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All Journal JURNAL SISTEM INFORMASI BISNIS Techno.Com: Jurnal Teknologi Informasi EDUTECH: Jurnal Ilmu Pendidikan dan Ilmu Sosial CESS (Journal of Computer Engineering, System and Science) Al Ishlah Jurnal Pendidikan JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING SCIENCE TECH: Jurnal Ilmiah Ilmu Pengetahuan dan Teknologi Syntax Literate: Jurnal Ilmiah Indonesia IJIS - Indonesian Journal On Information System JOURNAL OF APPLIED INFORMATICS AND COMPUTING METHOMIKA: Jurnal Manajemen Informatika & Komputerisasi Akuntansi Jurnal Sisfokom (Sistem Informasi dan Komputer) Jurnal Teknik Informatika UNIKA Santo Thomas INTECOMS: Journal of Information Technology and Computer Science Wacana: Jurnal Ilmiah Ilmu Komunikasi Jurnal Basicedu Journal of Education Technology Aptisi Transactions on Technopreneurship (ATT) SALTeL Journal (Southeast Asia Language Teaching and Learning) JURNAL TEKNOLOGI INFORMASI Jurnal Mantik Jutisi: Jurnal Ilmiah Teknik Informatika dan Sistem Informasi Technologia: Jurnal Ilmiah Bahastra: Jurnal Pendidikan Bahasa dan Sastra Indonesia Jurnal Pendidikan dan Konseling Jurnal Teknologi Informasi dan Multimedia Prosiding National Conference for Community Service Project JOURNAL OF INFORMATION SYSTEM MANAGEMENT (JOISM) Abdimas Galuh: Jurnal Pengabdian Kepada Masyarakat JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) Community Development Journal: Jurnal Pengabdian Masyarakat BERNAS: Jurnal Pengabdian Kepada Masyarakat Jurnal Teknologi Informatika dan Komputer JURNAL PENDIDIKAN SAINS SOSIAL DAN AGAMA Journal of Applied Data Sciences Mitra Mahajana: Jurnal Pengabdian Masyarakat International Journal of Multidisciplinary: Applied Business and Education Research KLIK: Kajian Ilmiah Informatika dan Komputer Dharmas Education Journal (DE_Journal) Journal of Information System and Technology (JOINT) Edu Cendikia: Jurnal Ilmiah Kependidikan Nama jurnal : International Journal of Education and Humanities Bulletin of Information Technology (BIT) International Journal of Social Science, Educational, Economics, Agriculture Research, and Technology (IJSET) Jurnal Teknik Informatika Unika Santo Thomas (JTIUST) Joong-Ki : Jurnal Pengabdian Masyarakat KOMMAS: Jurnal Pengabdian Kepada Masyarakat Jurnal Basicedu Jurnal Ilmu Pendidikan dan Sosial Mamangan Social Science Journal Jurnal MENTARI: Manajemen, Pendidikan dan Teknologi Informasi Indonesian Research Journal on Education Innovative: Journal Of Social Science Research TOFEDU: The Future of Education Journal Conference on Management, Business, Innovation, Education and Social Sciences (CoMBInES) Conference on Community Engagement Project (Concept) Conference on Business, Social Sciences and Technology (CoNeScINTech) Social Engagement: Jurnal Pengabdian Kepada Masyarakat Jurnal Ilmiah Research Student Jurnal Sains Student Research Cendikia Pendidikan Joong-Ki Jurnal Ilmiah Betrik : Besemah Teknologi Informasi dan Komputer Blockchain Frontier Technology (BFRONT) Bilingual : Jurnal Pendidikan Bahasa Inggris JURNAL PENDIDIKAN BAHASA Pengembangan Penelitian Pengabdian Jurnal Indonesia (P3JI) Pande Nami Jurnal (PNJ) Joong-Ki INOVTEK Polbeng - Seri Informatika Journal of Computer Science and Technology Application Jurnal Informatika
Mungkap Mangapul Siahaan
Universitas Internasional Batam
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The Effect Of Using Fluentu on Student' Reading Comprehension at Grade Eleven Manurung, Sri Maneni; Purba, Rudiarman; Marpaung, Tiarma Intan; Siahaan, Mungkap Mangapul
Jurnal Ilmu Pendidikan dan Sosial Vol. 5 No. 1 (2026): April
Publisher : CV Putra Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58540/jipsi.v5i1.1448

