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All Journal JURNAL SISTEM INFORMASI BISNIS Techno.Com: Jurnal Teknologi Informasi Scientific Journal of Informatics CESS (Journal of Computer Engineering, System and Science) Sinkron : Jurnal dan Penelitian Teknik Informatika JISTech (Journal of Islamic Science and Technology) JURNAL TEKNOLOGI DAN OPEN SOURCE JURNAL PENDIDIKAN TAMBUSAI Jurnal Nasional Komputasi dan Teknologi Informasi J-SAKTI (Jurnal Sains Komputer dan Informatika) IJISTECH (International Journal Of Information System & Technology) JOURNAL OF SCIENCE AND SOCIAL RESEARCH Jurnal Mantik JISKa (Jurnal Informatika Sunan Kalijaga) Technologia: Jurnal Ilmiah Jurnal Ilmu Komputer dan Bisnis Health Information : Jurnal Penelitian Journal of Applied Engineering and Technological Science (JAETS) JSR : Jaringan Sistem Informasi Robotik Jatilima : Jurnal Multimedia Dan Teknologi Informasi Journal of Computer System and Informatics (JoSYC) JIKA (Jurnal Informatika) INFOKUM Community Development Journal: Jurnal Pengabdian Masyarakat Journal of Computer Science, Information Technology and Telecommunication Engineering (JCoSITTE) El-Qist : Journal of Islamic Economics and Business (JIEB) Journal of Computer Networks, Architecture and High Performance Computing Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) IJISTECH Jurnal FASILKOM (teknologi inFormASi dan ILmu KOMputer) Walisongo Journal of Information Technology Syntax: Journal of Software Engineering, Computer Science and Information Technology Jurnal Teknologi Sistem Informasi dan Sistem Komputer TGD Instal : Jurnal Komputer Jurnal Teknisi J-SAKTI (Jurnal Sains Komputer dan Informatika) Jurnal Mandiri IT Jurnal Pustaka Data : Pusat Akses Kajian Database, Analisa Teknologi, dan Arsitektur Komputer JOMLAI: Journal of Machine Learning and Artificial Intelligence Data Sciences Indonesia (DSI) Internet of Things and Artificial Intelligence Journal Kesatria : Jurnal Penerapan Sistem Informasi (Komputer dan Manajemen)
Mhd Furqan
Universitas Islam Negeri Sumatera Utara
Aerospace Engineering Agriculture, Biological Sciences & Forestry Humanities 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 Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Neuroscience Nursing Physics Public Health Social Sciences Transportation Other

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Analisis Segmentasi Minat Baca Mahasiswa UINSU Menggunakan K-Means Clustering Nasution, Afri Yunda; Sembiring, Yogasurya Pranantha; Rifnandy, Muhammad Fauzan; Mahendra, Rifandi; Furqan, Mhd.
Jurnal Pendidikan Tambusai Vol. 9 No. 2 (2025): Agustus
Publisher : LPPM Universitas Pahlawan Tuanku Tambusai, Riau, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/jptam.v9i2.29547

Abstract

Minat baca mahasiswa merupakan salah satu indikator penting dalam menunjang kualitas akademik di lingkungan perguruan tinggi. Penelitian ini bertujuan untuk menganalisis segmentasi minat baca mahasiswa Universitas Islam Negeri Sumatera Utara (UINSU) menggunakan metode K-Means Clustering. Data dikumpulkan melalui kuesioner yang mencakup frekuensi membaca, jenis bacaan yang diminati, waktu yang dihabiskan untuk membaca, serta motivasi membaca. Metode K-Means digunakan untuk mengelompokkan mahasiswa ke dalam beberapa segmen berdasarkan kesamaan karakteristik minat baca. Hasil analisis menunjukkan bahwa mahasiswa dapat diklasifikasikan ke dalam tiga klaster utama, yaitu: (1) kelompok dengan minat baca tinggi, (2) kelompok dengan minat baca sedang, dan (3) kelompok dengan minat baca rendah. Segmentasi ini diharapkan dapat membantu pihak kampus dalam merancang program peningkatan literasi yang lebih terarah dan sesuai dengan karakteristik masing-masing segmen mahasiswa.
Analisis Kehadiran Mahasiswa Ilmu Komputer UINSU 2022 Pada Sains Data 2025 Via Google Sheets Farhan, Muhammad; Khairi, Nouval; Apriansyah, Yuda; Shafa, Dafa Ikhwanu; Furqan, Mhd.
Jurnal Pendidikan Tambusai Vol. 9 No. 2 (2025): Agustus
Publisher : LPPM Universitas Pahlawan Tuanku Tambusai, Riau, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/jptam.v9i2.29729

