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All Journal IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Seminar Nasional Aplikasi Teknologi Informasi (SNATI) Jupiter TELKOMNIKA (Telecommunication Computing Electronics and Control) Jurnal IPTEK Jurnal Informatika Upgris Informatika Mulawarman: Jurnal Ilmiah Ilmu Komputer Sinkron : Jurnal dan Penelitian Teknik Informatika Jurnal Informatika IJCIT (Indonesian Journal on Computer and Information Technology) Jurnal CoreIT Abdimas Talenta : Jurnal Pengabdian Kepada Masyarakat Indonesian Journal of Artificial Intelligence and Data Mining JURNAL TEKNOLOGI DAN ILMU KOMPUTER PRIMA (JUTIKOMP) JPPM (Jurnal Pengabdian dan Pemberdayaan Masyarakat) AMALIAH: JURNAL PENGABDIAN KEPADA MASYARAKAT Jurnal Teknik dan Informatika Jurnal Kridatama Sains dan Teknologi Jurnal Manajemen Informatika dan Sistem Informasi Jurnal Teknologi Informasi, Komputer, dan Aplikasinya (JTIKA ) Jurnal Sains dan Teknologi JUSTINDO (Jurnal Sistem dan Teknologi Informasi Indonesia) TRIDARMA: Pengabdian Kepada Masyarakat (PkM) JATI (Jurnal Mahasiswa Teknik Informatika) INFOKUM Jurnal Sistem Komputer dan Informatika (JSON) Jurnal SAINTIKOM (Jurnal Sains Manajemen Informatika dan Komputer) Bulletin of Information Technology (BIT) PROSISKO : Jurnal Pengembangan Riset dan observasi Rekayasa Sistem Komputer Journal of Artificial Intelligence and Engineering Applications (JAIEA) Jurnal Pendidikan Matematika Malikussaleh Blend Sains Jurnal Teknik Jurnal Teknologi Informasi INPAFI (Inovasi Pembelajaran Fisika) Innovative: Journal Of Social Science Research JS (Jurnal Sekolah) Amal Ilmiah: Jurnal Pengabdian Kepada Masyarakat Jurnal Sistem Informasi dan Ilmu Komputer Journal of Informatics and Data Science (J-IDS) Jurnal Pendidikan IPA Indonesia SISFOTENIKA JUSTINDO (Jurnal Sistem dan Teknologi Informasi Indonesia)
Kana Saputra S
Program Studi Ilmu Komputer, FMIPA, Universitas Negeri Medan
Agriculture, Biological Sciences & Forestry Arts Humanities Automotive Engineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Mechanical Engineering Physics Public Health Social Sciences Transportation Other

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Melody Transcription from Monophony Audio with Fast Fourier Transform Simanjorang, Rio Givent A; Kana Saputra S; Said Iskandar Al Idrus; Zulfahmi Indra
Journal of Informatics and Data Science Vol. 3 No. 2 (2024): November 2024
Publisher : Universitas Negeri Medan

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

Abstract

Music has been an inseparable part of human life since ancient times. One form of music that is often studied is monophonic music, which consists of a single note played at a time. In the digital era, melody transcription has become an important aspect of music processing, allowing sound to be converted into musical notation. This study focuses on melody transcription from monophonic sound recordings using the Fast Fourier Transform (FFT) method. The research aims to analyze the accuracy of FFT in extracting frequency components from monophonic signals and converting them into musical notation. The research methodology involves collecting monophonic sound recordings from piano and guitar, preprocessing the audio to remove noise and normalize volume, applying FFT to extract frequency features, and mapping these frequencies into musical notation. The evaluation process is conducted using Dynamic Time Warping (DTW) and a confusion matrix to measure accuracy, precision, recall, and F1-score. The results show that the FFT-based transcription system achieves an accuracy rate of 99.24% for piano and 98.86% for guitar. The study also highlights the impact of noise and audio quality on transcription accuracy, as well as the limitations of FFT in detecting closely spaced frequencies. Despite these limitations, FFT proves to be an efficient method for melody transcription in simple monophonic music. Future research could explore hybrid approaches combining FFT with other pitch detection algorithms to improve transcription accuracy.
Deteksi Kemacetan dengan Deep Learning YOLOv4 dan Euclidean Distance Tracker pada Jalan Raya di Kota Medan Manurung, Jeremia; Azizi, Nur; Anastasya, Disty; Valentino, Nicholas; Sanjaya, Aditia; Saputra, Kana
JUSTINDO (Jurnal Sistem dan Teknologi Informasi Indonesia) Vol. 8 No. 1 (2023): JUSTINDO
Publisher : Universitas Muhammadiyah Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32528/justindo.v8i1.220