Abstract

This research aims to investigate the effect of the FluentU application on the reading comprehension of eleventh-grade students. FluentU is an AI-assisted language learning application that uses authentic video content, such as movie clips, music videos, and interviews, integrated with interactive subtitles and vocabulary tools to improve learners’ listening, reading, and comprehension skills in a real-world context. This study employed a quantitative research design with a quasi-experimental approach. The population of this research consisted of eleventh-grade students of SMK Negeri 1 Siantar in the academic year 2024/2025. Two classes were taken as the sample: XIBS-1 as the experimental group (36 students) and XIBS-2 as the control group (36 students). The samples were selected using purposive sampling. The experimental group was taught using the FluentU application, while the control group was taught using conventional methods. Data were collected through pre-tests and post-tests administered to both groups. The findings showed that the mean pre-test score of the experimental group was 67.78, while the control group obtained 62.78. Furthermore, the mean post-test score of the experimental group was 81.94, compared to 75.14 in the control group. The standard deviations were 8.475 for the experimental group and 7.791 for the control group. Data analysis using the t-test revealed a Sig. (2-tailed) value of 0.000 < 0.05, indicating that the alternative hypothesis (Ha) was accepted and the null hypothesis (H0) was rejected. Therefore, it can be concluded that the use of the FluentU application has a significant effect on the reading comprehension of eleventh-grade students at SMK Negeri 1 Siantar
THE ANALYSIS OF USING ARTICULATE STORYLINE IN THE NARRATIVE TEXT OF EIGHTH GRADE AT MTS ALHIDAYAH ISLAMIYAH SOSIAL, HATONDUHAN IN 2024/2025 ACADEMIC YEAR Sarah Aufah Athiya; Mungkap Mangapul Siahaan; Yanti Kristina Sinaga; Irene Adryani Nababan
International Journal of Social Science, Educational, Economics, Agriculture Research and Technology (IJSET) Vol. 4 No. 10 (2025): SEPTEMBER
Publisher : RADJA PUBLIKA

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

Abstract

This research aims to analyze students’ reading comprehension ability and the difficulties they encounter in learning English. According to Sugiyono (2011: 55), a qualitative research method is a research method based on the philosophy of post-positivism, used to research natural object conditions (as opposed to experiments) where the researcher is the key instrument, data source sampling is carried out purposively and snowball, data collection techniques with triangulation (combination), data analysis is inductive or qualitative, and qualitative research results emphasize meaning more than generalization. The study employed a qualitative descriptive method involving 30 eighth-grade students as respondents. Data were collected through observation and interviews to obtain a detailed understanding of students’ reading performance. The results indicate that students’ reading comprehension ability is divided into three levels: low, middle, and high. Among the participants, 15 students (50%) are categorized as low, 8 students (26.7%) as middle, and 7 students (23.3%) as high. These findings suggest that the majority of students still face difficulties in understanding the content and meaning of English narrative texts. The study highlights the importance of using effective learning media and teaching strategies to enhance students’ English reading comprehension.
Distributed Data Integrity and Decentralized Storage Leveraging IPFS in Blockchain Systems Gunawan, Ahmad; Siahaan, Mungkap Mangapul; Adyatama, Rendhika; Kerimbekov, Toktar; Vaher, Kristina
Blockchain Frontier Technology Vol. 5 No. 2 (2026): Blockchain Frontier Technology
Publisher : IAIC Bangun Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34306/bfront.v5i2.915

