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All Journal Jurnal Ilmu Sosial dan Ilmu Politik (JISIP) METHOMIKA: Jurnal Manajemen Informatika & Komputerisasi Akuntansi INTECOMS: Journal of Information Technology and Computer Science KOMIK (Konferensi Nasional Teknologi Informasi dan Komputer) The IJICS (International Journal of Informatics and Computer Science) JOURNAL OF SCIENCE AND SOCIAL RESEARCH Journal of Humanities and Social Studies Jatilima : Jurnal Multimedia Dan Teknologi Informasi REMIK : Riset dan E-Jurnal Manajemen Informatika Komputer Journal of Computer System and Informatics (JoSYC) Budapest International Research and Critics Institute-Journal (BIRCI-Journal): Humanities and Social Sciences Instal : Jurnal Komputer Jurnal Info Sains : Informatika dan Sains Bulletin of Information Technology (BIT) INTERNATIONAL JOURNAL OF EDUCATION, INFORMATION TECHNOLOGY, AND OTHERS Jurnal Nasional Teknologi Komputer Jurnal Hasil Pengabdian Masyarakat (JURIBMAS) Jurnal Ekonomi dan Bisnis
Nasution, Darmeli
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Religion Arts Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Social Sciences

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PEMANFAATAN BUSINESS INTELLIGENCE UNTUK VISUALISASI DATA DAN PEMETAAN KASUS DATA KELUARGA BERISIKO STUNTING DENGAN MENGGUNAKAN TABLEAU Marsya, Alviona; Nasution, Darmeli; Wijaya, Rian Farta
JOURNAL OF SCIENCE AND SOCIAL RESEARCH Vol 8, No 2 (2025): May 2025
Publisher : Smart Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54314/jssr.v8i2.3160

Abstract

Abstract: The utilization of Business Intelligence (BI) with Tableau effectively aids in mapping and analyzing cases of families at risk of stunting. Stunting, a condition caused by chronic malnutrition, remains a major health issue in Indonesia, particularly in Langkat Regency, North Sumatra. A quantitative research methodology was applied using the BI framework, encompassing data collection, ETL (Extract, Transform, Load) processes, and interactive visualization through Tableau dashboards. Data from 2022 to 2024, including family risk categories and regional coordinates, were transformed into comprehensive visual representations. The visualization results demonstrate the effectiveness of Tableau in simplifying complex datasets and supporting more targeted interventions. Emphasis is placed on the importance of continuous monitoring and data updates to ensure accurate and timely responses to stunting cases. Keyword: Families At Risk Of Stunting; Business Intelligence; Data Visualization; TableauAbstrak: Pemanfaatan Business Intelligence (BI) dengan Tableau mampu membantu memetakan dan menganalisis kasus keluarga berisiko stunting. Stunting, sebagai kondisi kekurangan gizi kronis, menjadi masalah kesehatan utama di Indonesia, khususnya di Kabupaten Langkat, Sumatera Utara. Metodologi penelitian kuantitatif digunakan dengan kerangka kerja BI yang mencakup pengumpulan data, proses ETL (Extract, Transform, Load), serta visualisasi interaktif melalui dashboard Tableau. Data tahun 2022 hingga 2024, meliputi kategori risiko keluarga dan koordinat wilayah, diolah menjadi representasi visual yang komprehensif. Hasil visualisasi memperlihatkan efektivitas Tableau dalam menyederhanakan data kompleks dan mendukung tindakan yang lebih tepat sasaran. Pentingnya pemantauan berkelanjutan dan pembaruan data ditekankan agar respons terhadap kasus stunting dapat dilakukan secara akurat dan tepat waktu.Kata kunci: Keluarga Berisiko Stunting; Business Intelligence; Visualisasi Data; Tableau 
SISTEM INFORMASI PERPUSTAKAAN PADA MADRASAH ALIYAH AL-MA'ARIF BERBASIS WEB Nasywa, Khairun; Nasution, Darmeli; Yusman, Yanti
JOURNAL OF SCIENCE AND SOCIAL RESEARCH Vol 8, No 3 (2025): August 2025
Publisher : Smart Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54314/jssr.v8i3.3545

