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All Journal JURNAL SISTEM INFORMASI BISNIS 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 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 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 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 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
Mungkap Mangapul Siahaan
Universitas Internasional Batam
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The Effect of Picture and Picture Media on Understanding Writing Procedural Texts among Eighth-Grade Students at SMP HKBP Batu 4 Sinaga, Lambok Hasudungan Pratama Yuda; Manihuruk, Leonita Maria Efipanias; Hutahaean, David Togi; Siahaan, Mungkap Mangapul; Purba, Christian Neni; Pasaribu, Sunggul
Indonesian Research Journal on Education Vol. 4 No. 4 (2024): irje 2024
Publisher : Fakultas Keguruan dan Ilmu Pendidikan, Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/irje.v4i4.1676

Abstract

This research was carried out to find out the Effect of Picture and Picture Media on Understanding Writing Procedure Text at Grade Eight students of SMP HKBP Batu 4. The research methodology used in this research was a quantitative method. The population of this research was at grade VIII of SMP HKBP Batu 4 in the academic year 2024/2025. The researcher took two classes as the sample. The samples were VIII-A as experimental group consisted of 25 students and VIII-B as control group consisted of 25 students. Data collection was carried out using essay tests. The data were obtained by using pre-test and post-test given to both groups, score were calculated and analyzed using excel and manual method. The research results showed that the average score of the experimental class was a pre- test score of 63 and post-test score of 82.68. Meanwhile, the average score for the control class was a pre-test score of 57.56 and post-test 74.12. The t-test calculation shows that (8.8>2.068) at a significance level of 2.5%, a two-sided test means the null hypothesis (HO) is rejected and the alternative hypothesis (Ha) is accepted. This means that the effect of Picture and Picture on Understanding Writing Procedure Text at Grade Eight Students of SMP HKBP Batu 4.
Designing a Web-Based Light Novel Application with an LLM-Powered Chatbot Recommendation System Using Scrum Methodology Christian, Yefta; Siahaan, Mangapul; Hansvirgo
METHOMIKA: Jurnal Manajemen Informatika & Komputerisasi Akuntansi Vol. 8 No. 2 (2024): METHOMIKA: Jurnal Manajemen Informatika & Komputersisasi Akuntansi
Publisher : Universitas Methodist Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46880/jmika.Vol8No2.pp174-186

Abstract

In the era of the internet’s exponential growth, readers are often overwhelmed by the plethora of books available, particularly in the genre of light novels. This research aims to address this issue by developing a recommendation system for light novels, utilizing a chatbot interface. The methodology employed follows the Borg and Gall model, with a focus on research, information collection, planning, and development stages. The research stage involved the use of questionnaires to gather data and analyze the parameters to be used in the recommendation system. The development stage was carried out using the Scrum methodology and the Retrieval Augmented Generation (RAG) approach for the chatbot’s functionality. The outcome of this study is a web-based online light novel application and featuring a chatbot conversational recommender system. Through this system, users can access and read light novels online, while also utilizing the chatbot to request novel recommendations. The research findings demonstrate the successful integration of Large Language Model (LLM) technology into the web-based light novel application. The Scrum development approach facilitated efficient system creation, and the RAG-based chatbots are seen as successful in producing recommendations that match user queries based on existing knowledge. Recommendation results are obtained from semantic search and from the ranking vector with the highest score.
Perancangan Sistem Prediksi Harga Saham Berbasis Website Menggunakan Algoritma Hybrid (ARIMA-LSTM) Yeng, Handyca; Siahaan, Mangapul
Jutisi : Jurnal Ilmiah Teknik Informatika dan Sistem Informasi Vol 13, No 1: April 2024
Publisher : STMIK Banjarbaru

