang dicari. Adapun data lain yang berkaitan dipergunakan untuk melihat performa dan kecenderungan sistem. Berdasarkan data yang diperoleh dari hasil analisis, disimpulkan bahwa sistem dengan skema individual relatif lebih efisien dibandingkan dengan skema terpusat. Adapun dalam hal performa, sistem dengan skema individual juga relatif lebih baik, karena tidak ditemukan galat selama percobaan. Kata Kunci— smart charging, laptop, frekuensi
Classification Of Malaria Types Using Naïve Bayes Classification Hadin La Ariandi; Arief Setyanto; Sudarmawan Sudarmawan
Jurnal Indonesia Sosial Teknologi Vol. 5 No. 5 (2024): Jurnal Indonesia Sosial Teknologi
Publisher : Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59141/jist.v5i5.1088

Abstract

This study was conducted to determine the level of accuracy of the naïve bayes classification method in the process of determining the group type of malaria. This method is used to predict the category of malaria based on the symptoms displayed. In this study, the dataset used was divided into 60% for training and 40% for testing. The results showed that the naïve bayes algorithm had an accuracy rate of 99.8% in predicting malaria categories. Evaluation of model performance using confusion matrix and ROC curve also showed good results, with classification accuracy of 0.998, error 0.002, and AUC 0.999. The results of the classification report show that the Quartana, Tertiana, and Tropica categories are more dominant than the Ovale category, based on precision, recall, and f1-score. These results show that the naïve bayes classification method is effective in classifying types of malaria and can be used as an aid in the diagnosis of malaria.
Analisa Prediksi Turnover Karyawan menggunakan Machine Learning Arief Maehendrayuga; Arief Setyanto; Kusnawi
bit-Tech Vol. 7 No. 2 (2024): bit-Tech
Publisher : Komunitas Dosen Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32877/bt.v7i2.1999

Abstract

Penelitian ini membahas penerapan machine learning untuk memprediksi turnover karyawan, yang merupakan tantangan utama dalam manajemen Sumber Daya Manusia (SDM). Turnover karyawan sering kali disebabkan oleh berbagai faktor, termasuk ketidakseimbangan kehidupan kerja, ketidakpuasan kerja, dan minimnya peluang pengembangan karier. Dalam penelitian ini, digunakan dataset IBM HR Analytics untuk menganalisis faktor-faktor yang memengaruhi turnover karyawan. Algoritma yang diterapkan meliputi Support Vector Machine (SVM) dan Random Forest. Proses penelitian dimulai dengan pengumpulan data, eksplorasi awal, praproses data, seleksi fitur, dan penyeimbangan data menggunakan teknik Synthetic Minority Over-sampling Technique (SMOTE). Evaluasi kinerja model dilakukan menggunakan confusion matrix untuk mengukur akurasi, presisi, recall, dan f1-score. Hasil analisis menunjukkan bahwa algoritma Random Forest memberikan kinerja yang lebih baik dibandingkan SVM. Random Forest mencapai akurasi 97,72%, sedangkan SVM memperoleh akurasi 92,51%. Setelah menerapkan SMOTE, akurasi meningkat menjadi 97% untuk Random Forest dan 93% untuk SVM. Selain akurasi, Random Forest juga unggul dalam metrik presisi, recall, dan f1-score, membuktikan keandalannya dalam memprediksi turnover karyawan. Temuan ini menegaskan bahwa pendekatan machine learning dapat digunakan untuk memahami pola turnover secara lebih mendalam. Dengan prediksi yang lebih akurat, perusahaan dapat merancang strategi retensi karyawan yang lebih efektif dan berbasis data, menciptakan lingkungan kerja yang mendukung produktivitas serta meningkatkan stabilitas tenaga kerja secara keseluruhan.
Co-Authors (Menunda Publikasi) Abdillah, M A Agastya, I Made Artha Agung Budi Prastyo Agung Nugroho Agung, Kris Agus Sukarno Agus Tumulyadi Agustina Rahmawati Ahmad Afief Amrullah Ahmad Afief Amrullah Ahmad Naufal Labiib Nabhaan Ahmad Tantoni Ainul Yaqin Al Maky, Nuril Huda Aliyah, Nada Rahma Alva Hendi Muhammad Amanda Rifan Fathoni Amir Fatah Sofyan Amiruddin Khairul Huda Ammara, Laya Amrullah, Ahmad Afief An Braeken Anam, M. Choirul Anang Anang Andi Bahtiar Semma Andi Kriswantono Andi Sunyoto Andik Isdianto Anggit Dwi Hartanto Anggit Hartanto annisa gatri zakinah Annisa Gatri Zakinah Anthon Andrimida, Anthon Anton, Tri Arbiansyah, Moh Junit Arief Maehendrayuga 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 Béjar, Rodrigo Martínez Berlania Mahardika Putri Bruno da Silva Constantin Menteng Daduk Setyohadi Darmawan Ockto Sutjipto Dedi Tri Hermanto Desy Bawan, Sarah Bunda 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 Taufiq Luthfi F Purwanto Fadjeri, Akhmad 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 Hadin La Ariandi Hadiyah, Lisa Nur Hafidz Sanjaya, Hafidz Hamdallah, Dika Puja Hamdikatama, Bimantyoso Hamka Suyuti Hamzah Hamzah Hanif Al Fatta Hanif Al Fattah Hanifa Ramadhani Hari Susanto Harlyan, Ledhyane Eka Henderi . Hendi Muhammad, Alva Heri Sismoro Herlambang Priantoro Hidayat, Aji Said Wahyudi Hidayat, Kardilah Rohmat Hizbul Izzi I Gusti Ngurah Wikranta Arsa Arsa I Made Adi Purwantara I Made Artha Agastya Ilham Mubarog Imam Syafii Imam Syafii Imam Thoib Indra Listiawan Irianies Cahya Gozali Irwan Jatmiko Ishaq, Syafrial Yanuar Jimmy H Moedjahedy José Ramón Martínez Salio Kamila, Firda Nikmatul Karaman, Jamilah Kartikasari, Wahida Khairan marzuki Khasanah, Nabiila Rizqi Kholida Zia Abidin Komang Aryasa Kris Agung Kudrati, Amelinda Vivian Kumara Ari Yuana Kumoro, Danang Tejo Kusnawi Kusnawi Kusrini López, Alba Puelles M. Diah M. Rudyanto Arief M. RUDYANTO ARIEF Mardi Utomo Mardya Hayati Marsela, Kristina Marselina Endah Hiswati Martiani, Evi Martínez-Béjar, Rodrigo MEI PARWANTO KURNIAWAN Miftahul Madani Mohamad Syafri Lamato Morita Puspita Sari Muchamad Zainul Muhamad Maksum Hidayat Muhammad Abdul Basit 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. 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 Sarip, nfn Seniwati, Erni Septiansyah, Moch. Rafli Shahruri, Rifandi Annas Simone Martin Marotta Siswo Utomo, Mardi Siti Alvi Sholikhatin Siti Halimah Soejono, Ajie Wibowo Sofyan Pariyasto Sriyati Sriyati Stephan Adriansyah Hulukati Suardi, Heri Sucianingsih, Ni Komang Diah Sudarmawan Sudarmawan Sudarmawan Sudarmawan Sudarmawan Sudarmawan Sudarmawan Sudarmawan Sudarmawan, Sudarmawan Sudirman, San Suhardi Aras Sukoco Sunardi Sunardi Supriyadi Supriyadi Supriyadi Supriyadi Suputa Suputa 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