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All Journal International Journal of Electrical and Computer Engineering IAES International Journal of Artificial Intelligence (IJ-AI) Seminar Nasional Aplikasi Teknologi Informasi (SNATI) JURNAL SISTEM INFORMASI BISNIS Techno.Com: Jurnal Teknologi Informasi Syntax Jurnal Informatika Bulletin of Electrical Engineering and Informatics Jurnal Sarjana Teknik Informatika Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI) Jurnal Informatika Jurnal sistem informasi, Teknologi informasi dan komputer Jurnal Teknologi Informasi dan Ilmu Komputer Telematika Jurnal Edukasi dan Penelitian Informatika (JEPIN) CESS (Journal of Computer Engineering, System and Science) KLIK (Kumpulan jurnaL Ilmu Komputer) (e-Journal) InfoTekJar : Jurnal Nasional Informatika dan Teknologi Jaringan E-Dimas: Jurnal Pengabdian kepada Masyarakat Jurnal Ilmiah KOMPUTASI Sistemasi: Jurnal Sistem Informasi Jurnal Teknologi dan Sistem Komputer Sinkron : Jurnal dan Penelitian Teknik Informatika Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) International Journal of Artificial Intelligence Research AKSIOLOGIYA : Jurnal Pengabdian Kepada Masyarakat JURNAL MEDIA INFORMATIKA BUDIDARMA JITK (Jurnal Ilmu Pengetahuan dan Komputer) JOURNAL OF APPLIED INFORMATICS AND COMPUTING Jurnal Sisfokom (Sistem Informasi dan Komputer) Jurnal Infomedia JUTIM (Jurnal Teknik Informatika Musirawas) Jurnal Teknologi Informasi MURA Jiko (Jurnal Informatika dan komputer) MATRIK : Jurnal Manajemen, Teknik Informatika, dan Rekayasa Komputer ALGORITMA : JURNAL ILMU KOMPUTER DAN INFORMATIKA J-SAKTI (Jurnal Sains Komputer dan Informatika) IJISTECH (International Journal Of Information System & Technology) KOMIK (Konferensi Nasional Teknologi Informasi dan Komputer) The IJICS (International Journal of Informatics and Computer Science) JURIKOM (Jurnal Riset Komputer) JUSIM (Jurnal Sistem Informasi Musirawas) Building of Informatics, Technology and Science JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) Journal of Computer System and Informatics (JoSYC) Jurnal Sistem Komputer dan Informatika (JSON) TIN: TERAPAN INFORMATIKA NUSANTARA Brahmana : Jurnal Penerapan Kecerdasan Buatan Jurnal Tunas Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) Jurnal Pengabdian Masyarakat Asia IJISTECH Journal of Applied Data Sciences RESOLUSI : REKAYASA TEKNIK INFORMATIKA DAN INFORMASI JPM: JURNAL PENGABDIAN MASYARAKAT Bulletin of Computer Science Research Journal of Informatics Management and Information Technology KLIK: Kajian Ilmiah Informatika dan Komputer J-SAKTI (Jurnal Sains Komputer dan Informatika) EXPLORER BIOS : Jurnal Teknologi Informasi dan Rekayasa Komputer BEES: Bulletin of Electrical and Electronics Engineering Bulletin of Data Science Hello World Journal of Artificial Intelligence and Engineering Applications (JAIEA) Jurnal Pengabdian Masyarakat Inovasi JOMLAI: Journal of Machine Learning and Artificial Intelligence Jurnal Ilmiah Sistem Informasi dan Ilmu Komputer Journal of Computing and Informatics Research Jurnal Riset Rumpun Ilmu Teknik (JURRITEK) Journal of Systems Engineering and Information Technology Journal of Informatics, Electrical and Electronics Engineering Jurnal Teknologi Informasi Mura Bulletin of Informatics and Data Science Bulletin of Artificial Intelligence Bulletin of Information System Research Prosiding Seminar Nasional Unimus Kesatria : Jurnal Penerapan Sistem Informasi (Komputer dan Manajemen) International Journal of Informatics and Data Science Journal of Decision Support System Research
Agus Perdana Windarto
STIKOM Tunas Bangsa, Pematangsiantar, Indonesia
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Penerapan Data Mining Klasifikasi C4.5 dalam Menentukan Tingkat Stres Mahasiswa Akhir Anggi Trifani; Agus Perdana Windarto; Hendry Qurniawan
JURAL RISET RUMPUN ILMU TEKNIK Vol. 1 No. 2 (2022): Oktober : Jurnal Riset Rumpun Ilmu Teknik
Publisher : Pusat riset dan Inovasi Nasional

