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All Journal International Journal of Electrical and Computer Engineering Jurnal Edukasi Elektro Jurnal Teknologi Informasi dan Ilmu Komputer KLIK (Kumpulan jurnaL Ilmu Komputer) (e-Journal) JOIN (Jurnal Online Informatika) Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Jurnal CoreIT Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control BAREKENG: Jurnal Ilmu Matematika dan Terapan PRODUCTUM : Jurnal Desain Produk (Pengetahuan dan Perancangan Produk) J-Dinamika: Jurnal Pengabdian Kepada Masyarakat Jurnal Teknologi Informasi dan Pendidikan Journal of Applied Engineering and Technological Science (JAETS) Indonesian Journal of Electrical Engineering and Computer Science Community Development Journal: Jurnal Pengabdian Masyarakat Economics and Digital Business Review NUCLEUS: Jurnal Sains dan Teknologi Jurnal ComunitA Servizio Jurnal Pengabdian Masyarakat Akademisi Economic Reviews Journal JatiRenov: Jurnal Aplikasi Teknologi Rekayasa dan Inovasi JSSIT: Jurnal Sains dan Sains Terapan International Journal of Computing Science and Applied Mathematics-IJCSAM
Tegar Arifin Prasetyo
Information Technology, Faculty Of Vocational Studies, Institut Teknologi Del
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Pengembangan Aplikasi Rekomendasi Berbasis Mobile Pada Destinasi Wisata Di Sekitar Danau Toba Menggunakan Metode Moora Dengan Pembobotan ROC Chandra, Rudy; Pasaribu, Monalisa; Arifin Prasetyo, Tegar; Henry Agus Panjaitan, Goklas; Emy Sonia Sinambela; Suandika Napitupulu; Anastasia Marsada Uli Simamora
Jurnal Teknologi Informasi dan Ilmu Komputer Vol 12 No 4: Agustus 2025
Publisher : Fakultas Ilmu Komputer, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25126/jtiik.124

