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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 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 Jurnal Teknik Informatika (JUTIF) Journal of Applied Data Sciences JOURNAL LA MEDIHEALTICO MAHESA : Malahayati Health Student Journal Fitrah: Journal of Islamic Education Multidiciplinary Output Research for Actual and International Issue (Morfai Journal) Jurnal Kolaboratif Sains Prosiding Seminar Nasional Sisfotek (Sistem Informasi dan Teknologi Informasi) Journal of Data Science and Software Engineering Jurnal INFOTEL Jurnal Pengabdian Kepada Masyarakat Itekes Bali JUKEJ: Jurnal Kesehatan Jompa Jurnal Informatika Polinema (JIP) 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

Author-ID : 583678

Religion Agriculture, Biological Sciences & Forestry Arts Humanities 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 Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Immunology & microbiology Languange, Linguistic, Communication & Media 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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Image Classification of Traditional Indonesian Cakes Using Convolutional Neural Network (CNN) Azizah, Azkiya Nur; Budiman, Irwan; Indriani, Fatma; Faisal, M. Reza; Herteno, Rudy
Computer Engineering and Applications Journal (ComEngApp) Vol. 13 No. 2 (2024)
Publisher : Universitas Sriwijaya

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

Indonesia is one of the countries famous for its traditional culinary. Traditional cakes in Indonesia are traditional snacks typical of the archipelago's culture which have a variety of textures, shapes, colors that vary and some are similar so that there are still many people who do not know the name of the cake from the many types of traditional Indonesian cakes. The problem can be solved by creating a traditional cake image recognition system that can be programmed and trained to classify various types of traditional Indonesian cakes. The Convolutional Neural Network method with the AlexNet architecture model is used in this research to predict various kinds of traditional Indonesian cakes. The dataset used in this research is 1846 datasets with 8 classes of cake images. This study trained the AlexNet model with several optimizers, namely, Adam optimizer, SGD, and RMSprop. The best parameters from the model testing results are at batchsize 16, epoch 50, learning rate 0.01 for SGD optimizer and learning rate 0.001 for Adam and RMSprop optimizers. Each optimizer tested produces different accuracy, precision, recall, and f1_score values. The highest test results that have been carried out on the image dataset of typical Indonesian traditional cakes are obtained by the Adam optimizer with an accuracy value of 79%.

Perbandingan Tingkat Kepuasan Pasien JKN dan Umum Terhadap Kualitas Pelayanan Rawat Jalan di Rumah Sakit Umum Daerah Rantauprapat Ritonga, Egril Rehulina; Indriani, Fatma; Hasibuan, Rapotan
Health Information : Jurnal Penelitian Vol 17 No 2 (2025): Mei-Agustus
Publisher : Poltekkes Kemenkes Kendari

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36990/hijp.v17i2.1694

Berdasarkan pernyataan dari Organisasi Kesehatan Dunia (WHO), rumah sakit merupakan elemen penting dalam sistem sosial maupun kesehatan yang memiliki peran dalam masyarakat menyediakan layanan medis secara menyeluruh, termasuk tindakan pencegahan serta penanganan darurat secara luas. Penelitian ini merupakan penelitian analitik dengan desain cross sectional yang dilakukan di RSUD Rantauprapat pada bulan Februari hingga Maret 2025. Penelitian menggunakan pendekatan kuantitatif dengan metode komparatif untuk membandingkan kepuasan pasien JKN dan pasien umum. Data yang digunakan berupa data primer dan sekunder, dengan instrumen berupa kuesioner berdasarkan lima dimensi kualitas pelayanan: Tangible, Reliability, Responsiveness, Assurance, dan Empathy, yang diukur menggunakan skala Likert. Sampel dipilih secara Accidental Sampling dari pasien rawat jalan yang memenuhi kriteria inklusi dan eksklusi. Jumlah populasi pasien rawat jalan tahun 2024 adalah 130.488, terdiri dari 5.023 pasien umum dan 125.465 pasien JKN. Sampel sebanyak 136 responden, masing-masing 68 pasien JKN dan 68 pasien umum, ditentukan menggunakan rumus Isaac dan Michael. Data dianalisis menggunakan uji Mann-Whitney U karena data tidak berdistribusi normal.