Abstract

Kemacetan lalu lintas di Kota Medan menyebabkan waktu yang hilang sebesar 35,6 menit per hari untuk sepeda motor dan 48,5 menit per hari untuk mobil. Total biaya kemacetan di Kota Medan mencapai Rp. 22.535.355.867/tahun.  Dengan adanya pendeteksian kemacetan secara realtime maka diharapkan dapat mengurangi kemacetan lalu lintas apabila diintegrasikan dengan sistem pengatur lalu lintas. Penelitian ini menerapkan metode Deep Learning YOLO versi 4 Euclidean Distance Tracker. YOLOv4 digunakan untuk mendeteksi objek seperti mobil, motor, bus, dan becak. Euclidean Distance Tracker digunakan untuk melacak perpindahan objek yang telah dideteksi oleh YOLOv4. Adapun data yang digunakan adalah data lalu lintas berupa video dari CCTV yang disediakan oleh Pemerintah Kota Medan, Sumatera Utara. Dari hasil penelitian ini dapat diambil kesimpulan YOLOv4 dapat digunakan untuk mendeteksi kendaraan yang memiliki jarak kendaraan yang cukup antara kendaraan yang satu dengan kendaraan yang lainnya (Akurasi 61,3%). Dengan mengintegrasikan Euclidean Distance Tracker, pendeteksi kemacetan memiliki hasil akurasi maksimum (Akurasi 100%) pada sample frame yang diuji.
Face Recognition Motorcycle Rider Registration System for Rider Data Management Saputra S, Kana; Taufik, Insan; Ramadhani, Irham; Sasalia S, Putri; Syawali, Yusfi; Yusuf, Dede; Nadilla Putri, Rezkya; Latifah Hasibuan, Najwa; Hafiz Harahap, Fauzan
Bulletin of Information Technology (BIT) Vol 6 No 3: September 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bit.v6i3.2157

Abstract

This research aims to develop a motorcycle rider registration system using facial recognition technology that can improve the efficiency of rider data management. This system is designed to identify and authenticate riders with high accuracy, thereby simplifying the registration and monitoring process. The methods used in this research include collecting rider facial data through cameras, image processing for feature extraction, and implementing a facial recognition algorithm. Testing was conducted in several locations with varying lighting conditions and viewing angles to ensure the system's robustness. The results show that the developed system is capable of achieving facial recognition accuracy of up to 95%. In addition, this system provides an intuitive user interface to facilitate the registration and data management process. With the implementation of this system, it is expected to reduce the time and costs required in managing motorcycle rider data, as well as improve safety and comfort while riding.
Klasifikasi Akun Buzzer Menggunakan Algoritma K-Nearest Neighbor pada Tagar #STYTanpaDiasporaNol di Media Sosial X Lubis, Afiq Alghazali; Idrus, Said Iskandar Al; Indra, Zulfahmi; S, Kana Saputra; Chairunisah, Chairunisah
Blend Sains Jurnal Teknik Vol. 4 No. 2 (2025): Edisi Oktober
Publisher : Ilmu Bersama Center