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1074.729 KB) | DOI: 10.55606/jurritek.v1i2.414

Abstract

Penelitian ini bertujuan untuk melakukan Klasifikasi dalam menentukan tingkat Stres yang dialami oleh Mahasiswa Akhir di STIKOM Tunas Bangsa dengan menggunakan teknik data mining C4.5. Dengan mengetahui stres mahasiswa, pihak kampus dapat memberikan treatment dan perlakuan yang tepat terhadap mahasiswa akhir. Sumber data penelitian diperoleh dari beberapa kelas semester 6 dan 8 sebanyak 110 mahasiswa, melalui wawancara dan pembagian kuesioner. Atribut yang digunakan sebagai parameter penilaian untuk mengetahui tingkat stres yang dialami oleh mahasiswa akhir di STIKOM Tunas Bangsa, Pematang siantar antara lain: Interpersonal (C1), Intrapersonal (C2), Akademik (C3) dan Lingkungan (C4). Proses pengujian penelitian ini menggunakan bantuan software RapidMiner untuk membuat pohon keputusan. Dari hasil pengolahan C4.5 dengan menggunakan bantuan software RapidMiner atribut Interpersonal (C1) menjadi atribut yang paling berpengaruh terhadap tingkat stres Mahasiswa Akhir dan data performance yang ditunjukkan terhadap kesesuaian metode C4.5 akurasinya adalah 87,88%.
Refining CNN architecture for forest fire detection: improving accuracy through efficient hyperparameter tuning Kurniawan, Kurniawan; Perdana Windarto, Agus; Solikhun, Solikhun
Bulletin of Electrical Engineering and Informatics Vol 14, No 2: April 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v14i2.8805

Abstract

Forest fire detection is one of the critical challenges in disaster mitigation and environmental management. This research aims to increase the accuracy of forest fire detection through improving the convolutional neural network (CNN) architecture. The main focus of research is on efficient hyperparameter tuning, which includes selecting and optimizing key parameters in CNN architectures such as convolutional layers, kernel size, number of neurons in hidden layers, and learning algorithms. By utilizing grid search techniques and heuristic-based optimization algorithms, the resulting CNN model shows significant improvements in detection accuracy compared to previous approaches. The evaluation was carried out using a pre-processed forest fire image dataset, and the results show that architectural refinement and appropriate hyperparameter tuning can substantially improve model performance. Evaluation results comparing two models, VGG16 and the proposed method, show significant improvements over the proposed method. The proposed method shows better capabilities with an accuracy of 95.31% and a precision of 97.22%. This research contributes to developing a more reliable and efficient forest fire detection system, which is expected to be used in real applications to reduce the impact of forest fires more effectively.
Comparative Study of Mobilenet and Resnet for Watermelon Leaf Disease Classification Using Deep Learning Ahmad, Abdullah; Wanto, Anjar; Windarto, Agus Perdana; Poningsih, Poningsih
TIN: Terapan Informatika Nusantara Vol 6 No 1 (2025): June 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/tin.v6i1.7543