Abstract

Penelitian ini dilakukan untuk menganalisis data kehadiran mahasiswa Program Studi Ilmu Komputer UINSU angkatan 2022 pada mata kuliah Sains Data tahun ajaran 2025. Pengumpulan data dilakukan melalui Google Form yang disebarkan kepada mahasiswa setiap pertemuan perkuliahan, kemudian hasil respon otomatis tersimpan pada Google Sheets. Proses analisis dilakukan menggunakan fitur-fitur bawaan Google Sheets seperti filter, pivot table, dan diagram visualisasi untuk mempermudah interpretasi data. Hasil analisis menunjukkan bahwa mayoritas mahasiswa memiliki tingkat kehadiran yang baik, meskipun terdapat beberapa pertemuan dengan tingkat ketidakhadiran yang lebih tinggi. Selain itu, visualisasi data memudahkan dalam melihat rekap kehadiran tiap mahasiswa dan perkembangan kehadiran per pertemuan. Penelitian ini diharapkan dapat menjadi referensi dalam pengelolaan data kehadiran perkuliahan berbasis digital serta membantu dosen dalam memantau keaktifan mahasiswa secara efisien dan transparan.
DETEKSI KECURANGAN TRANSAKSI ONLINE DAN TRANSAKSI KARTU KREDIT MENGGUNAKAN ALGORITMA SUPPORT VECTOR MACHINE (SVM) SECARA REAL-TIME Wati, Putri Kurni; Widiya; Wulandari, Suci; Furqan, Mhd.
Bahasa Indonesia Vol 17 No 05 (2025): Instal : Jurnal Komputer
Publisher : Cattleya Darmaya Fortuna

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54209/jurnalinstall.v17i05.384

Abstract

Kemajuan teknologi terkini telah memicu peningkatan penggunaan kartu kredit yang signifikan, sehingga meningkatkan persentase penipuan kartu kredit baik dalam transaksi offline maupun online. Meskipun langkah-langkah seperti kode PIN, chip tertanam, dan kunci tambahan seperti token telah meningkatkan keamanan kartu kredit, lembaga keuangan dituntut untuk memperkuat kontrol penggunaan dan menerapkan sistem pemantauan waktu nyata untuk segera mengidentifikasi dan mengurangi aktivitas yang mencurigakan. Karena semakin populernya transaksi non-tunai, penipuan kartu kredit telah menjadi salah satu penipuan yang paling umum dan menyebabkan kerugian besar bagi lembaga keuangan dan individu dalam kehidupan nyata. Deteksi transaksi penipuan harus sangat cepat dan efektif. Ada lebih dari satu juta transaksi yang terjadi setiap hari, dan sulit untuk menyatukan setiap transaksi secara individu. Dengan demikian, sistem deteksi penipuan yang efektif digunakan untuk membedakan transaksi asli dan penipuan. Dalam jurnal ini, algoritma Support Vector Machine (SVM) digunakan untuk membangun model untuk menangani masalah deteksi penipuan kartu kredit. Penelitian ini menghasilkan kinerja algoritma Support Vector Machine (SVM), dalam mengidentifikasi transaksi keuangan yang mencurigakan. Penelitian ini bertujuan untuk mengembangkan model deteksi penipuan yang akurat dan efisien dengan memanfaatkan algoritma SVM. Dalam penelitian ini, data transaksi online maupun offline yang terdiri dari transaksi sah dan penipuan akan digunakan sebagai dataset. Proses penelitian meliputi tahapan preprocessing Data, model pelatihan dengan manfaat SVM, dan penilaian kinerja model berdasarkan ukuran akurasi, presisi, recal,dan F1-score. Diharapkan model yang dibuat dapat mengidentifikasi penipuan dengan akurasi yang tinggi dan dapat diterapkan secara efisien dalam sistem transaksi baik online maupun offline untuk meningkatkan keamanan dan kepercayaan para pengguna.
Security System With QR CODE Model For Digital Certificated Using Hash Function MD5 fandi, Fandi ahmad; Furqan, Mhd; Armansyah
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.v7i02.1412

