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All Journal International Journal of Advances in Applied Sciences Seminar Nasional Aplikasi Teknologi Informasi (SNATI) Jurnal Informatika Prosiding Semnastek Sinkron : Jurnal dan Penelitian Teknik Informatika JURNAL MEDIA INFORMATIKA BUDIDARMA INTECOMS: Journal of Information Technology and Computer Science Zero : Jurnal Sains, Matematika, dan Terapan KOMIK (Konferensi Nasional Teknologi Informasi dan Komputer) JURIKOM (Jurnal Riset Komputer) JOURNAL OF SCIENCE AND SOCIAL RESEARCH Jurnal Teknik dan Informatika Jurnal Elektro dan Telkomunikasi Journal of Computer System and Informatics (JoSYC) Journal of Computer Networks, Architecture and High Performance Computing RESOLUSI : REKAYASA TEKNIK INFORMATIKA DAN INFORMASI Jurnal Teknologi Sistem Informasi dan Sistem Komputer TGD Jurnal SAINTIKOM (Jurnal Sains Manajemen Informatika dan Komputer) Jurnal Info Sains : Informatika dan Sains Bulletin of Information Technology (BIT) Jurnal Minfo Polgan (JMP) TECHSI - Jurnal Teknik Informatika Jurnal Sistem Informasi Triguna Dharma (JURSI TGD) Jurnal Informatika Teknologi dan Sains (Jinteks) Jurnal Nasional Teknologi Komputer Jurnal Pengabdian Masyarakat Gemilang (JPMG) Jurnal Hasil Pengabdian Masyarakat (JURIBMAS) Jurnal Pengabdian Masyarakat International Journal of Industrial Innovation and Mechanical Engineering International Journal of Computer Technology and Science Bulletin of Engineering Science, Technology and Industry Proceedings of The International Conference on Computer Science, Engineering, Social Sciences, and Multidisciplinary Studies
Andysah Putera Utama Siahaan
Universitas Pembangunan Panca Budi
Religion Agriculture, Biological Sciences & Forestry Astronomy Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Industrial & Manufacturing Engineering Library & Information Science Materials Science & Nanotechnology Mathematics Physics Social Sciences Transportation Other

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Perancangan Sistem Informasi Serah Terima Barang Masuk dan Keluar di BPBD Kota Medan Berbasis Web Hermawan, Bagus; Siahaan, Andysah Putera Utama; Nasution, Darmeli
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.v5i3.208

Abstract

Penelitian ini bertujuan untuk merancang dan membangun sistem informasi serah terima barang masuk dan keluar berbasis web pada Badan Penanggulangan Bencana Daerah (BPBD) Kota Medan. Sistem ini dikembangkan sebagai solusi terhadap proses manual yang selama ini digunakan, yang sering menimbulkan ketidakteraturan, keterlambatan, dan kesalahan dalam pencatatan. Metode pengumpulan data dilakukan melalui observasi, wawancara, dan studi pustaka. Hasil dari penelitian ini adalah sistem informasi yang dapat mencatat aktivitas serah terima barang secara digital, dengan fitur pengelolaan data barang, pencatatan transaksi masuk dan keluar, serta pelaporan. Implementasi sistem ini menunjukkan peningkatan efisiensi dan akurasi dalam pengelolaan barang, sekaligus mendukung transparansi dan akuntabilitas. Dengan demikian, sistem ini diharapkan dapat menunjang kinerja BPBD Kota Medan dalam penanganan logistik kebencanaan secara lebih efektif.
Hamming Weight-Based Simulation of Correlation Power Analysis for AES Key Extraction Siahaan, Andysah Putera Utama; Ehkan, Phaklen; Ullah, Insaf
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.v9i1.24294

Abstract

This study investigates the effectiveness of Correlation Power Analysis (CPA) using the Hamming Weight model to extract AES encryption keys in a fully software-simulated environment. By leveraging Python programming, we emulate power traces not from hardware devices but through Hamming Weight calculations derived from byte-level operations during AES encryption. Simulated plaintexts are randomly generated, and key hypotheses are evaluated using Pearson correlation between expected bit-switching activity and simulated traces. The method achieved approximately 50% accuracy with just 10 plaintexts and up to 85% accuracy when using over 1,000 simulated inputs. Correlation coefficients above 0.90 were consistently observed for most key bytes. While the simulation avoids the complexity of real-world noise and hardware interference, it also lacks authentic electrical characteristics. This highlights both the novelty and the limitation of a software-only CPA framework. The findings underline the vulnerability of AES to side-channel attacks and suggest countermeasures like masking to reduce risk.
Pengenalan dan Implementasi Sistem Informasi Profil Sekolah Berbasis Web sebagai Media Promosi dan Manajemen Data di PAUD Istiqomah Kota Binjai Siahaan, Andysah Putera Utama; Muham, Dinda Novita Sari
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.v4i1.366

