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All Journal International Journal of Electrical and Computer Engineering International Journal of Reconfigurable and Embedded Systems (IJRES) Transmisi: Jurnal Ilmiah Teknik Elektro JURNAL SISTEM INFORMASI BISNIS Jurnal Sistem Komputer TELKOMNIKA (Telecommunication Computing Electronics and Control) Bulletin of Electrical Engineering and Informatics Jurnal Informatika Disease Prevention and Public Health Journal Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI) Prosiding Seminar Nasional Sains Dan Teknologi Fakultas Teknik CommIT (Communication & Information Technology) Bulletin of Electrical Engineering and Informatics Jurnal Teknologi Jurnal sistem informasi, Teknologi informasi dan komputer Sinergi Jurnal Edukasi dan Penelitian Informatika (JEPIN) JUITA : Jurnal Informatika International Journal of Advances in Intelligent Informatics Seminar Nasional Informatika (SEMNASIF) Jurnas Nasional Teknologi dan Sistem Informasi Khazanah Informatika: Jurnal Ilmu Komputer dan Informatika JURNAL NASIONAL TEKNIK ELEKTRO KLIK (Kumpulan jurnaL Ilmu Komputer) (e-Journal) Proceeding of the Electrical Engineering Computer Science and Informatics Fountain of Informatics Journal Jurnal Teknologi dan Sistem Komputer Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Jurnal Ilmiah FIFO Emerging Science Journal JIKO (Jurnal Informatika dan Komputer) Jurnal CoreIT Bina Insani ICT Journal JURNAL MEDIA INFORMATIKA BUDIDARMA Jurnal Penelitian Pendidikan IPA (JPPIPA) MUST: Journal of Mathematics Education, Science and Technology IT JOURNAL RESEARCH AND DEVELOPMENT Al-MARSHAD: Jurnal Astronomi Islam dan Ilmu-Ilmu Berkaitan JRST (Jurnal Riset Sains dan Teknologi) JITK (Jurnal Ilmu Pengetahuan dan Komputer) JURNAL REKAYASA TEKNOLOGI INFORMASI Jurnal Informatika Universitas Pamulang ILKOM Jurnal Ilmiah Jiko (Jurnal Informatika dan komputer) MATRIK : Jurnal Manajemen, Teknik Informatika, dan Rekayasa Komputer CYBERNETICS IJID (International Journal on Informatics for Development) JURIKOM (Jurnal Riset Komputer) JUMANJI (Jurnal Masyarakat Informatika Unjani) Informatika : Jurnal Informatika, Manajemen dan Komputer Jurnal Ilmiah Mandala Education (JIME) Abdimas Umtas : Jurnal Pengabdian kepada Masyarakat Jurnal Mantik JISKa (Jurnal Informatika Sunan Kalijaga) Buletin Ilmiah Sarjana Teknik Elektro Indonesian Journal of Business Intelligence (IJUBI) bit-Tech Aviation Electronics, Information Technology, Telecommunications, Electricals, Controls (AVITEC) Genta Mulia : Jurnal Ilmiah Pendidikan Jurnal Pengabdian Masyarakat Bumi Raflesia Journal of Robotics and Control (JRC) Journal of Applied Engineering and Technological Science (JAETS) Indonesian Journal of Electrical Engineering and Computer Science Bubungan Tinggi: Jurnal Pengabdian Masyarakat JUKI : Jurnal Komputer dan Informatika JITU : Journal Informatic Technology And Communication Journal of Innovation Information Technology and Application (JINITA) Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) Jurnal Pengabdian Masyarakat Indonesia Jurnal Nasional Pengabdian Masyarakat Jurnal Puan Indonesia Jurnal Informatika Teknologi dan Sains (Jinteks) Techno SIENNA Jurnal Informatika: Jurnal Pengembangan IT Advance Sustainable Science, Engineering and Technology (ASSET) INOVTEK Polbeng - Seri Informatika Khazanah Informatika : Jurnal Ilmu Komputer dan Informatika JOCHAC
Sunardi, Sunardi
Universitas Ahmad Dahlan Yogyakarta
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Spell Correction for the Minangkabau Language Using BERT-Based Embeddings Dewi Soyusiawaty; Abdul Fadlil; Sunardi
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 10 No 3 (2026): June 2026
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v10i3.7182