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56211/blendsains.v4i2.1093

Abstract

Peningkatan pengguna media sosial X pada tahun 2024 sebesar 639 ribu mengakibatkan penyebaran informasi yang sangat masif, menjadikan buzzer berperan dalam mengarahkan opini publik dan memicu konflik sosial, seperti yang terlihat pada tren #STYTanpaDiasporaNol usai gugurnya tim nasional Indonesia di ASEAN Championship 2024. Penelitian ini bertujuan untuk membangun model machine learning dalam klasifikasi akun buzzer menggunakan algoritma K-Nearest Neighbor (KNN). Data yang akan digunakan dalam penelitian ini berasal dari kumpulan tweet dari sosial media X dalam tagar #STYTanpaDiasporaNol. Penelitian ini memiliki prosedur penelitian, di antaranya pengumpulan data, pra-pemrosesan data (cleaning, labelling, feature engineering dan standardization), splitting data, pemrosesan data, dan evaluasi model. Hasil penelitian ini mendapatkan model dengan akurasi terbaik yaitu varian model perbandingan split data 80:20 dan K = 5 dengan nilai akurasi sebesar 89% serta nilai precision dan recall sebesar 89% lalu nilai F1-score sebesar 88%. Model sangat baik dalam memprediksi kelas mayoritas namun kesulitan dalam memprediksi kelas minoritas. Kemudian dilakukan eksperimen resampling data dengan tujuan membuat keseimbangan data. Hasil didapatkan bahwa varian pada split data 70:30 dengan K = 9 diperoleh akurasi sebesar 91% dengan precision, recall dan accuracy juga sebesar 91%. Model eksperimen ini cukup baik mendeteksi kelas mayoritas maupun kelas minoritas.
Implementation of the One-Stop Subdistrict Application (ASAKU) for Realizing Good Governance and Increasing Welfare Communities in Sidikalang Village Manik, Fuzy Yustika; Hutagalung, Arif Qaedi; Saputra S, Kana
ABDIMAS TALENTA: Jurnal Pengabdian Kepada Masyarakat Vol. 8 No. 2 (2023): ABDIMAS TALENTA: Jurnal Pengabdian Kepada Masyarakat
Publisher : Talenta Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32734/abdimastalenta.v8i2.13858

Abstract

Local government agencies at the sub-district level are also instructed to optimize the use of ICT in e-government development. Local government at the Kelurahan level is the basic foundation of public services and is the gateway for administrative processing up to the higher government levels. So local government at the sub-district level must continually improve satisfactory and good public services. This service is a community need that must be met. The still manual service system in sub-districts is the main problem that leads to community dissatisfaction and discomfort. So the innovation solution offered is to develop an integrated system (one-stop application). One application includes all the necessary systems and can be run online. The urgency of using information technology for the one-stop village application (ASAKU) at the Sidikalang village office, not only has implications for the field of communication but also influences every decision-making through automation and speed in data processing which ultimately affects services) District Office. The ASAKU application has several main features: e-government, e-archives, and e-commerce. These digital e-government services help improve government performance. With the implemented e-government, the Sidikalang sub-district wants to provide services without the intervention of public institution employees and support good governance. Through e-ASIP, all data and documents can be managed well, safely, and protected from loss. In addition, ASAKU is also a forum for the community to market agricultural products and products from MSMEs as well as products from social institutions such as youth organizations and PKK. Combining service providers (kelurahan) and the community with the proper adaptation of technology can create effectiveness and efficiency in managing areas at the kelurahan level. The main objective of the activity is the implementation and application of ASAKU so that local government institutions at the sub-district level can provide better (effective and efficient) public services by providing convenience for the community so that they can realize good governance. With this service activity, the Sidikalang sub-district can provide more optimal services. The public can submit letters in the Sidikalang sub-district using the ASAKU application which can be accessed anywhere and anytime. So that in the end it can realize good governance and improve the community's welfare in the Sidikalang sub-district.
Sistem Pakar Diagnosa Penyakit Ginjal Menggunakan Metode Dempster Shafer Di Rsud Pirngadi Medan Parapak, R Putri Angela; Kana Saputra S; Nasution, Hamidah; Indra, Zulfahmi; Taufik, Insan
Innovative: Journal Of Social Science Research Vol. 4 No. 5 (2024): Innovative: Journal Of Social Science Research
Publisher : Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/innovative.v4i5.15895

