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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) Technomedia Journal 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 Prosiding National Conference for Community Service Project Abdimas Galuh: Jurnal Pengabdian Kepada Masyarakat JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) Community Development Journal: Jurnal Pengabdian Masyarakat BERNAS: Jurnal Pengabdian Kepada Masyarakat Infotech: Journal of Technology Information Jurnal Teknologi Informatika dan Komputer JURNAL PENDIDIKAN SAINS SOSIAL DAN AGAMA Jurnal Teknimedia: Teknologi Informasi dan Multimedia 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 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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An Investigation of Using Think Talk Write Strategy to Enhance Writing Procedure Text Mungkap Mangapul Siahaan; Setia Oktaviana Sirait; Irene Adryana Nababan
Edu Cendikia: Jurnal Ilmiah Kependidikan Vol. 4 No. 03 (2024): Research Articles, December 2024
Publisher : ITScience (Information Technology and Science)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/educendikia.v4i03.4852

Abstract

This study aims to investigate the effect of using the Think Talk Write Strategy on the writing procedure text capability of eleventh-grade students at vocational SMK GKPI 1 Pematangsiantar. This research used a quasi-experimental research design. The population of this study was the eleventh-grade students of vocational SMK GKPI 1 Pematangsiantar, and the total number of students was 216. The sample of this study was divided into two classes: the experimental class was (XI KW), consisting of 27 students who used the Think Talk Write strategy, and the control class (XI TJTL) was composed of 27 students who only used the cturing strategy. The data collection instruments used writing tests for the pre-test and post-test. Brown’s writing assessment rubric was used in this research, and it included content, organization, grammar, vocabulary, and mechanics. SPSS 26 Version was used to analyze the data by conducting descriptive analysis, normality test, Wilcoxon test, homogeneity test, and Mann-Whitney test. The data analysis using the Mann-Whitney test showed that the Assymp. Sig (2-tailed) value of 0.007< 0.05. Based on these findings, Ha is accepted, and Ho is rejected. Therefore, it can be concluded that The ink Talk Write Strategy significantly affected the writing procedure text capability of the eleventh-grade students at vocational SMK GKPI I Pematangsiantar.
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.
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
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
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
ANALISIS KEAMANAN SISTEM INFORMASI MENGGUNAKAN ALGORITMA SUPPORT VECTOR MACHINE TERHADAP PENGGUNA SHOPEE Muhamad Dody Firmansyah; Christopher Christopher; Mangapul Siahaan
TEKNIMEDIA: Teknologi Informasi dan Multimedia Vol. 7 No. 1 (2026): June 2026
Publisher : Badan Penelitian dan Pengabdian Masyarakat (BP2M) STMIK Syaikh Zainuddin NW Anjani

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46764/teknimedia.v7i1.344

Abstract

The expansion of e-commerce in Indonesia has made information system security a crucial concern, especially on sites like Shopee that see a lot of user activity and transaction volumes. Potential security hazards, such as account misuse, unauthorized access, and suspicious activity, are increased by the volume of online transactions. Therefore, in order to comprehend the elements linked to security threats based on user characteristics and behavioral patterns, an analytical approach is necessary. The purpose of this study is to apply machine learning to examine security risk tendencies among Shopee users. A standardized questionnaire addressing demographic factors, usage frequency, security awareness levels, and experiences with questionable activity was used to gather data from 101 active users. Data cleaning, label encoding, Min–Max normalization, and feature selection were among the steps in the data processing procedure. The classification model used was the Support Vector Machine (SVM) technique with a Radial Basis Function (RBF) kernel. The creation of a security risk analysis model based on user perceptions and behavioral aspects rather than system log or transactional data is what makes this study unique. By using non-technical indications as predictive factors in e-commerce platforms, this method provides an alternate viewpoint for spotting possible security threats.
PERANCANGAN APLIKASI SOFTWARE DEFECT DETECTION DENGAN ALGORITMA BACKPROPAGATION, PCA DAN SVM Mangapul Siahaan; Rubin Rubin; Syaeful Anas Aklani
Infotech: Journal of Technology Information Vol 12, No 1 (2026): JUNI
Publisher : ISTEK WIDURI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37365/jti.v12i1.579