Abstract

Spell checking is an essential component of natural language processing, as it directly influences applications such as sentiment analysis, text classification, and machine translation. Developing a reliable system for low-resource languages like Minangkabau is challenging due to frequent spelling variations and limited annotated data. This study proposes a contextual spell correction model using pre-trained IndoBERT and multilingual BERT (mBERT) embeddings applied without additional training. The method masks misspelled words, extracts the contextual embedding of the [MASK] token, and compares it with candidate embeddings generated through dictionary filtering and Levenshtein Distance. Evaluation was conducted on the Spell Error Corpus for Minangkabau Language (SPEML), which includes insertion errors, deletion errors, substitution errors, transposition errors, punctuation errors, real-word errors, and loanword errors. Results show that mBERT consistently outperformed IndoBERT, achieving an average F1-score of 0.83 compared to 0.75. Statistical validation using paired t-test and Wilcoxon signed-rank test further confirmed that the performance difference between the two models was significant. Both models reached perfect scores (1.0) in real-word and loanword categories, and strong results in insertion_medium (0.97 for mBERT and 0.95 for IndoBERT). The lowest performance occurred in deletion_short (0.52 for IndoBERT) and long words cases (0.57 for mBERT). In addition, a small-scale external validation using 100 Twitter/X sentences was conducted to assess the applicability of the proposed method to real-world social media text. Overall, the findings confirm the effectiveness of contextual embeddings for Minangkabau spelling correction while highlighting challenges in long misspelled words, deletion errors, and informal real-world text.
TINJAUAN SISTEMATIS TREN, METODE, DAN DATA PADA PREDIKSI KELULUSAN MAHASISWA Rudy Ansari; Rudy Ansari; Sunardi Sunardi; Imam Riadi
Indonesian Journal of Business Intelligence (IJUBI) Vol 8 No 2 (2025): Indonesian Journal of Business Intelligence (IJUBI)
Publisher : Universitas Alma Ata

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21927/ijubi.v8i2.6551

Abstract

Penelitian tentang prediksi kelulusan mahasiswa banyak dipublikasikan akan tetapi biasanya metode beserta data yang dihasilkan dikemas secara terpisah dan kompleks sehingga gambaran tentang topik prediksi kelulusan mahasiswa saat ini kurang komprehensif. Tinjauan literatur ini bertujuan untuk mengidentifikasi dan menganalisis tren penelitian, dataset, dan metode tentang prediksi kelulusan mahasiswa yang dipublikasikan antara tahun 2020-2025. Berdasarkan kriteria inklusi dan ekslusi, tercatat sebanyak 75 artikel dari 199 artikel yang bersumber pada jurnal kuartil 1-4. Tinjauan literatur sistematis dapat didefinisikan sebagai proses mengidentifikasi, menilai, dan menginterpretasikan semua bukti penelitian yang tersedia untuk memberikan jawaban atas pertanyaan penelitian yang spesifik. Hasil analisis dalam lima tahun terakhir mengungkapkan bahwa penelitian prediksi kelulusan mahasiswa terdapat empat topik yaitu prediksi/klasifikasi, analisis dataset, pengelompokan (clustering), dan estimasi. Selain itu,  terdapat juga dua tren yang dibahas yaitu pemilihan fitur (feature selection) dan data tidak seimbang (imbalance data). Kategori data yang digunakan pada lima tahun terakhir lebih banyak menggunakan data private atau data real sebanyak 91% daripada data public. Metode yang paling sering digunakan pada topik-topik tersebut adalah Random Forest (RF), dan paling jarang yaitu metode Artificial Neural Network (ANN). Terdapat juga penggabungan metode untuk optimasi parameter di beberapa klasifikasi.
Analysis of Remote Access Trojan Attack using Android Debug Bridge Deco Aprilliansyah; Imam Riadi; Sunardi
IJID (International Journal on Informatics for Development) Vol. 10 No. 2 (2021): IJID December
Publisher : Faculty of Science and Technology, Universitas Islam Negeri (UIN) Sunan Kalijaga Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14421/ijid.2021.2839

