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All Journal IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Dinamik Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI) Paradikma: Jurnal Pendidikan Matematika JURNAL PENELITIAN SAINTIKA ELEMENTARY SCHOOL JOURNAL PGSD FIP UNIMED Jurnal Teknologi Informasi dan Ilmu Komputer Jurnal Daya Matematis Jurnal Informatika dan Teknik Elektro Terapan Seminar Nasional Informatika (SEMNASIF) JURNAL PENGABDIAN KEPADA MASYARAKAT Jurnal KARISMATIKA Bina Insani ICT Journal JURNAL SAINS INDONESIA Indonesian Journal of Artificial Intelligence and Data Mining INTECOMS: Journal of Information Technology and Computer Science Jurnal Cendekia : Jurnal Pendidikan Matematika Jurnal Perspektif M A T H L I N E : Jurnal Matematika dan Pendidikan Matematika JATI (Jurnal Mahasiswa Teknik Informatika) Community Development Journal: Jurnal Pengabdian Masyarakat Budapest International Research and Critics in Linguistics and Education Journal (Birle Journal) Informatics and Digital Expert (INDEX) Jurnal FASILKOM (teknologi inFormASi dan ILmu KOMputer) Journal of Soft Computing Exploration Djtechno: Jurnal Teknologi Informasi Jurnal Pengabdian kepada Masyarakat Teknik: Jurnal Ilmu Teknik dan Informatika INCODING: Journal of Informatics and Computer Science Engineering J-Intech (Journal of Information and Technology) Kharisma Tech Economic Reviews Journal PROSISKO : Jurnal Pengembangan Riset dan observasi Rekayasa Sistem Komputer Journal of Artificial Intelligence and Engineering Applications (JAIEA) Jurnal Riset Rumpun Matematika dan Ilmu Pengetahuan Alam (JURRIMIPA) Jurnal Umum Pengabdian Masyarakat (JUPEMAS) Journal of Informatics and Data Science (J-IDS) Jurnal KALANDRA Journal of Education Transportation and Business International Journal of Educational Insights and Innovations (IJEDINS) Ulil Albab Jurnal Informatika Dan Tekonologi Komputer
Hermawan Syahputra
Universitas Negeri Medan
Religion Agriculture, Biological Sciences & Forestry Arts Humanities Automotive Engineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Mathematics Mechanical Engineering Public Health Social Sciences Transportation Other

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Klasifikasi Usia Berdasarkan Suara Menggunakan Metode Linear Predictive Coding (LPC) dan Nearest Neighbor Berbasis Python Panjaitan, Nova Yanti; Syahputra, Hermawan
ULIL ALBAB : Jurnal Ilmiah Multidisiplin Vol. 3 No. 9: Agustus 2024
Publisher : CV. Ulil Albab Corp