Abstract

Danau Toba merupakan destinasi wisata unggulan di Sumatera Utara yang memiliki potensi wisata alam, wisata buatan, dan budaya Batak. Namun, wisatawan seringkali membutuhkan rekomendasi wisata yang sesuai dengan kriteria keinginan mereka. Untuk mengatasi masalah ini, aplikasi rekomendasi destinasi wisata di sekitar Danau Toba dikembangkan menggunakan metode Multi-Objective Optimization on the basis of Ratio Analysis (MOORA) dengan pembobotan Rank Order Centroid (ROC). Aplikasi rekomendasi wisata dirancang untuk mempermudah para wisatawan untuk mencari destinasi wisata yang menarik sesuai keinginannya. Aplikasi akan memberikan rekomendasi wisata yang optimal berdasarkan kriteria yang telah ditentukan, yaitu jenis wisata, wilayah, rating, harga tiket, hari operasional, dan jam operasional. Jumlah data pada aplikasi rekomendasi wisata menggunakan 123 objek wisata. Hasil aplikasi yang dibangun berupa pengembangan aplikasi rekomendasi wisata berbasis mobile dengan menggunakan API, PHP dan teknologi multi-platform yaitu Flutter. Pengujian aplikasi melibatkan beberapa pengujian, termasuk system testing, user testing, dan pengujian akurasi pengelolaan data. Hasil system testing menunjukkan bahwa aplikasi beroperasi dengan stabil tanpa error dan semua fungsi berjalan sesuai yang diharapkan. User testing dilakukan dengan menyebarkan kuesioner kepada 625 responden yang telah menggunakan aplikasi tersebut, terdiri dari masyarakat domisili Sumatera Utara sebanyak 144 orang (69,2%) dan luar Sumatera Utara sebanyak 65 orang (30,8%). Sebanyak 94,2% responden menyatakan bahwa aplikasi mudah digunakan, 94,1% merasa fungsi rekomendasi sesuai dengan kebutuhan, 83,2% menganggap desain tampilan menarik, 95,5% menyatakan informasi pada setiap destinasi wisata sudah jelas, 94,7% pengguna dari luar dan dalam Sumatera Utara dapat memahami alur aplikasi, dan 94,4% berencana menggunakan aplikasi ini sebagai panduan untuk mengunjungi destinasi wisata di Sumatera Utara. Hasil pengujian akurasi pengelolaan data menunjukkan kecocokan yang tinggi antara hasil perhitungan manual dan implementasi sistem dalam menambah, mengubah, dan menghapus data wisata. Aplikasi rekomendasi ini memiliki keunggulan yang mampu menekankan wisata disekitar Danau Toba sehingga potensi dan kearifan lokalnya dapat terlihat lebih menarik bagi pengunjung baru.   Abstract Lake Toba is a premier tourist destination in North Sumatra, renowned for its natural beauty, artificial attractions, and rich Batak culture. However, tourists often seek recommendations that align with their preferences. To address this need, a tourist destination recommendation application for the Lake Toba area has been developed using the Multi-Objective Optimization based on the Ratio Analysis (MOORA) method, incorporating Rank Order Centroid (ROC) weighting. This application aims to simplify the process for tourists to find appealing destinations based on their criteria. It provides optimal recommendations according to various factors, including type of tourism, region, ratings, ticket prices, operational days, and hours. The application features data on 123 tourist attractions. The resulting application is a mobile-based platform developed using API, PHP, and cross-platform technology, specifically Flutter. Thorough testing has been conducted, including system testing, user testing, and data management accuracy testing. The system testing revealed that the application operates smoothly without errors and that all functionalities perform as intended. User testing involved distributing questionnaires to 625 respondents who had used the application, comprising 144 individuals from North Sumatra (69.2%) and 65 from outside the region (30.8%). The feedback was overwhelmingly positive, with 94.2% of respondents finding the application easy to use, 94.1% satisfied that the recommendations met their needs, 83.2% deeming the design attractive, and 95.5% confirming that the information about each tourist destination was clear. Furthermore, 94.7% of users, both from within and outside North Sumatra, reported understanding the application flow, and 94.4% expressed their intention to use the app as a guide for visiting tourist sites in North Sumatra. The data management accuracy test indicated a strong correlation between manual calculations and the application's data handling capabilities for adding, modifying, and deleting tourism data. This recommendation application highlights tourism around Lake Toba, making its potential and local wisdom more appealing to new visitors.
Alternative Characteristics Analysis of Mixture Oil Transformer using Breakdown Voltage Method Yahya, Muhammad Amri; Prasetyo, Tegar; Hermialingga, Septi; Putri Manurung, Nancy Eka
Jurnal Edukasi Elektro Vol. 7 No. 1 (2023): Jurnal Edukasi Elektro, Volume 7, Nomor 1, 2023
Publisher : DPTE FT UNY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21831/jee.v7i1.60005

Abstract

This research shows the effect of oil mixture and temperature on breakdown voltage. Palm oil is combined with diala-b oil in various mix ratios and various temperatures. Test results on the sample, as the concentration of the mixture of diala-b oil increases, the breakdown voltage value also increases. The breakdown voltage values of all oil mixture samples that have gone through the treatment process have met the IEC standard No. 56 of 1991 with results that are classified as above the standard (standard ≥ 30kV/2.5mm). Breakdown voltage values for the composition of 100% diala-b oil, 100% palm oil, and a mixture of 50% diala-b oil: 50% palm oil at 60 °C, 70 °C, 80 °C, 90 °C, and 100 °C is above the standard that is ≥ 30 kV. Water content and acidity affect the breakdown voltage value. Based on the results of breakdown voltage testing that has been done, palm oil can be used as an alternative to transformer oil.
Development of a Mobile-Based Application for Classifying Caladium Plants Using the CNN Algorithm Chandra, Rudy; Arifin Prasetyo , Tegar; Lumbangaol, Heni Ernita; Siahaan, Veny; Sianipar, Johan Immanuel
JOIN (Jurnal Online Informatika) Vol 9 No 1 (2024)
Publisher : Department of Informatics, UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15575/join.v9i1.1296