Abstract

The security hole in the android operating system sometimes not realized by users such as malware and exploitation by third parties to remote access. This study conducted to identify the vulnerabilities of android operating system by using Ghost Framework. The vulnerability of the android smartphone are found by using the Android Debug Bridge (ADB) with the exploitation method as well as to analyze the test results and identify remote access Trojan attacks. The exploitation method with several steps from preparing the tools and connecting to the testing commands to the testing device have been conducted. The result shows that android version 9 can be remote access by entering the exploit via ADB. Some information has been obtained by third parties, enter and change the contents of the system directory can be remote access like an authorized to do any activities on the device such as opening lock screen, entering the directory system, changing the system, etc.
PENGENALAN APLIKASI JIRA DALAM MANAJEMEN PROYEK DI SMK YPKK 1 SLEMAN, YOGYAKARTA Rudy Ansari; Rudy Ansari; Irwansyah Irwansyah; Irwansyah Irwansyah; Nia Ekawati; Nia Ekawati; Herman Herman; Sunardi Sunardi
PUAN INDONESIA Vol. 8 No. 1 (2026): Jurnal PUAN Indonesia Vol. 8 No. 1 Juli 2026
Publisher : ASOSIASI IDEBAHASA KEPRI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37296/jpi.v8i1.517

Abstract

The community service activity at SMK YPKK 1 Gamping aims to align the vocational education curriculum with industry standards through the introduction of Agile and Scrum methods using the JIRA application. The main challenge faced was the students' lack of understanding of professional project management tools, so this training focused on mastering JIRA features such as Scrum/Kanban boards and issue tracking. Through training and mentoring of 30 students, there was a significant increase in competence. Data shows that the highest score on the pre-test was 80 (9 participants), which then increased on the post-test to a perfect score of 100 achieved by 15 participants. The evaluation results concluded that 50% of participants had achieved the maximum level of understanding in operating JIRA. Thus, this implementation successfully bridged the gap between academic theory and the practical needs of the workplace, while equipping students with globally relevant project management skills.
Anchovy-inspired filter algorithm: A bio-inspired optimization approach for high-dimensional benchmark functions Azrul Mahfurdz; Muhammad Muizz Mohd Nawawi; Sunardi Sunardi; Mohd Azriq Abd Aziz
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 24, No 1: February 2026
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v24i1.27594

Abstract

This paper presents the anchovy-inspired filter algorithm (AFA), a novel bio-inspired metaheuristic optimization method motivated by the filter feeding behavior of anchovies. Unlike conventional swarm intelligence algorithms, AFA employs a filtering mechanism in which each agent generates multiple candidate solutions within a local sampling radius and selects the best, mimicking how anchovies filter microscopic prey from seawater. To evaluate its performance, AFA was benchmarked against particle swarm optimization (PSO) and genetic algorithm (GA) using six standard test functions: Sphere, Rosenbrock, Schwefel 1.2, Rastrigin, Griewank, and Ackley in 30-dimensional search spaces. Simulation results demonstrate that AFA consistently outperforms PSO and GA across unimodal and multimodal functions. For unimodal problems such as Sphere, Rosenbrock, and Schwefel 1.2, AFA achieved significantly lower best and mean fitness values, reflecting strong exploitation capability. For multimodal functions including Rastrigin, Griewank, and Ackley, AFA effectively avoided local minima, maintained robustness, and achieved stable convergence with lower variance. Convergence analysis further indicates that AFA steadily approaches near-global optima without premature stagnation. Overall, the results highlight the effectiveness of the filter-based exploitation mechanism in balancing exploration and exploitation. Future research will focus on adaptive filtering strategies, hybrid integration with other metaheuristics, and applications to real-world optimization problems.
Desain Sistem Monitoring Lahan Pertanian Berbasis Internet of Things (IoT) Wilda Rina Hasibuan; Sunardi Sunardi; Herman Herman
JUKI : Jurnal Komputer dan Informatika Vol. 8 No. 1 (2026): JUKI : Jurnal Komputer dan Informatika, Edisi Mei 2026
Publisher : Yayasan Kita Menulis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53842/juki.v8i1.2297