Abstract

In the digital era that increasingly relies on distributed systems, data integrity has become a major challenge for various technological platforms, ranging from cloud services to blockchain-based infrastructures. The dispersion of data across multiple nodes without centralized oversight increases the risk of manipulation, loss, and inconsistency. This study aims to evaluate the effectiveness of the InterPlanetary File System (IPFS) as a distributed data storage solution capable of maintaining data integrity in an automatic, efficient, and verifiable manner. The research method involves a literature review of 30 scientific references and a case study-based simulation conducted within a local network consisting of four active IPFS nodes. The tests include file uploads, verification of Content Identifiers (CID), simulation of node failures, and evaluation of system performance based on parameters such as security, efficiency, and scalability. The results indicate that IPFS successfully detects file changes through CID discrepancies, ensures continued data access despite node failures, and optimizes bandwidth usage via caching and replication mechanisms. In conclusion, IPFS offers a secure, scalable, and tamper-resistant approach to distributed data storage, making it highly relevant for modern digital systems requiring transparency, reliability, and strong data integrity guarantees.
HOW IMPORTANT MARKET AND TECHNOLOGICAL ALIGNMENT IN DEVELOPING PROACTIVE DECISION-MAKING AND DESIGN FLEXIBILITIES: A SYSTEMATIC LITERATURE REVIEW Sama, Hendi; Gabriella, Jessica; Siahaan, Mangapul
IJIS - Indonesian Journal On Information System Vol 11, No 1 (2026): APRIL
Publisher : POLITEKNIK SAINS DAN TEKNOLOGI WIRATAMA MALUKU UTARA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36549/ijis.v11i1.436

Abstract

This systematic literature review examines how aligning market demands with technology fosters proactive decision-making. Synthesizing recent academic literature, it confirms that AI-driven analytics are crucial for shifting organizations to a proactive strategic posture, enhancing agility and forecasting. However, this transformation is hindered by significant challenges, including dependency on data quality, integration complexity, financial barriers, and ethical issues like algorithmic bias. Successful adoption requires robust risk management and the strategic integration of human oversight—encompassing critical evaluation and ethical judgment—into the data-driven process. This research provides a framework for balancing technological adoption with human-centric governance to help organizations remain competitive in the digital age. Keywords: Market and Technology Alignment, Proactive Decision-Making, Design Flexibility.
Implementing Mobile-based AI in Household Waste Type and Condition Classification Suwarno, Suwarno; Lie, Joen; Siahaan, Mangapul
Bulletin of Information Technology (BIT) Vol 7 No 1: Maret 2026
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bit.v7i1.2504

Abstract

Urbanization and population growth have significantly increased waste generation, creating challenges for effective waste management and recycling. Improper waste sorting and management often results to unrecyclable waste contaminating recycling streams or recyclable waste ending up in landfill. This research presents a mobile-based waste classification application that integrates YOLOv11n for real-time object detection, and uses TensorFlow Lite with a Flutter-based user interface. The model was trained on a dataset of 4,410 images, which combines self-gathered images and images from Kaggle dataset. The images are then augmented to 10,936 images covering 23 waste classes, including organic, inorganic, hazardous, and residual types, with their recyclability conditions. The application allows users to detect objects using their phone camera, to identify their classification and condition, as well as receive actionable 3R (Reduce, Reuse, Recycle) recommendations. Evaluation results show a precision of 0.5963, recall of 0.60563, mAP@0.5 of 0.62246, and mAP@0.5:0.95 of 0.5279, indicating decent classification despite challenges posed by visually similar objects and variable backgrounds. Overall, the system demonstrates the feasibility of deploying a lightweight AI model on mobile devices in hopes of supporting proper waste segregation, increase user awareness, and potentially reduce contamination in recycling streams through practical waste classification.
Semi-Supervised Bullying Detection in Narrative Student Counselling Reports Using a Hybrid CNN-LSTM with Pseudo-Labelling Suwarno Suwarno; Muthia Andini; Mangapul Siahaan
Jurnal Informatika Vol. 13 No. 1 (2026): April
Publisher : Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/ji.v13i1.11512

Abstract

Bullying incidents in schools are often documented in narrative student counselling reports containing informal language, emotional expressions, and contextual dependencies, which pose challenges for automated text classification, particularly under limited labeled data conditions. This study aims to develop a bullying detection model for narrative student counselling reports using a Hybrid CNN-LSTM architecture combined with a pseudo-labelling-based semi-supervised learning approach. The proposed model is trained through a two-stage process, consisting of pre-training on approximately 70,000 publicly available abusive-language texts and fine-tuning using 1,000 anonymized student counselling reports validated by guidance counsellors. Pseudo-labelling is employed to expand the training data while preserving domain relevance and adhering to ethical considerations. Experimental results show that the proposed model achieves an accuracy of 0.8698, a recall of 0.8570, and an F1-score of 0.7951. Although the precision value (0.7415) is relatively lower, higher recall is prioritized to reduce the risk of overlooking potential bullying cases in the school counselling context. Comparative analysis with Logistic Regression and Linear SVM indicates that the Hybrid CNN-LSTM model demonstrates more stable performance when processing longer narrative inputs that require contextual interpretation. This study contributes empirical evidence on the effectiveness of semi-supervised deep learning for bullying detection in low-resource, narrative student counselling data, a setting that remains underexplored in prior work.
Behavioral Manipulation In Big Data Implementation: Systematic Literature Review Hendi Sama; Mangapul Siahaan; Nancy Vanessa
Techno.Com Vol. 25 No. 1 (2026): February 2026
Publisher : LPPM Universitas Dian Nuswantoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62411/tc.v25i1.15099