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35889/jutisi.v13i1.1620

Abstract

Stock investment, known as a high-risk, high-return instrument, has gained significant attention during the pandemic with a notable 44.42% increase in novice investors in Sidoarjo City. This research focuses on developing a web-based stock price prediction system utilizing a hybrid algorithm (ARIMA-LSTM) and integrating the Extreme Programming method in its development. Quantitative stock price data were obtained from Yahoo Finance. The research outcome is an implemented system that meets user requirements. More importantly, the system is capable of providing stock price predictions that closely align with actual data for the period from 2018 to 2022. Model evaluation employing Mean Squared Error (MSE) yielded a value of 0.0078, Mean Absolute Error (MAE) with a value of 0.556, and Mean Absolute Percentage Error (MAPE) at 0.412, which is equivalent to 41.89%. These evaluation results indicate that the hybrid ARIMA-LSTM model performs well, delivering accurate predictions. This research has the potential to benefit investors, financial analysts, and stock market stakeholders, enabling more informed and efficient decision-making.Keywords: Stock Prediction; Hybrid Algorithm; Extreme Programming; Web-Based System; ARIMA-LSTM.AbstrakInvestasi saham, yang dikenal sebagai instrumen high risk, high return, menjadi sorotan selama pandemi dengan peningkatan signifikan investor pemula sebesar 44.42% di Kota Sidoarjo. Penelitian ini berfokus pada pengembangan sistem prediksi harga saham berbasis website dengan memanfaatkan algoritma hybrid (ARIMA-LSTM) dan mengintegrasikan metode Extreme Programming dalam pengembangannya. Data harga saham yang digunakan diperoleh melalui Yahoo Finance secara kuantitatif. Hasil penelitian ini adalah sistem yang berhasil diimplementasikan dan sesuai dengan kebutuhan pengguna. Lebih penting, sistem ini mampu memberikan prediksi harga saham yang mendekati data aktual untuk periode tahun 2018 hingga 2022. Evaluasi model menggunakan MSE (Mean Squared Error) dengan nilai 0.0078, MAE (Mean Absolute Error) dengan nilai 0.556, MAPE (Mean Absolute Percentage Error) dengan nilai 0.412 yaitu 41.89%. Hasil evaluasi ini menunjukkan bahwa model hybrid ARIMA-LSTM berkinerja baik, memberikan prediksi yang akurat. Penelitian ini berpotensi memberikan manfaat bagi para investor, analis keuangan, dan pemangku kepentingan pasar saham, memungkinkan pengambilan keputusan yang lebih informasi dan efisien. 
Jurnal Penerapan Artificial Intellegence pada Penghapusan Object Dalam Video Editing: Penerapan AI , Loren; Siahaan, Mangapul
Journal of Information System and Technology (JOINT) Vol. 5 No. 1 (2024): Journal of Information System and Technology (JOINT)
Publisher : Program Sarjana Sistem Informasi, Universitas Internasional Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37253/joint.v5i1.4290

Abstract

Penelitian ini merupakan salah satu contoh implementasi artificial intellegence pada sebuah software. Penelitianini dibuat dengan tujuan mengembangkan fitur yang sudah ada menjadi lebih baik yaitu fitur untukmenghilangkan suatu objek pada video. Metode yang digunakan adalah fitur object removal pada photoshopyang mana akan dikembangkan dan di implementasikan sehingga fitur ini dapat berkembang menjadi lebih baikdan membantu kecepatan dan kemudahan dalam video editing. Masih banyak hal yang dapat diimplementasikandengan AI. Maka dari itu diharapkan dengan adanya jurnal penelitian ini dapat menginspirasi pembaca untukmengembangkan implementasi AI pada objek sehari-hari.
Improving Student’s Writing Skill Of Recount Text Through Diary Writing For Tenth Grade At Sma Swasta Kampus Nommensen Pematangsiantar Hutahaean, Grace Saurma; Siahaan, Mungkap Mangapul; Sihombing, Partohap Saut Raja; Pasaribu, Sunggul
Innovative: Journal Of Social Science Research Vol. 4 No. 6 (2024): Innovative: Journal Of Social Science Research
Publisher : Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/innovative.v4i6.16266