Abstract

Penelitian ini dilakukan pada lahan pertanian jambu Madu Deli Hijau di Kecamatan Stabat, Kabupaten Langkat, Provinsi Sumatera Utara dengan luas 1 ha dan ditanami 500 pohon. Selama ini, pengelolaan pertanian masih dilakukan secara tradisional dan berakibat pada penurunan kualitas dan hasil panen. Pemanfaatan teknologi IoT, petani dapat memonitor suhu dan kelembapan udara, kadar kelembapan tanah, serta tingkat nutrisi nitrogen (N), fosfor (P), dan kalium (K) secara otomatis. Data yang didapat secara real-time memungkinkan petani untuk segera melakukan tindakan pengelolaan yang tepat. Metode pada penelitian ini menggunakan menggunakan metode Research and Development (R&D) yang dapat menghasilkan sistem yang efektif, efisien, dan user-friendly sehingga sistem monitoring berbasis IoT ini diharapkan dapat membantu petani mendapatkan hasil panen yang lebih memuaskan dan berkualitas. Hasil uji coba di lahan pertanian mendapatkan akurasi rata–rata suhu, kelembapan udara, dan kelembapan tanah masing-masing sebesar 98,56%, 98,89%, dan 98,92%. Pengukuran dengan termometer sebagai alat standar SNI diperoleh perbedaan yang sangat kecil yaitu masing-masing sebesar 0,42%, 0,71%, dan 0,71%. Parameter indeks resiko pengeringan tanah (IRTP) minimal terjadi pada 9,24% dan maksimal 10,50%. Pengukuran indeks kelembapan tanah terhadap udara (IMSA) minimal sebesar 86,66% dan maksimal 98,52%. Kadar unsur hara memiliki rata–rata Nitrogen 24,12 mg/Kg, Posfor 100,50 mg/Kg, dan Kalium 44,75 mg/Kg.
PERBANDINGAN CNN UNTUK DETEKSI PENYAKIT DAUN TANAMAN NEW PLANT DISEASES BERBASIS CLOUD COMPUTING Bambang Priambodo; Abdul Fadlil; Sunardi
Jurnal Informatika Teknologi dan Sains (Jinteks) Vol 7 No 4 (2025): EDISI 26
Publisher : Program Studi Informatika Universitas Teknologi Sumbawa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51401/jinteks.v7i4.6782