Abstract

A digital certificate is an official declaration of recognition that is usually given to particular people or organizations in appreciation of their education, experience, and skill. Because of their ability to reduce paper usage and improve operational efficiency, these certificates have become increasingly popular in today's digital environment, being used for a variety of purposes and replacing traditional paper certificates. But since digital certificates are stored in a digital file format, malicious actors can easily manipulate them. Known for being a one-way encryption method, the MD5 hash function converts messages of any length into a fixed-length string of 128 bits. The MD5 hash function is primarily used to confirm the legitimacy of files. It makes it easier to compare the calculated hash value with the original, protecting the integrity of the data. Meanwhile, two-dimensional matricies represented graphically as QR Codes are flexible data storage devices that can hold binary, alphanumeric, and numeric data. By combining the MD5 hash function with QR Regulations, data can be given a distinct identity that enhances its authenticity and prevents attempts at forgery or replication. This combination strengthens data security protocols, which is a vital requirement in a time when digital data powers many aspects of modern life.
Sentiment Analysis on Teacher Salary Policy in Indonesia 2025 Using Support Vector Machine: A Case Study on Instagram Data Zabni, Nur Hera; Furqan, Mhd.
Journal of Computer Networks, Architecture and High Performance Computing Vol. 7 No. 3 (2025): Articles Research July 2025
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/cnahpc.v7i3.6487

Abstract

The government's policy regarding salary increases for both civil servant (ASN) and non-civil servant (honorary) teachers in 2025 has generated various responses from the public, especially on social media. This issue has sparked public debate, with the emergence of both positive and negative comments, particularly on the Instagram platform. This study employs the Support Vector Machine (SVM) approach to classify public sentiment based on Instagram comments. A total of 1,500 comments were collected from the @folkative account during December 2024. The data were analyzed through several preprocessing stages (cleaning, case folding, tokenization, filtering, stopword removal, and stemming), followed by TF-IDF word weighting, normalization, and SVM model training and testing with an 80% training and 20% testing data split. The developed model demonstrated excellent performance, achieving an accuracy of 86%, precision of 87%, recall of 99%, and F1-score of 93%. These results indicate that the SVM algorithm is effective in classifying public opinion on government policies. This research also contributes to the advancement of machine learning applications in policy analysis based on public opinion, which can serve as valuable input for formulating more responsive policies.
Application of fuzzy time series method to determine medical equipment inventory Iskandar, Rozai; Furqan, Mhd.
Jurnal Mandiri IT Vol. 14 No. 1 (2025): July: Computer Science and Field.
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/mandiri.v14i1.417

Abstract

This study applied the Fuzzy Time Series (FTS) method to forecast monthly stock requirements for medical equipment at PT. Karya Metropolis. The FTS process including interval determination, fuzzification, fuzzy rule formation, and defuzzification successfully identified historical patterns in sales data and produced predictions closely aligned with actual values. Forecast results indicated the next month’s needs for several items, such as 154.5 units of gauze rolls, 129 units of leukocrepe, 26.5 units of hypafix, 25 liters of 95% alcohol, 487.5 oxygen nebulizer masks, 109.5 units of Vaseline swabs, and 61 Maxter gloves. Forecast accuracy was assessed using Mean Absolute Percentage Error (MAPE), where most items showed low error rates, including gauze rolls (6.16%), Vaseline swabs (7.21%), and Maxter gloves (9.28%). However, the oxygen nebulizer mask showed a higher MAPE value of 47.28%, indicating a need for method refinement or integration with other approaches for that item. Overall, the FTS method proved effective in supporting accurate, efficient, and measurable stock planning decisions for medical supplies.
SENTIMENT ANALYSIS ON THE CHANGE OF COACH OF THE INDONESIAN NATIONAL TEAM USING SUPPORT VECTOR MACHINE ALGORITHM Syamia, Nanda; Furqan, Mhd.
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.v7i02.1510