Abstract

Abstract: The library has an important role in providing information sources for students and educators to support the teaching and learning process. However, the library management system that is still done manually often faces obstacles such as inefficient recording of borrowing and returning books, difficulty in searching collections, and the lack of a real-time book availability monitoring system. To overcome these problems, this study aims to design and build a web-based library information system at Madrasah Aliyah Al-Ma'arif to improve efficiency in managing books and library transactions. The system developed has main features such as book data management, searching collections by category, a digital-based borrowing and returning system, and creating transaction reports to make it easier for managers to monitor library activities. With a web-based system, this system can be accessed from various devices and makes it easier for users to obtain information about book availability and make transactions faster and more accurately. The results of the study show that the implementation of a web-based library information system can accelerate transaction recording, increase the ease of searching for books, and facilitate monitoring of library collections. With this system, library management at Madrasah Aliyah Al-Ma'arif becomes more efficient, modern, and supports the digitalization of educational services. Keywords: Information System, Library, Web, Digitization, Book Management. Abstrak: Perpustakaan memiliki peran penting dalam menyediakan sumber informasi bagi siswa dan tenaga pendidik untuk mendukung proses belajar mengajar. Namun, sistem pengelolaan perpustakaan yang masih dilakukan secara manual sering menghadapi kendala seperti pencatatan peminjaman dan pengembalian buku yang tidak efisien, sulitnya pencarian koleksi, serta kurangnya sistem monitoring ketersediaan buku secara real-time. Untuk mengatasi permasalahan tersebut, penelitian ini bertujuan untuk merancang dan membangun sistem informasi perpustakaan berbasis web pada Madrasah Aliyah Al-Ma’arif guna meningkatkan efisiensi dalam pengelolaan buku dan transaksi perpustakaan. Sistem yang dikembangkan memiliki fitur utama seperti manajemen data buku, pencarian koleksi berdasarkan kategori, sistem peminjaman dan pengembalian berbasis digital, serta pembuatan laporan transaksi untuk mempermudah pengelola dalam memantau aktivitas perpustakaan. Dengan berbasis web, sistem ini dapat diakses dari berbagai perangkat dan memberikan kemudahan bagi pengguna dalam memperoleh informasi mengenai ketersediaan buku serta melakukan transaksi secara lebih cepat dan akurat. Hasil penelitian menunjukkan bahwa implementasi sistem informasi perpustakaan berbasis web dapat mempercepat pencatatan transaksi, meningkatkan kemudahan pencarian buku, serta mempermudah monitoring koleksi perpustakaan. Dengan adanya sistem ini, pengelolaan perpustakaan di Madrasah Aliyah Al-Ma’arif menjadi lebih efisien, modern, dan mendukung digitalisasi layanan pendidikan. Kata kunci: Sistem Informasi, Perpustakaan, Web, Digitalisasi, Manajemen Buku.
ANALISIS DATA MINING DALAM PENGELOLAAN PERSEDIAAN STOK DENGAN ALGORITMA RANDOM FOREST DAN APRIORI (STUDI KASUS: TOKO CERIA BABYSHOP) Zalukhu, Anzas Ibezato; Iqbal, Muhammad; Nasution, Darmeli
JOURNAL OF SCIENCE AND SOCIAL RESEARCH Vol 8, No 3 (2025): August 2025
Publisher : Smart Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54314/jssr.v8i3.3544