Abstract

Penyakit tanaman merupakan ancaman serius bagi ketahanan pangan global, sehingga deteksi dini yang akurat penting untuk meminimalkan kerugian panen. Perkembangan Convolutional Neural Networks (CNN) memungkinkan klasifikasi penyakit daun dengan akurasi tinggi, namun keterbatasan komputasi sering menghambat, terutama di negara berkembang. Untuk itu, dibutuhkan arsitektur CNN ringan namun andal yang dapat diimplementasikan pada cloud platform (CP) dengan sumber daya terbatas. Penelitian ini membandingkan tiga arsitektur CNN—MobileNetV3-Small, EfficientNetB0, dan ResNet-50—dengan pendekatan transfer learning dua tahap menggunakan teknik unfreeze-layer. Dataset yang digunakan adalah New Plant Diseases yang mencakup 85.486 citra dari 38 kelas dan 14 spesies dengan rasio 82:13:5. Eksperimen dilakukan pada cloud platform menggunakan pipeline replikatif dengan konfigurasi hyperparameter dan callback seragam. Hasil menunjukkan ResNet-50 meraih akurasi uji tertinggi (99,34%), MobileNetV3-Small sesuai untuk keterbatasan ekstrem (97,16%) namun memilik  9 kelas dengan performa di bawah 95%, sedangkan EfficientNetB0 menawarkan keseimbangan (98,92%) dengan hanya satu kelas bermasalah. Ini konsisten dengan studi sebelumnya yang mengadaptasi EfficientNetB0 (98,4%) serta variannya dengan Focal Loss (99,72%) dan ResNet-50 (95,1%) dengan subset New Plant Diseases 10 kelas dengan rasio 80:20. Temuan ini menegaskan trade-off akurasi–efisiensi lebih nyata, sekaligus memberi rekomendasi praktis pemilihan arsitektur CNN untuk sistem deteksi penyakit tanaman berbasis komputasi terbatas di negara berkembang.
Detecting Smoking Activity Behavior using YOLOv8 and YOLOv11 Salsabilla Azahra Putri; Murinto; Sunardi
Journal of Innovation and Technology Polbeng Series on Informatics (INOVTEK Polbeng - Seri Informatika) Vol. 10 No. 2 (2025): July
Publisher : P3M Politeknik Negeri Bengkalis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35314/0q6grf14

Abstract

Smoking behavior in public spaces remains a major challenge in the implementation of public health policies, particularly within designated smoke-free zones. This study aims to examine whether architectural improvements and spatio-temporal modeling in object detection models can enhance the accuracy of real-time smoking behavior detection. Specifically, the performance of YOLOv8 and an experimental version, YOLOv11, is compared using a vision-based approach. A dataset of 3,000 annotated images is used, consisting of smoking and non-smoking activities such as drinking or phone use, with variations in lighting, body posture, and camera angles. The dataset was divided into 80% for training, 20% for validation, and 20% for testing, with data augmentation applied to improve generalization. YOLOv11 incorporates spatio-temporal modules and attention mechanisms not present in YOLOv8. Evaluation results show that YOLOv11 outperforms YOLOv8, achieving a Precision of 0.95, Recall of 0.91, and F1-Score of 0.93, while YOLOv8 reached 0.89, 0.87, and 0.88 respectively. These findings indicate that YOLOv11 offers a more robust and adaptive solution for automatically recognizing smoking behavior in real-world environments and supports the development of intelligent surveillance systems for enforcing smoke-free policies.
PELATIHAN MENCEGAH DAN MENGATASI CYBERBULLYING MELALUI ETIKA DI MEDIA SOSIAL STUDY KASUS: SMK INFORMATIKA WONOSOBO Sunardi Sunardi; Herman Herman; Fitriah; Syifa’ah Setya Mawarni
Jurnal Pengabdian Masyarakat Bumi Rafflesia Vol. 6 No. 3 (2023): Desember : Jurnal Pengabdian Kepada Masyarakat Bumi Raflesia
Publisher : Universitas Muhammadiyah Bengkulu