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56799/jim.v3i9.4754

Abstract

Tiap-tiap manusia mempunyai keunikan suara yang berbeda-beda yang disebabkan karena resonansi pada tenggorokan yang pula berbeda. Terdapat sejumlah hal yang dapat menjadi kendala ketika proses ekstraksi suara yakni bersumber dari variabilitas suara pada keadaaan seseorang sakit, dialog asing, emosi dan lingkungan. Maka dari itu diperlukan proses filtering. Proses filtering ini sangatlah penting karena dapat menyaring suara untuk menghilangkan noise-noise pada suara. Filtering suara dilaksanakan sebelum proses ekstraksi suara. Dengan adanya klasifikasi usia, ruang masalah dalam pengenalan suara dapat dibatasi hanya berlandaskan usia yang sudah diklasifikasikan. Pembagian usia berlandaskan karakteristiknya yakni anak-anak 5 11 tahun, remaja 12 25 tahun, dewasa 26-45 tahun serta lansia 46 65 tahun. Adapun tujuan dari penelitian ini yaitu agar dapat diketahui bagaimana penerapan Linear Predictive Coding (LPC) dan Nearest Neighbor dalam pengklasifikasian usia berdasarkan suara. Oleh karena itu akan dilaksanakan penelitian untuk tugas akhir dengan mengidentifikasikan usia berlandaskan suara dan mengklasifikasikan suara tersebut kedalam jenis tipe suara anak-anak, remaja, dewasa dan lansia dengan mempergunakan metode Linear Predictive Coding (LPC) dan Nearest Neighbor Berbasis Python. Hasil penelitian ini yaitu: (1). Pembuatan sistem klasifikasi usia memanfaatkan aplikasi Pyhton. (2). Pengujian akurasi K-Fold Cross Validation diperoleh akurasi senilai 75%, presisi 39%, recall 39%. (3). Berlandaskan total kinerja sistem yang sudah diperoleh, maka bisa ditarik kesimpulannya dengan menerapkan metode Linear Predictive Coding (LPC) selaku ekstraksi ciri dan Nearest Neighbor bisa dipergunakan dalam mengelompokkan usia anak-anak, remaja, dewasa, lansia berlandaskan suaranya.
Optimalisasi Dashboard Pemesanan Makanan Online Menggunakan Looker dan JavaScript Angginy Akhirunisa Siregar; Citra; Khairun Nadiah; Hermawan Syahputra; Fanny Rahmadani
Economic Reviews Journal Vol. 3 No. 3 (2024): Economic Reviews Journal
Publisher : Masyarakat Ekonomi Syariah Bogor

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56709/mrj.v3i3.322

Abstract

Advances in information technology have enabled rapid development in internet-based services, including online food ordering applications. This growth demands efficient data management and analysis systems to improve user experience and operational performance. This research focuses on developing an optimal online food ordering dashboard using Looker and JavaScript. Research methods include needs identification, literature study, needs analysis, design, and implementation. The research results show that the dashboard developed is able to manage and analyze order data effectively, identify trends, predict customer needs, and increase operational efficiency. This dashboard visualizes important information such as number of orders based on age, gender, income, as well as customer behavior analysis. In doing so, service providers can gain better insight into consumer behavior and ordering trends, supporting more informed and strategic decision making. The results of this study contribute to the literature on the use of data visualization technologies in the online food service sector.
Peningkatan Produksi Usaha May’s Kitchen dengan menerapkan Teknologi Tepat Guna Oven Pemanggang Kue Kukus Ritonga, Winsyahputra; Syah, Dedy Husrizal; Oktora, Maya; Solahudin, Ahmad Andi; Syahputra, Hermawan; Rangkuti, Muhammad Aswin; Harahap, Mukti Hamjah; Panggabean, Deo Demonta
KALANDRA Jurnal Pengabdian Kepada Masyarakat Vol 3 No 4 (2024): Juli
Publisher : Yayasan Kajian Riset Dan Pengembangan Radisi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55266/jurnalkalandra.v3i4.412

Abstract

Pengabdian masyarakat ini berfokus pada peningkatan produktivitas UMKM May's Kitchen di Desa Mangga Dua, Kecamatan Tanjung Beringin, Kabupaten Serdang Bedagai, melalui penerapan teknologi tepat guna. Permasalahan utama yang dihadapi mitra adalah keterbatasan teknologi produksi, khususnya dalam proses pemanggangan kue kukus, yang berdampak pada kualitas dan daya saing produk. Untuk mengatasi hal ini, tim pengabdi mengimplementasikan pendekatan terpadu meliputi edukasi, pelatihan, dan pendampingan intensif. Inti dari program adalah introduksi oven pemanggang kue kukus berkapasitas 6 loyang dengan 1 rak berbahan stainless steel. Hasil menunjukkan peningkatan efisiensi produksi hingga tiga kali lipat, disertai perbaikan signifikan pada kualitas dan konsistensi produk. Evaluasi pasca-program mengindikasikan peningkatan pengetahuan mitra sebesar 85% mencakup aspek teknis operasional, food safety, dan quality control. Analisis ekonomi memproyeksikan penurunan biaya produksi hingga 20% dan potensi peningkatan margin keuntungan 15-20%.
The Effect of Problem Based Learning Models on the Mathematical Dispositions of Class VIII Students of SMP Negeri 5 Stabat Luthfiah, Dina Aulia; Napitupulu, E. Elvis; Syahputra, Hermawan
PARADIKMA: JURNAL PENDIDIKAN MATEMATIKA Vol. 16 No. 2 (2023): PARADIKMA JURNAL PENDIDIKAN MATEMATIKA (July - December 2023)
Publisher : Study Program of Mathematics Education of Unimed Postgraduate Program