Abstract

Dalam era modern yang dipenuhi dengan kemajuan teknologi komputerisasi, perkembangan teknologi informasi terjadi dengan kecepatan yang luar biasa dan memiliki dampak yang signifikan dalam berbagai aspek kehidupan manusia. Dalam konteks ini, penting untuk diakui bahwa penyakit ginjal merupakan salah satu masalah kesehatan yang perlu mendapatkan perhatian serius dari masyarakat. Sayangnya, penyakit ini seringkali sulit dideteksi secara dini dan dapat mengancam nyawa seseorang jika tidak ditangani dengan tepat. Dalam situasi di mana kesadaran akan kesehatan seringkali rendah, terdapat kebutuhan yang mendesak untuk mengembangkan solusi yang dapat membantu meningkatkan deteksi dini dan diagnosis penyakit ginjal. Salah satu solusi yang inovatif adalah dengan memanfaatkan teknologi informasi dalam bentuk aplikasi sistem pakar. Melalui pendekatan ini, penulis merancang sebuah aplikasi sistem pakar yang bertujuan untuk mendeteksi penyakit ginjal akut dan kronis. Aplikasi ini dibangun dengan menggunakan metode Dempster-Shafer, sebuah teknik yang mampu menggabungkan data dari berbagai sumber untuk menghasilkan estimasi yang lebih akurat. Dengan menggunakan bahasa pemrograman PHP, HTML, dan SQL Server, aplikasi ini mampu mengumpulkan gejala yang dilaporkan oleh pengguna dan menganalisisnya untuk memberikan diagnosis yang lebih tepat. Tidak hanya memberikan diagnosis, aplikasi ini juga memberikan informasi tentang tingkat kepercayaan terhadap kemungkinan penyakit ginjal yang diderita oleh pengguna. Dengan memberikan informasi yang komprehensif dan akurat, aplikasi ini diharapkan dapat membantu pengguna dalam mengidentifikasi penyakit ginjal yang mungkin dialami dan memberikan informasi yang berguna untuk langkah-langkah pengobatan selanjutnya. Dengan demikian, aplikasi sistem pakar ini tidak hanya bertujuan untuk meningkatkan kesadaran akan pentingnya deteksi dini terhadap penyakit ginjal, tetapi juga untuk memberikan solusi yang konkret dan terukur dalam menangani masalah kesehatan ini.
Implementasi Algoritma Brute Force Dalam Pencocokan String Pada Aplikasi Pencarian Musik Saputra S, Kana; Al-Areef, M. Hafizh; Fadhilah, Nazifatul; Rifqi Naufal, Muhammad; Rifqi Maulana, Muhammad; Fajar Harahap, Muhammad
Jurnal Informatika UPGRIS Vol 7, No 2: Desember 2021
Publisher : Universitas PGRI Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26877/jiu.v7i2.8464

Abstract

Musik adalah hal yang sering kita jumpai dalam kehidupan sehari-hari. Banyak kegiatan sehari-hari kita yang ikut ditemani dengan musik. Aplikasi musik berbasis web ini dapat membantu pengguna dalam pencarian informasi mengenai suatu musik, seperti judul, album, artis, dan liriknya. Sebelumnya pencarian lirik lagu berdasarkan judul lagu, penyanyi adalah hal yang sulit. Penelitian ini bertujuan untuk membuat aplikasi pencarian lirik lagu dengan menerapkan algoritma brute force sebagai fitur pencari. Pengguna hanya memasukkan judul lagu atau lirik lagu atau nama penyanyi untuk melakukan pencarian. Algoritma brute force cocok digunakan dalam kasus pencocokan string dalam pencarian informasi mengenai musik yang dilihat dari sisi efektifitas dan efesiensi waktu.
Integration of Analytical Chemistry Flipbooks Based on Project-Based Learning in Improving Critical Thinking Skills and Scientific Literacy to Support SDG-4 Sari, Sri Adelila; Dewi, Ratna Sari; Saputra, Kana; Kembaren, Agus; Hasibuan, Hanisah; Talib, Corrienna Abdul
Jurnal Pendidikan IPA Indonesia Vol. 14 No. 1 (2025): March 2025
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/jpii.v14i1.21038

Abstract

This study was aimed at assessing the effectiveness of Project-Based Learning (PjBL)-based analytical chemistry flipbooks in improving students’ critical thinking skills and scientific literacy, and linking the results to the achievement of Sustainable Development Goals (SDG-4), namely quality education. This study used a quantitative approach with a quasi-experimental design, involving two groups: an experimental group (n = 250) using PjBL-based flipbooks, and a control group (n = 250) using conventional textbooks. The projects in PjBL were designed to challenge students to apply critical thinking skills in solving real problems in analytical chemistry. Scientific literacy was measured based on students’ ability to understand, evaluate, and apply chemical concepts in the context of the project. Critical thinking skills and scientific literacy tests were used to measure learning outcomes before and after the intervention. The instrument in this study was a test of critical thinking skills and scientific literacy. Statistical tests showed that the data were normally distributed (significance value 0.216), homogeneous variance (0.074), and significant differences between the experimental and control groups (t = 0.038, p < 0.05). The increase in n-gain in the experimental group reached 0.9 (high category), compared to 0.63 (moderate category) in the control group. This study concluded that Project-Based Learning-based flipbooks were significantly more effective than conventional textbooks in improving students’ critical thinking skills and scientific literacy. The results of this study confirmed the superiority of PjBL-based flipbooks in significantly improving students’ critical thinking skills and scientific literacy compared to conventional textbooks. Statistical data support (normal distribution, homogeneous variance, significant differences between groups, and high n-gain in the experimental group) encourages the adoption of PjBL-based flipbooks as an effective learning strategy to achieve quality education according to SDG-4.
Pengembangan Aplikasi Perkuliahan Interaktif dengan Fitur Pemilihan Posisi Duduk Mahasiswa untuk Meningkatkan Interaksi Insan Taufik; Kana Saputra S; Fevi Rahmawati Suwanto
Jurnal Sistem Komputer dan Informatika (JSON) Vol. 7 No. 2 (2025): Desember 2025
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/json.v7i2.9308