Abstract

Kegiatan pengabdian kepada masyarakat ini bertujuan untuk memperkenalkan dan melatih penggunaan Sistem Informasi Profil PAUD berbasis web kepada guru dan admin di PAUD Istiqomah Kota Binjai. Sistem ini dirancang untuk mempermudah pengelolaan data profil sekolah, data peserta didik, dokumentasi kegiatan, serta komunikasi antara sekolah dan orang tua. Metode pelaksanaan dilakukan melalui sesi pelatihan langsung yang mencakup demonstrasi, praktik penggunaan, dan diskusi interaktif. Hasil kegiatan menunjukkan bahwa sistem ini diterima dengan baik oleh para pengguna karena memberikan kemudahan dan efisiensi dalam pengelolaan informasi sekolah. Diharapkan, dengan sistem ini, proses administrasi di lingkungan PAUD dapat berjalan lebih efektif dan transparan.
Analysis of Inpatient Data Using Cluster Analysis on Simulation Dataset Putera Utama Siahaan , Andysah; Azizah Harahap, Nur; Yuni Simanullang, Rahma; Khairunnisa; Wanny, Puspita; Utari
Bulletin of Information Technology (BIT) Vol 6 No 1: Maret 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bit.v6i1.1830

Abstract

This study aims to analyze inpatient data using the K-Means Clustering method on a simulated dataset. The dataset includes various patient-related attributes such as age, billing amount, length of stay, medical condition, and type of admission. Several preprocessing steps were applied, including date conversion, duration calculation, numerical normalization, and one-hot encoding for categorical attributes. The Elbow Method was used to determine the optimal number of clusters, and clustering quality was evaluated using both the Silhouette Score and Davies-Bouldin Index. The analysis results show that the patients can be segmented into three major clusters, each exhibiting distinct characteristics—for example, younger patients with short and low-cost stays, and elderly patients with prolonged and more expensive hospitalizations. The resulting Silhouette Score of 0.14 and Davies-Bouldin Index of 1.74 reflect a moderate clustering performance, yet the model remains informative and meaningful. These clusters provide actionable insights that hospitals can use to optimize their service strategies, improve resource allocation, and enhance operational efficiency. Moreover, the study illustrates the practical application of unsupervised learning techniques in healthcare settings, contributing to data-driven decision-making practices and offering a foundation for further research into patient segmentation.
Classification Of Pistachio Varieties Using Machine Learning Algorithms Siahaan, Andysah Putera Utama; Iqbal, Muhammad; Dika, Dika; Syahputri, Maulisa
Jurnal Minfo Polgan Vol. 14 No. 1 (2025): Artikel Penelitian
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/jmp.v14i1.15088

Abstract

The accurate classification of pistachio varieties plays a crucial role in ensuring quality control, enhancing traceability, and improving market segmentation in the agricultural sector. This study explores the application of various machine learning algorithms—including Decision Tree, Random Forest, XGBoost, Support Vector Classifier (SVC), k-Nearest Neighbors (KNN), and Logistic Regression—for the classification of pistachio types based on morphological features. A publicly available dataset containing measurements such as kernel length, shell width, and aspect ratio was used to train and evaluate the models. The results demonstrated that ensemble methods like XGBoost and Random Forest consistently outperformed other algorithms, achieving accuracy scores of 0.86 and 0.85, respectively, with high Area Under the Curve (AUC) values in the Receiver Operating Characteristic (ROC) analysis. Furthermore, hyperparameter tuning improved model performance across the board. These findings indicate the potential of machine learning as a reliable tool for automating pistachio variety classification and supporting decision-making in agricultural practices. Future research may involve real-time classification using image-based features and integration into precision agriculture systems.
EVALUASI TATA KELOLA IT DAN PREDIKSI KINERJA BISNIS BERBASIS DATA SCIENCE UNTUK OPTIMALISASI STRATEGI PADA MANAJEMEN HOTEL DAILY INN Irsyad, Muhammad; Siahaan, Andysah Putera Utama; Marlina, Leni
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.v8i3.3546