Abstract

The change in the coach of the Indonesian national team has ignited a range of public responses on social media, particularly on the X platform (formerly Twitter). This research intends to examine public opinion regarding the firing of coach Shin Tae-yong and the hiring of Patrick Kluivert through the Support Vector Machine (SVM) algorithm. A dataset of 1,000 public comments was gathered via crawling methods from the @timnasindonesia account, subsequently classified as either positive or negative sentiment using a lexicon-based technique. The stages of the research involved text preprocessing (cleaning, tokenization, stemming, and stopword elimination), word weighting through TF-IDF, and sentiment classification with the SVM algorithm. Initial findings indicated a classification accuracy of 77%, which rose to 83% following upsampling to rectify class imbalance. The evaluation of the model utilized a confusion matrix, resulting in high precision, recall, and F1-score metrics. This research shows that SVM is successful in categorizing public sentiment on particular social matters and can serve as a data-informed decision-making resource. These findings further enhance understanding of public views on strategic policies within national sports, especially football.
DYNAMIC VISUALIZATION OF THE SPREAD OF COVID-19 IN MEDAN CITY USING HEATMAP WITH PYTHON Hasrul Hasibuan, Mhd Fikri; Ramadhani, Fredy Kusuma; Badria, Lailatul; Nurzannah, Laila; Haikal, Fikri; Furqan, Mhd
JURNAL TEKNISI Vol 5, No 2 (2025): Agustus 2025
Publisher : Smart Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54314/teknisi.v5i2.3791

Abstract

Abstract: The rapid and widespread transmission of COVID-19 has posed significant challenges for public health management, particularly in densely populated urban areas like Medan. Manual data reporting often fails to convey the dynamic nature of the virus's spread in a clear and actionable manner. This study aims to address this gap by developing dynamic visualizations of COVID-19 distribution using heat maps created with Python programming. The study utilized official COVID-19 datasets sourced from platforms like Kaggle, which include district- and municipal-level data across North Sumatra. Methodological steps included data collection, preprocessing, and visualization using Python libraries like Pandas and Matplotlib. These tools enable the transformation of static tabular data into interactive heat maps that highlight spatial and temporal trends in infections, recoveries, and mortality. The visualizations reveal that Medan City recorded the highest number of confirmed and recovered cases, while Deli Serdang had the highest number of deaths. Conversely, North Nias and South Nias showed the lowest mortality rates. The resulting spreadsheets provide a practical solution for monitoring the pandemic's development and serve as decision-support tools for policymakers and health authorities. In conclusion, dynamic data visualization improves understanding of COVID-19 patterns and supports effective pandemic response strategies.Keywords: dynamic visualization; COVID-19; python; heatmap. Abstrak: Penularan COVID-19 yang cepat dan meluas telah menimbulkan tantangan yang signifikan bagi manajemen kesehatan masyarakat, terutama di daerah perkotaan yang padat penduduk seperti Kota Medan. Laporan data manual sering kali gagal menyampaikan sifat dinamis penyebaran virus dengan cara yang jelas dan dapat ditindaklanjuti. Penelitian ini bertujuan untuk mengatasi kesenjangan ini dengan mengembangkan visualisasi dinamis distribusi COVID-19 menggunakan peta panas yang dibuat dengan pemrograman Python. Penelitian ini menggunakan kumpulan data resmi COVID-19 yang bersumber dari platform seperti Kaggle, yang mencakup data tingkat kabupaten dan kotamadya di seluruh Sumatera Utara. Langkah-langkah metodologis meliputi pengumpulan data, prapemrosesan, dan visualisasi menggunakan pustaka Python seperti Pandas dan Matplotlib. Alat-alat ini memungkinkan transformasi data tabular statis menjadi peta panas interaktif yang menyoroti tren infeksi, pemulihan, dan mortalitas secara spasial dan temporal. Visualisasi tersebut mengungkapkan bahwa Kota Medan mencatat jumlah kasus terkonfirmasi dan sembuh tertinggi, sementara Deli Serdang memiliki jumlah kematian tertinggi. Sebaliknya, Nias Utara dan Nias Selatan menunjukkan tingkat mortalitas terendah. Heatmap yang dihasilkan memberikan solusi praktis untuk memantau perkembangan pandemi dan berfungsi sebagai alat pendukung keputusan bagi para pembuat kebijakan dan otoritas kesehatan. Kesimpulannya, visualisasi data dinamis meningkatkan pemahaman pola COVID-19 dan mendukung strategi respons pandemi yang efektif.Kata Kunci: visualisasi dinamis; COVID-19; python; peta panas.
APPLICATION OF WEIGHTED AVERAGE ALGORITHM IN RECREATIONAL PARK TOURIST DESTINATION RECOMMENDATION SYSTEM BASED ON GOOGLE MAPS USER RATINGS Faiza, Nayla; Siregar, Hervilla Amanda R.; Sitorus, Nur Shafwa Aulia; Nugroho, Agung; Aulia, Muhammad Fathir; Furqan, Mhd
JURNAL TEKNISI Vol 5, No 2 (2025): Agustus 2025
Publisher : Smart Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54314/teknisi.v5i2.3790