Abstract

Penelitian ini mengembangkan sistem manajemen pembelajaran digital dengan fitur pemilihan posisi duduk mahasiswa secara manual berbasis antarmuka visual untuk meningkatkan efektivitas interaksi dosen-mahasiswa dalam lingkungan hybrid. Sistem yang dikembangkan mengintegrasikan tiga peran utama (admin, dosen, dan mahasiswa) dengan fitur unggulan pemantauan posisi duduk mahasiswa melalui grid interaktif. Metode pengembangan menggunakan pendekatan Agile melalui tahapan analisis kebutuhan, perancangan sistem, implementasi, dan pengujian. Hasil penelitian menunjukkan bahwa sistem berhasil dibangun dengan arsitektur multi-role yang mencakup modul manajemen kursus, sesi interaktif, presensi real-time, dan dashboard pemantauan. Pengujian fungsional dengan 44 responden mahasiswa menunjukkan semua modul berjalan dengan baik, sementara kuesioner kepuasan pengguna menghasilkan skor rata-rata 4,6 (dari skala 5). Sistem ini memberikan solusi inovatif untuk menciptakan lingkungan pembelajaran yang lebih personal dan interaktif, khususnya dalam konteks kelas besar perguruan tinggi.
Classification of Purple Passion Fruit Ripeness Levels Using Convolutional Neural Network (CNN) Siregar, Mochammad Gani Alfa Alkhoiri; Said Iskandar Al Idrus; Hermawan Syahputra; Insan Taufik; Kana Saputra S
Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 5 No. 2 (2026): February 2026
Publisher : Yayasan Kita Menulis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59934/jaiea.v5i2.1787

