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All Journal Jurnal Edukasi dan Penelitian Informatika (JEPIN) JURNAL PENGABDIAN KEPADA MASYARAKAT Sinkron : Jurnal dan Penelitian Teknik Informatika Tech-E RABIT: Jurnal Teknologi dan Sistem Informasi Univrab JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING JURNAL MEDIA INFORMATIKA BUDIDARMA Abdimas Talenta : Jurnal Pengabdian Kepada Masyarakat Nizhamiyah JurTI (JURNAL TEKNOLOGI INFORMASI) Query : Jurnal Sistem Informasi Zero : Jurnal Sains, Matematika, dan Terapan ALGORITMA : JURNAL ILMU KOMPUTER DAN INFORMATIKA JISTech (Journal of Islamic Science and Technology) Jurnal Teknologi Sistem Informasi dan Aplikasi Digital Zone: Jurnal Teknologi Informasi dan Komunikasi J-SAKTI (Jurnal Sains Komputer dan Informatika) IJISTECH (International Journal Of Information System & Technology) JURIKOM (Jurnal Riset Komputer) Journal on Education JOURNAL OF SCIENCE AND SOCIAL RESEARCH Saintifik : Jurnal Matematika, Sains, dan Pembelajarannya Jurnal Ilmiah Binary STMIK Bina Nusantara Jaya Jurnal Kridatama Sains dan Teknologi Jurnal Ilmu Komputer dan Bisnis Aisyah Journal of Informatics and Electrical Engineering Jatilima : Jurnal Multimedia Dan Teknologi Informasi JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) Journal of Computer System and Informatics (JoSYC) INFOKUM Jurnal Sistem Komputer dan Informatika (JSON) TIN: TERAPAN INFORMATIKA NUSANTARA Brahmana : Jurnal Penerapan Kecerdasan Buatan MEANS (Media Informasi Analisa dan Sistem) Journal of Computer Networks, Architecture and High Performance Computing Jurnal Teknologi Informasi dan Komunikasi Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) IJISTECH JINAV: Journal of Information and Visualization Jurnal FASILKOM (teknologi inFormASi dan ILmu KOMputer) Jurnal Responsif : Riset Sains dan Informatika Journal La Multiapp Jurnal Abdi Mas Adzkia Fitrah: Journal of Islamic Education KLIK: Kajian Ilmiah Informatika dan Komputer Journal of Information Technology (JIfoTech) Instal : Jurnal Komputer J-SAKTI (Jurnal Sains Komputer dan Informatika) Journal of Dinda : Data Science, Information Technology, and Data Analytics International Journal Software Engineering and Computer Science (IJSECS) Journal of Computer Science and Informatics Engineering sudo Jurnal Teknik Informatika Jurnal Sistem Informasi Triguna Dharma (JURSI TGD) Jurnal Nasional Teknologi Komputer Journal of Computers and Digital Business Sewagati: Jurnal Pengabdian Masyarakat Indonesia DEVICE : JOURNAL OF INFORMATION SYSTEM, COMPUTER SCIENCE AND INFORMATION TECHNOLOGY Jurnal Pengabdian Masyarakat The Indonesian Journal of Computer Science Cosmic Jurnal Teknik

Ilka Zufria

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Author-ID : 2532866

Religion Aerospace Engineering Agriculture, Biological Sciences & Forestry Arts Humanities Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry 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 Social Sciences Veterinary Other

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Application of Data Mining with C5.0 Algorithm to Recommend Prosperous Family Card (KKS) Recipients Fadilla, Nurul; Zufria, Ilka; Fakhriza, M.
Journal of Computer Networks, Architecture and High Performance Computing Vol. 7 No. 2 (2025): Research Article, Volume 7 Issue 2 April, 2025
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/cnahpc.v7i2.5913

Poverty is a social problem that still often occurs in various regions in Indonesia, including in Silau Laut District which consists of several villages such as Bangun Sari, Silo Bonto, Silo Lama, Lubuk Palas, and Silo Baru. Although the area is quite large, there are still many families who are classified as poor and unable to meet their basic needs. To overcome this, the government launched the Prosperous Family Card (KKS) program as a form of social assistance. However, the process of determining prospective KKS recipients still faces various obstacles, such as a random selection method based on data sent by each village to the central government. This raises concerns about the inaccuracy of the target in the distribution of aid, so that the aid is not received by families who really need it. In addition, a lot of data has not been utilized optimally in the selection process. Therefore, this study aims to design a website-based information system that can help Silau Laut District in providing recommendations for prospective KKS assistance recipients by utilizing data mining techniques. The algorithm used is C5.0, because it is able to produce a decision tree with high accuracy, while the system development method used is Rapid Application Development (RAD) to accelerate the system development process. The result of this research is an information system that can process community data and provide recommendations for prospective KKS assistance recipients in a more objective and targeted manner in the next period.