Abstract

Software defects are a major issue in software development because they can affect the quality, reliability, and performance of a system. As digital technology advances at an increasingly rapid pace, software complexity is also rising, thereby increasing the likelihood of software defects. This study aims to apply and compare several machine learning and artificial intelligence methods for detecting software defects. The methods used in this study include Support Vector Machine (SVM), Principal Component Analysis (PCA) as a dimension reduction technique, and Backpropagation as a neural network-based method. The research process was conducted through a series of experiments to evaluate and compare the performance of each method based on the accuracy values obtained. The results show that the combination of SVM and PCA provides the best performance in detecting software defects compared to other methods. The highest accuracy obtained was 85.78% when using 13, 15, and 16 PCA components. Meanwhile, SVM without PCA achieved an accuracy of 85.47%, and Backpropagation achieved an accuracy of 84.83%. These results indicate that the application of PCA is capable of improving SVM classification performance through a dimension reduction process that preserves important features in the dataset. However, the performance achieved is still influenced by the characteristics of the dataset, the data distribution, and the model configuration used.
Co-Authors , Loren Adi Agnes Sianipar Agung Rizky Ahmad Gunawan Ahmad Mawardi Lubis 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 Chintya Lorenz Christian S. Putra Girsang Christian, Yefta Christopher Christopher Christopher Harsana Jasa Daniel Arnoldi Gultom Darius Angtony David Gordon Gultom Dedy Susanto Deli Derlina Derlina Dewi, Syasya Tri Puspita Dian Winda Tamba Edwards, John Efrinda Yuliarmi Damanik Eka Setiawati Erica Titoni Eryc, Eryc Febri Yanti Firmansyah, Muhamad Dody Fitri May Danthi Saragih Frank Lurich Gabriella Clarisa Silaban Gabriella, Jessica Glorya Natalia Rohani Napitupulu Gultom, Erwin Geovanis Guntara, Muhammad Arif Hafizh akmal Hafizh Akmal Haloho, Uci Nursanty Handyca Yeng Hansen Jonatan Hansvirgo Hansvirgo Hendi Che Hendi Sama Heppy Theresia Sitompul Herna Febrianty Sianipar Herna Febrianty Sianipar Hisar Marulitua Manurung Hutahaean, David Togi Hutahaean, Grace Saurma Indasari Deu Irene Adryana Nababan Irene Adryani Nababan Jason Angelo Ong Jefriyanto Chandra Jennifer Jennifer Jocelyn Jocelyn Joen Lie Julia Julia Justin Justin Kamal Arif Al-Farouqi Kelvin Kelvin Kurniawan Kenidy, Ryan Kevin Anderson Kevin William Andri Siahaan Kgomotso Moyo Khomali, Carlos Justin Kristiani Siagian Kristina Vaher Leonita Maria E Manihuruk Liang, Suwarno Lie, Joen Lim, Tevin Lim, Vincent 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 Muhtarom Muthia Andini Nababan, Irene Adryana Nainggolan, Lonatasya Sevari Nancy Vanessa Nancy Vanessa Napitupulu, Selviana Nopia Sihombing Novita Forena Simanungkalit Oktaviani, Katherine Oktavina Oktavina Pane, Eva Pratiwi PANJAITAN, MUKTAR B Paroli Paroli 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 Randy Sitompul Rendhika Adyatama Restu Maulana Nashuha Richard Andre Sunarjo Ricky Hartanto Rizky Sebastian Rosalia, Balinda Oca Roy Valentino Chandra Rubin Gu Rubin Rubin Ruth Yuni Lisa Simangunsong Ryan Kenidy Ryan Kenidy Sabariman Sabariman Sabariman Sabariman Sama, Hendi Sama, Hendi Samosir, Hottua Sanggam Magda Lasmaria Siahaan Sanggam Siahaan Sarah Aufah Athiya Satria Lim Setia Oktaviana Sirait Setiawan Joddy 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 Steven Harazaki Lase Sudy Sumiati Butar-Butar Sunoto Sunoto Suwarno Liang Suwarno Liang Suwarno Suwarno Syaeful Anas Aklani, Syaeful Syahputra, Bayu Syahrul Muarif Wahid Syasya Tri Puspita Dewi Taai, Derwin Tambunan, Betty Jeniari Tambunan, Marlina Agkris Terizla, Rizky Fredrin Tessa Handra Tevin Lim Theresia Monika Siahaan Thesalonika, Emelda Tiarma Intan Marpaung Tiarma Marpaung Tjahyadi, Surya Toktar Kerimbekov TRI SUSANTI Tukino Tukino Vanessa, Nancy Vendhy Vendhy Vincent Lim Vincent Octarian Vianto Wahyu Yudianto Wenky, Wenky Wijaya, Ricky Wijaya Wilson Wilson Yanti Kristina Sinaga Yanti kristina Sinaga Yanto Gui Yeng, Handyca Yeni Enjela Sianturi Yosua Marasi Parningotan Siagian Yulsen Yulsen Zulkarnain Zulkarnain Zulkarnain