Abstract

This research aims to determine and describe students' difficulties in writing procedural texts in the tenth grade of SMA Swasta Kampus Nommensen Pematangsiantar and completion through diary media. This research method is designed as a quantitative research. The research chose students of grades X-2 and X-3 as the subjects of this research, consisting of 50 students. The technique used in collecting data was a writing test. The researcher chose alternative media to help students improve their recount text writing skills by using diaries. Upon examining the data, it was revealed that the cumulative score for the grammar test amounted to 1,246, resulting in a mean of 49.84. In contrast, the writing test yielded a total score of 1,610, with an average of 64.40. To The findings unveiled a robust connection between these two domains, with a correlation coefficient of 0.127, signifying a notably high correlation, as values ranging from 0.00 to 0.199 indicate a strong association.
The Effect of HOTS on Eleventh Grade Students' Reading Comprehension in Narrative Text at SMK Swasta HKBP Pematangsiantar Nainggolan, Lonatasya Sevari; Siahaan, Basar Lolo; Siahaan, Mungkap Mangapul
Innovative: Journal Of Social Science Research Vol. 4 No. 6 (2024): Innovative: Journal Of Social Science Research
Publisher : Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/innovative.v4i6.16490

Abstract

Tujuan dari penelitian ini adalah untuk mengetahui pengaruh strategi Higher Order Thinking Skills (HOTS) terhadap kemampuan siswa dalam membaca pemahaman teks naratif di kelas sebelas SMK Swasta HKBP Pematangsiantar. Penelitian ini menggunakan desain kuasi-eksperimental untuk menentukan penelitian ini. Sampel penelitian ini diambil dari dua kelas yang terdiri dari 60 siswa, 30 siswa di kelas eksperimen di kelas XI TKRO-2 dan 30 siswa di kelas kontrol di kelas XI TKRO-1. Peneliti menemukan bahwa total nilai rata-rata pre-test di kel as eksperimen adalah 60,33 dan post-test adalah 82,16. Total skor rata-rata pre-test di kelas kontrol adalah 57 dan post-test adalah 67,66. Setelah menghitung data dari semua skor, peneliti menemukan nilai t-test adalah 6,684. Kemudian peneliti menghitung dengan skor pada t-tabel dengan menggunakan signifikansi 0,05 dan diperoleh nilai 1,672. Jadi, peneliti menemukan bahwa t-test lebih tinggi dari t-tabel (6,684 > 1,672). Dapat disimpulkan bahwa pengaruh strategi HOTS terhadap pemahaman membaca teks naratif siswa kelas sebelas di SMK Swasta HKBP Pematangsiantar adalah afektif.
Prototipe Kurikulum PBI dan IKMBKM Sesuai Permendikbudristek No.53 Tahun 2023: PBI and IKMBKM Curriculum Prototype According to Permendikbudristek No. 53 of 2023 Sirait, Jumaria; Tambunan, Marlina Agkris; Sianturi, Canni Loren; Siahaan, Mungkap Mangapul; Purba, Johannes Riscy
Edu Cendikia: Jurnal Ilmiah Kependidikan Vol. 4 No. 02 (2024): Artikel Riset Edisi Agustus 2024
Publisher : ITScience (Information Technology and Science)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/educendikia.v4i02.4594

