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All Journal ComEngApp : Computer Engineering and Applications Journal Bulletin of Electrical Engineering and Informatics Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI) Inspiratif Pendidikan Jurnal Teknologi Informasi dan Ilmu Komputer Journal of Information Systems Engineering and Business Intelligence KLIK (Kumpulan jurnaL Ilmu Komputer) (e-Journal) Sistemasi: Jurnal Sistem Informasi Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control UICELL Conference Proceeding Jurnal Sains dan Informatika JURNAL ILMIAH INFORMATIKA Hearty : Jurnal Kesehatan Masyarakat JOURNAL OF SCIENCE AND SOCIAL RESEARCH Jurnal Biomedika dan Kesehatan Psikologi Konseling: Jurnal Kajian Psikologi dan Konseling Journal of Electronics, Electromedical Engineering, and Medical Informatics Jurnal Pengabdian Kepada Masyarakat (Mediteg) Health Information : Jurnal Penelitian International Journal of Advances in Data and Information Systems Jurnal Teknik Informatika (JUTIF) Journal of Applied Data Sciences JOURNAL LA MEDIHEALTICO Journal of Gender and Social Inclusion in Muslim Societies MAHESA : Malahayati Health Student Journal Fitrah: Journal of Islamic Education Jurnal Kolaboratif Sains Prosiding Seminar Nasional Sisfotek (Sistem Informasi dan Teknologi Informasi) Journal of Data Science and Software Engineering Jurnal Pengabdian Kepada Masyarakat Itekes Bali JUKEJ: Jurnal Kesehatan Jompa Jurnal Informatika Polinema (JIP) Jurnal Ilmiah Kesehatan Mandala Waluya Jurnal Kesehatan Masyarakat Perkotaan Indonesian Journal of Electronics, Electromedical Engineering, and Medical Informatics Holistik Jurnal Kesehatan
Fatma Indriani
Program Studi Ilmu Komputer, Fakultas Matematika Dan Pengetahuan Alam, Universitas Lambung Mangkurat, Indonesia
Religion Agriculture, Biological Sciences & Forestry Humanities Biochemistry, Genetics & Molecular Biology Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Immunology & microbiology Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Medicine & Pharmacology Nursing Public Health Social Sciences Veterinary Other

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Penerapan Metode Giving Question and Getting Answer untuk Meningkatkan Hasil Belajar Siswa pada Mata Pelajaran Pendidikan Agama Islam Azis, Abdul; Zali, Muhammad; Indriani, Fatma; Lubis, Masruroh
Fitrah: Journal of Islamic Education Vol. 4 No. 1 (2023): Juni (2023)
Publisher : Sekolah Tinggi Agam Islam Sumatera Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53802/fitrah.v4i1.379

Abstract

Mistakes in choosing learning methods have an impact on learning outcomes. So in that case the teacher must be able to determine the appropriate learning method. This study aims to improve student learning outcomes in the Islamic Religious Education subject by applying the Giving Question and Getting Answer learning method. The focus of this research is on two things, namely improving post-action learning outcomes and student learning activities. This research was conducted on class XI students of Madrasah Aliyah, Laboratory of UIN Sumatra Utara Medan. This study used the Classroom Action Research method, which was carried out in three cycles. Collecting data using observation, tests, and interviews. The results of this study indicate that the learning outcomes of students in cycle I got an average score of 76.34 in the calculation of 27 people who had completed and 3 people who had not completed the KKM score that had been determined, cycle II with an average score of 86.66 in the calculation of 28 people has been completed and 2 people have not completed the specified KKM value, cycle III with an average value of 95.12 in the calculation of 29 people has been completed and 1 person has not completed the specified KKM value. This research succeeded in proving the allegation that the giving question and getting answar methods can help improve learning outcomes.
Hubungan Perilaku Tidak Aman Dan Masa Kerja Dengan Kecelakaan Kerja Pada Pekerja Bengkel Las Di Kecamatan Sei Bamban Kabupaten Serdang Bedagai: The Relationship Between Unsafe Behavior and Length of Service with Work Accidents Among Welding Workers in Sei Bamban District, Serdang Bedagai Regency Putri Maimunah; Fatma Indriani
Jurnal Kolaboratif Sains Vol. 8 No. 12: Desember 2025
Publisher : Universitas Muhammadiyah Palu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56338/jks.v8i12.9198