Abstract

This study investigated the phenomenon of behavioral manipulation in big data implementation through a systematic literature review of thirty peer-reviewed articles published between 2020 and 2025. The objective of the review was to provide a comprehensive understanding of the mechanisms, impacts, and mitigation strategies related to the use of big data for influencing human behavior. The review was conducted following the PRISMA 2020 framework, ensuring transparency and reproducibility in the selection and evaluation process. Out of an initial 250 records identified across major academic databases, 30 studies were ultimately included based on predefined inclusion and exclusion criteria. The analysis revealed that behavioral manipulation was primarily executed through algorithmic recommendation systems, dynamic pricing models, deceptive interface design, and data-driven persuasion techniques. The reviewed studies indicated that such practices compromised individual autonomy, shaped consumer and political decisions, and contributed to psychological strain and social inequality. The findings also highlighted the paradox of algorithmic transparency, showing that disclosure without user comprehension could legitimize manipulation rather than reduce it. Furthermore, evidence suggested that emerging interventions, such as dynamic consent mechanisms and independent algorithmic audits, showed potential in restoring trust and protecting user rights, although their implementation remained limited. Approximately 83.3% of the reviewed studies concluded that behavioral manipulation through big data is a multidimensional challenge requiring an integrated response that combines technical safeguards, ethical design, adaptive regulation, and enhanced digital literacy.   Keywords - Behavioral manipulation, Big data implementation, Decision making
Iris Identification Using Resnet Iris Feature Extraction Architecture For Better Biometric Security Sama, Hendi; Tukino, Tukino; Siahaan, Mangapul; Titoni, Erica
Journal of Applied Data Sciences Vol 7, No 2: May 2026
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v7i2.1166

Abstract

Iris recognition is widely acknowledged as one of the most reliable biometric modalities due to its high uniqueness, rich textural patterns, and long-term stability. Unlike other biometric traits, iris characteristics resist forgery, aging effects, and environmental variations, making it suitable for high-security applications. Recently, convolutional neural networks (CNNs) have been extensively applied in iris recognition to improve feature representation and classification accuracy. However, many CNN-based approaches still depend on conventional segmentation and handcrafted features, which reduce robustness under noisy data, illumination variations, occlusions, or unconstrained environments. To address these limitations, this study proposes an enhanced iris identification framework combining a modified T-Net for precise segmentation with deep residual feature extraction for improved discrimination. Unlike conventional systems focus mainly on classification, the proposed approach emphasizes segmentation-driven feature consistency, ensuring extracted features originate from accurately localized iris regions. This design enhances stability and reliability, particularly under challenging imaging conditions. The framework leverages transfer learning and efficient representation learning strategies, enabling high accuracy even with a limited labelled data. Evaluations on three benchmark datasets CASIA-IrisV4, IITD Iris Database, and UBIRIS.v2 covering both controlled and less-constrained acquisition scenarios. Results show that it achieves classification accuracy of up to 98.35%, while maintaining computational efficiency suitable for deployment. The proposed architecture offers a robust, data-efficient, and scalable solution for secure biometric authentication, with strong potential for real-world applications such as access control, identity verification, and high-security authentication systems.
Efektivitas Learning Management System terhadap Hasil Belajar Siswa SMP Plus Al Kaffah Firmansyah, Muhamad Dody; Guntara, Muhammad Arif; Siahaan, Mangapul
Technologia : Jurnal Ilmiah Vol 17, No 2 (2026): Technologia (April)
Publisher : Universitas Islam Kalimantan Muhammad Arsyad Al Banjari