Abstract

Watermelon leaf diseases, caused by various factors such as fungi, viruses, and bacteria, can have a significant impact on agricultural yields. To increase the amount and quality of watermelon produced, early diagnosis of this disease is essential. This study aims to compare the performance of two Convolutional Neural Networks (CNN) architectures included in Deep Learning, namely MobileNet and ResNet, in classifying watermelon leaf diseases using a dataset taken from Kaggle. This dataset consists of 1000 watermelon leaf images with three conditions, namely Downy Mildew (380 images), Healthy (205 images), and Mosaic Virus (415 images). ). 95% accuracy, 96% precision, 94% recall, and 95% f1-score are the results of the MobileNet model. In contrast, the ResNet model performs better, with 97% accuracy, 96% precision, 97% recall, and 97% f1-score. The study's findings show that ResNet outperforms MobileNet in the classification of watermelon leaf illnesses, despite both models' excellent and effective performance for automatic plant disease detection applications.
Penerapan Metode VIKOR Dalam Menentukan Jasa Ekspedisi Terbaik Berdasarkan Konsumen Aprilia Syahputri; Rizal Efendi; Dewi Fortuna Efendi; Agus Perdana Windarto
Journal of Computing and Informatics Research Vol 4 No 3 (2025): July 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/comforch.v4i3.2060

Abstract

Kemajuan teknologi informasi dan komunikasi yang pesat telah mempermudah masyarakat dalam menjalankan berbagai aktivitas secara instan, termasuk dalam melakukan transaksi jual beli secara daring. Peningkatan minat masyarakat terhadap belanja online mendorong meningkatnya permintaan terhadap layanan ekspedisi yang mampu menjamin pengiriman barang dengan cepat, aman, dan tepat waktu. Namun demikian, banyaknya pilihan jasa ekspedisi yang tersedia sering kali membuat konsumen merasa kesulitan dalam menentukan pilihan terbaik. Selain itu, berbagai kendala seperti keterlambatan pengiriman, kerusakan barang, hingga ketidakakuratan pelacakan paket secara real-time menjadi keluhan umum yang dialami konsumen. Penelitian ini bertujuan untuk membantu konsumen dalam memilih jasa ekspedisi terbaik dengan menerapkan Sistem Pendukung Keputusan menggunakan metode VIKOR (VIšekriterijumsko KOmpromisno Rangiranje). Metode ini mempertimbangkan beberapa faktor penting yang relevan dengan kebutuhan konsumen, antara lain kecepatan pengiriman, cakupan wilayah, kemudahan pelacakan paket, kualitas layanan pelanggan, serta biaya pengiriman. Data diperoleh melalui penyebaran kuesioner daring menggunakan Google Form kepada responden pengguna jasa ekspedisi. Hasil analisis menunjukkan bahwa JNT Express terpilih sebagai jasa ekspedisi terbaik dengan nilai indeks VIKOR sebesar 0,102. Penelitian ini tidak hanya memberikan rekomendasi berbasis data kepada konsumen, tetapi juga dapat dijadikan sebagai masukan strategis bagi perusahaan ekspedisi dalam meningkatkan daya saing dan kualitas layanannya di tengah persaingan industri logistik yang semakin ketat.
Model Peramalan Artificial Neural Network pada Peserta KB Aktif Jalur Pemerintahan menggunakan Artificial Neural Network Back-Propagation B. Herawan Hayadi; I Gede Iwan Sudipa; Agus Perdana Windarto
MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer Vol. 21 No. 1 (2021)
Publisher : Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/matrik.v21i1.1273