Abstract

Abstract: This research analyzes inventory management at Toko Ceria Babyshop by applying data mining techniques, specifically Random Forest and Apriori algorithms. Effective inventory management is crucial for aligning product availability with market demand, preventing overstocking or stockouts, and optimizing operational costs. Sales transaction data from June to December 2024, comprising 20,578 sales transactions, 3,593 purchase entries, 2,736 initial stock entries, and 1,331 final stock entries, were divided into 80:20 training and testing sets. The Random Forest implementation showed that weekly purchase quantity predictions were more effective than monthly predictions, evidenced by lower Mean Squared Error (MSE), Mean Absolute Error (MAE), and Root Mean Squared Error (RMSE) values for weekly predictions (16.10, 1.76, 4.01) compared to monthly (39.68, 3.19, 6.30). Furthermore, the R-squared (R²) value was higher for the weekly model (0.21) than the monthly (0.04), indicating better weekly prediction accuracy. The Apriori algorithm successfully identified product association patterns for both 2-itemsets and 3-itemsets, with all rules exhibiting lift values above 1, signifying positive relationships between products. This purchasing pattern information is highly beneficial for developing marketing strategies such as bundling, shelf arrangement, cross-selling promotions, and improved inventory planning. Keywords: Data mining, Random Forest, Apriori, stok Inventory, Toko Ceria Babyshop Abstrak: Penelitian ini berfokus pada analisis pengelolaan persediaan stok di Toko Ceria Babyshop melalui penerapan teknik data mining menggunakan algoritma Random Forest dan Apriori. Efektivitas pengelolaan persediaan sangat krusial dalam bisnis untuk menyelaraskan ketersediaan produk dengan permintaan pasar, mencegah kelebihan atau kekurangan stok, dan mengoptimalkan biaya operasional. Data transaksi penjualan yang dikumpulkan dari Juni hingga Desember 2024 terdiri dari 20.578 transaksi penjualan, 3.593 entri pembelian, 2.736 entri stok awal, dan 1.331 entri stok akhir, yang kemudian dibagi menjadi set pelatihan dan pengujian dengan rasio 80:20. Hasil implementasi algoritma Random Forest menunjukkan prediksi kuantitas pembelian mingguan lebih efektif dibandingkan bulanan, ditunjukkan oleh nilai Mean Squared Error (MSE), Mean Absolute Error (MAE), dan Root Mean Squared Error (RMSE) yang lebih rendah pada prediksi mingguan (16.10, 1.76, 4.01) dibandingkan bulanan (39.68, 3.19, 6.30). Selain itu, nilai R-squared (R²) juga lebih tinggi untuk model mingguan (0.21) dibandingkan bulanan (0.04), mengindikasikan akurasi prediksi mingguan yang lebih baik. Algoritma Apriori berhasil mengidentifikasi pola asosiasi produk, baik untuk 2-itemset maupun 3-itemset, dengan semua aturan memiliki nilai lift di atas 1, yang menunjukkan hubungan positif antar produk. Informasi mengenai pola pembelian ini sangat bermanfaat untuk pengembangan strategi pemasaran seperti bundling, penataan rak, promosi cross-selling, serta perencanaan persediaan stok yang lebih baik. Kata kunci: Data mining, Random Forest, Apriori, Persediaan stok, Toko Ceria  Babyshop
Pelatihan Media Sosial untuk Pemasaran UMKM dengan Digital Marketing di Desa Kota Pari Wadly, Fachrid; Kurniawan, Heri; Akbar, Ahmad; Muttaqin, Muhammad; Nasution, Darmeli
JURIBMAS : Jurnal Hasil Pengabdian Masyarakat Vol 4 No 1 (2025): Juli 2025
Publisher : LKP KARYA PRIMA KURSUS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62712/juribmas.v4i1.478

Abstract

Kegiatan pengabdian masyarakat ini bertujuan untuk membantu pelaku Usaha Mikro, Kecil, dan Menengah (UMKM) di Desa Kota Pari dalam mengoptimalkan pemanfaatan media sosial sebagai sarana pemasaran produk melalui penerapan strategi digital marketing yang efektif. Banyak pelaku UMKM yang belum memahami pentingnya digital branding dan teknik promosi online yang sesuai dengan target pasar. Kegiatan ini dilaksanakan dalam bentuk pelatihan dan pendampingan yang mencakup materi mengenai pembuatan konten menarik, pemanfaatan platform media sosial seperti Instagram, Facebook, dan WhatsApp Business, serta pengenalan dasar analisis performa melalui insight media sosial. Hasil kegiatan menunjukkan peningkatan pemahaman peserta terhadap pentingnya strategi digital dalam memperluas jangkauan pasar dan meningkatkan penjualan. Dengan adanya pelatihan ini, diharapkan UMKM di Desa Kota Pari dapat beradaptasi dengan perkembangan teknologi serta bersaing di era digital secara lebih efektif.
PEMETAAN PILIHAN LULUSAN SMK PANCA BUDI MEDAN MENGGUNAKAN ALGORITMA K-MEANS DAN VISUALISASI DATA Indrayani, Maida; Iqbal, Muhammad; Nasution, Darmeli
JOURNAL OF SCIENCE AND SOCIAL RESEARCH Vol 8, No 3 (2025): August 2025
Publisher : Smart Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54314/jssr.v8i3.3543