Abstract

Kegiatan pengelasan memiliki risiko kecelakaan kerja yang cukup tinggi seperti luka bakar, luka gores, tertimpa benda, hingga cedera mata akibat percikan api. Penelitian ini digunakan pendekatan kuantitatif dengan desain cross-sectional. Sampel diambil dengan menggunakan total sampling dengan jumlah 40 perkerja yakni semua pekerja bengkel las di Kecamatan Sei Bamban Kabupaten Serdang Bedagai. Hasil analisis Chi-Square menunjukkan nilai p-value sebesar 0,033 yang berarti ada hubungan signifikan antara perilaku tidak aman dengan kejadian kecelakaan kerja sedangkan masa kerja dengan kecelakan kerja tidak memiliki hubungan yang signifikan dengan nilai p-value sebesar 0,256. Dapat disimpulkan bahwa perilaku tidak aman sangat berpengaruh terhadap terjadinya kecelakaan kerja, shingga penting bagi pekerja untuk menerapkan perilaku kerja yang aman dan melalukan pelatihan kerja serta bagi pemilik usaha untuk meningkatkan kesadaran dan pengawasan terhadap keselamatan kerja di lingkungan bengkel las.
The Relationship Between Workload and Work-Life Balance and Job Satisfaction of Employees at PT. X Medan Effendi, Khairunnisa; Indriani, Fatma
Jurnal Kesehatan Masyarakat Perkotaan Vol. 5 No. 2 (2025): Jurnal Kesehatan Masyarakat Perkotaan
Publisher : LPPM Universitas Mohammad Husni Thamrin

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37012/jkmp.v5i2.3161

Abstract

In the era of globalization, increasingly fierce business competition requires companies to have competent and high-performing human resources. Job satisfaction is a crucial aspect in the workplace that influences productivity and employee well-being, where excessive workload and imbalance in work-life balance can impact job satisfaction. This study aims to analyze the relationship between workload and work-life balance on employee job satisfaction at PT.X Medan. This study used a quantitative approach with a cross-sectional design. The sampling technique used purposive sampling of 50 employees from the Engineering and Processing Division. The data were analyzed using Pearson's correlation test Product Moment test. The results of the study indicate a very strong and significant negative relationship between workload and job satisfaction (r = -0.977), meaning that as workload increases, job satisfaction tends to decrease. Conversely, there is a very strong and significant positive correlation between work-life balance and job satisfaction (r = 0.958), indicating that the better the work-life balance, the higher the job satisfaction. These results confirm that high workload and poor work-life balance are associated with a decrease in employee job satisfaction. Therefore, evaluating and redistributing workload more proportionally, as well as implementing policies that support work-life balance for employees, are important for improving overall job satisfaction.
Ergonomic Analysis to Assess Comfort and Risk of Musculoskeletal Injuries in Office Workers at PT X Using Rosa's Method Siregar, Baharuddin; Wahyuni, Dewi Sri; Indriani, Fatma; Dalimunthe, Nadiyah Rahma; Zakwan, M. Hadin; Asti, Rahmah Dwi; Darmansyah, Rendi
JUKEJ : Jurnal Kesehatan Jompa Vol 4 No 4 (2025): JUKEJ: Jurnal Kesehatan Jompa
Publisher : Yayasan Jompa Research and Development

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57218/jkj.Vol4.Iss4.2130

Abstract

Abstract This study aims to analyze the level of workplace comfort and the risk of musculoskeletal injuries among office workers at PT X using the Rapid Office Strain Assessment (ROSA) and Nordic Body Map (NBM) methods, as well as to examine the relationship between working posture and MSD complaints. This study uses a quantitative descriptive design with a cross-sectional approach involving 50 respondents. The results indicate that most employees are categorized as having a moderate ergonomic risk (ROSA score 4-5), while a small portion has a high ergonomic risk (score 5). Based on the NBM results, most workers experience mild to moderate musculoskeletal complaints, particularly in the neck, shoulders, lower back, and wrists. The main factors contributing to ergonomic risk are non-adjustable office chairs and desks, as well as prolonged static working postures. Overall, the ergonomic conditions at PT X are relatively good. However, improvements in workstation facilities and increasing workers' awareness of ergonomic principles are necessary to reduce the risk of musculoskeletal injuries and enhance workplace comfort. As a large-scale plantation company, PT X faces a high potential risk of Musculoskeletal Disorders (MSDs) among its employees. This risk primarily stems from the nature of the work, which often requires repetitive or static activities.
Hubungan beban kerja terhadap stres kerja di PT X Siregar, Nurul Syahputri; Salianto, Salianto; Indriani, Fatma
Holistik Jurnal Kesehatan Vol. 19 No. 9 (2025): Volume 19 Nomor 9
Publisher : Program Studi Ilmu Keperawatan-fakultas Ilmu Kesehatan Universitas Malahayati