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24114/paradikma.v16i2.48044

Abstract

The purpose of this research is to investigate: (1) how students' mathematical dispositions differ depending on whether they were taught using a Problem-Based Learning model or an Ordinary Learning model; (2) how the mathematical dispositions of students are affected by the relationship between the learning style and Previous Students' Ability. This study is a quantitative investigation employing procedures that are semi experimental. The instruments of this research are problem solving ability tests and student disposition questionnaires. The participants in this research project are all 222 students enrolled in class VIII at SMP Negeri 5 Stabat during the academic year 2022/2023. There are a total of 222 individuals. The method of sampling utilized for this investigation was a straightforward random sampling method, and the total number of students comprising the sample was calculated using the Issac and Michael formula. Essay examinations and questionnaires were the research tools that were utilized in this investigation. A Two Way ANOVA was utilized in the analysis of the results. The findings of the research indicate the following: (1) the mathematical disposition of students in the class that uses problem-based learning is higher than that of students in the class that uses ordinary learning; (2) there is no interaction between the learning model and early mathematical abilities (high, medium, and low) on students' mathematical dispositions.Keywords: Problem Based Learning, Quasi Experiment, Mathematical Dispositions
Development of Cooperative Learning Tools Type Course Review Horay and Geogebra Media to Improve Spatial Thinking Skills and Mathematical Resilience of Grade VIII Students Siregar, Putri Mayang Sari; Syahputra, Hermawan; Fauzi, KMS. Amin
PARADIKMA: JURNAL PENDIDIKAN MATEMATIKA Vol. 16 No. 2 (2023): PARADIKMA JURNAL PENDIDIKAN MATEMATIKA (July - December 2023)
Publisher : Study Program of Mathematics Education of Unimed Postgraduate Program

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24114/paradikma.v16i2.48947

Abstract

This study aims to investigate the improvement and development of spatial thinking skills and mathematical resilience abilities of students using cooperatively developed learning tools of the Course Review Horay and Media Geogebra type; to investigate the validity, practicability, and efficacy of cooperatively developed learning tools of the Course Review Horay and Media Geogebra type in enhancing spatial thinking skills and resilience. This type of research is development research based on the ADDIE model. 33 MTs Al-Washliyah Tembung students participated in the study. The results demonstrated that 97% of the students, or 32 out of 33, improved their spatial reasoning skills. While only 19 of 33 students, or 58%, exhibited an increase in mathematical resilience. In addition, the results indicate that this development model is more effective than conventional classroom learning models at enhancing spatial reasoning and mathematical resilience. The learning aids created using cooperative Course Review Horay type and Geogebra are valid, applicable, and efficient.Keywords: ADDIE, Spatial Thinking Skills, Mathematical Resilience, Development Research
BOOTCAMP TEKNIK JARINGAN TELEKOMUNIKASI FIBER OPTIK UNTUK SISWA/I TKJ SMKS TRI SAKTI LUBUK PAKAM Dedy Kiswanto; Hermawan Syahputra; Suvriadi Panggabean; Sri Dewi; Nurul Maulida Surbakti
Community Development Journal : Jurnal Pengabdian Masyarakat Vol. 6 No. 2 (2025): Volume 6 No. 2 Tahun 2025
Publisher : Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/cdj.v6i2.43050