Abstract

Abstract: This research maps the career choices of SMK Panca Budi Medan graduates using the K-Means algorithm and data visualization. The study included 219 graduates from 2024 across eight study programs. The majority (44.7%) chose to work, followed by 32.0% who pursued higher education, 16.4% were undecided, and 6.8% became entrepreneurs. Graduates with higher average report card scores tended to continue their studies, while those with lower scores often opted to work or were undecided. The K-Means algorithm successfully clustered graduates, with Cluster 1.0 showing the highest academic potential (average score: 94.60). The findings provide strategic recommendations for the school, including intensifying career guidance for undecided graduates, strengthening higher education pathways for high-achievers, accelerating entrepreneurship incubators, and implementing personalized alumni coaching based on clustering analysis. Keywords: Tracer Study, K-Means, Data Visualization, SMK, Alumni Outcomes Abstrak: Penelitian ini memetakan pilihan karier lulusan SMK Panca Budi Medan menggunakan algoritma K-Means dan visualisasi data. Studi melibatkan 219 lulusan tahun 2024 dari delapan program studi. Sebagian besar lulusan (44,7%) memilih langsung bekerja, diikuti oleh 32,0% yang melanjutkan kuliah, 16,4% "belum tahu", dan 6,8% berwirausaha. Alumni dengan rata-rata nilai rapor tertinggi cenderung melanjutkan kuliah, sedangkan yang lebih rendah umumnya memilih bekerja atau belum memiliki rencana. Algoritma K-Means berhasil mengelompokkan lulusan, dengan cluster 1.0 merepresentasikan potensi akademik tertinggi (rata-rata nilai: 94,60). Temuan ini menghasilkan rekomendasi strategis bagi sekolah, meliputi pengintensifan program bimbingan karier, penguatan jalur kuliah bagi siswa berprestasi tinggi, akselerasi pengembangan inkubator wirausaha, serta implementasi pembinaan alumni berbasis personalisasi dari hasil clustering. Kata kunci: Tracer Study, K-Means, Visualisasi Data, SMK, Outcome Alumni
Time Management as a Foundation for Ethics, Integrity, Competence, Professionalism, and Communication in Higher Education Discipline Akbar, Muhammad Caesar; Pulungan, Ahmad Fakhrizal; Nasution, Darmeli; Haralayya, Bhadrappa
Jurnal Ilmu Sosial dan Ilmu Politik (JISIP) Vol 14, No 2 (2025)
Publisher : Universitas Tribhuwana Tungga Dewi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33366/jisip.v14i2.3278

