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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) 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

Author-ID : 621425

Aerospace Engineering 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 Dentistry Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Immunology & microbiology Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Neuroscience Nursing Physics Public Health Social Sciences Transportation Veterinary Other

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Peningkatan Literasi Digital Bagi Masyarakat Desa Melalui Pelatihan Keamanan Siber Dasar Berbasis Komunitas Putrama Alkhairi; Agus Perdana Windarto; Solikhun; Anjar Wanto
JPM: Jurnal Pengabdian Masyarakat Vol. 6 No. 1 (2025): Juli 2025
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/jpm.v6i1.2529

Low digital literacy in rural communities is a big gap for increasing cases of digital crime such as online fraud, phishing, and the spread of hoaxes. This community service activity aims to increase the understanding and awareness of the community of LK.I Sukamulia Village, Sinaksak Village, Tapian Dolok District, Simalungun Regency regarding the importance of cybersecurity through community-based basic training. The activity was carried out for five days, attended by 50 participants with various professional backgrounds such as farmers, traders, laborers, motorcycle taxi drivers, teachers, and online entrepreneurs. The method of implementing the activity consisted of the initial survey stage, module preparation, interactive training, direct practice, and evaluation of results. The material presented included an introduction to digital threats, how to create a secure password, the use of two-factor authentication, and the practice of using security applications. Evaluation was carried out through pre-tests and post-tests as well as observations during the activity. The results showed an average increase in participant understanding of 83% after participating in the training. In addition, the Village Digital Community was also formed as a sustainable step for local digital security education. This activity proves that a practical and contextual educational approach can increase community resilience to digital risks and can be replicated in other villages to expand the impact of community service.

Pelatihan Pemanfaatan Mendeley Desktop Sebagai Program Istimewa Untuk Akademisi Dalam Membuat Citasi Karya Ilmiah Windarto, Agus Perdana; Hartama, Dedy; Wanto, Anjar; Parlina, Iin
Aksiologiya: Jurnal Pengabdian Kepada Masyarakat Vol 2 No 2 (2018): Agustus
Publisher : Universitas Muhammadiyah Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30651/aks.v2i2.1319

Desktop mendeley application is actually an application intended to facilitate the creation of citations and a list of libraries commonly used by the authors, so the authors will be pressed error in making the bibliography and facilitate in obtaining the writings to be cited. In addition to creating scientific papers, this application can also be used to manage the files of online journal articles that are the output of a scientific work. Furthermore, participants can utilize this application for the purpose of making a bibliography or collection of abstracts of certain fields of journal articles subscribed. Training activities undertaken in Community Service activities show that participants have a material understanding and the potential to make refernsi managers better and maximum by utilizing mendeley desktop applications.

Optimizing convolutional neural network hyperparameters to enhance liver segmentation accuracy in medical imaging Purnama, Iwan; Windarto, Agus Perdana; Solikhun, Solikhun
International Journal of Electrical and Computer Engineering (IJECE) Vol 15, No 4: August 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v15i4.pp3876-3887

Liver segmentation in medical imaging is a crucial step in various clinical applications, such as disease diagnosis, surgical planning, and evaluation of response to therapy, which require a high degree of precision for accurate results. This research focuses on increasing the accuracy of liver segmentation by optimizing hyperparameters in the convolutional neural network (CNN) model using the developed ResNet architecture. The uniqueness of this research lies in the application of hyperparameter optimization methods such as random search and Bayesian optimization, which allow broader and more efficient exploration than conventional approaches. The results show that the DeepLabV3Plus model (the proposed model) significantly outperforms the standard ResNet in the image segmentation task. DeepLabV3Plus shows excellent performance with an MIoU score of 0.965, a PA Score of 0.929, and a meager loss value of 0.011. These results show that DeepLabV3Plus is able to recognize and predict segmentation areas very accurately and consistently and minimize prediction errors effectively. In conclusion, the results of this study show a significant improvement in segmentation accuracy, with the optimized model providing better performance in the evaluation.

Enhancing Autonomous Vehicle Navigation in Urban Traffic Using CNN-Based Deep Q-Networks Windarto, Agus Perdana; Solikhun, Solikhun; Wanto, Anjar
Journal of Applied Data Sciences Vol 6, No 4: December 2025
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v6i4.896

This research proposes a CNN-based Deep Q-Network (CNN-DQN) model to enhance the navigation capabilities of autonomous vehicles in complex urban environments. The model integrates CNN for spatial abstraction with reinforcement learning to enable end-to-end decision-making based on high-dimensional sensor data. The primary objective is to evaluate the impact of CNN-DQN state abstraction on the quality and stability of the resulting policy. Using a grid-based simulator, the agent is trained on a synthetic dataset representing urban traffic scenarios. The CNN-DQN model consistently outperforms standard DQN in multiple metrics: cumulative reward increased by 14.3%, loss convergence accelerated by 22%, and mean absolute error (MAE) reduced to 0.028. Furthermore, the model achieved a Pearson correlation coefficient of 0.94 in predicted actions and demonstrated superior robustness under Gaussian noise perturbation, with reward loss limited to 6.18% compared to 18.7% in the baseline. Visualizations of CNN feature maps reveal spatial attention patterns that support efficient path planning. The action symmetry index confirms that the CNN-DQN agent exhibits consistent left-right decision behavior, validating its policy regularity. The novelty of this study lies in its combined use of deep spatial encoding and value-based reinforcement learning for structured, rule-based environments with real-time control implications. These findings indicate that CNN-enhanced reinforcement learning architectures can significantly improve autonomous navigation performance and robustness in dynamic urban settings.