Abstract

Caladium is a popular ornamental plant and has business potential. However, difficulties in recognizing the type of Caladium often occur because of the similarities in shape, pattern, and color of the leaves between the different kinds of Caladium. To overcome this problem, research will use machine learning with the Convolutional Neural Network (CNN) algorithm to build a mobile application that can accurately classify four types of Caladiums. The data set used is 1200 data with four classes; each class has 300 data. The best model is found with the parameter epoch 100, learning rate 0.001, and batch size 64. The model is then implemented in a mobile application with two menus, "Take a photo" and "Choose an image," which will display the classification output and confidence values of the four types of Caladiums. Testing with 30 test data per class achieves 0.975 accuracy on both menus. On the “Take a photo” menu, precision is 0.974, recall is 0.9725, and f1-score is 0.965. Meanwhile, on the “Choose an image” menu a precision and recall value is 0.975, and f1-score value of 0.97.
Pemanfaatan Botol Plastik Bekas Menjadi Pot Hias Melalui Participatory Action Research MANURUNG, NANCY EKA PUTRI; PRASETYO, TEGAR; Tanjung, Muhammad Al Chapis Abdilla; AFRICANO, FERNANDO; DEWANTARA, BILLY; AJI NUGRAHA, YOGA; Agustin, Ririn Dita; Agustina, Silvia; Fernandez, Melanie; Pratami, Viekhen Irza
Jurnal Pengabdian Masyarakat Akademisi Vol. 4 No. 3 (2025)
Publisher : Jurnal Pengabdian Masyarakat Akademisi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54099/jpma.v4i3.1420

Abstract

Sampah merupakan hasil sisa pembuangan dari aktivitas masyarakat. Sampah botol plastik merupakan salah satu sampah anorganik yang menjadi permasalahan umum saat ini dan lingkungan sekolah lingkungan sekolah yang menjadi salah satu sumber penghasilnya sehingga perlukan upaya pengolahan sampah botol plastik bekas untuk mengurangi tumpukan sampah khususnya anorganik. Pengabdian masyarakat ini bertujuan menerapkan konsep reuse melalui pembuatan pot hias. Pengabdian dilakukan di SMK Mardi Wacana yang diikuti oleh seluruh siswa dan staf sekolah sebagai peserta pengabdian. Pengabdian dilakukan dengan metode Participatory Action Research (PAR) agar seluruh peserta terlibat secara aktif pada keseluruhan rangkaian pengabdian. Metode PAR diterapkan melalui tiga tahap: (1) survei lapangan, (2) persiapan pengabdian, dan (3) pelaksanaan pengabdian yang mencakup sosialisasi pemilahan dan pembuatan 3 tong sampah (organik, anorganik, B3) yang memanfaatkan ember cat bekas serta pelatihan pemanfaatan botol plastik bekas menjadi pot hias yang akan digantung disekitar lingkungan kelas. Metode PAR ini akan memberikan pengalaman secara langsung dalam mengimplementasikan ilmu secara langsung untuk menciptakan lingkungan sekolah yang asri. Hasil pengabdian menunjukkan peningkatan kapasitas peserta dalam pengelolaan sampah dan terciptanya produk daur ulang berupa pot hias tanaman yang mendukung keasrian lingkungan sekolah. Program ini membuktikan efektivitas pendekatan partisipatif dalam menangani masalah sampah plastik sekaligus menanamkan kesadaran lingkungan berkelanjutan.
Analisis Kebijakan Otonomi Daerah dalam Peningkatan Kualitas Pelayanan dalam Tinjauan Islam Ilhami, Ilhami; Aulia Akhmad; Iammillah, Azmiyatul; Rahmawati, Elmi; Juniasari, Juniasari; Lestari, Leni Ayu; Akbar, M. Jofandio; Najah, Nabila Safinatun; Hafizah, Nanda Nur; Safitri, Nita Octaria; Fauziah, Putri Khafifah; Aprianda, Ridho; Ardian, Rizki; Prasetyo, Tegar; Wardani, Yoshinta Kusuma
Economic Reviews Journal Vol. 3 No. 2 (2024): Economic Reviews Journal
Publisher : Masyarakat Ekonomi Syariah Bogor