Abstract

Pertumbuhan penduduk di Indonesia yang terus meningkat setiap tahunnya dan tidak disertai dengan ketersediaan lapangan pekerjaan yang mampu menampung seluruh angkatan kerja bisa menimbulkan pengangguran, kriminalitas, yang bersinggungan pula dengan rusaknya moralitas masyarakat. Oleh karena pemerintah memberikan serangkaian usaha untuk menekan laju pertumbuhan penduduk agar tidak terjadi ledakan penduduk yang lebih besar. Salah satu cara yang dilakukan adalah dengan menggalakkan program KB (Keluarga Berencana). Tujuan dari penelitian untuk membuat model prediksi dengan memanfaatkan Artificial Neural Network (ANN) pada peserta KB aktif jalur pemerintahan untuk melihat laju pertumbuhan penduduk kedepannya dalam rentang waktu tertentu guna mempermudah pemerintah dalam membuat rancangan perencanaan ke depannya. Back-propagation merupakan salah satu metode yang digunakan untuk melakukan peramalan yang merupakan bagian dari ANN. Hal ini perlu dilakukan mengingat jumlah kepadatan penduduk terus meningkat setiap tahunnya dan KB merupakan salah satu program pemerintah yang bertujuan mengendalikan laju kenaikan penduduk di Indonesia. Dataset yang digunakan yakni peserta KB aktif di Kota Pematangsiantar bulan agustus 2019 – januari 2020. Pengujian dilakuan dengan bantuan software matlab dengan menguji 5 model arsitektur (try error) yakni model 4-5-1; model 4-7-1; model 4-8-5-1; dan model 4-9-7-1. Hasil analisis diperoleh bahwa model arsitektur 4-8-5-1 merupakan yang terbaik dan dijadikan acuan untuk meramalkan peserta KB aktif pada jalur pemerintah dengan tingkat akurasi sebesar 71% (terbaik dari 4 model arsitektur lainnya). Model ANN tersebut dapat diimpementasikan untuk melakukan prediksi terhadap peserta KB aktif jalur pemerintahan sehingga pemerintah dapat melakukan rancangan untuk kedepannya.
OPTIMIZATION OF PREDICTION OF LUNG DISORDERS USING LSTM COMPARISON OF RMSPROP AND ADAM Batubara, Egi; Solikhun; Windarto, Agus Perdana
JITK (Jurnal Ilmu Pengetahuan dan Teknologi Komputer) Vol. 11 No. 3 (2026): JITK Issue February 2026
Publisher : LPPM Nusa Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33480/jitk.v11i3.7767

Abstract

Accurate prediction of pulmonary disorders is essential to support early diagnosis and clinical decision-making. Medical time-series data are inherently nonlinear and temporally dependent, making conventional statistical approaches insufficient. This study formulates pulmonary disorder prediction as a regression problem and proposes an optimized Long Short-Term Memory (LSTM) model by comparing two widely used optimization algorithms, RMSProp and Adam. The dataset consists of 30,000 clinical records obtained from an open-source Kaggle repository, including demographic, behavioral, and health-related variables relevant to respiratory conditions. Data preprocessing involved categorical encoding and Min–Max normalization, followed by an 80:20 train–test split. Model performance was evaluated using Mean Squared Error (MSE), Mean Absolute Error (MAE), and the coefficient of determination (R²). Experimental results demonstrate that the Adam optimizer achieves superior performance with lower prediction errors and more stable convergence compared to RMSProp and the baseline SGD optimizer. These findings highlight the critical role of optimizer selection in LSTM-based medical time-series modeling.
Pelatihan Literasi Digital untuk Guru dan Siswa dalam Meningkatkan Kualitas Pembelajaran Jarak Jauh Windarto, Agus Perdana; Hutahaean, Jeperson; Sussolaikah, Kelik; Setiawansyah, Setiawansyah
Jurnal Pengabdian Masyarakat Inovasi Vol. 5 No. 1 (2026): February 2026
Publisher : Sekolah Tinggi Ilmu Manajemen Sukma Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35126/jpmi.v5i1.998

Abstract

This community service activity aims to improve the digital literacy of teachers and students to support the quality of distance learning. The implementation method was carried out through practice-based training involving 20 participants from among teachers and students. Evaluation results showed that before the activity, the digital literacy level of participants was in the basic to intermediate category with an average score of 1-2, while after the activity there was a significant increase to an average score of 4-5. Participants' satisfaction responses also showed that 80% expressed satisfaction or were very satisfied, confirming the effectiveness of the training. This activity successfully addressed the needs of partners regarding the constraints of low digital competency in online learning, despite the limitations of the limited number of participants and the short duration of implementation. Therefore, this activity is recommended to be expanded and integrated into the ongoing professional development program for teachers and students.
Penerapan Metode Multi Objective Optimization on The Basic of Ratio Analysis (MOORA) pada Pemilihan Masker Organik Wajah Berdasarkan Kriteria Ade Dwi Amanda; Fildzah Nadya Arieni; Agus Perdana Windarto
Jurnal Sistem Komputer dan Informatika (JSON) Vol. 2 No. 3 (2021): Mei 2021
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/json.v2i3.3011