Abstract

Abstract: The development of digital technology has changed the behavior patterns of tourists in choosing travel destinations. Google Maps is now not only used to find restaurant locations but has also become the main source for searching nearby tourist destinations based on user ratings and reviews. This research aims to build a recommendation system for recreational park tourist destinations in Medan City by applying the Weighted Average algorithm using Google Maps user rating data. The data used comes from reviews by five users of five popular recreational parks in Medan City during the period from January 1, 2025, to April 30, 2025. The Weighted Average algorithm was chosen because it can provide a more objective and fair assessment by taking into account the weight of each rating given by users. As a result, this system can recommend the best recreational parks based on user experiences related to cleanliness, parking facilities, toilets, security, running paths, and accessibility. It is hoped that this system can help tourists choose destinations that meet their needs and preferences, as well as provide a more enjoyable and satisfying travel experience.Keywords : digital technology; google maps; recommendation system; weighted average algorithmAbstrak: Perkembangan teknologi digital telah mengubah pola perilaku wisatawan dalam memilih destinasi wisata. Google Maps kini tidak hanya digunakan untuk mencari lokasi restoran, tetapi juga menjadi sumber utama dalam mencari destinasi wisata terdekat berdasarkan rating dan ulasan pengguna. Penelitian ini bertujuan untuk membangun sistem rekomendasi destinasi wisata taman rekreasi di Kota Medan dengan menerapkan algoritma Weighted Average menggunakan data rating pengguna Google Maps. Data yang digunakan berasal dari lima ulasan pengguna terhadap lima taman rekreasi populer di Kota Medan selama periode 1 Januari 2025 hingga 30 April 2025. Algoritma Weighted Average dipilih karena mampu memberikan penilaian yang lebih objektif dan adil dengan memperhatikan bobot setiap rating yang diberikan pengguna. Hasilnya, sistem ini dapat merekomendasikan taman rekreasi terbaik berdasarkan pengalaman pengguna terkait aspek kebersihan, fasilitas parkir, toilet, keamanan, lintasan lari, dan aksesibilitas. Diharapkan sistem ini dapat membantu wisatawan dalam memilih destinasi yang sesuai dengan kebutuhan, preferensi, dan memberikan pengalaman wisata yang lebih menyenangkan dan memuaskan. Kata Kunci: google maps; sistem rekomendasi; teknologi digital; weighted average algorithm
Penerapan Algoritma Naive Bayes Untuk Memprediksi Tingkat Stres Mahasiswa Prayogi, Ahmad; Furqan, Mhd.
Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) Vol 10, No 2 (2025): Edisi Agustus
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/jurasik.v10i2.928