FACTORS AFFECTING WORK STRESS AMONG EMPLOYEES AT PT. MARINDA UTAMAKARYA SUBUR DELI SERDANG BRANCH Khairiyah Dwie Vanesa; Fatma Indriani; Reni Agustina Harahap
Multidiciplinary Output Research For Actual and International Issue (MORFAI) Vol. 5 No. 4 (2025): Multidiciplinary Output Research For Actual and International Issue
Publisher : RADJA PUBLIKA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54443/morfai.v5i4.3080

Work stress is a global problem with around 450 million people affected according to WHO, with stress levels in the Asia Pacific region reaching 48%. This study aims to analyze the factors that influence work stress in employees of PT. Marinda Utamakarya Subur, Deli Serdang Branch. The research method uses an analytical study with a quantitative approach and cross-sectional design. The study population includes all employees of PT. Marinda Utamakarya Subur, Deli Serdang Branch with a total sampling technique, so that the sample size is 36 people. Data analysis uses the Mann Whhitney, Kruskal Wallis, and Spearman tests. The results showed that there was no significant correlation between age and work stress (r = -0.028; p = 0.871) and education level with work stress (p = 0.190). While there was a significant correlation between workload and work stress (r = 0.410; p = 0.013) with a moderate negative correlation, gender with work stress ( p = 0.042) where male employees tend to experience higher work stress, and length of service with work stress (p = 0.015) with a tendency for employees who work more than 4 years to have higher stress levels. The conclusion of the study shows that gender, length of service and workload are significant factors that influence work stress and age and education status do not have a significant effect on work stress in employees of PT. Marinda Utamakarya Subur, Deli Serdang Branch.

Hubungan Posisi Kerja Dengan Keluhan Musculoskletal Disorder (MSDs) Pada Pemanen Sawit di PTPN IV Tanah Itam Ulu Ananda, Zahra; Astuty, Delfriana Ayu; Indriani, Fatma
Jurnal Biomedika dan Kesehatan Vol 8 No 2 (2025)
Publisher : Fakultas Kedokteran Universitas Trisakti

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Background Musculoskeletal disorders (MSDs) are a common occupational health issue among plantation workers due to unergonomic working postures. Oil palm harvesters are especially vulnerable because of repetitive physical activities and awkward body positions. Work processes involving strenuous physical effort, such as lifting tools, cutting bunches, bending, and reaching for fronds for extended periods, along with unergonomic postures, increase the risk of MSDs. This study aims to determine the relationship between work posture and MSDs complaints among oil palm harvesting workers at PTPN IV Tanah Itam Ulu. Methods A cross-sectional quantitative study was performed with a sample of 50 Fresh Fruit Bunch (FFB) harvesters. Data were collected through observations and interviews using the Rapid Entire Body Assessment (REBA) to evaluate work posture and the Nordic Body Map (NBM) to assess MSDs symptoms. Data analysis was conducted using the Chi-Square test with a significance level of α = 0.05 in SPSS. Results The study revealed that 52% of workers experienced high-risk MSDs, while 48% faced very high-risk MSDs. A statistically significant relationship was identified between work posture and MSDs complaints (p = 0.000). Conclusions Poor ergonomic posture significantly increases the risk of MSDs among palm oil harvesters. Ergonomic interventions, including training on proper posture and the use of assistive tools, are strongly recommended to reduce risk and improve occupational health well-being.

Improving Diabetes Prediction Using Feedforward Neural Network with Adam Optimization and SMOTE Technique Wijaya Kusuma, Arizha; Mazdadi, Muhammad Itqan; Kartini, Dwi; Farmadi, Andi; Indriani, Fatma; P., Chandrasekaran
Indonesian Journal of Electronics, Electromedical Engineering, and Medical Informatics Vol. 7 No. 3 (2025): August
Publisher : Jurusan Teknik Elektromedik, Politeknik Kesehatan Kemenkes Surabaya, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35882/ijeeemi.v7i3.127

Diabetes mellitus is a chronic metabolic disorder that demands early and accurate detection to prevent life-threatening complications. Traditional diagnostic procedures, such as blood glucose tests and oral glucose tolerance tests, are often invasive, time-consuming, and resource-intensive, making them less practical for widespread screening. This study aims to explore the potential of artificial intelligence, specifically Feedforward Neural Networks (FNN), in predicting diabetes based on clinical data from the National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK). The main contribution of this research lies in the application of the Adaptive Moment Estimation (Adam) optimization algorithm and the Synthetic Minority Oversampling Technique (SMOTE) to enhance the performance and generalization of the FNN on imbalanced medical datasets. The methodology involves preprocessing steps such as imputing zero values with feature means, normalizing input features using Min-Max scaling, and applying SMOTE to balance class distribution. Two model configurations were compared: a baseline FNN trained manually using full-batch gradient descent and a second FNN optimized using Adam. Experimental results demonstrated that the baseline model achieved an accuracy of 70.13%, precision of 56.06%, recall of 68.52%, and F1-score of 61.67%, while the Adam-optimized model achieved superior results with an average accuracy of 73.31%, precision of 60.97%, recall of 66.67%, and F1-score of 63.64% across ten independent runs. These findings indicate that combining adaptive optimization with oversampling significantly enhances the robustness and reliability of neural networks for medical classification tasks. In conclusion, the proposed method provides an effective framework for AI-assisted early diabetes detection and opens pathways for future development using deeper network architectures and explainable AI models for clinical applications.