Implementasi Algoritma Apriori dan FP-Growth untuk Rekomendasi Produk Guna Meningkatkan Penjualan pada Toko (Studi Kasus: Warung Sidorukun) Kesuma, Beny; Zufria, Ilka; Rusydi, Ibnu
sudo Jurnal Teknik Informatika Vol. 4 No. 1 (2025): Edisi Maret
Publisher : Ilmu Bersama Center

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56211/sudo.v4i1.783

Warung Sidorukun adalah sebuah usaha yang bergerak dalam bidang penjualan. Produk yang dijual sangat banyak, di antaranya sembako, rokok, makanan ringan, minuman, dan lain sebagainya. Masalah yang terjadi adalah Warung Sidorukun tidak mengetahui pola transaksi yang dilakukan pelanggan dalam pembelian produk sehingga sulit dalam menyusun produk pada rak tertentu yang dapat mempermudah pelanggan menemukan produk yang biasa dibeli. Oleh karena itu, dibutuhkan sebuah cara yang dapat membantu Warung Sidorukun dalam melakukan penggalian data dan mengetahui pola transaksi yang dilakukan pelanggan dalam pembelian produk. Penelitian ini membandingkan algoritma apriori dengan FP-Growth untuk memberikan hasil perbandingan terhadap pencarian rekomendasi produk Warung Sidorukun. Aplikasi ini memberikan dua hasil, yaitu Apriori menghasilkan pola pembelian dan FP-Growth menghasilkan pohon keputusan berdasarkan pola yang ditemukan. Kemudian, kedua hasil tersebut dibandingkan sehingga dapat diketahui algoritma yang paling tepat. Dengan adanya penerapan algoritma FP-Growth, Warung Sidorukun mendapatkan kemudahan dalam mengetahui pola transaksi yang dilakukan pelanggan dalam pembelian produk.

Implementation Of Genetic Algorithm In Advertising Scheduling On Commercial Radio Stations siregar, idris; Zufria, Ilka; Nasution, Yusuf Ramadhan
Bahasa Indonesia Vol 15 No 02 (2023): Instal : Jurnal Komputer Periode (Juli-Desember)
Publisher : Cattleya Darmaya Fortuna

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54209/jurnalkomputer.v15i02.138

In this research, scheduling ad plays on a commercial radio station. Ad plays In this study, scheduling of advertisements was carried out on a commercial radio station. Ads are shown every day from Sunday to Saturday. There are two types of playing time, namely prime time and regular time. Prime time (pt) is 06-10 and 16:00-20:00, while regular time (rt) is 05-06, 11:00-15:00 and 21:00-24:00. The number of ad playback slots is 3 slots per hour and thus for pt time there are 15 slots, where at 16 to 20 hours there are 15 slots, so in total at pt time there are 30 slots per day and for rt time there are 15 slots and 21 hours -23 there are 3 clocks x 3 slots makes 9 slots. So in total at re time there are 27 slots. Prime time rules apply, namely the hours when the general public (listeners) have the greatest opportunity to listen to the radio, namely between 6:00-10:00 in the morning and 16:00-20:00 in the evening. The number of broadcasts of the same advertisement in one day is limited to prime time, which is 5 times, while for regular time it is 8 times. The radio scheduling process is carried out using a genetic algorithm which consists of the processes of chromosome initialization, selection, crossover and mutation. A chromosome represents the chromosomal matrix, namely Ad, Day and Time code. Each chromosome will be evaluated based on its fitness value which is calculated based on the number of penalties that occur on each chromosome in an individual. Where penalty 1 is the number of ad screenings more than once at a time while penalty 2 is the ad playing not at the specified type of time. The results of this study are to produce the best ad schedule by scheduling all ad data, the day and time of ad playing.