Abstract

This research aims to analyze time management as an essential pillar in the development of ethics, integrity, competence, professionalism, and communication among students at Medan Aviation Polytechnic. Effective time management plays a vital role in developing a student's character, especially in forming the discipline that is the foundation of professional behavior in the aviation world. By adopting a qualitative approach, this research collected data through interviews, observations, and documentation studies of students and lecturers at the Medan Aviation Polytechnic. The research results indicate that effective time management plays a significant role in enhancing student ethics, integrity, and competence. Apart from that, time management also plays a crucial role in improving professionalism and effective communication, which are essential aspects in the aviation sector. This research offers recommendations for enhancing time management training within the higher education curriculum, aiming to foster students who are more disciplined and prepared to face future professional challenges. This is relevant to the needs of the aviation industry, which prioritizes punctuality, team coordination, and high adaptability in a dynamic work environment.Penelitian ini bertujuan untuk menganalisis manajemen waktu sebagai pilar penting dalam pembentukan etika, integritas, kompetensi, profesionalisme, dan komunikasi di kalangan mahasiswa Politeknik Penerbangan Medan. Manajemen waktu yang efektif berperan vital dalam pengembangan karakter mahasiswa, terutama dalam membentuk kedisiplinan yang menjadi dasar dari perilaku profesional di dunia penerbangan. Dengan mengadopsi pendekatan kualitatif, penelitian ini mengumpulkan data melalui wawancara, observasi, dan studi dokumentasi terhadap mahasiswa dan dosen di Politeknik Penerbangan Medan. Hasil penelitian menunjukkan bahwa manajemen waktu yang baik berkontribusi signifikan terhadap peningkatan etika, integritas, serta kompetensi mahasiswa. Selain itu, manajemen waktu juga berperan dalam meningkatkan profesionalisme dan komunikasi yang efektif, yang merupakan aspek penting dalam dunia kerja di sektor penerbangan. Penelitian ini memberikan rekomendasi untuk penguatan pelatihan manajemen waktu dalam kurikulum pendidikan tinggi, guna mendukung pengembangan karakter mahasiswa yang lebih disiplin dan siap menghadapi tantangan profesional di masa depan. Hal ini relevan dengan kebutuhan industri penerbangan yang mengutamakan ketepatan waktu, koordinasi tim, serta kemampuan adaptasi yang tinggi dalam lingkungan kerja yang dinamis.
Sentiment Analysis Classification of E-commerce User Reviews Using Natural Language Processing (NLP) and Support Vector Machine (SVM) Methods Iqbal Wiranata Siregar, Jimmy; Putera Utama Siahaan, Andysah; Iqbal, Muhammad; Nasution, Darmeli; Farta Wijaya, Rian
Bulletin of Information Technology (BIT) Vol 6 No 2: Juni 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bit.v6i2.2018

Abstract

In the swiftly changing digital age, e-commerce has become a vital component of everyday living. Individuals actively share product reviews, whether favorable or unfavorable, which companies can utilize to grasp users' views on their services. An efficient approach for evaluating and categorizing user sentiments is required to aid in analyzing these reviews. In this scenario, the Support Vector Machine (SVM) and Natural Language Processing (NLP) methods offer the appropriate answer. This research intends to develop a classification model capable of sorting e-commerce user feedback into positive, negative, or neutral sentiments. Utilizing NLP methods to analyze the review text and SVM as the classification approach, this model aims to achieve high accuracy in identifying user sentiment. Words that do not affect sentiment analysis, like "and," "that," "for," are eliminated, and SVM is utilized once the review data is converted into vectors via the TF-IDF method. The labeled sentiment training data will be used to train the SVM model.
Analisis Prediksi Pretasan Data Pribadi Berdasarkan Umur Pengguna Di Kota Tanjungbalai Menggunakan Algoritma C4.5 Sitorus, Mhd Arfan; Nasution, Darmeli; Iqbal, Muhammad
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.v7i02.1589

Abstract

Personal data security has become a critical issue amidst the rapid development of digital technology. Online activities such as social media use, online transactions, and cloud data storage have increased the potential risk of hacking. This study aims to predict the level of risk of personal data hacking based on the age and digital behavior of users in Tanjungbalai City. Age is thought to influence users' awareness and habits in maintaining data security, such as the use of strong passwords, utilization of two-step verification, and the use of protective software. This study used a data mining approach with the C4.5 algorithm to build a classification model that identifies age groups with high vulnerability to hacking. Data were collected through a questionnaire with an ordinal scale that reflects respondents' digital behavior and experience. The results show a significant pattern between age, digital habits, and the level of hacking risk, and produce a classification model that can be used as a basis for decision-making regarding data security policies. These findings are expected to contribute to the development of more effective digital education strategies that are adaptive to user demographic characteristics.
Performance Analysis of CNN (Convolutional Neural Network) in Nominal Classification of Rupiah Emissions 2022 Sahputra, Fajar; Sitorus, Zulham; Iqbal, Muhammad; Marlina, Leni; Nasution, Darmeli
The IJICS (International Journal of Informatics and Computer Science) Vol. 9 No. 2 (2025): July
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/ijics.v9i2.8903