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31602/tji.v17i2.22363

Abstract

Pembelajaran berbasis teknologi semakin menuntut penggunaan sistem yang mampu mendukung proses evaluasi secara terukur. Penelitian ini mengkaji pemanfaatan sistem manajemen pembelajaran dalam meningkatkan hasil belajar siswa melalui penerapan metode pretest dan posttest. Penelitian dilakukan dengan pendekatan kuantitatif menggunakan desain eksperimen satu kelompok pada siswa kelas VII SMP Plus Al Kaffah Batam. Tahapan penelitian meliputi pengukuran kemampuan awal siswa, pelaksanaan pembelajaran berbasis sistem manajemen pembelajaran, serta pengukuran hasil belajar setelah perlakuan diberikan. Data dianalisis secara statistik untuk melihat perbedaan capaian belajar sebelum dan sesudah pembelajaran. Temuan penelitian menunjukkan adanya peningkatan hasil belajar siswa setelah penerapan sistem manajemen pembelajaran, sehingga sistem tersebut berpotensi mendukung proses pembelajaran dan evaluasi hasil belajar di tingkat sekolah menengah pertama.
Penerapan Program Les Sore Pengabdian kepada Masyarakat (PKM) Universitas HKBP Nommensen Pematangsiantar dalam Meningkatkan Motivasi Belajar Siswa Sekolah Dasar di Desa Manik Hataran Marbun, Shopia Sonata; Siahaan, Mungkap Mangapul; Yosua Marasi Parningotan Siagian; Ruth Yuni Lisa Simangunsong; Christian S. Putra Girsang; Efrinda Yuliarmi Damanik; Agnes Sianipar; Mawar Febrianti Irene Manurung; Paulus Nugraha Simanjuntak; Cesya Rosenta Purba; Nopia Sihombing
BERNAS: Jurnal Pengabdian Kepada Masyarakat Vol. 7 No. 2 (2026)
Publisher : Universitas Majalengka