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56709/mrj.v3i2.233

Abstract

The aim of this research is to analyze the regional autonomy policy to improve the quality of public service in the Islamic perspective. Regional autonomy as a policy of decentralization gives authority to local governments to self-regulate regional affairs, with the aim of improving the efficiency and effectiveness of service to local communities. In Islamic terms, the concept of leadership and public service is strongly based on the principles of justice, trust, and the well-being of the people (maslaha). This study uses a method of literature study used to examine articles published in scientific journals at a particular time to find out how Islamic principles can be applied in the context of regional autonomy policy in Indonesia. Research results show that the implementation of Islamic values in regional autonomy policies can improve the quality of public service by strengthening accountability, transparency, and public participation. Furthermore, the implementation of a policy based on Islamic doctrine can encourage the formation of a government that is more responsive and accountable to the needs and wishes of local communities. The study concludes that there is great potential for achieving better public service through the synergy of regional autonomy policies and Islamic principles.
PENYULUHAN TENTANG SAMPAH ORGANIK DAN ANORGANIK, PEMILAHAN SAMPAH, SERTA PENGOLAHANNYA Prasetyo, Tegar; Manurung, Nancy Eka Putri; Africano, Fernando; Desiana, Lidia; Evelina, Evelina; Dewantara, Billy; Hermialingga, Septi; Burhan, Abi; Nugraha, Yoga Aji; Adha, Ufairi; Cahya, Gemala; Nadeak, Ebtaria; Kurniawan, Edi; Yahya, Muhammad Amri
Community Development Journal : Jurnal Pengabdian Masyarakat Vol. 4 No. 6 (2023): Volume 4 Nomor 6 Tahun 2023
Publisher : Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/cdj.v4i6.21771

Abstract

Sampah merupakan hasil sisa aktivitas manusia yang dibuang dan tidak terpakai. Sampah yang dapat terurai dikategorikan sebagai sampah organik, dan sampah yang tidak dapat terurai dikategorikan sebagai sampah anorganik. Tujuan dari pengabdian ini untuk memberikan ilmu pengetahuan kepada masyarakat tentang sampah organik dan anorganik serta pentingnya pemilahan dan pengolahan sampah organik dan anorganik. Penyuluhan berlangsung pada bulan Oktober 2023 di Desa Perambahan Kabupaten Banyuasin 1, Sumatera Selatan dan materi disampaikan oleh tim pengabdi yang merupakan dosen dari Politeknik Negeri Sriwijaya. Peserta pengabdian terdiri dari perangkat Desa dan ibu-ibu Kader Posyandu dan PKK. Tim pengabdi menyampaikan materi tentang perbedaan sampah organik dan anorganik, contoh-contoh sampah organik dan anorganik, pemilahan sampah organik dan anorganik, serta pengolahan sampah. Peserta pengabdian antusias terhadap kegiatan pengabdian ini dengan tingkat tanya jawab yang tinggi kepada tim pengabdi. Masyarakat setempat diharapkan mendapatkan ilmu pengetahuan baru tentang sampah dan menjadikan lingkungan sekitar menjadi lebih bersih, asri, serta dapat menjadi tempat untuk memberikan perekonomian tambahan bagi masyarakat.
Perancangan produk alat pengupas kulit dan pemipil biji jagung dengan Metode AHOQ di Kecamatan Silaen Siagian, Wesly Mailander; Silaen, Willy Cristover; Prasetyo, Tegar Arifin; Maulana, Muhammad Ilham
PRODUCTUM Jurnal Desain Produk (Pengetahuan dan Perancangan Produk) Vol 8, No 2 (2025)
Publisher : Institut Seni Indonesia Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24821/productum.v8i2.14926

Abstract

The farmer group in the Silaen sub-district which is located in Toba Regency is a farmer group where the majority of farmers are corn farmers. The general problems faced by this farmer group include the ineffectiveness of the harvest process where farmers have to peel and dry the corn before the corn is ground using a corn sheller machine. Therefore, this research was carried out in order to answer the problems faced by this farmer group. Where in this research we will design a machine for peeling and shelling corn, so that farmers will be more practical when carrying out the harvest process. In this research, the Axiomatic House of Quality (AHOQ) method was used by integrating it with the House of Quality (HOQ) and Axiomatic design (AD). Then you will get a design and specifications for a corn peeling and shelling machine that uses an oil-fueled engine.
Optimizing parameter selection in bidirectional encoder portrayal for transformers algorithm using particle swarm optimization for artificial intelligence generate essay detection Prasetyo, Tegar Arifin; Chandra, Rudy; Siagian, Wesly Mailander; Siregar, Horas Marolop Amsal; Siahaan, Samuel Jefri Saputra
International Journal of Electrical and Computer Engineering (IJECE) Vol 15, No 6: December 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v15i6.pp5543-5554