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33024/hjk.v19i9.1876

Abstract

Background:  Work stress is a psychological and physiological response that occurs when job demands exceed a person's coping capacity. This condition can negatively impact employee mental and physical health and productivity. Purpose: To analyze the relationship between workload and job stress among employees at PT X. Method: This study used a quantitative correlational approach with a total sampling technique involving 37 respondents. Data were collected through a questionnaire and analyzed using the Spearman Rank test. Results: Based on the study results, 30 (81.1%) employees had a high level of workload, and 21 (56.8%) respondents had a high level of workload. The results of the bivariate analysis using the Spearman Rank test showed a probability or significance value of 0.00 (<0.05), indicating a significant relationship. Furthermore, a correlation value of (+) 0.756 indicates a strong correlation between the two variables, and a positive value indicates a unidirectional correlation. Thus, there is a significant and unidirectional relationship between workload and job stress in this study. Conclusion: There is a significant and strong relationship between workload and job stress. The higher the workload, the higher the level of work stress experienced by employees.   Keywords: Employees; Workload; Work Stress.   Pendahuluan: Stres kerja merupakan respons psikologis dan fisiologis yang muncul ketika tuntutan pekerjaan melebihi kapasitas individu untuk mengatasinya. Kondisi ini dapat berdampak negatif terhadap kesehatan mental, fisik, serta produktivitas karyawan. Tujuan: Untuk menganalisis hubungan antara beban kerja terhadap stres kerja pada karyawan PT X. Metode: Penelitian menggunakan pendekatan kuantitatif korelasional dengan teknik total sampling terhadap 37 responden. Data dikumpulkan melalui kuesioner dan dianalisis menggunakan uji Spearman Rank. Hasi: Berdasarkan hasil penelitian, sebanyak 30 (81.1%) karyawan memiliki tingkat beban kerja dengan dan stress kerja  tinggi 21 (56.8%) responden. Hasil analisis bivariat dengan metode Spearmanrho menunjukkan nilai probabilitas atau signifikansi 0.00 (< 0.05) yang artinya terdapat hubungan signifikan. Selain itu, nilai korelasinya adalah (+) 0.756 yang mempunyai arti bahwa korelasi/hubungan kedua variabel bernilai kuat dan nilai yang positif menunjukkan korelasi yang searah. Jadi, terdapat hubungan antara beban kerja dengan stres kerja pada penelitian ini dengan nilai yang signifikan dan searah. Simpulan: Terdapat hubungan yang signifikan dan kuat antara beban kerja dengan stres kerja. Semakin tinggi beban kerja yang diterima, semakin tinggi pula tingkat stres kerja yang dirasakan oleh karyawan.   Kata Kunci: Beban Kerja; Karyawan; Stres Kerja.
Hubungan Safety Talk Dan Pengawasan Terhadap Kepatuhan Penggunaan Alat Pelindung Diri (APD) Pada Pekerja Dalam Keadaan Bertegangan (PDKB) PT. PLN UP3 Medan Fahira Ramadhani Saragih; Fatma Indriani; Putra Apriadi Siregar
Jurnal Ilmiah Kesehatan Mandala Waluya Vol. 5 No. 2 (2025): Jurnal Ilmiah Kesehatan Mandala Waluya
Publisher : Lembaga Penelitian dan Pengabdian Masyarakat Universitas Mandala Waluya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54883/jikmw.v5i2.1331