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

Abstract

SMK Informatika Wonosobo terletak di Kabupaten Wonosobo Provinsi Jawa Tengah. Sekolah ini fokus dalam memberikan pendidikan di bidang informatika. SMK Informatika Wonosobo memberikan perhatian serius terhadap masalah Cyberbullying. Cyberbullying merujuk pada tindakan yang disengaja dilakukan oleh individu atau kelompok melalui media sosial untuk menyebabkan kerugian atau penderitaan pada orang lain. Tindakan ini meliputi ancaman, pelecehan, penyebaran informasi pribadi yang tidak diinginkan. Program Pemberdayaan Umat (PRODAMAT) Program Studi magister Informatika Universitas Ahmad Dahlan melibatkan dosen dan mahasiswa dalam melakukan pelatihan yang bertujuan untuk menyadarkan pentingnya menghindari Cyberbullying dalam lingkungan sekolah. Pelatihan meliputi berbagai aspek, termasuk etika digital, pemahaman akan dampak negatif dari Cyberbullying, pentingnya menghormati privasi dan keamanan online, serta pengembangan keterampilan mengelola konflik dan empati di dunia maya. Hasil penelitian menggunakan kuisioner menunjukkan keberhasilan. Dengan skor indeks sebesar 82,16% pada skala Likert sehingga pelatihan Cyberbullying ini dapat dijadikan acuan untuk dilaksanakan di tempat yang berbeda.   Kata Kunci: cyberbullying, etika, media
Optimasi Deteksi Hama Tanaman Melon Berbasis YOLOv9 Muhammad Immawan Aulia; Anton Yudhana; Sunardi
JITU Vol 10 No 1 (2026)
Publisher : Universitas Boyolali

