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All Journal Jurnal TIMES Sinkron : Jurnal dan Penelitian Teknik Informatika International Journal of Artificial Intelligence Research Jurnal Informatika Jurnal Mantik Penusa JIPN (Journal of Informatics Pelita Nusantara) JURTEKSI JURNAL TEKNOLOGI DAN ILMU KOMPUTER PRIMA (JUTIKOMP) TRIDARMA: Pengabdian Kepada Masyarakat (PkM) Jurnal Sistem Komputer dan Informatika (JSON) Community Development Journal: Jurnal Pengabdian Masyarakat Jurnal Ilmu Komputer dan Sistem Informasi (JIKOMSI) Journal of Computer Networks, Architecture and High Performance Computing Jurnal Pengabdian kepada Masyarakat Nusantara Jurnal Visi Pengabdian Kepada Masyarakat Jurnal Media Informatika Jurnal Sistem Informasi, Teknik Informatika dan Teknologi Pendidikan (JUSTIKPEN) JURNAL PENELITIAN BIDANG PENDIDIKAN Jurnal Pengabdian Pada Masyarakat METHABDI Jurnal Pengabdian Inovasi Masyarakat Indonesia Jurnal Ilmiah Multidisiplin Indonesia Journal of Technology and Computer (JOTECHCOM) Jurnal Pengabdian Masyarakat Multi Disiplin Ilmu Jurnal Pengabdian Masyarakat (Jubdimas) Jurnal Pengabdian Kepada Masyarakat Teknologi Informasi dan Komunikasi
Erwin Panggabean
STMIK Pelita Nusantara, Medan
Religion Agriculture, Biological Sciences & Forestry Arts Humanities Chemistry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Health Professions Immunology & microbiology Languange, Linguistic, Communication & Media Mathematics Mechanical Engineering Medicine & Pharmacology Physics Public Health Social Sciences Other

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Pengembangan Perangkat Lunak Analisis Sentimen Komentar Mahasiswa pada Kegiatan Belajar Mengajar Menggunkan Metode Long Short-Term Memory Berbasis Text Mining Erwin Panggabean; Penda Sudarto Hasugian; Amran Sitohang; Nadia Wulan Dari; Rangga Permana Sanjaya
Jurnal Pengabdian Pada Masyarakat METHABDI Vol 5 No 2 (2025): Jurnal Pengabdian Pada Masyarakat METHABDI
Publisher : Universitas Methodist Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46880/methabdi.Vol5No2.pp249-258

Abstract

This research focuses on the development of sentiment analysis software designed to evaluate students’ comments at SMKS Methodist 8 Medan concerning teaching and learning activities through a text mining approach. The software aims to support educational evaluation by automatically identifying the emotional tone and opinions expressed by students in their feedback. In this study, text mining techniques are employed to preprocess and analyze comment data collected from online learning platforms and school surveys. The preprocessing stages include tokenizing, stopword removal, and stemming to prepare clean textual data for analysis. Subsequently, the Naïve Bayes classification algorithm is implemented to categorize the comments into three sentiment classes: positive, negative, and neutral. The results of experimental testing demonstrate that the developed system can accurately identify sentiment tendencies with satisfactory precision and reliability. Moreover, the visualization of sentiment results enables educators to better understand students’ perceptions and engagement levels in the learning process. This research contributes to the field of educational technology by providing a data-driven tool that helps schools evaluate teaching effectiveness, identify areas of improvement, and enhance the overall quality of learning experiences through objective analysis of student feedback.
Analyzing the Impact of Information Systems Digitalization on Organizational Performance through the Technology Acceptance Model (TAM) Sitompul, Novian Paisal; Haqki, Bay; Harahap, Baginda; Harahap, Solianna; Panggabean, Erwin
Journal of Technology and Computer Vol. 3 No. 3 (2026): August 2026 - Journal of Technology and Computer
Publisher : PT. Technology Laboratories Indonesia (TechnoLabs)