Abstract

Abstract: This study aims to evaluate the maturity level of Information Technology (IT) governance at Hotel Daily Inn using the COBIT 2019 framework and to predict hotel reservation trends through a data science approach using the Bayesian Structural Time Series (BSTS) algorithm. A mixed-method approach is applied, combining qualitative methods for IT governance evaluation and quantitative methods for reservation prediction. Data collection involves literature review, interviews with four main divisions (Front Office, Food & Beverage, Housekeeping, and Security), observations, and documentation of reservation data from 2018 to 2022. The evaluation results indicate that the IT governance maturity level is at the "Managed" stage, with several areas requiring improvement, particularly in process monitoring and control. Meanwhile, the BSTS algorithm effectively models reservation fluctuations by accounting for external factors such as national holidays and the COVID-19 pandemic. The model demonstrates good predictive performance, evaluated through MAPE, MAE, MSE, and RMSE metrics. The study concludes that strengthening IT governance and leveraging data-driven predictions can enhance business strategy effectiveness in the hospitality sector Keywords: COBIT 2019, BSTS, hotel reservation, IT governance, prediction, data science Abstrak: Penelitian ini bertujuan untuk mengevaluasi tingkat kematangan tata kelola teknologi informasi (TI) di Hotel Daily Inn menggunakan kerangka kerja COBIT 2019 serta memprediksi tren reservasi hotel dengan pendekatan data science menggunakan algoritma Bayesian Structural Time Series (BSTS). Metode campuran digunakan dalam penelitian ini, yaitu dengan pendekatan kualitatif untuk analisis tata kelola TI dan pendekatan kuantitatif untuk analisis prediktif reservasi hotel. Pengumpulan data dilakukan melalui studi literatur, wawancara dengan empat divisi utama (Front Office, Food & Beverage, Housekeeping, dan Security), observasi, serta dokumentasi data reservasi dari tahun 2018 hingga 2022. Hasil evaluasi menunjukkan bahwa tingkat kematangan tata kelola IT masih berada pada level "Managed" dengan beberapa area yang perlu diperkuat, khususnya dalam pemantauan dan pengendalian proses. Sementara itu, algoritma BSTS berhasil memodelkan fluktuasi reservasi dengan memperhitungkan faktor eksternal seperti hari libur nasional dan pandemi COVID-19. Model ini menunjukkan performa yang baik dengan nilai akurasi prediktif yang dievaluasi menggunakan metrik MAPE, MAE, MSE, dan RMSE. Penelitian ini menyimpulkan bahwa penguatan tata kelola IT dan pemanfaatan prediksi berbasis data dapat meningkatkan efektivitas strategi bisnis di sektor perhotelan.  Kata kunci: COBIT 2019, BSTS, reservasi hotel, tata kelola IT, prediksi, data science
ANALISIS ALGORITMA K-MEANS CLUSTERING DALAM IDENTIFIKASI TINGKAT RISIKO PENYAKIT BERDASARKAN DATA REKAM MEDIS PASIEN Aulia, Wina; Siahaan, Andysah Putera Utama; Marlina, Leni; Khairul, Khairul; Iqbal, Muhammad
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.v8i3.3551