Analisis Sentimen Masyarakat pada Platform Media Sosial X (Twitter) terhadap Pelantikan Kabinet Merah Putih Menggunakan Bernoulli Naïve Bayes Rambe, M. Riski Andika; Zufria, Ilka; Rifki, Mhd. Ikhsan
DEVICE : JOURNAL OF INFORMATION SYSTEM, COMPUTER SCIENCE AND INFORMATION TECHNOLOGY Vol 6, No 1: JUNI 2025
Publisher : Universitas Dharmawangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46576/device.v6i1.6360

Penelitian ini bertujuan untuk menganalisis sentimen masyarakat terhadap pelantikan Kabinet Merah Putih melalui platform media sosial X (sebelumnya Twitter) menggunakan algoritma Bernoulli Naive Bayes. Data sebanyak 1.000 tweet dikumpulkan dan diproses melalui tahapan preprocessing, tokenisasi, penghapusan stopwords, stemming, serta pembobotan menggunakan TF-IDF. Selanjutnya, data diklasifikasikan ke dalam sentimen positif dan negatif. Model dilatih dengan 700 data dan diuji dengan 300 data. Hasil evaluasi menunjukkan bahwa model mencapai akurasi sebesar 78%, dengan precision untuk kelas positif sebesar 0.775 dan recall sebesar 0.677, sedangkan precision dan recall untuk kelas negatif masing-masing sebesar 0.783 dan 0.856. Temuan ini menunjukkan bahwa Bernoulli Naive Bayes efektif dalam mengidentifikasi sentimen masyarakat secara umum, terutama pada sentimen negatif. Penelitian ini memberikan gambaran persepsi publik terhadap pelantikan kabinet serta menjadi dasar untuk pengambilan keputusan kebijakan komunikasi pemerintah yang lebih baik.

Penentuan Kelas Unggulan Berbasis Decision Support System Dengan Metode Simple Additive Weighting (Saw) Zufria, Ilka; Hasugian, Abdul Halim; Simanjuntak, Salmah
MEANS (Media Informasi Analisa dan Sistem) Volume 5 Nomor 2
Publisher : LPPM UNIKA Santo Thomas Medan

MTs 2 state Medan Jl. Administrator No. 3 Medan Estate Complex is one of the school governments engaged in education. With the rapid development of technology that develops with the development of science and technology, we must prepare human resources who are able to compete excellently. In order for the formation of quality students, the superior class is a gap in efforts to improve the quality of education in Indonesia. To get quality students will not be separated from good religious knowledge, because if students do not have religious knowledge it will cause competent children to do things that are deviant, whereas in the hadith it has been stated that morals are higher in the placement of knowledge, then a student who does not there are morals then their knowledge will be in vain. This study is to see that to enter the superior class with several specified criteria, namely: Al-Quran test, IQ test, medical history, parent's income, Sem-Odd Value, Sem-Even Value. If these criteria are met, a student will be selected through the results of the ranking of each criterion. Because it takes too much time and the limited ability to see all aspects at one time that has been determined accurately, it causes several errors in decision making. Therefore, a decision support system for selecting a superior class is needed with the criteria determined by the MTs state 2 Medan school, by using the simple additive weighting method (SAW) which can help the school to determine superior class students quickly and accurately. By using the SAW method formula that is connected with each existing criterion to produce a decision in selecting the superior class student.Â Keywords: superior class, decision support system, SAW

Rancangan Sistem Informasi Pengolahan Event Kampus Berbasis Web Menggunakan Metode Waterfall Muhammad Nabhan Akbar Marpaung; sarah, siti; Ragilia Putri Dinanti; Gilang Reynabil; Nurul Fikria; Alfin Budiman Sihotang; Marini; Revina Putri Damayanti; Dinda Ayu Ningsih; Ilka Zufria
Jurnal Nasional Teknologi Komputer Vol 5 No 3 (2025): Juli 2025
Publisher : CV. Hawari