Abstract

Sebanyak 79% kecelakaan kerja di PLN, dari kejadian tersebut 25,5% disebabkan oleh ketidakpatuhan dalam penggunaan Alat Pelindung Diri (APD). Penelitian ini bertujuan untuk mengetahui hubungan antara pelaksanaan Safety talk dan pengawasan terhadap kepatuhan penggunaan APD pada pekerja PDKB di PT. PLN (Persero) UP3 Medan. Penelitian ini menggunakan pendekatan kuantitatif dengan desain potong lintang (cross-sectional), Populasi dalam penelitian ini mencakup seluruh pegawai PDKB (Pekerja dalam keadaan bertegangan) sebanyak 30 orang, penentuan sampel penelitian ini melalui teknik total sampling, sehingga diperoleh 30 responden penelitian. Pengumpulan data dilakukan dengan menggunakan kuesioner, dan dianalisis dengan uji Chi-Square. Hasil penelitian menunjukkan bahwa 60% pekerja belum menerapkan Safety talk secara optimal, dan 66,7% berada dalam kategori pengawasan rendah. Tingkat kepatuhan terhadap penggunaan APD juga masih tergolong rendah, yakni hanya 36,7%. Hasil penelitian ini menunjukkan terdapat hubungan yang signifikan antara pelaksanaan Safety talk (p = 0,001) dan pengawasan (p = 0,002) dengan kepatuhan penggunaan APD. Sehingga diperoleh hasil bahwa efektivitas Safety talk dan rendahnya tingkat pengawasan berkontribusi pada rendahnya kepatuhan pekerja. Oleh karena itu, pelaksanaan Safety talk yang konsisten dan pengawasan yang aktif sangat diperlukan guna meningkatkan keselamatan kerja pada pekerja PDKB.
Enhancing Classification of Self-Reported Monkeypox Symptoms on Social Media Using Term Frequency-Inverse Document Frequency Features and Graph Attention Networks Rizian, Rizailo Akfa; Budiman, Irwan; Faisal, Mohammad Reza; Kartini, Dwi; Indriani, Fatma; Ahmad, Umar Ali
Jurnal Teknik Informatika (Jutif) Vol. 6 No. 6 (2025): JUTIF Volume 6, Number 6, Desember 2025
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2025.6.6.5482

Abstract

Early detection of infectious diseases plays a crucial role in minimizing their spread and enabling timely intervention. In the digital era, social media has emerged as a valuable source of real-time health information, where individuals often share self-reported symptoms that can serve as early warning signals for disease outbreaks. However, textual data from social media is typically unstructured, noisy, and contextually diverse, posing challenges for conventional text classification methods. This study proposes a hybrid model combining Term Frequency–Inverse Document Frequency (TF-IDF) feature representation with a Graph Attention Network (GAT) to enhance the early detection of Monkeypox-related self-reported symptoms on Indonesian social media. A dataset of 3,200 tweets was collected through Tweet-Harvest and subsequently preprocessed and manually labeled, producing a balanced distribution between positive (51%) and negative (49%) samples. TF-IDF vectors were used to construct a document similarity graph via the k-Nearest Neighbors (k-NN) method with cosine similarity, enabling GAT to leverage both textual and relational information across posts. The model’s performance was evaluated using accuracy, precision, recall, and macro-F1, with macro-F1 serving as the primary indicator. The proposed TF-IDF + GAT model achieved 93.07% accuracy and a macro-F1 score of 93.06%, outperforming baseline classifiers such as CNN (92.16% macro-F1), SVM (85.73%), Logistic Regression (84.89%). These findings demonstrate the effectiveness of integrating classical text representations with graph-based neural architectures for improving social media based disease surveillance and supporting early epidemic response strategies.
KNN-MVO-SMOTE Algorithm for Air Quality Imbalanced Data Classification Rizky, Muhammad Miftahur; Mazdadi, Muhammad Itqan; Muliadi, Muliadi; Faisal, Mohammad Reza; Indriani, Fatma; Rozaq, Hasri Akbar Awal; Yildiz, Oktay
International Journal of Advances in Data and Information Systems Vol. 6 No. 3 (2025): December 2025 - International Journal of Advances in Data and Information Syste
Publisher : Indonesian Scientific Journal

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59395/ijadis.v6i3.1424

Abstract

This research addresses air pollution, a pressing global issue influenced by geographic and temporal factors, using advanced machine-learning techniques to enhance air quality classification. By integrating the K-Nearest Neighbors (KNN) algorithm with the Synthetic Minority Over-sampling Technique (SMOTE) and Multi-Verse Optimization (MVO), we tackle challenges like data imbalance and parameter optimization. Our novel approach, which combines SMOTE and MVO within the KNN framework, has significantly increased classification accuracy to 97%, substantially improving over previous methods. The dataset includes diverse geographic and temporal data, with potential biases acknowledged and addressed. This study highlights the efficacy of merging MVO and SMOTE to optimize classification models, making a substantial contribution to environmental analysis and the fight against air pollution. Future research will explore AutoML technology to improve algorithmic optimization, offering more efficient and adaptive solutions. This pioneering effort emphasizes the critical role of technological innovation in tackling environmental challenges and marks a significant advancement in combating global air pollution.
Impact of Different Kernels on Breast Cancer Severity Prediction Using Support Vector Machine Mahmudah, Kunti; Surono, Sugiyarto; Rusmining, Rusmining; Indriani, Fatma
Journal of Electronics, Electromedical Engineering, and Medical Informatics Vol 8 No 1 (2026): January
Publisher : Department of Electromedical Engineering, POLTEKKES KEMENKES SURABAYA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35882/jeeemi.v8i1.960