Abstract

Passiflora edulis Sims (purple passion fruit) is a fruit that offers numerous health benefits and possesses high economic value. However, the manual assessment of ripeness by traders tends to be subjective and inconsistent, leading to post-harvest losses of up to 50%. This study developed a classification model for determining the ripeness level of purple passion fruit using a Convolutional Neural Network (CNN) and implemented it in a web-based application. The CNN model was designed to classify four ripeness stages (unripe, half-ripe, ripe, and rotten) with the addition of a non-passion-fruit class to enhance the system’s robustness. The dataset consisted of 2,000 images divided into five classes: four ripeness levels of purple passion fruit (unripe, half-ripe, ripe, and rotten) and one non-passion-fruit class as a comparator. All images were in JPG and PNG formats. The CNN architecture comprised four convolutional layers with 16, 32, 64, and 128 filters, respectively. Evaluation of various data-splitting ratios (80:20, 70:30, 60:40) and learning rates (0.001, 0.0001, 0.01) showed that the optimal configuration was achieved at a ratio of 80:20 with a learning rate of 0.001, resulting in a training accuracy of 96.72% and a testing accuracy of 95.76%, with a loss value of 0.1811. Validation using 5-Fold Cross Validation produced an average accuracy of 95.40%. The model was integrated into a web application developed using Flask and JavaScript, deployed on the PythonAnywhere cloud platform, enabling users to upload images and automatically obtain ripeness predictions to assist traders in sorting fruits more quickly and accurately.
Co-Authors Adidtya Perdana, Adidtya Advis Ambrosius Sitohang, Yuda Afif Nashi Ulwan, Mhd Agus Buono Agus Kembaren Agus Waruwu, Stefen Al-Areef, M. Hafizh Alfattah Atalarais Alfin, Muhammad Amanda Fitria Amelia Br Siregar, Ririn Ananda Hafika, Rizky anastasya, disty Anggi Tasari Anti Nada Nafisa Arnita Azizi, Nur Azqal Azkia Bambang Suseno Budi Akbar, Muhammad Bush Henrydunan, John Chairunisah Chairunisah, Chairunisah citra, Citra Dewan Dinata Tarigan DIdi Febrian Dinda Farahdilla Dharma Dinda Kartika Eka Nainggolan, Rinay Erika Nia Devina Br Purba Fachry Abda El Rahman Fadhilah, Nazifatul Fadhillah, Mhd. Fahri Aulia Alfarisi Harahap Fajar Harahap, Muhammad Fajar Muharram Fajar Muharram Farhan Ramadhan, Haikal Fevi Rahmawati Suwanto Fitrahuda Aulia Fitri Aulia Fuzy Yustika Manik Fuzy Yustika Manik, Fuzy Yustika Habibi, Rizki Hafiz Harahap, Fauzan Hafiz, Alvin Haikal Al Majid, Muhammad Halimatun Nisa Harahap, Muhammad Abarorya Hasibuan, Hanisah Hermawan Syahputra Hutagalung, Arif qaedi Ida Ayu Putu Sri Widnyani Ihsan Zulfahmi Ilyasyah Drilanang, Mhd Imam Ahmad Impana Manik, Kristin Indriani, Dechy Deswita Insan Taufik Irham Ramadhani Irya Shakila Syukron, Ananda Jasmidi Jasmidi Jeremia Manurung Josafat Simanjutak, Todo Jufita Sari Sitorus Karimuddin Hakim Hasibuan Kartika, Dinda Khonofi, Khoidir Khusnul Arifin Khusnul Arifin Kurniawan, Catur Latifah Hasibuan, Najwa Lidia Pebrianti Lubis, Afiq Alghazali Luge, Miclyael Maharani, Raysa Malik Fajri, Maulana MANSUR AS Manurung, Jeremia Mhd Hidayat Mhd Hidayat Misgiya, Misgiya Mochammad Iswan Mochammad Iswan Perangin-Angin Mochammad Iswan Perangin-Angin Mohammed Hafizh Al-Areef Muhammad Affandes Muhammad Ardiansyah Muhammad Badzlan Darari Muhammad Usman Muslim Sinaga, Rizal Nadilla Putri, Rezkya Nasution, Hamidah . Neltriana Syafira Niska, Debi Yandra Nugraha, Zidan Indra Nur Hairiyah Harahap Nurul Adawiyah Putri Pane, Yeremia Yosefan Parapak, R Putri Angela Pinem, Josua Pittauli Ambarita Pizaini Pizaini Prana Walidin, Adamsyach Pratama, Ega Purwanto Putri, Alsya Adelia Putri, Rezkya Nadilla Raffi Akbar Tjg, Muhammad Raiyan Fairozi Ramadhan Manik, Albert Ramadhan, Sahrul Ramadhan, Taufiq Ramadhani, S.Pd., M.Pd, Irham Ratna Sari Dewi Reo Rizki Ananda Rifqi Maulana, Muhammad Rifqi Naufal, Muhammad Rizki Alfahri , Muhammad Ronaldo Mardianson Sinaga Rosyid Fauzan, Muhammad Ryan Ananda Nolly Said . Iskandar Sanjaya, Aditia Sanusi Sasalia S, Putri Setiawan, Abi Simanjorang, Rio Givent A Siregar, Angginy Akhirunnisa Siregar, Mochammad Gani Alfa Alkhoiri Siringoringo, Andi Roi Berlian Siti Rahmah Sitompul, Sigun Putra Hasian Sri Adelila Sari Sri Dewi Sri Wahyuni Suci Frisnoiry Syahri, Alfin Syarifuddin Syarifuddin Syawali, Yusfi Talib, Corrienna Abdul Tartiyoso, Seget Tiur Malasari Siregar, Tiur Malasari Tuti Hardianti Ulfa, Nadya Valentino, Nicholas Wahyu Tri Atmojo Wahyudi, Rizky Wisnu Ananta Kusuma Yanthy Leonita Perdana Simanjuntak Yazid Noor, Muhammad Yoakim Telaumbanua, Louders yola, beby Yulita Molliq Rangkuti Yulita Molliq Rangkuti Zaharani, Firna Zai, Samuel Anaya Putra Zulfahmi Indra, Zulfahmi Zulfahrizan, Atta