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61306/jnastek.v5i3.225

Perkembangan teknologi informasi yang pesat menuntut adanya sistem digital yang efisien dan terintegrasi dalam berbagai sektor, termasuk di lingkungan kampus. Laporan ini membahas perancangan dan implementasi Sistem Informasi Pengelolaan Event Kampus berbasis web yang bertujuan untuk menggantikan proses manual dalam manajemen event seperti seminar, pelatihan, dan kegiatan organisasi kemahasiswaan. Sistem ini dirancang dengan metode Waterfall yang mencakup tahapan analisis kebutuhan, perancangan, implementasi, pengujian, dan dokumentasi. Fitur utama yang disediakan antara lain manajemen event, pendaftaran peserta, pencatatan kehadiran, laporan kegiatan, dan dokumentasi galeri. Dengan penerapan sistem ini, proses pengelolaan event menjadi lebih cepat, efisien, dan terdokumentasi secara baik, sekaligus meningkatkan transparansi dan profesionalisme penyelenggara. Sistem dikembangkan menggunakan teknologi open-source seperti HTML, CSS, PHP, JavaScript, dan MySQL. Hasil implementasi menunjukkan bahwa sistem mampu memenuhi kebutuhan pengguna dan mendukung kegiatan event internal kampus secara optimal.

IMPLEMENTASI PENAMBANGAN DATA UNTUK PREDIKSI PENJUALAN PRODUK SUKU CADANG VESPA MENGGUNAKAN METODE MULTIPLE LINEAR REGRESSION Zaim Izza Makarim; Ilka Zufria
Jurnal Multimedia dan Teknologi Informasi (Jatilima) Vol. 7 No. 02 (2025): Jatilima : Jurnal Multimedia Dan Teknologi Informasi
Publisher : Cattleya Darmaya Fortuna

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54209/jatilima.v7i02.1461

Pertumbuhan kendaraan bermotor di Indonesia meningkat signifikan seiring dengan meningkatnya mobilitas masyarakat. Salah satu merek yang tetap diminati adalah Vespa, skuter klasik Italia yang telah menjadi simbol gaya hidup perkotaan dan kolektivitas budaya populer sejak tahun 1950-an. Popularitas ini berdampak langsung pada tingginya permintaan suku cadang, baik untuk kebutuhan perawatan rutin maupun modifikasi. Namun, fenomena ketidaksesuaian antara ketersediaan dan permintaan suku cadang Vespa seperti kasus di Dito Vespa Medan, di mana 42% permintaan servis terkait sistem pengapian tidak terpenuhi karena stok minim, mengindikasikan sistem prediksi penjualan adaptif yang lemah. Berdasarkan permasalahan tersebut, penelitian ini bertujuan untuk menerapkan metode data mining berbasis multiple linear regression untuk membangun model prediksi kuantitatif untuk penjualan produk suku cadang Vespa. Metode penelitian ini meliputi observasi langsung, wawancara mendalam, dan pengolahan 500 entri data transaksi menggunakan Python. Variabel seperti harga, stok awal, promo diskon, hari, dan bulan dianalisis sebagai prediktor volume penjualan. Hasil model menunjukkan nilai R-kuadrat 0,28, menunjukkan bahwa model tersebut mampu menjelaskan 28% dari variabilitas penjualan. Temuan ini memberikan kontribusi praktis dalam manajemen rantai pasokan dan manfaat akademik dalam memperluas literatur tentang aplikasi penambangan data di sektor otomotif konvensional berbasis kendaraan klasik.

Predicting Student Stress Levels Based on Lifestyle Factors Using the Catbost Algorithm Rani, Putri Meuthia; Zufria, Ilka
ZERO: Jurnal Sains, Matematika dan Terapan Vol 9, No 1 (2025): Zero: Jurnal Sains Matematika dan Terapan
Publisher : UIN Sumatera Utara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30829/zero.v9i1.24537

This study developed a machine learning model to classify student stress levels based on lifestyle factors using the CatBoost algorithm. Data were collected from 630 students of the SciTech Faculty at State Islamic University of North Sumatra through a questionnaire comprising 14 Likert-scale items. Instrument validation was confirmed using Pearson’s r (>0.821, p < 0.05) and Cronbach’s Alpha (0.866). Preprocessing included outlier removal with IQR, feature encoding, stratified train-test split (80:20), and 5-fold cross-validation. The training set was imbalanced and addressed using the SMOTE technique. Model evaluation used accuracy (85%), precision, recall, and F1-score per class, with high recall (0.97) for moderate and improved F1-score (0.79) for low stress. Final classification used a 20% test subset (126 samples). Feature importance analysis identified task procrastination, poor sleep quality, and weak time management as key predictors. These findings affirm CatBoost's reliability through consistent results, scalability, and balanced evaluation metrics beyond mere accuracy.