Efektivitas Edukasi Dini Menggunakan Leaflet Terhadap Peningkatan Pengetahuan Diabetes Melitus pada Siswa MTsS Nurhasanah Labuhan Ruku Barus, Nency Utami Br; Mawandri, Dwi; Risma, Ade; Zahra, Fairuz; Susanti, Nofi; Indriani, Fatma
JUKEJ : Jurnal Kesehatan Jompa Vol 4 No 2 (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.Iss2.1865

Diabetes Mellitus (DM) is a global and national health issue with a continuously rising prevalence. Data from the 2023 Indonesian Health Survey (SKI) indicates that the prevalence of DM in individuals aged ≥15 years has reached 11.7%. This increase highlights the crucial need for early education, especially among students. This study aims to evaluate the effectiveness of education using a leaflet medium in improving students' knowledge of DM. The research employed a quantitative method with a quasi-experimental approach and a one-group pretest-posttest design. The sample consisted of 31 seventh and eighth-grade students from MTsS Nurhasanah Labuhan Ruku, selected through total sampling. Knowledge was measured using a questionnaire administered both before (pretest) and after (posttest) the educational intervention with the leaflet. A bivariate data analysis using the Paired Samples Test revealed a significant increase in students' knowledge levels. Before the education, 71% of students had poor knowledge, which decreased to 16.1% after the intervention. Conversely, the percentage of students with good knowledge increased from 29% to 83.9%. The statistical test result showed a p-value of 0.0001, confirming a significant difference in student knowledge before and after the intervention. Therefore, this study concludes that education through a leaflet medium is effective in improving students' knowledge of diabetes mellitus.

Performance Comparison of AdaBoost, LightGBM, and CatBoost for Parkinson's Disease Classification Using ADASYN Balancing Anshari, Muhammad Ridha; Saragih, Triando Hamonangan; Muliadi, Muliadi; Kartini, Dwi; Indriani, Fatma; Rozaq, Hasri Akbar Awal; Yıldız, Oktay
Jurnal Teknik Informatika (Jutif) Vol. 6 No. 5 (2025): JUTIF Volume 6, Number 5, Oktober 2025
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2025.6.5.4726

Parkinson's disease is a neurodegenerative condition identified by the decline of neurons that produce dopamine, causing motor symptoms such as tremors and muscle stiffness. Early diagnosis is challenging as there is no definitive laboratory test. This study aims to improve the accuracy of Parkinson's diagnosis using voice recordings with machine learning algorithms, such as AdaBoost, LightGBM, and CatBoost. The dataset used is Parkinson's Disease Detection from Kaggle, consisting of 195 records with 22 attributes. The data was normalized with Min-Max normalization, and class imbalance was resolved with ADASYN. Results show that ADASYN-LightGBM and ADASYN-CatBoost have the best performance with 96.92% accuracy, 97.10% precision, 96.92% recall, and 96.92% F1 score. This improvement suggests that combining boosting methods and data balancing techniques can improve the accuracy of Parkinson's diagnosis. These results demonstrate the effectiveness of ADASYN in addressing data imbalance and improving the performance of boosting algorithms for medical classification problems. The findings contribute to the development of intelligent diagnostic systems in the field of medical informatics and computer science. These findings are essential for developing more accurate and efficient diagnostic tools, supporting early diagnosis and better management of Parkinson's disease.