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

Abstract

The digitalization of information systems has become a key strategy for organizations seeking to improve operational efficiency, decision-making quality, and overall organizational performance. However, the successful implementation of digital technologies depends largely on users’ acceptance and willingness to adopt such systems. This study aims to analyze the impact of information systems digitalization on organizational performance using the Technology Acceptance Model (TAM). The research examines the relationships between perceived usefulness, perceived ease of use, user acceptance, and organizational performance. A quantitative research approach was employed by collecting data through structured questionnaires distributed to employees who actively use digital information systems within their organizations. The collected data were analyzed using Structural Equation Modeling (SEM) to evaluate the proposed research model and test the hypotheses. The findings indicate that perceived usefulness and perceived ease of use significantly influence user acceptance, which subsequently contributes to improved organizational performance. These results highlight the importance of designing user-friendly and beneficial digital information systems to maximize organizational outcomes. The study provides valuable insights for organizations in developing effective digital transformation strategies and enhancing sustainable organizational performance through technology adoption.
Performance Analysis of Parallel Merge Sort Using MPI (Message Passing Interface) on Big Data Dataset Erwin Panggabean; Yuda Perwira; Dedi Candro Parulian Sinaga; Annisa Tri Utami; Vincha Swe Meiya Pricilla Sembiring
Jurnal Sistem Komputer dan Informatika (JSON) Vol. 7 No. 2 (2025): Desember 2025
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/json.v7i2.9307

Abstract

The rapid growth of data in the era of Big Data demands efficient and scalable algorithms to handle large datasets. Sorting, as a fundamental operation in data processing, plays a crucial role in various computational tasks. This study focuses on the performance analysis of the Parallel Merge Sort algorithm using the Message Passing Interface (MPI) to accelerate sorting operations on large-scale datasets. The implementation utilizes MPI for distributed memory communication across multiple processes, enabling concurrent data partitioning and merging. Experiments were conducted on datasets ranging from several hundred megabytes to multiple gigabytes to evaluate performance metrics such as execution time, speedup, and efficiency. The results demonstrate that the parallel implementation significantly reduces computation time compared to the sequential version, especially as the dataset size and the number of processes increase. However, the performance gain tends to decrease when communication overhead between MPI processes becomes dominant. Overall, the findings indicate that MPI-based Parallel Merge Sort is an effective approach for large-scale data sorting, providing a balance between computation and communication efficiency in parallel environments.
Co-Authors Abdul Jabbar Lubis Ade Putri Humaira Aispriyani Amala, Dwi Novia Amran Sitohang Annisa Tri Utami Apriani , Wira Arikhifo, Arikhifo Aritana Lahagu Aritonang, Tri Evalina Baginda Harahap Bella Saputri Damayanti, Alfina Dedi Candro Parulian Sinaga Dedi Sinaga, Dedi Dewi, Sumitra Faduhusi Lombu Fauduziduhu Laia Fitra, Awaludin Fransisco alexander Simbolon Gea, Asaziduhu Ginting, Ricky Martin Guntur Syahputra Guntur Syahputra Haida Dafitri Haqki, Bay Harahap, Solianna Harefa, Jikarni Hartati Palentina Sipahutar Hasugian, Penda Sudarto Hasugian, Penda Sudarto Hengki Tamando Sihotang Herlina Zebua Ira Lina Kendayto Panjaitan Jijon R. Sagala Jijon R. Sagala Jijon Raphita Sagala Jijon Raphita Sagala Jijon Raphita Sagala, Jijon Raphita Josua, Alpon Juandi Syahfutra Simatupang Junita , Diana Justrina Br. Surbakti Justrina Br.Surbakto Kune, Margaritha M. Lahagu, Aritana Laia, Fauduziduhu Lase , Yulianto Logaraj Logaraj Lombu, Faduhusi Lubis, Risa Kartika Margaritha M. Kune Mulyana, Sri Ulina Nadia Aulia Nadia Wulan Dari Nora Anisa Br. Sinulingga Nur Wulan Nuraisana Nuraisana , Nuraisana Nuraisana, Nuraisana Olven Manahan Pakpahan, Robertus Rinaldi Penda Sudarto Hasugian Prasanth Kumar Pria Dimas R. Mahdalena Simanjorang Ramadhan, Alya Sophia Rangga Permana Sanjaya Selvia, Sindu Siagian, Tesalonika Pesta Sianturi, Ariani Natalia Sihombing, Agus Putra Emas Simangunsong, Agustina Simanjorang, R. Mahdalena Simanjorang, R. Mahdelena Sinaga, Anita Sindar Sinaga, Anita Sindar RM Sinaga, Anita Sindar Ros Maryana Sindar Sinaga, Anita Sipahutar, Hartati Palentina Sitio, Arjon Samuel Sitohang, Amran Sitompul, Novian Paisal Sitorus, Martua Sri Mulyani Sri Ulina Mulyana Sulindawaty, Sulindawaty Sumi Khairani Telaumbanua, Imelda Tiara W Pratiwi Utami, Yulia Vincha Swe Meiya Pricilla Sembiring Vinsensia, Desi Wanra Tarigan Wira Apriani Yerianus Lase Yuda Perwira Yuda Perwira