Abstract

Breast cancer poses a critical global health challenge and continues to be one of the most prevalent causes of cancer-related deaths among women worldwide. Accurate and early classification of cancer severity is essential for improving treatment outcomes and guiding clinical decision-making, since timely intervention can significantly reduce mortality rates and enhance patient survival. This study evaluates the performance of Support Vector Machine (SVM) models using different kernel functions of Linear, Polynomial, Radial Basis Function (RBF), and Sigmoid for breast cancer severity prediction. The impact of feature selection was also examined, using the Random Forest algorithm to select the top features based on Mean Decrease Accuracy (MDA), which serves to reduce redundancy, improve interpretability, and enhance model efficiency. Experimental results show that the RBF kernel consistently outperformed other kernels, especially in terms of sensitivity, a critical metric in medical diagnostics that emphasizes the ability of the model to identify positive cases correctly. Without feature selection, the RBF kernel achieved an accuracy of 0.9744, a sensitivity of 0.9772, a precision of 0.9722, and an AUC of 0.9968, indicating strong performance across all evaluation metrics. After applying feature selection, the RBF kernel further improved the accuracy to 0.9754, the sensitivity to 0.9770, the precision to 0.9742, and the AUC to 0.9975, which demonstrated enhanced generalization and reduced overfitting, highlighting the benefits of targeted feature reduction. While the Polynomial kernel yielded the highest precision (up to 0.9799), its lower sensitivity (as low as 0.9237) indicates a greater risk of false negatives, which is particularly concerning in cancer detection. These findings underscore the importance of optimizing both kernel function and feature selection. The RBF kernel, when combined with targeted feature selection, offers the most balanced and sensitive model, making it highly suitable for breast cancer classification tasks where diagnostic accuracy is vital
Deep Learning-Based Lung Sound Classification Using Mel-Spectrogram Features for Early Detection of Respiratory Diseases Yabani, Midfai; Faisal, Mohammad Reza; Indriani, Fatma; Nugrahadi, Dodon Turianto; Kartini, Dwi; Satou, Kenji
Journal of Electronics, Electromedical Engineering, and Medical Informatics Vol 8 No 1 (2026): January
Publisher : Department of Electromedical Engineering, POLTEKKES KEMENKES SURABAYA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35882/jeeemi.v8i1.1256