Abstract

Academic-related stress is a critical issue that can adversely affect students’ mental health and academic performance. This study wants to create a system that can predict how stressed students are. It uses the Naïve Bayes algorithm. Naïve Bayes is a way of classifying things using probabilities. It is based on Bayes’ Theorem and makes a key assumption that each feature is independent. It works by calculating the chances of different outcomes to decide which category something belongs to. Primary data were collected from 117 students of Universitas Islam Negeri Sumatera Utara through a questionnaire based on the Transactional Model of Stress and Coping by Lazarus and Folkman, covering academic, emotional, social, and psychological factors. The research stages included data cleaning, feature selection, training-testing data splitting, model training, and performance evaluation. The results indicated an accuracy rate of 95%, with optimal performance in predicting low and moderate stress categories. The model was implemented in an Android-based application developed using Flutter and integrated with a Flask API, enabling users to perform self-assessment and receive stress management recommendations according to their predicted category. This study makes a practical contribution to the early detection of student stress levels, supporting preventive interventions and enhancing the effectiveness of mental health services in higher education institutions
Co-Authors Abdul Aziz Abdul Halim Hasugian Adha, Rifki Mahsyaf Agpina, Pipi Ahmad Fakhri Ab. Nasir Ahmad Fauzi Aidil Halim Lubis Aisyah Nurrahmah Siregar Akmal, Muhammad Haikal Anwar, Mufti Husain Apriansyah, Yuda Ardyanti, Tiwy Armansyah Armansyah Armansyah Armansyah Armansyah Armansyah Armansyah, A Aulia, Atiqah Aulia, Muhammad Arief Aulia, Muhammad Fathir Aulia, Rafif Risdi Badria, Lailatul Bagus Ageng Alfahri Br Rambe, Indri Gusmita Cahyadi, Bhagaskara Daulay, Ikhsan Agus Martua Elce, Furkan Fadil, Ulfi Muzayyanah Fadillah, Rini Fahrul Azis Nasution Faiza, Nayla Fakhriza, M. fandi, Fandi Ahmad FIKRI HAIKAL Gunawan, Irwan Harahap, Khaila Mukti Harahap, Raihan Rizieq Harahap, Rosa Linda Hasrul Hasibuan, Mhd Fikri Heri Santoso Himawan Hasibuan, Riswanda Ichsan HP, Kiki Iranda Hsb, Dinda Umami Hsb, Munawir Siddik Hutagalung, Muhammad Wandisyah R Ilham Fuadi Nasution Imam Zaki Husein Nst Iskandar, Rozai Ismail Pulungan Januar, Bagus juwita sari K Khairunnisa Kartikasari, Diah Putri Khairi, Nouval Khairunnisa Khairunnisa Khairunnisa, K Kurniawan, Riski Askia Lely Sahrani Lubis, Akbar Maulana M. Fakhriza Mahendra, Rifandi Matondang, Toibatur Rahma Maulana Ihsan, Maulana Mey Hendra Putra Sirait Mhd Ikhsan Rifki Mhd Reza Alfani Muhammad Akbar Ramadhan Tanjung Muhammad Farhan Muhammad Ikhsan Muhammad Luthfi Muhammad Naufal Shidqi Muhammad Ridzki Hasibuan Muhammad Rizki Munadi Munadi Nabawy, Putri Nabila, Siti Fadiyah Nasution, Afri Yunda Nasution, Irma Yunita Nasution, Romaito Nasution, Zulia Lestari Ningsih, Siti Alus Novrianty, Amanda Nugroho, Agung Nur Bainatun Nisa Nurhasanah Nurhasanah Nurhidayati Nurhidayati Nurul Hadi Muliani Hariadi Saputra Nurzannah, Laila Pane, Putri Pratiwi Pangestu, Dimas Panggabean, Alwi Andika Pratama, Haris Prayoga Elfanda Fachmi Hasibuan Prayogi, Ahmad Pulungan, Miftahul Rizky Putra, Suan Ekie Nanda Putri, Alma Irawanti Raissa Amanda Putri Rakhmat Kurniawan R Ramadani, Wily Supi Ramadhan Nasution, Yusuf Ramadhani, Fredy Kusuma Razzaq H. Nur Wijaya Reza Muhammad Rifnandy, Muhammad Fauzan Rivaldi Prima Nanda Rizka Rizki Ananda Rizki Siregar, Awal Rizqi Hidayat Tanjung RR. Ella Evrita Hestiandari Saparuddin Siregar Saputri Nasution, Intan Widya Sembiring, Yogasurya Pranantha Shafa, Dafa Ikhwanu Sinaga, Meri Siregar, Dzilhulaifa Siregar, Hervilla Amanda R. Siregar, Kalfida Eka Wati Sitepu, Anggi Jelita Siti Saniah Siti Sarah Harahap Siti Sumita Harahap Sitorus, Nur Shafwa Aulia Solly Aryza Sri Rahmadani Sri Wahyuni Sriani Sriani Sriani Sriani Sriani, S Suci Syahputri Suci Wulandari Suhardi, S Suhardi, Suhardi Susan Mayang Sari Syamia, Nanda Tambak, Tiara Ayu Triarta Tanjung, Tegar Haryahya Tria Elisa Wan Fadilla Rischa Wati, Putri Kurni Widiya Yuli Kartika Siregar Yusuf Ramadhan Nasution Yusuf Ramadhan Nasution, Yusuf Ramadhan Zabni, Nur Hera Zahra Humaira Kudadiri Ziqra Addilah