Application of the Naïve Bayes Algorithm in Sentiment Analysis of Using the Shopee Application on the Play Store Sitorus, Rina Afriani; Zufria, Ilka
Digital Zone: Jurnal Teknologi Informasi dan Komunikasi Vol. 15 No. 1 (2024): Digital Zone: Jurnal Teknologi Informasi dan Komunikasi
Publisher : Publisher: Fakultas Ilmu Komputer, Institution: Universitas Lancang Kuning

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31849/digitalzone.v15i1.19828

This research aims to find out the opinions of users of the Shopee application on the Play Store using the Naive Bayes Naive Algorithm and to find out the suitability of the correct application of the Naive Bayes algorithm in carrying out sentiment analysis with the classification of three sentiment classes. The dataset used in this study consisted of 2000 customer reviews obtained from the Play Store in 2024 collected by the scraping process using the Python library. The dataset has 1,198 examples of negative attitudes, 583 examples of good sentiment, and 219 examples of neutral sentiment. The results of this study are expected to be used as evaluation material for Shopee Apilkation to improve the performance of Shopee applications. Research findings show that the Bayes naive approach reaches accuracy determined by various aspects, such as the quantity of data collections and positive and negative data distribution. This study shows that the Bayes naive algorithm can function properly as a technique to evaluate user sentiment for applications in the Play Store. However, with the classification of three classes, another algorithm is needed to produce higher accuracy.

Classification of Lung TB Levels by Region in Medan City Using Logistic Regression Algorithm Purnamawati, Sri; Zufria, Ilka
JURIKOM (Jurnal Riset Komputer) Vol. 12 No. 4 (2025): Agustus 2025
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/jurikom.v12i4.8914

The Indonesia Smart Program is a cash assistance for education aimed at elementary, middle, and high school students aged 6-21 who come from underprivileged families. In the selection process for prospective recipients of the Indonesia Smart Program at SMA Negeri 1 Kutalimbaru, several problems arose due to the still conventional data processing. This issue is primarily caused by technological limitations and the absence of a computerized system to process that data. As a result, the process is time-consuming and prone to high error rates. Therefore, a computer-based system is needed to assist in the Recommendation of Prospective Recipients of the Indonesia Smart Program. In this study, a combination of two methods was used, namely the Rank Order Centroid (ROC) method for criterion weighting and Additive Ratio Assessment (ARAS) for ranking. Based on the tests conducted on 180 data of students eligible to receive the Program Indonesia Pintar at SMA Negeri 1 Kutalimbaru, the ranking results established Restu (A142) in the first position as the most recommended Candidate Recipient of the Program Indonesia Pintar with a final score of “1”, with criteria including having a KIP Card “Yes”, having a KKS Card “Yes”, being an orphan “Orphan”, number of dependents “2”, parental income “No Income’. Thus, the ROC and ARAS methods prove to be suitable in assisting decision-making for recommendations for Candidates to Receive the Program Indonesia Pintar.