Abstract

This study aims to analyze the performance of Convolutional Neural Network (CNN) algorithm in classifying the nominal of Rupiah banknotes issued in 2022. Three test models are developed, namely two CNN architectures with different optimizers (Adam and RMSprop), and one transfer learning model using VGG16. The dataset used consists of 1,848 banknote images of seven denominations: Rp1,000, Rp2,000, Rp5,000, Rp10,000, Rp20,000, Rp50,000, and Rp100,000. The data was collected using a smartphone camera and processed through augmentation, normalization, and classification stages. The model was evaluated using accuracy, precision, recall, and F1-score metrics. The results show that CNN with Adam's optimizer achieves a validation accuracy of 98.97%, while CNN with RMSprop reaches 99.59%. Meanwhile, the VGG16 model achieved perfect validation accuracy of 100%, with precision, recall, and F1-score values of 1.00 each. These results show that the transfer learning approach provides the best performance compared to conventional CNN models. This research supports the development of an accurate and efficient banknote recognition automation system for digital finance applications.
Development of A Web-Based Employee Performance Monitoring and Reporting System to Enhance Productivity and Performance Evaluation Devina, Annisa; Nasution, Darmeli
Bahasa Indonesia Vol 17 No 07 (2025): Instal : Jurnal Komputer
Publisher : Cattleya Darmaya Fortuna

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54209/jurnalinstall.v17i07.420

Abstract

The Attorney General's Office, as a law enforcement institution, requires optimal employee performance to achieve effectiveness in law enforcement. However, the current employee performance monitoring and reporting processes at the Binjai District Attorney's Office are still manual, leading to inefficiencies, lack of transparency, and difficulties in objective evaluation. This research aims to develop a Web-Based Employee Performance Monitoring and Reporting System as a solution to address these issues. The system is designed to improve the accuracy, transparency, and integration of performance data, thereby enabling more objective and measurable evaluations. With this system, leaders can provide accurate feedback, identify performance problems earlier, and ultimately enhance employee productivity and the overall performance of the Attorney General's Office. The research has successfully developed a web-based system with an interface that allows centralized management of user data, employee information, tasks, and performance evaluations. The implementation of this system is expected to significantly positively impact operational efficiency and support the achievement of organizational goals in more effective and efficient law enforcement.
Co-Authors Ahmad Akbar, Ahmad Akbar, Muhammad Caesar Amren S, Hairul Amril, M. Andi Ernawati Andysah Putera Utama Siahaan Atmaja, Niko Surya Barutu, Sipra Devina, Annisa Farta wijaya, Rian Hadi Prayitno Hafni Hafni Haralayya, Bhadrappa Herdianto Herdianto, Herdianto Heri Kurniawan, Heri Hermawan, Bagus Indrayani, Maida IQBAL , MUHAMMAD Iqbal Wiranata Siregar, Jimmy Iswandi Idris Jabar, Ami Abdul Khairul Khairul Khairul, Khairul Kurniawan, Fahmi Leni Marlina Liber Tommy Hutabarat Lubis, Darma Putra Marsya, Alviona Mentari, Risca Sri Muhammad Iqbal Muhammad Muttaqin Nasywa, Khairun Pane, Danang Putra Panjaitan, Albert Parhusip, Nelviony Permata, Dinda Suci Aliya Pranoto, Sugeng Pulungan, Ahmad Fakhrizal Ramatika, Desy Rian Farta Wijaya Rian Putra, Randi Rizaldy Khair Rizky Rinaldi Romani, Daniel D. Sahputra, Fajar Sari, Ayu Ofta SARIFUDIN Sebayang, Ayu Nuriana Septiadi, Fahri Siburian, Ramli S Simanjuntak, Yosei Ht Simorangkir, Elsya Sabrina Asmita Sirait, Donna Nurhaida Masdiana Sitorus, Mhd Arfan Sitorus, Zulham Situkkir, Meiarni Sri Wahyuni Sutiono, Sulis Syahputra, Afandi Syahrul R, Syahrul Tuti Andriani Usman Usman Wadly, Fachrid Wahyudi Sihombing, Ridho Wardani, Ivana Wijaya, Rian Farta Yahya, Susilawati Yusman, Yanti Zalukhu, Anzas Ibezato