Abstract

Kegiatan bootcamp teknik teknik jaringan telekomunikasi fiber optik untuk siswa/siswi teknik komputer dan jaringan di SMKS Tri Sakti Lubuk Pakam bertujuan untuk meningkatkan kompetensi siswa/i jurusan Teknik Komputer dan Jaringan (TKJ) di SMKS Tri Sakti Lubuk Pakam terkait instalasi jaringan fiber optik. Kegiatan ini diadakan untuk menjawab kebutuhan industri yang terus berkembang, di mana instalasi fiber optik menjadi standar dalam jaringan telekomunikasi secara Global. Metode yang dilakukan meliputi training materi teori instalasi fiber optik oleh praktisi Industri, demonstrasi, dan pelatihan langsung instalasi fiber optik. Hasil dari kegiatan ini menunjukkan bahwa sebagian besar peserta mampu memahami prinsip dasar fiber optik, jenis kabel yang digunakan, dan teknik instalasi yang benar. Namun, masih terdapat beberapa peserta yang belum sepenuhnya memahami aspek-aspek teknis tertentu. Diakhir kegiatan dilakukan penyerahan alat instalasi fiber optik kepada sekolah dengan harapan dapat mendukung peningkatan kompetensi instalasi fiber optik lebih lanjut dan memastikan kesiapan siswa menghadapi dunia kerja pada bidang telekomunikasi fiber optik.
Analisis Identifikasi Buah Jeruk Menggunakan Metode Warna RGB pada Aplikasi Berbasis Web Triwanti Andini Hutasoit; Claudia Agatha Br. Tarigan; Jonathan Rio Gultom; Hermawan Syahputra
Informatics and Digital Expert (INDEX) Vol. 8 No. 1 (2026): INDEX, Mei 2026
Publisher : LPPM Universitas Perjuangan Tasikmalaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36423/index.v8i1.2761

Abstract

Penelitian ini bertujuan untuk mengembangkan aplikasi berbasis web yang dapat digunakan untuk mengidentifikasi kualitas buah jeruk secara otomatis menggunakan analisis warna RGB. Permasalahan yang diangkat dalam penelitian ini adalah proses identifikasi kualitas buah yang masih dilakukan secara manual, sehingga kurang efisien dan berpotensi menimbulkan subjektivitas. Metode yang digunakan adalah pengolahan citra digital dengan memanfaatkan nilai warna RGB sebagai dasar dalam proses klasifikasi. Sistem dirancang untuk menerima input berupa citra buah, kemudian memproses dan mengklasifikasikan kondisi buah ke dalam kategori segar, matang, dan busuk. Hasil pengujian menunjukkan bahwa sistem mampu mengidentifikasi kualitas buah dengan tingkat akurasi mencapai 100% pada data uji yang digunakan. Selain itu, waktu respon sistem berada pada rentang 1.1 hingga 1.3 detik, yang menunjukkan bahwa proses deteksi dapat dilakukan secara cepat dan konsisten. Dengan demikian, sistem yang dikembangkan dapat menjadi solusi alternatif dalam membantu proses identifikasi kualitas buah secara otomatis, lebih cepat, dan lebih objektif dibandingkan metode manual.
Decision Support System Using the Analytical Hierarchy Process Method in Determining Credit Recipient Eligibility Erika Nia Devina Br Purba; Arnita; Hermawan Syahputra; Lasker P Sinaga; Adidtya Perdana
Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 5 No. 3 (2026): June 2026
Publisher : Yayasan Kita Menulis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59934/jaiea.v5i3.2256

Abstract

Banks play a fundamental role in improving public welfare by collecting funds through savings and redistributing them as credit. Although credit is the primary source of bank revenue, it carries significant risks if the feasibility analysis of prospective borrowers is flawed, potentially leading to non-performing loans that disrupt financial stability. BPR Nusantara Bona Pasogit 17 faces this challenge as it currently lacks an automated decision support system, resulting in assessments that are often inconsistent or subjective. This research aims to develop a web-based decision support system using the Analytical Hierarchy Process (AHP) method to determine credit recipient eligibility. Developed using PHP and MySQL, the system incorporates criteria management, AHP calculation processing, and automated eligibility ranking. Comprehensive validation through black-box and white-box testing confirmed that all functional components performed correctly with consistent "PASS" results. The AHP implementation produced a Consistency Ratio (CR) of 0.03797, indicating high reliability in decision-making. Criterion priority weights were identified as: Income (0.386), Character (0.219), Loan Amount (0.162), Collateral (0.103), Loan Term (0.07), and Age (0.06). System testing on 100 customer records resulted in a maximum eligibility score of 0.93501 and a minimum of 0.41839.
Eye Disease Classification System Based on Fundus Images Using the InceptionV3 Architecture Annisa Aulia; Hermawan Syahputra; Yulita Molliq Rangkuti; Insan Taufik; Kana Saputra S
Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 5 No. 3 (2026): June 2026
Publisher : Yayasan Kita Menulis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59934/jaiea.v5i3.2263