Abstract

This research is based on the paradigm of curriculum application or implementation, so the research data analysis technique uses the ADDIE method, namely Analyze, Design, Development, Implementation, and Evaluation to answer the research problem questions: (a) How is the current prototype of the PBI study program curriculum?; (b) How is the prototype of the PBI study program curriculum according to Permendikbudristek No. 53 of 2023? Thus, the purpose of the study is to determine the current PBI curriculum prototype and the PBI curriculum prototype according to Permendikbudristek No. 53 of 2023. The research was carried out in the odd semester of the 2023/2024 academic year. The research results obtained were in the form of a prototype of the PBI study program curriculum development FKIP-UHKBPNP according to Permendikbudristek RI No. 53 of 2023. Furthermore, the agile development method and prototype of the results of the curriculum development were used to be implemented in the PBI study program FKIP-UHKBPNP. The definition of development in this study is a scientific way to obtain data based on initial data, so that it can be used to produce, develop, and validate products. Product validation is also confirmed to users which is carried out through FGD, zoom, or direct meetings. The state of the arts of the research is a documentation study of the current PBI curriculum prototype and curriculum development to produce a PBI curriculum prototype according to Permendikbudristek RI No. 53 of 2023. Thus, the novelty or newness as a research finding is the PBI curriculum prototype according to Permendikbudristek RI No. 53 of 2023 which will be implemented in the PBI study program FKIP-UHKBPNP.
Analysis of Rice Yield Prediction with Mlpregressor and Long Short-Term Memory Models Sunoto; Mangapul Siahaan
INOVTEK Polbeng - Seri Informatika Vol. 10 No. 1 (2025): March
Publisher : P3M Politeknik Negeri Bengkalis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35314/wnpm3846

Abstract

This research aims to analyse and compare the accuracy of rice productivity prediction using Multi-Layer Perceptron  Regressor (MLPRegressor) and Long Short-Term Memory (LSTM) models. The data used comes from the Badan Pusat Statistik (BPS) for the period 2018-2023, covering rice productivity from 34 provinces in Indonesia. The study employed six different architectural models for each model, with training data using the 2018-2020 period and testing data for 2021-2023. The results show that the LSTM model with 2-42-42-42-1 architecture achieved the highest accuracy rate of 94.12% with MSE 0.00305660, while the MLPRegressor model with 2-22-1 architecture achieved 91.18% accuracy with MSE 0.00471975. These results indicate that LSTM performs slightly better in predicting rice productivity, which can be used as a reference for agricultural planning and food policy in Indonesia.
The Role of Natural Language Processing in Enhancing Chatbot Effectiveness for E-Government Services Siahaan, Mungkap Mangapul; Sunarjo, Richard Andre; Sebastian, Rizky; Wahid, Syahrul Muarif
CORISINTA Vol 2 No 1 (2025): February
Publisher : Pandawan Sejahtera Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/corisinta.v2i1.71

Abstract

The rapid digital transformation of public administration has led to the adoption of (B) Natural Language Processing (NLP)-powered chatbots to enhance the accessibility, efficiency, and responsiveness of (O) e-government services. However, despite their increasing deployment, many government chatbots still struggle with intent recognition, response accuracy, multilingual processing, and user engagement, limiting their effectiveness. This study investigates (M) the role of NLP in improving chatbot performance within e-government services by evaluating four case studies: Ask Jamie (Singapore), UK Government Digital Assistant, MyGov Corona Helpdesk (India), and Gov.sg Chatbot. Using a mixed-methods approach, this research assesses chatbot effectiveness based on accuracy, response time, query resolution rate, and user satisfaction metrics. The findings indicate that (R) NLP-driven chatbots significantly outperform rule-based systems, with higher accuracy (up to 89%), faster response times (~2.1 seconds), and improved query resolution rates (92%), demonstrating their capacity to automate public service delivery efficiently. However, key challenges remain, including bias in NLP models, data privacy concerns, and the difficulty of integrating NLP chatbots into legacy IT infrastructures. Additionally, multilingual processing remains a limitation, affecting inclusivity for diverse populations. To overcome these challenges, this study proposes advancements in adaptive NLP models, real-time learning algorithms, ethical AI frameworks, and blockchain-based security solutions to ensure fair, secure, and transparent chatbot interactions in digital governance. These findings contribute to the growing body of research on AI-driven public service automation and highlight the potential of NLP to enhance (C) citizen-government interactions, reduce administrative burdens, and improve trust in e-government platforms. Future research should focus on bias mitigation, improving multilingual NLP capabilities, and integrating AI ethics into chatbot governance frameworks to ensure sustainable, scalable, and citizen-centric e-government chatbot solutions.
Perancangan Sistem Informasi Penjualan Barang Bekas Berbasis Website dengan Metode Extreme Programming Siahaan, Mangapul; Lim, Tevin
CESS (Journal of Computer Engineering, System and Science) Vol. 9 No. 1 (2024): January 2024
Publisher : Universitas Negeri Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24114/cess.v9i1.51465