Co-Authors Abdul Halim Hasugian Abdul Rasyid Adnan Buyung Nasution Afira Zulfa Afriani Afriani Agung Hamdika Surya Aidil Halim Lubis Aidil Halim Lubis Aidil Halim Lubis Aila Oktavia Abdul Nst Alfahri, Bagus Ageng Alfiansyah, Raja Alfin Budiman Sihotang Ali Ikhwan Ali Ikhwan Amri, M Choirul Aninda Muliani Anjani, Retno Anwar Fauzi Apriani Syahputri Aprilia, Nia Arfina Handayani Armansyah Armansyah Armansyah Atiqi, Muhammad Farros Aulia, Muhammad Fathir Batubara, Qisti Azraladiba Ba’ayesh, Mubarak Beni Frandian Bimantara, Muhammad Dhuha Buyung Satrio Dasopang Buyung Satrio Dasopang Chairul Rizal Chintya Anggraini Cindy Juliani Cindy Novi Syahputri Danang Wahyu Wicaksono Darsih, D Daulay, Darisma dedi irawan Desmi Roma Putra Lubis Dimas Arya Dimas Arya Dinda Ayu Ningsih Dion Wirayuda Bahri Dollar, Dzulfikri Akbar Edilia, Fazila Nazifa Efriliya Hafni Yuswinda Erwin Nasution Fachri, Barany Fadila, Daffa Fadilla, Nurul Fahmi Dian Pratama Fahrizal Alwafi Chandra Susi Syafriana Barus Fakhriza, M Fakhriza, M. Farentika, Yosi Firman Syarif Fitri, Wan Ilia Gilang Reynabil Gina Sania Habib Asy Muhyi Hafiz Fawi Anugerah Harahap, Parlindungan Harry Setiawan Hasugian, Aldi Ridwansyah Hazizah Ulfa Nasution Heri Santoso Heri Santoso Herman, Bintang Kurniawan Ibnu Rusydi Idris Siregar, Idris Ilham Maulana Ritonga Intan Saleha Tinendung Irawati, Cici Iskandar, Isna Damaiani Ismail Husein, Ismail Juliani, Cindy Kesuma, Beny Khairani, Melvika Kherina Surya Ningsih M Fakhriza M Fakhriza M Ferdiansah Rkt M Taufiq Rachman Siregar M. Fakhriza M. Fakhriza M. Ihsan Lubis Machfudz, Emir Syarif Mardiah Ramadhani Marini Maulana, Rexa Mhd Ikhsan Rifki Mhd. Syahnan Muchain, Alfira Nafhan Muhamad Alda Muhammad Arif Suhada Muhammad Dedi Irawan Muhammad Eka Muhammad Iqbal Nahwi Muhammad Nabhan Akbar Marpaung Muhammad Reyhandi Akbar Muhammad Siddik Hasibuan Muhammad Syahputra Novelan Muhammad Zulfikar Lubis Nasution, Muhammad Irwan Padli Nia Aprilia Nst, Aila Oktavia Abdul Nst, Khusnul Khotimah Nur Hasanah Pohan Nur Nofrizal Agustina Srg Nurainun Syahdia Nurhasanah, Mutia Nurul Fadhillah Nurul Fikria Okta Yuliardi Pandi Ahmad Jawara Pradana, Riski Ananta Pratama, Bagus Aji Purba, Ony Hizri Kaifa Purnamawati, Sri Putra, Fahrialdy Febriansyah Ragilia Putri Dinanti Raissa Amanda Putri Raisyah, Shafira Isra Rakhmat Kurniawan R Ramadani, Suci Adina Ramadhan, M Irsyad Rambe, M. Riski Andika Rambe, Rinanda Putri Rani, Putri Meuthia Rendy Andika, Rendy Revina Putri Damayanti Reza Adhitya Budiman Rina Afriani Sitorus Rini Halila Nasution Rio Rinaldi Risky, Tengku Tanzil Azhari Riswandi Riswandi Riswandi, Arif Rita Sari Dewi Rizky, Ishlahiyah Nur Rkt, M Ferdiansah Roy Surya Fikriadi Samsudin Samsudin Samsudin, Samsudin Sari, Silvia Sarmila Sarmila Sephia, Putri Aisyah Septiana Dewi Andriana, Septiana Dewi Shania Oktawijaya Simanjuntak, Salmah Simbolon, Zianah Nafisah Sinaga, Annisa Fitri Siti Sarah, Siti Siti Septia Febiyaula Sitorus, Dhafa Hibrizi Sitorus, Nur Shafwa Aulia Sitorus, Puan Syaharani Sitorus, Rina Afriani Sriani Sriani Suendri Suendri Suendri, Suendri Suhardi Suhardi Suhardi Suhardi, S Suhardi, Suhardi Sulindawaty Sulindawaty Supiyandi Supiyandi Surbakti, Miftah Hadi Syafitri, Febry Dwi Syafrida, Desy Syapira, Tiwi Talita, Friza Tanjung, Erti Belastari Tanjung, Siti Maya Sari Triase Triase Triase Triase, Triase Ulfia Zahra Utomo, Imam Wahyu Rahmansyah Wahyudi Wahyudi Wardani, Dina Ayu Winny Wiyandari Wiranda Wiranda Yusuf Ramadhan Nasution Yusuf Ramadhan Nasution, Yusuf Ramadhan Zaim Izza Makarim Zebua, Jelita Rahmah

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