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31949/jb.v7i2.17907

Abstract

Pelaksanaan pengabdian kepada masyarakat ini dilatarbelakangi oleh rendahnya motivasi belajar siswa sekolah dasar di Desa Manik Hataran yang ditandai dengan kurangnya partisipasi, rendahnya pemahaman materi, serta keterbatasan pendampingan belajar di luar sekolah. Tujuan kegiatan ini adalah untuk meningkatkan motivasi dan kemampuan belajar siswa melalui program les sore. Metode yang digunakan adalah Participatory Action Research (PAR) yang meliputi tahapan sosialisasi awal, pemetaan sosial, perencanaan partisipatif, pelaksanaan aksi, serta monitoring dan evaluasi. Kegiatan dilaksanakan selama sepuluh hari dengan melibatkan 40 siswa SD Negeri 091440 Manik Hataran. Hasil kegiatan menunjukkan adanya peningkatan yang signifikan pada partisipasi belajar, keterampilan membaca, menulis, menghitung, serta motivasi dan minat belajar siswa, yang awalnya berada pada kategori sedang meningkat menjadi kategori tinggi setelah mengikuti program les sore. Dengan demikian, program les sore terbukti efektif dalam meningkatkan motivasi dan kualitas belajar siswa
Co-Authors , Loren Adi Adyatama, Rendhika Agnes Sianipar Ahmad Gunawan Ahmad Mawardi Lubis Aklani , Syaeful Anas Andik Yulianto Anita Panjaitan Anita Sitanggang Annisya Putri Nadhia Anton Luvi Siahaan Apriani Sijabat Ariq Bimantoro Balinda Oca Rosalia Basar Lolo Siahaan Bertaria Sohnata Hutauruk Canni Loren Sianturi Cesya Rosenta Purba Chandra, Jefriyanto Christian S. Putra Girsang Christian, Yefta Christopher Harsana Jasa Daniel Arnoldi Gultom Darius Angtony David Gordon Gultom Dedy Susanto Deli Dewi, Syasya Tri Puspita Edwards, John Efrinda Yuliarmi Damanik Eka Setiawati Eryc, Eryc Febri Yanti Firmansyah, Muhamad Dody Firmansyah, Muhammad Dody Fitri May Danthi Saragih Frank Lurich Gabriella Clarisa Silaban Gabriella, Jessica Glorya Natalia Rohani Napitupulu Gultom, Erwin Geovanis Guntara, Muhammad Arif Hafizh akmal Haloho, Uci Nursanty Handyca Yeng Hansvirgo Hendi Che Hendi Sama Heppy Theresia Sitompul Herna Febrianty Sianipar Herna Febrianty Sianipar Hisar Marulitua Manurung Hutagaol, Yevana Arthika Hutahaean, David Togi Hutahaean, Grace Saurma Indasari Deu Irene Adryana Nababan Irene Adryani Adryani Nababan Jason Angelo Ong Jennifer Jennifer Jocelyn Jocelyn Julia Julia Justin Justin Kelvin Kelvin Kurniawan Kenidy, Ryan Kerimbekov, Toktar Kevin Anderson Kevin William Andri Siahaan Khomali, Carlos Justin Kristiani Siagian Leonita Maria E Manihuruk Liang, Suwarno Lie, Joen Lim, Tevin Lim, Vincent Lorenz, Chintya Manurung, Sri Maneni Marbun, Lastri Evati Mori Marbun, Shopia Sonata Maret Ningsihermina Sihombing Maryanto Saragih Maulana, Azhar Mawar Febrianti Irene Manurung Meilani Sidabutar Melda Veby Ristella Munthe Melissa Valentino Rosiana Mely Christi Sihotang Mikhael Chendra Muhamad Dody Firmansyah Muhammad Dody Firmansyah Muhammad Ridho Alfarizi Muhammad Sulton Maulana Muthia Andini Nababan, Irene Adryana Nainggolan, Lonatasya Sevari Nancy Vanessa Napitupulu, Selviana Nopia Sihombing Novita Forena Simanungkalit Oktaviani, Katherine Oktavina Oktavina Pane, Eva Pratiwi PANJAITAN, MUKTAR B Partohap S. R Sihombing, Partohap S. R Partohap Sihombing Pasaribu, Sunggul Paulus Nugraha Simanjuntak Purba, Christian Neni Purba, Johannes Riscy Purba, Rudiarman Purba, Yoel Octobe Restu Maulana Nashuha Ricky Hartanto Rosalia, Balinda Oca Roy Valentino Chandra Ruth Yuni Lisa Simangunsong Ryan Kenidy Ryan Kenidy Sabariman Sabariman Sabariman Sabariman Sama, Hendi Samosir, Hottua Sanggam Magda Lasmaria Siahaan Sanggam Siahaan Sarah Aufah Athiya Satria Lim Sebastian, Rizky Setia Oktaviana Sirait Setiawan Joddy Siahaan, Basar Lolo Siahaan, Rina Devi Siahaan, Theresia Monika SIANTURI, TAMBOS AUGUST Sibagariang, Susy Alestriani Sibarani, Ega Putri Sani Sidabutar, Ropinus Sihombing, Santa R Silitonga, Immanuel Douglas Silvia Torong Simangunsong, Anita Debora Br. Simanjuntak, Fredian Simanjuntak, Harry Cristofel Simatupang, Leo Fernando Sinaga, Asima Rohana Sinaga, Asima Rohani Sinaga, Christa Voni Roulina Sinaga, Lambok Hasudungan Pratama Yuda Sinurat, Bloner Sirait, Esti Marlina Sirait, Jumaria Sirait, Setia Oktaviana Siska Natalia Situmeang Sitorus, Ester Sudy Sumiati Butar-Butar Sunarjo, Richard Andre Sunoto Suwarno Liang Suwarno Suwarno Suwarno Suwarno Syaeful Anas Aklani, Syaeful Syahputra, Bayu Syasya Tri Puspita Dewi Taai, Derwin Tamba, Dian Winda Tambunan, Betty Jeniari Tambunan, Marlina Agkris Terizla, Rizky Fredrin Tevin Lim Theresia Monika Siahaan Thesalonika, Emelda Tiarma Intan Marpaung Tiarma Marpaung Titoni, Erica Tjahyadi, Surya TRI SUSANTI tukino, tukino Vaher, Kristina Vanessa, Nancy Vendhy Vendhy Vincent Octarian Vianto Wahid, Syahrul MuArif Wahyu Yudianto Wenky, Wenky Wijaya, Ricky Wijaya Wilson Wilson Yanti kristina Sinaga Yeng, Handyca Yeni Enjela Sianturi Yosua Marasi Parningotan Siagian Yulsen Yulsen, Yulsen Zulkarnain Zulkarnain Zulkarnain