Abstract

Ketertarikan masyarakat terhadap barang bekas atau preloved semakin meningkat seiring dengan adanya peningkatan daya konsumtif terhadap barang bekas. Saat ini, masih banyak penjualan barang bekas yang dilakukan secara konvensional, terutama di Batam. Untuk mengatasi masalah ini, diperlukan pengembangan aplikasi penjualan barang bekas yang efektif, efisien, terjangkau, dan mudah diakses oleh masyarakat dengan menggunakan model bisnis peer to peer (P2P). Aplikasi ini dibangun dengan model penelitian Extreme Programming yang melibatkan tahap perencanaan, desain, pengkodean, dan pengujian, serta menggunakan berbagai diagram seperti diagram use case, diagram aktivitas, dan diagram hubungan entitas. Metode penelitian ini berfokus pada kualitatif dan Extreme Programming. Hasil penelitian ini berupa sebuah sistem yang telah diimplementasikan menggunakan framework Laravel dan teknologi Livewire, yang telah diuji melalui metode Black-box Testing, dan hasilnya menunjukkan bahwa sistem memenuhi kriteria yang telah ditetapkan. Dengan demikian, sistem ini siap digunakan untuk memfasilitasi transaksi barang bekas secara online.
Co-Authors , Loren Adi 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 Chandra, Jefriyanto Christian, Yefta Christopher Harsana Jasa Daniel Arnoldi Gultom Darius Angtony David Gordon Gultom Dedy Susanto Deli Dewi, Syasya Tri Puspita Edwards, John Eka Setiawati Eryc, Eryc Febri Yanti Firmansyah, Muhamad Dody Firmansyah, Muhammad Dody Fitri May Danthi Saragih Frank Lurich Gabriella Clarisa Silaban Glorya Natalia Rohani Napitupulu Gultom, Erwin Geovanis Hafizh akmal Haloho, Uci Nursanty Handyca Yeng Hansvirgo Hendi Che 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 Jason Angelo Ong Jennifer Jennifer Jocelyn Jocelyn Julia Julia Justin Justin Kelvin Kelvin Kurniawan Kenidy, Ryan Kevin Anderson Kevin William Andri Siahaan Khomali, Carlos Justin Kristiani Siagian Kristina Vaher Leonita Maria E Manihuruk Liang, Suwarno Lie, Joen Lim, Tevin Lim, Vincent Lorenz, Chintya Marbun, Lastri Evati Mori Maret Ningsihermina Sihombing Maryanto Saragih Maulana, Azhar 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 Nababan, Irene Adryana Nainggolan, Lonatasya Sevari Napitupulu, Selviana Novita Forena Simanungkalit Oktaviani, Katherine Oktavina Oktavina Pane, Eva Pratiwi PANJAITAN, MUKTAR B Partohap S. R Sihombing, Partohap S. R Partohap Sihombing Pasaribu, Sunggul Purba, Christian Neni Purba, Johannes Riscy Purba, Rudiarman Purba, Yoel Octobe Rendhika Adyatama Restu Maulana Nashuha Ricky Hartanto Rosalia, Balinda Oca Roy Valentino Chandra Ryan Kenidy Ryan Kenidy Sabariman Sabariman Sabariman Sabariman Sama, Hendi Samosir, Hottua Sanggam Magda Lasmaria Siahaan Sanggam Siahaan 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 Tjahyadi, Surya Toktar Kerimbekov TRI SUSANTI 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 Yulsen Yulsen, Yulsen Zulkarnain Zulkarnain Zulkarnain