Pemanfaatan Minyak Jelantah Sebagai Bahan Baku Lilin Aromaterapi: Upaya Mengurangi Limbah Rumah Tangga Di Labuhan Ruku Mawandri, Dwi; Indriani, Fatma; Br Barus, Nency Utami; Risma, Ade; Zahra, Fairuz
Jurnal Abdimas ITEKES Vol 5 No 1 (2025)
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat Institute Teknologi dan Kesehatan (ITEKES) Bali

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37294/jai.v5i1.796

ABSTRAK Pemakaian minyak goreng secara berkali-kali dapat menghasilkan minyak bekas atau jelantah yang berpotensi merusak lingkungan dan membahayakan kesehatan manusia. Sebagai solusi pemanfaatan limbah tersebut, salah satu upaya yang dapat dilakukan ialah mengolahnya menjadi produk bernilai guna, seperti lilin aromaterapi. Tujuan dari kegiatan ini ialah mengubah minyak jelantah menjadi bahan dasar pembuatan lilin aromaterapi sekaligus memberikan penyuluhan kepada masyarakat mengenai pentingnya pengelolaan limbah rumah tangga terhadap lingkungan. Metode pelaksanaan berupa praktik langsung pembuatan lilin bersama kelompok ibu-ibu perwiritan di Lingkungan VII, Kelurahan Labuhan Ruku, Kecamatan Talawi, Kabupaten Batu Bara. Berdasarkan hasil kegiatan, peserta menunjukkan pemahaman terhadap tahapan pembuatan lilin, aktif terlibat dalam prosesnya, dan mulai menyadari pentingnya pengelolaan limbah jelantah. Dari pembahasan dapat disimpulkan pemanfaatan minyak jelantah tidak hanya membantu mengurangi dampak pencemaran, tetapi juga memiliki potensi ekonomi serta dapat dijadikan sebagai peluang usaha skala rumah tangga. Secara keseluruhan, kegiatan ini menunjukkan bahwa pengolahan minyak jelantah menjadi lilin aromaterapi merupakan alternatif yang efektif dalam mendukung pengelolaan limbah rumah tangga serta meningkatkan kesadaran lingkungan dan kemandirian ekonomi masyarakat. Kata kunci : Aromaterapi, lingkungan, minyak jelantah, wirausaha

K-Modes Clustering untuk Mengetahui Jenis Masakan Daerah yang Populer pada Website Resep Online (Studi Kasus: Masakan Banjar di cookpad.com) Indriani, Fatma; Budiman, Irwan
Jurnal Teknologi Informasi dan Ilmu Komputer Vol 4 No 4: Desember 2017
Publisher : Fakultas Ilmu Komputer, Universitas Brawijaya

AbstrakPada makalah ini dipaparkan clustering pada data resep masakan daerah Banjar untuk mengetahui jenis makanan yang paling banyak di-post secara online oleh pengguna website recipe sharing. Pertama-tama data resep sebanyak 355 dikumpulkan dari suatu website resep, untuk selanjutnya dilakukan ekstraksi data bahan dan pembersihan. Metode clustering yang dipilih adalah k-modes karena cocok digunakan pada data kategorikal. Berdasar metode Elbow, jumlah cluster yang ideal adalah k=4 dan k=8. Jumlah cluster k=4 menghasilkan kelompok yang lebih umum, sedangkan k=8 menghasilkan kelompok yang lebih spesifik. Adapun kelompok yang berhasil diidentifikasi untuk k=4 adalah sayur asam, soto banjar, masakan gurih lain-lain, kue dan bubur manis. Sedangkan kelompok dengan jumlah cluster k=8 adalah sayur asam, soto banjar, kue basah, masakan gurih lain-lain, masak habang, bubur manis, kuah ketupat, dan masakan gurih asam. Evaluasi nilai purity menunjukkan nilai masing-masing 0,825 untuk k=4 dan 0,831 untuk k=8.Kata kunci: data mining, clustering, k-modes, resep masakan, bahanAbstractIn this paper, we cluster user-submitted recipes of Banjar regional cuisine to find out which type of cuisine are popular according to its ingredients. 355 recipes are collected from a recipe sharing website, then the ingredients extracted and cleaned. The clustering method chosen is k-modes because it is suitable for categorical data. Based on the Elbow method, the ideal number of clusters is k = 4 and k = 8. The number of clusters k = 4 produces more general cuisines group, whereas k = 8 produces more specific groups. The groups identified for k = 4 are (1) “sayur asam” (sour soup), (2)“soto banjar” (Banjar chicken soup), (3) savory dishes, and (4) sweet dishes. While the group with the number of clusters k = 8 consists of (1)“sayur asam” (sour soup) (2) “soto banjar”, (3) Banjar sweet puddings, (4) various savory dishes, (5) “masak habang” (Banjar sweet chili dishes), (6) sweet porridge, (7) “kuah ketupat” (spicy coconut soup) and (8) various savory sour dishes. The purity of clusters are shown to be 0.825 for k=4 and 0.831 for k=8.Keywords: clustering, k-modes, data mining, recipe, ingredient