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36596/jitu.v10i1.2265

Abstract

Pest attacks are one of the main problems in melon cultivation, significantly impacting productivity and crop quality. Manual pest identification has limitations in terms of objectivity, consistency, and efficiency, especially in medium to large-scale agricultural fields. This study developed a computer vision-based visual detection system for melon pests by utilizing the YOLOv9 architecture and public datasets obtained from the Roboflow platform. The dataset used consisted of 1,198 images, divided into 879 training images, 131 validation images, and 188 test images. The model training process employed data augmentation techniques, generating three outputs per training example and adding noise up to 2.52% of pixels to enhance the model's resilience to visual variations. The research methodology included system architecture design, data preprocessing, model training, and performance evaluation using precision, recall, and mean Average Precision (mAP) metrics. The test results showed that the system achieved mAP@50 of 61.6%, with 56.9% precision and 58.8% recall, indicating adequate detection capability with good inference efficiency. Thus, the developed system has the potential to be used as an early detection mechanism for melon plant pests to support decision-making in precision agriculture.
Co-Authors Abd. Rasyid Syamsuri Abdul Djalil Djayali Abdul Fadlil Abdul Fadlil Abdul Fadlil Abdul Fadlil Abdul Fadlil Abdul Fadlil Abdul Hadi Achmad Dito Ahmad Azhar Kadim Ahmad Ikrom Ahmad Raditya Cahya Baswara Ahmad Syahril Mohd Nawi Aldi Bastiatul Fawait Fawait Alfian Ma’arif Alwas Muis Anggit Pamungkas Anton Yudhana Anton Yudhana Anton Yudhana Anton Yudhana Apik Rusdiarna Indra Praja Ardiansyah Ardiningtias, Syifa Riski Ardiningtias Arief Setyo Nugroho Ariful Aziz Arizona Firdonsyah Asep Setyaji Aulia, Aulia Azrul Mahfurdz Azrul Mahfurdz Azrul Mahfurdz Azrul Mahfurdz Bambang Priambodo Bambang Subana Budi Santosa Deco Aprilliansyah Denis Prayogi Denis Prayogi Dewi Sahara Dewi Sahara Nasution Dewi Soyusiawaty Dewi Soyusiawaty Dian Novianti Doddy Teguh Yuwono Dwi Aryanto Dwi Aryanto Eko Aribowo Eko Handoyo Ermin Al Munawar Ermin Ermin Evrynda Widyasari Puspa Dewi Faqihuddin Al-anshori Fatma Nuraisyah, Fatma Fiftin Noviyanto Fijaya Dwi Bima Sakti Putra Fijaya Dwi Bima Sakti Putra Fijaya Dwi Bimasakti Firdonsyah, Arizona Fitriah Fitriyani Tella Fitriyanto, Rachmad Furizal Furizal Furizal Furizal Gema Kharismajati Guguh Makbul Rahmadani Fitra H. Ahmad Hartanta, Agus Jaka Sri Hartini, Sri Haryani Alamsyah Herman Herman Herman Herman Herman Herman Herman Herman Herman Yuliansyah Hernawan Aji Nugroho Heru Hermawan Hikmatyar Insani Himawan I Azmi Ibnu Muakhori Ihyak Ulumuddin Iif Alfiatul Mukaromah Imam Riadi Imam Riadi Imam Riadi Imam Riadi Imam Riadi Imam Riadi Imam Riadi Imam Riadi Imam Riadi Imam Riadi Irhash Ainur Rafiq Irwansyah Irwansyah Irwansyah Irwansyah Jafri Din Janu Prasetyo januari audrey January Audrey Joko Supriyanto Joko Triyanto Kemal Thoriq Al-Azis Khoir, Syaiful Amrial Krisna Astianingrum Lina Handayani Luh Putu Ratna Sundari Lukman Reza Lukman Reza M Murinto M. Ihya A. Elfatih Mardhiatul Ihsaniah Miftahuddin Fahmi Mirza Sutrisno Mitra Adhimukti Mohd Azriq Abd Aziz Muchamad Kurniawan Muchlas, Muchlas Muchrisal Muchrisal Muchrisal Muflih, Ghufron Zaida Muh. Hajar Akbar Muhammad Amirul Mu'min Muhammad Fauzan Gustafi Muhammad Fauzan Gustafi Muhammad Kunta Biddinika Muhammad Kunta Biddinika Muhammad Muizz Mohd Nawawi Muhammad Nashiruddin Darajat Muhammad Nur Ardhiansyah Muhammad Sabiq Dzakwan Muhammad Sabiq Dzakwan Muntiari, Novita Ranti Murinto Murinto Musri Iskandar Nasution Muzakkir Pangri Nasirudin Nasirudin Nazuki Nazuki Nia Ekawati Nia Ekawati Nugroho, Hernawan Aji Nur Makkie Perdana Kusuma Nur Ratnawati Nuril Mustofa Pahlevi, Ryan Fitrian Panggah Widiandana Pradana Ananda Raharja Priyatno Priyatno Puji Ristianto Puriyanto, Riky Dwi Rachmad Fitriyanto Rachmad Very Ananda Saputra Raja Bidin Raja Hassan Rajunaidi Rajunaidi Rani Rotul Muhima Restu Prima Yudha Restu Prima Yudha Rezki Ramdhani Ricky Irawan Putra Rifkan Firdaus Rio Dwi Listianto Rio Ikhsan Alfian Rosmini Rosmini Rudy Ansari Rudy Ansari Rusydi Umar Rusydi Umar Rusydi Umar Rusydi Umar Saberi Mawi Sahiruddin Sahiruddin Saifullah, Shoffan Salsabilla Azahra Putri Saputro, Mochammad Yulianto Andi Septiyawan Rosetya Wardhana Sharipah Salwa Mohamed Son Ali Akbar Sri Rahayu Astari Sri Rahayu Astari Sri Winiarti Sri Winiarti Subrata, Arsyad Cahya Sukma Aji Supriyanto Syaiful Khoir Syed Abdullah Syed Abdullah Syifa Riski Ardiningtias Syifa'ah Setya Mawarni Syifa’ah Setya Mawarni Syifa’ah Setya Mawarni Tole Sutikno Tomy Chandra Mahendra Tresna Yudha Prawira Tri Antoro Tristanti, Novi Ummi Syafiqoh Virasanty Muslimah Wahyu S Aji Watra Arsadiando Wawan Darmawan Wijaya, Setiawan Ardi Wilda Rina Hasibuan Yana Mulyana Yuniarti Lestari Yuwono Fitri Widodo