Abstract

This study aims to develop an automated eye disease classification system based on retinal fundus images using the InceptionV3 deep learning architecture. The dataset consists of four classes: cataract, diabetic retinopathy, glaucoma, and normal, collected from public sources and clinical data. The proposed method applies several preprocessing techniques, including background segmentation, data augmentation, data normalization, and an 80:20 data split to improve model performance and generalization. Transfer learning is implemented by utilizing pretrained ImageNet weights and modifying the final layers to suit the classification task. The model is trained using the Adam optimizer with a learning rate of 0.001 and categorical cross-entropy loss function. Evaluation results show that the model achieves an accuracy of 96%, with average precision, recall, and F1-score values of 0.97, 0.96, and 0.97, respectively. The confusion matrix analysis indicates that most predictions are correctly classified, demonstrating strong performance across all classes. Furthermore, the model is successfully integrated into a web-based system that enables users to upload fundus images and obtain classification results automatically. These findings indicate that the proposed system can effectively assist in early detection of eye diseases and support clinical decision-making.
Smart Absen Implementation of a Facial Recognition-Based Student Attendance System Using the Haar Cascade Method and LBPH Frengki Alfredo Matondang; Sahara Lani Lestari; Dinda Syafitri; Kayla Amelia Putri; Hermawan Syahputra
Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 5 No. 3 (2026): June 2026
Publisher : Yayasan Kita Menulis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59934/jaiea.v5i3.2301