Abstract

This research proposes a novel method for detecting artificial intelligence (AI)-generated essays by integrating the bidirectional encoder representations from transformers (BERT) model with particle swarm optimization (PSO). Unlike traditional approaches that rely on manual hyperparameter tuning, this study introduces a systematic optimization technique using PSO to improve BERT’s performance in identifying AI-generated content. The key problem addressed is the lack of effective, real-time detection systems that preserve academic integrity amidst rapid AI advancements. This optimization enhances the model’s detection accuracy and operational efficiency. The research dataset consisted of 46,246 essays, which, after data cleaning, were refined to 44,868. The model was then tested on 9,250 essays. Initial evaluations showed BERT's accuracy ranging from 83% to 94%. After being optimized with PSO, the model achieved an accuracy of 98%, an F1-score of 98.31%, precision of 97.75%, and recall of 98.87%. The model was deployed using a FastAPI-based web interface, enabling real-time detection and providing users with an efficient way to quickly verify text authenticity. This research contributes a scalable, automated solution for AI-generated text detection and offers promising implications for its application in various academic and digital content verification contexts.
Enhancing the Effectiveness of the YOLO Model Through Caladium Leaf Images Generated by Generative Adversarial Networks Chandra, Rudy; Prasetyo, Tegar Arifin; Simamora, Akdes Simon; Simbolon, Amanda Artha Regina; Sinaga, Ester Krismayani; Perdanasari, Lukie
Journal of Applied Engineering and Technological Science (JAETS) Vol. 7 No. 1 (2025): Journal of Applied Engineering and Technological Science (JAETS)
Publisher : Yayasan Riset dan Pengembangan Intelektual (YRPI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37385/jaets.v7i1.6624

Abstract

The need for ornamental caladium plants is very popular, but there are several obstacles to recognizing its type. Caladium species classification using AI is needed to overcome the problem of misidentification among enthusiasts. This study uses the Generative Adversarial Network (GAN) algorithm to generate new images from the Caladium dataset: Amazon Caladium, Bicolor Caladium, White Queen Caladium, and Skull Caladium. We combine GAN with YOLOv5 to detect Caladium in real time to improve accuracy. The quality of the generated images is evaluated using the Kernel Inception Distance (KID) method, with the highest scores of 0.2320 for Amazon Caladium, 0.1966 for Bicolor, 0.1713 for Skull, and 0.1857 for White Queen, indicating close similarity to the original images. We chose the best model to generate three datasets: Original Dataset, Mixed Dataset (original images plus GAN-generated images), and Dataset consisting mainly of GAN images. The Mixed Dataset achieved the best results, with a mean Average Precision (mAP) of 0.695 for an Intersection over Union (IoU) of 0.50:0.95 outperforming the GAN dataset and the original Dataset. This training used 50 epochs, a learning rate of 0.0003, and a batch size of 16, to obtain the best model and significantly improve Caladium detection. From this experiment, it was found that the GAN, combined with the original data, was able to support the accuracy of YOLOv5 for real-time caladium classification and was also able to create new images that resembled the original leaves. In the mobile application, this model allows real-time identification of Caladium types, making it easier for users to buy Caladium according to the desired type.
YOLOv9-Assisted Vision System for Health Assessment in Poultry Using Deep Neural Networks Risma, Pola; Prasetyo, Tegar; Muhammad Amri , Yahya
Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Vol. 11, No. 1, February 2026
Publisher : Universitas Muhammadiyah Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22219/kinetik.v11i1.2414