HUBUNGAN LITERASI KESEHATAN MENTAL DENGAN SIKAP MENCARI BANTUAN PROFESIONAL PSIKOLOGI PADA MAHASISWA FKM UIN SUMATERA UTARA Hayati, Sera Br; Indriani, Fatma
PSIKOLOGI KONSELING Vol. 15 No. 2 (2023): Jurnal Psikologi Konseling
Publisher : Universitas Negeri Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24114/konseling.v15i2.55278

Seseorang dapat menyadari potensi sebenarnya dari dirinya, mengatasi stres, bekerja dengan hasil berdaya guna, dan berkontribusi terhadap lingkungannya ketika berada dalam kondisi yang baik. Penelitian ini bertujuan untuk mengetahui hubungan literasi kesehatan mental dengan kecenderungan mahasiswa FKM UIN Sumatera Utara mencari bantuan profesional psikologi. Penelitian ini menggunakan metodologi kuantitatif dengan menggunakan metodologi cross sectional. Sebanyak 154 responden dijadikan sampel. Pengumpulan data dilakukan melalui penggunaan kuesioner dan analisis data yang dikumpulkan dianalisis menggunakan uji univariat dan bivariat. Literasi kesehatan mental mahasiswa FKM UIN Sumatera Utara berada pada kategori tinggi sebanyak 117 responden atau 76,0%. Sikap mencari bantuan professional mahasiswa FKM UIN Sumatera Utara berada pada kategori baik yaitu sebanyak 95 responden atau 61,7%. Hasil penelitian bivariat pada penelitian ini menunjukkan angka signifikansi (Î±) yakni 0,516. Hal ini menunjukkan bahwa penelitian ini tidak menemukan adanya korelasi antara literasi kesehatan mental dengan sikap mencari bantuan profesional pada mahasiswa FKM UIN Sumatera Utara.Kata Kunci: Literasi Kesehatan Mental, Sikap Mencari Bantuan Profesional

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) Al Habesyah, Noor Zalekha Amini, Aisah Ananda, Zahra Andi Farmadi Andi Farmadi Anshari, Muhammad Ridha Ansyari, Muhammad Ridho Arianti, Tiara Aryanti, Agustia Kuspita Asti, Rahmah Dwi Astuti, Yeni Ayu Astuty, Delfriana Ayu Athavale, Vijay Annant Azizah, Azkiya Nur Badali, Rahmat Amin Baharuddin Siregar, Baharuddin Baron Hidayat Barus, Nency Utami Br Berutu, Marwiyah Br Barus, Nency Utami br Damanik, Cici Rahayu Carolina, Ayu DALIMUNTHE, NADIYAH RAHMA Darmansyah, Rendi Dendy Fadhel Adhipratama Dendy Dewi Sri Wahyuni, Dewi Sri Difa Fitria Dodon Turianto Nugrahadi Dwi Kartini Dwi Kartini, Dwi Effendi, Khairunnisa Fahmi Setiawan Fairudz Shahura Faisal, M. Reza Faisal, Mohammad Reza Fajrin Azwary Fitriani, Karlina Elreine Friska Abadi Ghinaya, Helma Gustara, Rizki Asih Hafizah, Rini Harahap, Helma Denisah Hartati Hartati Hasyimi , Ali Hayati, Sera Br Hermiati, Arya Syifa Herteno, Rudi Heru Kartika Chandra I Gusti Ngurah Antaryama Ichwan Dwi Nugraha Ihsan, Muhammad Khairi Irwan Budiman Irwan Budiman Khairiyah Dwie Vanesa Lilies Handayani Lubis, Masruroh M. Apriannur M. Khairul Rezki Mahmud Mahmud 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 Putri Maimunah Radityo Adi Nugroho Rapotan Hasibuan Reni Agustina Harahap Riadi, Agus Teguh Risma, Ade Ritonga, Egril Rehulina Rozaq, Hasri Akbar Awal Rudy Herteno Salianto Salianto, Salianto Saputro, Setyo Wahyu Saragih, Triando Hamonangan Sa’diah, Halimatus Selvia Indah Liany Abdie Siregar, Nurul Syahputri Soesanto, Oni Sri Rahayu Suci Wulandari Triyoolanda, Anggun Utami, Tri Niswati Wahyu Caesarendra Wardana, Muhammad Difha Wati, Desi Indriani Rahma Wijaya Kusuma, Arizha YILDIZ, Oktay Yulia Khairina Ashar Yunida, Rahmi Zahra, Fairuz Zakwan, M. Hadin Zali, Muhammad Zata Ismah Zida Ziyan Azkiya

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