Abstract

Organic masks are masks made from natural ingredients that have good nutritional content for the face. Organic masks have many benefits which are certainly no less than treatments at a beauty doctor. Facial masks are beauty masks in the form of gels, pastes and powders which are applied to clean and tighten the skin, especially facial skin. Face masks also function as carriers for active ingredients that are useful for skin health, such as extra plants, essential oils, or seaweed that can be absorbed by the skin's surface to be carried into the blood circulation. The purpose of this study is to help consumers determine the best organic face mask. This research method uses the MOORA method. The criteria used are Variant (A), Size (B), Price (C), Aroma (D), Method of Use (E), Rules of Use (F), Results of Use (G). The alternatives used are Crushlicious (0.1147), Namo.Id (0.2758), NHM (0.2257), Lea Gloria (0.7218), Poupeepou (0.1692), and Natuna Oilvera (0.1157). Thus, the best value of the six alternatives is the Lea Gloria Organic Face Mask with a value of 0.7218.
Deep Learning-Based Early Detection Optimization for Rice Leaf Diseases to Support Sustainable Local Agriculture Putrama Alkhairi; Agus Perdana Windarto; Mesran Mesran; Roznim Roznim
Building of Informatics, Technology and Science (BITS) Vol 7 No 4 (2026): March 2026
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v7i4.9338