Abstract

Abstract: This study aims to classify patients' health conditions based on six indicators: systolic blood pressure, diastolic blood pressure, fasting blood glucose, normal blood glucose, cholesterol level, and uric acid level using the K-Means Clustering method. The optimal number of clusters was determined using the Elbow Method and Silhouette Score, which resulted in five as the optimal number of clusters. The results show that the manual approach produces a more stable distribution that closely aligns with the clinical interpretation of cluster categories: Healthy (C1), Safe (C2), Alert (C3), Moderate (C4), and Severe (C5). Visualization was performed for each indicator through scatter plots and color mapping against normal value thresholds, aiding in the understanding of the distribution of patient conditions across clusters. The analysis reveals that even if a patient has one or more indicators within normal limits, they are not automatically classified into the Healthy or Safe clusters. Discrepancies in other indicators can place them in higher-risk clusters such as Alert, Moderate, or Severe. Therefore, this clustering approach provides a comprehensive view of health conditions based on a combination of features, rather than a single parameter. This research is useful in supporting early diagnosis and data-driven decision-making processes and can be integrated into health information systems for automatic risk classification of patient populations. Keywords: K-Means, Clustering, Health, Blood Pressure, Blood Glucose, Cholesterol, Uric Acid, Data Visualization Abstrak: Penelitian ini bertujuan untuk mengelompokkan kondisi kesehatan pasien berdasarkan enam indikator, yaitu tekanan darah sistolik, tekanan darah diastolik, kadar gula puasa, kadar gula normal, kadar kolesterol, dan kadar asam urat menggunakan metode K-Means Clustering. Penentuan jumlah klaster optimal dilakukan dengan metode Elbow dan Silhouette Score, yang menghasilkan lima klaster sebagai jumlah optimal. Hasil menunjukkan bahwa pendekatan manual menghasilkan distribusi yang lebih stabil dan mendekati pemaknaan klinis dari kategori klaster, yaitu: Sehat (C1), Aman (C2), Waspada (C3), Sedang (C4), dan Berat (C5). Visualisasi dilakukan untuk setiap indikator melalui scatter plot dan pemetaan warna terhadap batas nilai normal, yang membantu dalam memahami sebaran kondisi pasien pada masing-masing klaster. Hasil analisis menunjukkan bahwa meskipun seorang pasien memiliki satu atau lebih indikator dalam batas normal, tidak secara otomatis tergolong dalam klaster Sehat atau Aman. Ketidaksesuaian pada indikator lainnya dapat menempatkan pasien ke dalam klaster yang lebih tinggi risikonya, seperti Waspada, Sedang, atau Berat. Oleh karena itu, pendekatan clustering ini memberikan gambaran menyeluruh terhadap kondisi kesehatan berdasarkan kombinasi fitur, bukan hanya pada satu parameter. Penelitian ini bermanfaat untuk mendukung proses diagnosis awal dan pengambilan keputusan berbasis data, serta dapat diintegrasikan dalam sistem informasi kesehatan untuk klasifikasi risiko populasi pasien secara otomatis.Kata kunci: K-Means, Clustering, Kesehatan, Tekanan Darah, Gula Darah, Kolesterol, Asam Urat, Visualisasi Data
SISTEM INFORMASI PEMBAYARAN UANG SEKOLAH DI PAUD MEKAR AMAN DAMAI BERBASIS WEB Sitepu, Nabila Putri Br; Siahaan, Andysah Putera Utama; Novelan, Muhammad Syahputra
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.v8i3.3548

Abstract

Abstract: The administration of school fee payments at PAUD Mekar Aman Damai was previously conducted manually, leading to frequent recording errors, delays in reporting, and difficulties in tracking student payment histories. Therefore, this study aims to design and develop a web-based school fee payment information system to facilitate a more efficient and structured recording and management process. The system was developed using HTML, PHP, and CSS, with MySQL as the database to store payment records, student data, teacher data, and other relevant information. System testing was conducted using the Black Box method, focusing on evaluating system functionality without analyzing the underlying code. The test results indicate that all core features, including payment recording, student and teacher data management, and system administration, function properly without significant technical issues. The implementation of this information system has made the school fee payment process more structured, accurate, and easily accessible to administrators. However, the system has certain limitations, such as the absence of access for students and parents to view payment history and the lack of an automatic notification feature for payment reminders. Therefore, further development is recommended to incorporate these features to enhance system efficiency and transparency. Keywords: Information System, School Fee Payment, PAUD Mekar Aman Damai, Web, MySQL, Black Box Abstrak: Administrasi pembayaran uang sekolah di PAUD Mekar Aman Damai sebelumnya dilakukan secara manual, sehingga sering terjadi kesalahan pencatatan, keterlambatan laporan, dan kesulitan dalam menelusuri riwayat pembayaran siswa. Oleh karena itu, penelitian ini bertujuan untuk merancang dan membangun sistem informasi pembayaran uang sekolah berbasis web yang dapat membantu proses pencatatan dan pengelolaan pembayaran secara lebih efisien dan terstruktur. Sistem ini dikembangkan menggunakan bahasa pemrograman HTML, PHP, dan CSS, serta memanfaatkan MySQL sebagai database untuk menyimpan data pembayaran, data siswa, data guru, dan informasi lainnya. Pengujian sistem dilakukan menggunakan metode Black Box, yang menitikberatkan pada pengujian fungsionalitas sistem tanpa memperhatikan kode program. Hasil pengujian menunjukkan bahwa seluruh fitur utama sistem, termasuk pencatatan pembayaran, pengelolaan data siswa dan guru, serta administrasi sistem, telah berjalan dengan baik tanpa mengalami kendala teknis yang signifikan. Dengan diterapkannya sistem informasi ini, proses pembayaran uang sekolah menjadi lebih terstruktur, akurat, dan mudah diakses oleh admin. Sistem ini masih memiliki beberapa keterbatasan, seperti belum tersedianya akses bagi siswa dan orang tua untuk melihat riwayat pembayaran serta fitur notifikasi otomatis untuk pengingat jatuh tempo pembayaran. Oleh karena itu, pengembangan lebih lanjut disarankan untuk menambahkan fitur tersebut guna meningkatkan efektivitas dan transparansi sistem. Kata kunci: Sistem Informasi, Pembayaran Uang Sekolah, PAUD Mekar Aman Damai, Web, MySQL, Black Box
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.
ANALYSIS OF THE LEVEL OF EFFECTIVENESS OF THE INDEPENDENT CAMPUS MERDEKA LEARNING PROGRAM (MBKM) USING METHODSPREFERENCE SELECTION INDEX (PSI) AND VIKOR METHOD Kiki Artika; Muhammad Iqbal; Zulham Sitorus; Andysah Putera Utama Siahaan; Rian Farta Wijaya
Bulletin of Engineering Science, Technology and Industry Vol. 2 No. 3 (2024): September
Publisher : PT. Radja Intercontinental Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59733/besti.v2i3.61