Abstract

Manual attendance systems in higher education institutions are often hampered by inefficiency, data inaccuracy, and vulnerability to fraud such as proxy attendance. This study presents the design and implementation of Absen Smart, a face recognition-based attendance system developed using the Haar Cascade and Local Binary Pattern Histogram (LBPH) algorithms within the React.js and Flask frameworks. This system enables the automatic and real-time identification of students via a webcam without requiring additional hardware. Face detection is performed using the Haar Cascade classifier from OpenCV, while face recognition uses the LBPH Face Recognizer with a confidence threshold of 50. Testing was conducted with 28 registered students from the Computer Science Program at UNIMED, Class A, 2024 cohort. Functional evaluation results show that all seven core system features—including face detection, face recognition, duplicate prevention, automatic absence tracking, and Excel report generation—were successfully executed with a 100% success rate. The system achieved a facial recognition accuracy of 92.86%, with an average processing time of 1.2 seconds per verification. These results indicate that the proposed system is an effective, practical, and scalable solution for automating academic attendance in a university setting.
Co-Authors Abil Mansyur, Abil Ade Amelia, Tasya Adhi Guna, Ekin Adidtya Perdana, Adidtya Agus Harjoko Ahmad Andi Solahuddin Ahmad Hidayat Ajizah Siregar Aldiva Wibowo Alfarizi Wijaya Alfattah Atalarais Amelia Br Siregar, Ririn Amelia Vega S. Meliala, Ruth Ami . Riana Andani D N Andika Maulana, Sandy Angel Tumanggor, Asri Angginy Akhirunisa Siregar Ani Sutiani Annisa Aulia Apiek Gandamana Arion Pardede Arnita Arnita Arnita Arnita Asrin Lubis Augis Dinanti Azril Arfansyah Batubara, Saatira Hilma BORNOK SINAGA Bornok Sinaga Budi Akbar, Muhammad Calvin Sahputra Buulolo citra Claudia Agatha Br. Tarigan Daniel Pandiangan Daulay, Leni Karmila Davina, Sherly Dedy Husrizal Syah, Dedy Husrizal Dedy Kiswanto Defiyanti, Aqilah Delvin Ibo, Martince Deo Demonta Panggabean Dhea Putri Adriani Dina Aulia Luthfiah Dinda Syafitri Drilanang, Mhd Ilyasyah Dwi Zahra Putri, Raisya E. Elvis Napitupulu E. Elvis Napitupulu, E. Elvis Edi Syahputra Edward Perdana Sinaga Elisabet Butarbutar, Lastri Erika Nia Devina Br Purba Fanny Rahmadani Farmawaty Tambunan, Vivielda Fauzi, KMS. Amin Fransiska Sihombing, Esra Frengki Alfredo Matondang Hafiz, Alvin Harefa, Meilinda Suriani Hasratuddin Siregar Hidayatul Arifin, Muhammad Husna Batubara, Shabrina Ihsan Zulfahmi Ika Purnama Sari Imelda, Yusmita Impana Manik, Kristin Indriani.S, Dechy Deswita Insan Taufik Irhamna Irhamna Irmaya, Nia Irya Shakila Syukron, Ananda Iwan Jepri Izwita Dewi Jonathan Rio Gultom Kana Saputra S Karimuddin Hakim Hasibuan Kayla Amelia Putri Khairany Zuhriyyah Jinan Hsb Khairun Nadiah Kms. Amin Fauzi Lasker Pangarapan Sinaga Lazuardi Harahap, Muhammad Luthfiah, Dina Aulia M. Ari Maulana M. Revano Ananda Lubis Mahyuni Mahyuni Manurung, Jeremia Martina Restuati Maulana, Raihan Maya Oktora MHD. Reza M.I. Pulungan Mia Yolanda Siregar Mochammad Gani Alfa Alkhoiri Siregar Muhammad Febrilian Zulrahman Muhammad Iqbal Fahrezzi Muhammad Rizki Andrian Fitra Mukti Hamjah Harahap, Mukti Hamjah Nafil Rizq Trianto Nasution, Dinda Indriani Neysa Talitha Jehian Nico Pasaribu, Michael Niska, Debi Yandra Nova Yanti Panjaitan Nur Wahyuni Nurmala Berutu Nurul Azmi Nurul Maulida Surbakti Oktavia, Grace Palendeo Sitepu, Kalpin Pane, M Iqbal Anata Pane, Yeremia Yosefan Panggabean, Suvriadi Panjaitan, Clara Kresensia Panjaitan, Nova Yanti Permata Putri Pasaribu, Yohanna Prana Walidin, Adamsyach Purba, Boy Hendrawan Purba, Desni Paramitha Putri Mayang Sari Putri Mayang Sari Siregar R Givent A Simanjorang Ramadhan Manik, Albert Ramadhani, Fanny Rambe, Imelda Wardani Rangkuti, Muhammad Aswin Riana, Ami Richi, Alfina Ridho Affandi Sahara Lani Lestari Said . Iskandar SANTI MARIA SIMARMATA Santi Maria Simarmata Sembiring, Rinawati Shaqila Rahmayani Gultom Sinaga, Elya Juni Arta Siregar, Putri Mayang Sari Siti Nabila Panjaitan Solahudin, Ahmad Andi Sri Dewi Sriadhi Sriadhi, Sriadhi Steven Imanuel Naibaho Sukma, Ayman Human Suleho, Febrina Suvriadi Panggabean Syamsah Fitri Syarief Afifi Sumantri Syawal Gultom Sybil Auzi Syti Salwaa Nafiisah Thania Dealva Arsyad Tri Bowo Atmojo Triwanti Andini Hutasoit Veryawan, Veryawan Waliyul M Siregar Warjaya, Angga winsyahputra Ritonga Yazid Noor, Muhammad Yulita Molliq Rangkuti Zul Amry Zulfahrizan, Atta