Abstract

Rice leaf diseases such as Bacterial Blight and Blast are major threats to rice productivity that directly impact food security and the sustainability of local agriculture. This study aims to develop and optimize a deep learning-based early detection system for rice leaf diseases using a Convolutional Neural Network (CNN) architecture, specifically the Inception_v3 model. The research method includes five main stages, namely collecting rice leaf image datasets, data pre-processing (resize, normalization, and augmentation), CNN model design, model training and evaluation, and performance optimization through the application of different optimizer algorithms. Two model variants were tested and compared, namely Inception_v3 Basics with the RMSprop optimizer and Inception_v3 Optimization with the Adam optimizer. Experimental results showed that the Inception_v3 Optimization model provided the best performance, with a Precision value of 0.9672, Recall of 0.8939, F1-score of 0.9291, Balanced Accuracy of 0.9297, Matthews Correlation Coefficient (MCC) of 0.8578, Cohen's Kappa of 0.8573, and AUC ROC of 0.98. These results indicate that the Adam optimizer is able to accelerate convergence and improve model accuracy compared to RMSprop, while producing a more stable and efficient classification system. Thus, this study successfully demonstrated that the optimized Inception_v3 architecture can be used effectively for early detection of rice leaf diseases and has high potential for integration into smart farming systems to support sustainable, technology-based local agricultural practices.
Co-Authors Abdul Karim Abdullah Ahmad Acai Sudirman Ade Dwi Amanda Adinda Putri Azhari Afrialita Widiastari Afrina Wati Alkhairi, Putrama Alkhairi, Putrama Alrizca Trydillah Alrizca Trydillah M Amanda, Ade Dwi Ambariyanto Ambariyanto Amri Amri Anan Wibowo Anandi Ayu Anggi Trifani Anjani, Dila Dwi Annisa, Liza Aprilia Syahputri Arfandi Arfandi Ariana, Anak Agung Gede Bagus Arieni, Fildzah Nadya Arifah Hanum Arifin Nur, Khairun Nisa Aulanda, Lulu Aulia Sugarda Aulia Sugarda Ayu Wulandari Ayu, Nur Zannah sekar Azhari, Ridhan Azzahra, Fahrija B. Herawan Hayadi Badawi, Masrof Batubara, Egi Beauti, Intan Bintang Aufa Sultan Butarbutar, Marisi Chairul Fadlan Chairul Fadlan Chintya Irwana Cici Astria Cici Astria Cici Astria Dedi Suhendro Dedi Suhendro Dedi Suhendro Dedi Suhendro Dedi Suhendro Dedy Hartama Dedy Hartama Dedy Hartama Dedy Hartama Dedy Hartama Dedy Hartama Defit, Sarjon Della Puspita Deri Setiawan Desi Asima Silitonga Desi Asima Silitonga Desi Ratna Sari Devi Syahfitri Dewi Fortuna Efendi Dewinta Marthadinata Sinaga Deza Geraldin Salsabilah Saragih Dicky Wahyudi Manurung Dinda Nabila Batubara Dinda Nabila Batubara Dinda Nabila Batubara Dini Rizky Sitorus P Dio Hutabarat Disty Wahyuli Dwi Findi Auliasari Dwi Findi Auliasari Dwira Azi Pragana Dwira Azi Pragana Dwita Elisa Sinaga Edi Suharto Edy Satria Efendi, Muhamad Masjun Ega Widya Sari Eka Desriani Aritonang Eka Irawan Eka Irawan Eka Irawan Erbin Chandra Erlin Windia Ambarsari Evani Sitohang Fachri, Barany Fadhillah Azmi Tanjung Fadilla Anissa Fadillah Alwi Pambudi Fadlan, Chairul Fahrija Azzahra Fahry Husaini Fahry Husaini Fajar Syahputra Fania, Fira Fanny Adelia Fatmawati, Kiki Febiola, Adinda Fica Oktavia Lusiana Fifto Nugroho Fildzah Nadya Arieni Fira Fania Fira Fania Fitri Rizki Frskila Parhusip Gita Febrianti Gita Febrianti Gumilar Ramadhan Pangaribuan Handrizal Handrizal Handrizal Handrizal Hanifah Urbach Sari Hanifah Urbach Sari Harahap, Zaki Faizin Hartama, Dedy Hartama, Dedy Hasudungan Siahaan Hendry Qurniawan Hendry Qurniawan Hendry Qurniawan Hersatoto Listiyono Heru Satria Tambunan Ht. Barat, Ade Ismiaty Ramadhona I Gede Iwan Sudipa Ida Mayanju Pandiangan Ihsan Maulana Muhamad Ihsan Syajidan Iin Indriani Iin Parlina Iin Parlina Iin Parlina Iis Warlinda Ikhwan Lubis Ilham Syahputra Saragih Ima Kurniawan Indah Dea Anastasia Indah Pratiwi M.S Indah Syahputri Indra Riyana Rahadjeng Indri Fatma Irfan Sudahri Damanik