Abstract

This research aims to analyze the level of effectiveness of the Independent Campus Learning Program (MBKM) using the Preference Selection Index (PSI) Method and VIKOR Method. The MBKM program is an initiative of the Ministry of Education and Culture of the Republic of Indonesia which aims to provide more flexibility and learning opportunities for students through various off-campus activities. This research was conducted to measure the extent to which the program succeeded in achieving its goals. The PSI method is used to determine preferences for various aspects of the program based on assessments from students and academic staff, while the VIKOR method is used to identify the best compromise solution that can maximize stakeholder satisfaction. Analysis was carried out to assess the effectiveness of the program based on several criteria, including the quality of the learning experience, relevance to the world of work, and contribution to student skills development. This research suggests that to further increase the effectiveness of the MBKM Program, there needs to be an emphasis on developing a curriculum that is more responsive to industry needs and improving supporting facilities for students. The implications of the results of this research are important for policy makers in designing educational strategies that are more adaptive and oriented to labor market needs.
Co-Authors A. Khalid, Noor Aldeen Afandi Syahputra Alex Siregar Alfiandi, Alfiandi Andreas Ghanneson Nainggolan Anwar, Dede Utari Anzas, Anzas Ibezato Zalukhu Aprijal, Rendi Arahman Harahap Arif Rahman Asyifa, Nathania Aulia, Popi Aulia, Wina Ayu, Ayu Ofta Sari Azizah Harahap, Nur Bambang, Bambang Sugito beckham pratama, arya Binti Saari, Erni Marlina Chairul Indra Angkat Datin, Maha Valne Dewi Sartika Didi Riswan Dika, Dika Dina Marsauli Sibarani Efendi, Syahril Ehkan, Phaklen Eko Hariyanto Eko Hariyanto EKO WAHYUDI Farta wijaya, Rian Fawaz, Muhammad Ayyas Fawaz, Muhammad Ayyasi Hafizhah Sufina Azzahra Hasibuan, Peronika Br Hassan, Moustafa Hussein Ali Hendra Harnanda Hermansyah Hermansyah Hermawan, Bagus Ibrahim Ibrahim Imam Solihin Iqbal Wiranata Siregar Iqbal Wiranata Siregar, Jimmy Izhari, Fahmi Juliyandri Saragih Kariyani Khairil Putra Khairul Khairul , Khairul Khairul Khairul, Khairul Khairunnisa Kiki Artika Leni Marlina Leni Marlina Leni Marlina Manurung, Monica M Melva Sari Panjaitan Mesran, Mesran Muham, Dinda Novita Sari Muhammad Akbar Syahbana Pane Muhammad Indra Muhammad Iqbal Muhammad Iqbal Muhammad Irsyad Muhammad Syahputra Novelan Muhammad Wahyudi Muhammad Zarlis Nasution, Darmeli Natalia Nahampun Nurwijayanti Rabe, Siska Mayasari Ramatika, Desy Rambe, Rezkinah Rendi Aprijal Rian Farta Wijaya Rizky Rinaldi Simamora, Siska Simorangkir, Elsya Sabrina Asmita Sinyo Andika Nasution, Ahmad Siregar, Iqbal Wiranata Sitepu, Nabila Putri Br Sitorus, Zulham Solihin, Imam Sony Putra Sri Wahyuni Suheri Supiyandi Supiyandi Swandi Dedi Arnold Pardede Syafran Panggabean, Edwin Syahputri, Maulisa Syahri, Rahma Syamsiar, Syamsiar Syamsul Arifin Trisnani, Anis A Ullah, Insaf Utari Wanny, Puspita Wiko Pratama Wina Aulia Wulan Ramadhani Yuni Simanullang, Rahma Zuhri Ramadhan Zulham, Zulham Sitorus