Implementation of Random Forest Optimized with Ant Colony Optimization (ACO) for Breast Cancer Prediction Ht. Barat, Ade Ismiaty Ramadhona; Siregar, Sandy Putra; Poningsih, Poningsih; Windarto, Agus Perdana; Solikhun, Solikhun; Sembiring, Rahmat Widia
Journal of Computer System and Informatics (JoSYC) Vol 6 No 4 (2025): August 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josyc.v6i4.7116

Breast cancer is a significant disease impacting women globally, highlighting the necessity for precise and dependable diagnostic models. This study aims to improve breast cancer prediction by optimizing the Random Forest algorithm using Ant Colony Optimization (ACO). This study uses datasets containing various cell characteristics to build and evaluate models. The ACO algorithm is applied to fine-tune the hyperparameters of the Random Forest model and improve its predictive performance. The experimental results showed that the optimized Random Forest model outperformed the baseline model in all evaluation metrics. The optimized model achieved an accuracy of 94.74%, precision of 97.92%, recall 90.38%, an F1 score of 92.93%, and an AUC score of 0, 9449 compared to the basic Random Forest model, with lower scores across all metrics. This improvement highlights the effectiveness of ACOs in improving model performance, especially in reducing false negatives, which are critical for medical diagnosis. This study demonstrates that ACO successfully fine-tunes Random Forest hyperparameters, achieving superior accuracy compared to baseline and outperforming previous optimization methods such as PSO. These findings confirm that the combination of Random Forest and ACO offers a powerful and effective approach to improving the accuracy of breast cancer predictions, making them a valuable tool for clinical decision-making.

Optimization of Accuracy Improvement through Modified ShuffleNet Architecture in Rice Classification Ahmad, Abdullah; Hartama, Dedy; Windarto, Agus Perdana; Wanto, Anjar
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 9 No 5 (2025): October 2025
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v9i5.6411

Accurate rice classification is essential to determine the quality and market value of rice. Traditional methods of rice classification are often time-consuming and error-prone, so a more efficient and accurate solution is needed. This study aims to optimize rice classification using Convolutional Neural Networks (CNN) combined with the ShuffleNet architecture, which offers high computational efficiency without sacrificing accuracy. The dataset used comes from Kaggle, containing 8750 rice grain images divided into five classes: Arborio, Basmati, Ipsala, Jasmine, and Karacadag. The uniqueness of this study is the application of ShuffleNet Proposed in rice classification, which provides improved performance compared to basic CNN models such as MobileNet, ShuffleNet, and RestNet. The results showed that the MobileNet model achieved 80% accuracy, RestNet 94%, and ShuffleNet achieved 100% accuracy with precision, recall, and F1 values also 100%. However, the ShuffleNet model experienced overfitting when tested with new data, resulting in an accuracy of only 20%. To overcome this, further optimization was carried out on the model. The results of statistical tests (paired t-test and Wilcoxon test) show significant differences between ShuffleNet Proposed and other models, which proves that the improvements applied to this model provide significant improvements. The implications of this study can improve the efficiency and accuracy of rice classification, which has the potential to improve the quality and market value of rice in the agricultural industry.

Optimasi LSTM Mengurangi Overfitting untuk Klasifikasi Teks Menggunakan Kumpulan Data Ulasan Film Kaggle IMDB Alkhairi, Putrama; Windarto, Agus Perdana; Efendi, Muhamad Masjun
Building of Informatics, Technology and Science (BITS) Vol 6 No 2 (2024): September 2024
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v6i2.5850

This study aims to develop and optimize a Long Short-Term Memory (LSTM) model to reduce overfitting in text classification using the Kaggle IMDB movie review dataset. Overfitting is a common problem in machine learning that causes the model to overfit to the training data, thus degrading its performance on the test data. In this study, various optimization techniques such as regularization, dropout, and careful training methods are applied to improve the generalization of the LSTM model. This study shows that overfitting reduction techniques, such as dropout and the use of the RMSProp optimizer, significantly improve the performance of the Long Short-Term Memory (LSTM) model in IMDB movie review text classification. The optimized LSTM model achieves an accuracy of 83.45%, an increase of 2.07% compared to the standard model which has an accuracy of 81.38%. The precision of the optimized model increases to 89.65%, compared to 84.46% in the standard model, although the recall is slightly lower (75.69% compared to 76.91%). The F1-score of the optimized model is also higher, which is 82.07% compared to 80.53% in the standard model. The experimental results show that the techniques successfully improve the accuracy and reliability of the text classification model, with better performance on the test data. This research makes a significant contribution to understanding and overfitting in deep learning models in the context of natural language processing, and offers insights into best practices in applying LSTM models to text classification.