Abstract

Respiratory diseases such as asthma, chronic obstructive pulmonary disease, and pneumonia remain among the leading causes of death globally. Traditional diagnostic approaches, including auscultation, rely heavily on the subjective expertise of medical practitioners and the quality of the instruments used. Recent advancements in artificial intelligence offer promising alternatives for automated lung sound analysis. However, audio is an unstructured data format that must be converted into a suitable format for AI algorithms. Another significant challenge lies in the imbalanced class distribution within available datasets, which can adversely affect classification performance and model reliability. This study applied several comprehensive preprocessing techniques, including random undersampling to address data imbalance, resampling audio at 4000 Hz for standardization, and standardizing audio duration to 2.7 seconds for consistency. Feature extraction was then performed using the Mel Spectrogram method, converting audio signals into image representations to serve as input for classification algorithms based on deep learning architectures. To determine optimal performance characteristics, various Convolutional Neural Network (CNN) architectures were systematically evaluated, including LeNet-5, AlexNet, VGG-16, VGG-19, ResNet-50, and ResNet-152. VGG-16 achieved the highest classification accuracy of the tested models at 75.5%, demonstrating superior performance in respiratory sound classification tasks. This study demonstrates the potential of AI-based lung sound classification systems as a complementary diagnostic tool for healthcare professionals and the general public in supporting early identification of respiratory abnormalities and diseases. The findings suggest that automated lung sound analysis could enhance diagnostic accessibility and provide more valuable support for clinical decision-making in respiratory healthcare applications
Co-Authors Abdilah, Muhammad Fariz Fata Abdul Azis Abdullayev, Vugar Achmad Rizal Afifa, Ridha Ahmad Rusadi Arrahimi - Universitas Lambung Mangkurat) Ahmad Rusadi Arrahimi - Universitas Lambung Mangkurat) Ahmad Zaki Al Habesyah, Noor Zalekha Amini, Aisah Ananda, Zahra Andi Farmadi Andi Farmadi Anggi Cahya Utari Anshari, Muhammad Ridha Ansyari, Muhammad Ridho Arianti, Tiara Aryanti, Agustia Kuspita Ashar, Yulia Khairina Asti, Rahmah Dwi Astuti, Yeni Ayu Astuty, Delfriana Ayu Athavale, Vijay Annant Aulia, Rizky Gunadi Azizah, Azkiya Nur Badali, Rahmat Amin Baharuddin Siregar, Baharuddin Baron Hidayat Barus, Nency Utami Br Batubara, Rini Warahmah Berutu, Marwiyah Br Barus, Nency Utami br Damanik, Cici Rahayu Carolina, Ayu Daffa Dhiba Oesraini DALIMUNTHE, NADIYAH RAHMA Darmansyah, Rendi Daulay, Rangga Muriansyah Dendy Fadhel Adhipratama Dendy Dewi Sri Wahyuni, Dewi Sri Difa Fitria Dodon Turianto Nugrahadi Dwi Kartini Dwi Kartini, Dwi Effendi, Khairunnisa Fadilah, Sylva Qamara Nur Fahira Ramadhani Saragih Fahmi Setiawan Fairudz Shahura Faisal, M. Reza Faisal, Mohammad Reza Fajrin Azwary Fitriani, Karlina Elreine Friska Abadi Ghinaya, Helma Gunawan, Muhammad Khair Gustara, Rizki Asih Hafizah, Rini Harahap, Dwi Adelia Putri Harahap, Helma Denisah Hasyimi , Ali Hayati, Sera Br Hermiati, Arya Syifa Herteno, Rudi Heru Kartika Chandra I Gusti Ngurah Antaryama Ichwan Dwi Nugraha Ihsan, Muhammad Khairi Iqbal, M. Irwan Budiman Irwan Budiman Lauchan, Agil maritho Lilies Handayani Lubis, Masruroh M. Apriannur M. Khairul Rezki Mahmud Mahmud Mahmudah, Kunti Masyithah, Ruhul Maulana, Muhammad Rafly Alfarizqy Mawandri, Dwi Mohammad Mahfuzh Shiddiq Muhammad Alkaff Muhammad Itqan Mazdadi Muhammad Nadim Mubaarok Muhammad Reza Faisal, Muhammad Reza Muhammad Ridha Maulidi Muliadi Muliadi Muliadi Aziz Nafiz, Muhammad Fauzan Nita Arianty Nofi Susanti Nurhayani nurhayani Nurhayati Octavia, Mayang Dwi Oni Soesanto P., Chandrasekaran Patrick Ringkuangan Prastya, Septyan Eka Purnajaya, Akhmad Rezki Putra Apriadi Siregar Putri Maimunah Putri, Adelia Radityo Adi Nugroho Ramadhanu, Suhada Rapotan Hasibuan Riadi, Agus Teguh Risma, Ade Ritonga, Egril Rehulina Rizian, Rizailo Akfa Rizky, Muhammad Miftahur Rozaq, Hasri Akbar Awal Rudy Herteno rusmining, rusmining Safira, Putri Salianto Salianto, Salianto Saputro, Setyo Wahyu Saragih, Triando Hamonangan Satou, Kenji Sa’diah, Halimatus Selvia Indah Liany Abdie Siregar, Nurul Syahputri Siregar, Siti Romaito Soesanto, Oni Sri Rahayu Suci Wulandari Sugiyarto Surono, Sugiyarto Tarigan, David Brando Pratama Triyoolanda, Anggun Umar Ali Ahmad Utami, Tri Niswati Wahyu Caesarendra Wardana, Muhammad Difha Wati, Desi Indriani Rahma Wijaya Kusuma, Arizha Yabani, Midfai YILDIZ, Oktay Yulia Khairina Ashar Yunida, Rahmi Zahra, Fairuz Zakwan, M. Hadin Zali, Muhammad Zata Ismah Zida Ziyan Azkiya