Irnanda, Khairunnissa Fanny Irwana, Chintya Isnaini, Alvina Ivo Yohana Manurung Iwan Purnama Jahril Jalaluddin Jalaluddin Jaya Tata Hardinata Jeperson Hutahaean Johan Muslim Jufriadif Na`am, Jufriadif Khairun Nisa Arifin Nur Khairunnissa Fanny Irnanda Khairunnissa Fanny Irnanda Kiki Apni Puspita Sari Kiki Fatmawati Kurniawan Kurniawan Kusuma, Rizky Tri Leza Khairani Linda Sari Dewi Listy Oktaviani Lubis, Ikhwan M Fauzan M Fauzan M Fauzan M Fauzan M Fauzan M Fauzan M FAUZAN M Mesran M Mesran M. Fauzan M.Ridwan Lubis Manurung, Dicky Wahyudi Maria Etty Simbolon Marini Marini Masitha Masitha Masitha, Masitha Maulidya Rahma Siregar Mawaddah Anjelita Mawaddah Anjelita Mesran Mesran Mesran Mesran Mesran, Mesran Mhd Gading Sadewo Mhd Gading Sadewo Mhd Gading Sadewo Mhd Ridhon Ritonga Millah Sari Miralda, Viya Mita Yustika Mokhamad Ramdhani Raharjo Mokhamad Ramdhani Raharjo Mora Malemta Sitomorang Muhamad Muhamad Muhammad Alfahrizi Lubis Muhammad Aliyul Amri Muhammad Dwi Chandra Muhammad Fachrur Rozi Muhammad Fauzan Muhammad Kurniawansyah Muhammad Mahendra Muhammad Noor Hasan Siregar Muhammad Ridwan Lubis Muhammad Ridwan Lubis Muhammad Yasin Simargolang muhammad yuda rizki Muhammad Yuda Rizki Muliadi Musiafa, Zayid Mustika Azzahra N Nurhayati N Nurhayati Nasution, Della Fatricia Nasution, Irmanita Nasution, Rizki Alfadillah Nazlina Izmi Addyna Nelson Butarbutar Nila Soraya Damanik Ninaria Purba Ningsih, Selfia Novika, Tri Nur Wulandari Nurul Atina Nurul Izzah Hadiana Nurul Rofiqo Nurwijayanti Ogi Wahyudi Okprana, Harly Oktaviani, Selli Onita Sari Sinaga P, Dini Rizky Sitorus P.P.P.A.N.W Fikrul Ilmi R.H.Zer Parinduri, Ikhsan Parlina, Iin Poningsih Poningsih Poningsih Poningsih Poningsih Poningsih, Poningsih Prakasiwi, Cindy Pramesti, Adinda Frizy Prihandoko Prihandoko Putrama Alkhairi Putrama Alkhairi Putrama Alkhairi Putrama Alkhairi Rafiqotul Husna Raharjo, Mokhamad Ramdhani Rahmat Widia Sembiring - Rahmat Zulpani Raichan Septiono Ramadana, Rica Ramadani, Sri Ramadhani, Cerah Fitri Ranjani Rapianto Sinaga Ratih Ramadhanti Ratika Rizka Lubis Razalfa Aindi Siregar Rica Ramadana Ridho, Ihda Innar Rika Nur Adiha Rika Setiana Rika Setiana Rika Setiana Riski Yanti Rizal Efendi Rizki, Muhammad Yuda Rofiqo, Nurul Rohmat Indra Borman Rohmat Indra Borman Ronal Watrianthos Roni Kurniawan Rosanti, Yerika Puspa Rotua Sihombing Hutasoit Roy Chandra Telaumbanua Roznim Roznim Rozy, Muhammad Fachrur S Solikhun S Solikhun Sadewo, Mhd Gading Sahendra Fahreza Saidah, Fatiyah Saifullah Saifullah Saifullah Saifullah Salis, Rahmi Samosir, Rafiah Aini Sandy Erlangga Sari, Hanifah Urbach Sari, Riyani Wulan Sari, Riyani Wulan Sarjon Defit Sekar Rizkya Rani Selfia Ningsih Setiawan, Yudika Dwi Setiawansyah Setiawansyah Sigit Anugerah Wardana Sinaga, Dolli Sari Sinaga, Waris Pardingatan Sinta Maulina Dewi Sinta Maulina Dewi Sintya Sintya Siregar, Razalfa Aindi Siregar, Sandy Putra Siti Hajar Siti Hawani Siti Maysaroh Siti Sundari Sitompul, Wati Rizky Pebrianti Sitti Rachmawati Yahya Solikhun Solikhun Solikhun Solikhun Solikhun Solikhun Solikhun Solikhun, Solikhun Sri Rahayu Ningsih Sri Ramadani Suci Cahya Mita Suhada Suhada Suhendro, Dedi Sundari Retno Andani Sundari Retno Andani Susi Susilowati, Susi Sussolaikah, Kelik Syahfitri, Retno Ayu Syahputra, Fajar Syahputra, Muhammad Tania Dian Tri Utami Tanjung, Fadhillah Azmi Tanjung, Fatimah Dwi Puspa Tia Imanda Sari Tia Imandasari Tia Imandasari Tira Sifrah Saragih Manihuruk Tri Ayu Lestari Tri Novika Tri Novika Tri Welanda Trydillah, Alrizca Ulfah Indriani Viya Miralda Waldi Setiawan Wanto, Anjar Warlinda, Iis Wendi Robiansyah Wendi Robiansyah Wida Prima Mustika Widiastari, Afrialita Widodo Saputra Widya Try Taradipa Winanjaya, Riki Winda Lidyasari Winda Permata Sari Wiranto Hernandesz Sirait Yanto, Musli Yuegilion Pranavarna Purba Yuegilion Pranayama Purba Yuhandri Yuhandri, Yuhandri Yuhandri, Muhammad Habib Yuli Sartika Nasution Yulia Andini Yuni Sara Luvia Zahra Nur Atthiyah Zahra Syahara Zaki Faizin Harahap Zer, P. P.P.A.N.W.Fikrul Ilmi R.H. Zulfia Darma Zuly Budiarso