Abstract

Poultry farming represents one of the fastest growing sectors in global food production, yet disease outbreaks, high mortality, and labor shortages continue to threaten its sustainability. Conventional health monitoring methods based on visual inspection are time-consuming, subjective, and inadequate for early anomaly detection. In response, computer vision and deep learning have emerged as transformative tools for livestock management. While prior implementations of the YOLO object detection family, such as YOLOv5 and YOLOv8, have achieved notable success, their performance often deteriorates in dense flocks, low-light conditions, and occlusion-prone environments. This study introduces a YOLOv9-assisted vision framework tailored for poultry health assessment in commercial farm settings. The system integrates smart cameras with edge computing to enable real-time detection of behavioral and physiological anomalies without dependence on high-bandwidth or cloud-based resources. A dataset of 903 annotated poultry images, categorized into healthy and sick classes, was employed for model development. The trained model achieved 88.7% precision, 97% recall, an F1-score of 0.82, and a mAP@0.5 of 0.88, demonstrating robustness under variable illumination, bird occlusion, and high-density environments. Comparative evaluation confirmed that YOLOv9 provides a superior balance of accuracy, generalization, and computational efficiency relative to YOLOv8–YOLOv11, supporting practical deployment on edge devices. Limitations include the binary scope of health classification and reliance on a single dataset. Future directions involve extending the framework to multi-class disease recognition, cross-dataset validation, behavior-based temporal modeling, and multimodal fusion, advancing predictive analytics and welfare-oriented poultry farming.
Co-Authors Abda Abda Abi Burhan Adha, Ufairi Africano, Fernando Agustin, Ririn Dita Aji Nugraha, Yoga Akbar, M. Jofandio Anastasia Marsada Uli Simamora Andree Panjaitan Aprianda, Ridho Ardian, Rizki Asido Saragih Aulia Akhmad BillY Dewantara Christian Benedict Lumbantoruan Dame Sisri Haryati Katarina Rumapea Desiana, Lidia Dewi Handayani Ebtaria Nadeak, Ebtaria Eka Putri Manurung, Nancy Elmi Rahmawati, Elmi Emy Sonia Sinambela Ester Saulina Hutabarat Evan Richardo Sianipar Evelina Evelina Fauziah, Putri Khafifah Fernandez, Melanie Frengki Simatupang Fritz Marpaung Gemala Cahya Goklas Henry Agus Panjaitan Hafizah, Nanda Nur Hamzah, Muhammad Luthfi Henny Flora Panjaitan Henry Agus Panjaitan , Goklas Henry Agus Panjaitan, Goklas Herbeth Augustinus Napitupulu Hermialingga, Septi Iammillah, Azmiyatul Ilhami, Ilhami Italiano Wowiling, Gerry Joshua Pratama Silitonga Juan Carlos Munthe Juli Yanti Damanik Juniasari, Juniasari Lawy Xenna Lestari, Leni Ayu Lilis Marito Pardosi Lumban Gaol, Tiurma Lumbangaol, Heni Ernita Manurung, Nancy Eka Putri Matthew Alfredo Mei Pane Muhammad Amri Yahya Muhammad Fikri Muhammad Ilham Maulana Muhammad Rizki Mula Timbul Sigiro, Marojahan N. Nazaruddin Najah, Nabila Safinatun Nathan Fernando Lumban Tobing Nico Felix Sipahutar Nugraha, Yoga Aji Panca Rahmat Siagian, Iqbal Pangaribuan, Maria Partogi Pardede, Immanuel Pasaribu, Monalisa Perdanasari, Lukie Poibe Leny Naomi Pola Risma Pratami, Viekhen Irza Putri Manurung, Nancy Eka Risky Saputra Siahaan Roberd Saragih Romauli Sianipar Rudy Chandra Rudy Chandra Safitri, Nita Octaria Samuel Sibuea Saodin, Saodin Sarbaini Sarbaini Sarbaini Sarbaini Sari Utami, Aldila SIAGIAN, WESLY MAILANDER Siahaan, Samuel Jefri Saputra Siahaan, Veny Sianipar, Johan Immanuel Sihombing, Tahan HJ Silaen, Willy Cristover Silvia Agustin Simamora, Akdes Simon Simbolon, Amanda Artha Regina Sinaga, Ester Krismayani Siregar, Horas Marolop Amsal Suandika Napitupulu Tanjung, Muhammad Al Chapis Abdilla Tessalonika Siahaan Timothy Timothy Tiurma Lumban Gaol Togu Novriansyah Turnip Trito Exaudi Manik Umam, Muhammad Isnaini Hadiyul Victor Lambok Desrony Wardani, Yoshinta Kusuma Wesly Mailander Siagian Yohana Sihombing Yohanssen Pratama