PREDICTION OF PRODUCT SALES RESULTS USING ADAPTIVE NEURO FUZZY INFERENCE SYSTEM (ANFIS) Sinaga, Dolli Sari; Windarto, Agus Perdana; Nasution, Rizki Alfadillah; Damanik, Irfan Sudahri
Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 1 No. 2 (2022): February 2022
Publisher : Yayasan Kita Menulis

This study aims to optimize profits and minimize losses from product sales at X Market has achieved in the future. The data used in this study were obtained directly from X Market Trade by observing and interviewing. X Market Tradingis one of the industries that produces and sells food products to be marketed in the region and outside the region. The data to be processed is the result of the sale of food products at X Market uses the adaptive neuro fuzzy inference system (ANFIS) method which is a combination of Fuzzy Logic and Artificial Neural Networks. The data used is monthly sales data from 2018 to 2020 as many as 36 data. From a total of 36 data, it will be divided into 2 types of training and test data distribution, namely 90:10 with a total of 60 epochs and a learning rate range of 0.1 – 0.9. From the research results obtained the highest accuracy of 88.55% on 90% training data and 10% test data with a learning rate of 0.6. It was concluded that the ANFIS method could be implemented in predicting the sales of tofu. By doing this research is expected to provide input to X Market in optimizing profits and minimizing losses from product sales in the future.

RETRACTED : Decision support system in Predicting the Best teacher with Multi Atribute Decesion Making Weighted Product (MADMWP) Method Solikhun, Solikhun; Windarto, Agus Perdana; Amri, Amri
International Journal of Artificial Intelligence Research Vol 1, No 1 (2017): June 2017
Publisher : Universitas Dharma Wacana

Following a rigorous, carefully concerns and considered review of the article published in International Journal of Artificial Intelligence ResearchÂ to article entitled â€œDecision support system in Predicting the Best teacher with Multi-Attribute Decision Making Weighted Product (MADMWP) Methodâ€ Vol 1, No 1, pp. 47-53, June 2017, DOI:Â https://doi.org/10.29099/ijair.v1i1.1This paper has been found to be in violation of the International Journal of Artificial Intelligence Research Publication principles and has been retracted.The article contained redundant material, the editor investigated and found that the paper published in JURASIK(Jurnal Riset Sistem Informasi dan Teknik Informatika) Vol. 1, No. 1, pp. 56-63, 2016, Â http://ejurnal.tunasbangsa.ac.id/index.php/jurasik/article/view/9The document and its content have been removed from International Journal of Artificial Intelligence Research, and reasonable effort should be made to remove all references to this article.

Implementation of Data Mining on Rice Imports by Major Country of Origin Using Algorithm Using K-Means Clustering Method Windarto, Agus Perdana
International Journal of Artificial Intelligence Research Vol 1, No 2 (2017): December 2017
Publisher : Universitas Dharma Wacana

Indonesia is a country where most of its people rely on the agricultural sector as a livelihood. Indonesia's rice production is so high that it can not meet the needs of its population, consequently Indonesia still has to import rice from other food producing countries. One of the main causes is the enormous population. Statistics show that in the range of 230-237 million people, the staple food of all residents is rice so it is clear that the need for rice becomes very large. This study discusses the application of datamining on rice import by main country of origin using K-Means Clustering Method. Sources of data of this study were collected based on import import declaration documents produced by the Directorate General of Customs and Excise. In addition since 2015, import data also comes from PT. Pos Indonesia, records of other agencies at the border, and the results of cross-border maritime trade surveys. The data used in this study is the data of rice imports by country of origin from 2000-2015 consisting of 10 countries namely Vietnam, Thailand, China, India, Pakistan, United States, Taiwan, Singapore, Myanmar and Others. Variable used (1) total import of rice (net) and (2) import purchase value (CIF). The data will be processed by clustering rice imports by main country of origin in 3 clusters ie high imported cluster, medium imported cluster and low import level cluster. The clustering method used in this research is K-Means method. Cetroid data for high import level clusters 7429180 and 2735452,25, Cetroid data for medium import level clusters 1046359.5 and 337703.05 and Cetroid data for low import level clusters 185559.425 and 53089.225. The result is an assessment based on rice import index with 2 high imported cluster countries namely Vietnam and Thailand, 4 medium-level clusters of moderate import countries namely China, India, Pakistan and Lainya and 4 low imported cluster countries namely USA, Taiwan, Singapore and Myanmar. The results of the research can be used to determine the amount of rice imported by the main country of origin

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 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 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 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 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 Rafiqotul Husna Raharjo, Mokhamad Ramdhani 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 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 Sembiring, Rahmat Widia 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 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

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