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All Journal JBIO: jurnal biosains (the journal of biosciences) Jurnal Pendidikan Fisika Al Ishlah Jurnal Pendidikan Jurnal Biologi Tropis PENDIPA Journal of Science Education Jurnal Basicedu Journal on Education MAJU : Jurnal Ilmiah Pendidikan Matematika Logista: Jurnal Ilmiah Pengabdian Kepada Masyarakat Aptisi Transactions on Technopreneurship (ATT) Jurnal Ilmiah Aquinas Gema Wiralodra Jurnal Pendidikan dan Konseling MES: Journal of Mathematics Education and Science Jurnal Eduscience (JES) Best Journal (Biology Education, Sains and Technology) TRIDARMA: Pengabdian Kepada Masyarakat (PkM) Jurnal Educatio FKIP UNMA Abdimas Galuh: Jurnal Pengabdian Kepada Masyarakat Masyarakat Berdaya dan Inovasi Bubungan Tinggi: Jurnal Pengabdian Masyarakat Community Development Journal: Jurnal Pengabdian Masyarakat BERNAS: Jurnal Pengabdian Kepada Masyarakat Mattawang: Jurnal Pengabdian Masyarakat Mitra Mahajana: Jurnal Pengabdian Masyarakat Bioscientist : Jurnal Ilmiah Biologi ADI Pengabdian kepada Masyarakat Jurnal (ADIMAS Jurnal) Jurnal Altifani Penelitian dan Pengabdian kepada Masyarakat International Journal of Social Science, Educational, Economics, Agriculture Research, and Technology (IJSET) NUSRA: Jurnal Penelitian dan Ilmu Pendidikan Joong-Ki : Jurnal Pengabdian Masyarakat Journal of Advanced Sciences and Mathematics Education KOMMAS: Jurnal Pengabdian Kepada Masyarakat Prisma Sains: Jurnal Pengkajian Ilmu dan Pembelajaran Matematika dan IPA IKIP Mataram Lensa: Jurnal Kependidikan Fisika Startupreneur Business Digital (SABDA Journal) Jurnal Basicedu SWARNA Research and Development in Education (RaDEn) JURNAL MUARA PENDIDIKAN JURNAL TUNAS PENDIDIKAN PIJAR: Jurnal Pendidikan dan Pengajaran Al-Irsyad Journal of Physics Education Innovative: Journal Of Social Science Research Social Engagement: Jurnal Pengabdian Kepada Masyarakat Abdimas Mandalika MULTIPLE: Journal of Global and Multidisciplinary Jurnal Pengabdian Masyarakat dan Riset Pendidikan Joong-Ki Inovasi Sosial : Jurnal Pengabdian Kepada Masyarakat Jurnal Pengabdian Masyarakat Indonesia (JPMI) SWARNA: Jurnal Pengabdian Kepada Masyarakat Pengembangan Penelitian Pengabdian Jurnal Indonesia (P3JI) Jurnal Elementaria Edukasia International Transactions on Artificial Intelligence (ITALIC) Joong-Ki Journal of Computer Science and Technology Application Edumaspul: Jurnal Pendidikan
Apriani Sijabat
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Religion Agriculture, Biological Sciences & Forestry Arts Humanities Astronomy Biochemistry, Genetics & Molecular Biology Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Immunology & microbiology Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Neuroscience Nursing Physics Public Health Social Sciences Veterinary Other

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Journal : journal of computer science and technology application

 1 
Challenges and Opportunities in Implementing Big Data for Small and Medium Enterprises (SMEs) Dwi Cahyono; Apriani Sijabat; Muktar Bahruddin Panjaitan; Dwi Julianingsih; Agung Lorenzo
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.v2i1.74

Abstract

Small and Medium Enterprises (SMEs) play a crucial role in the global economy but often face significant challenges when adopting new technologies like Big Data. While Big Data offers opportunities for improving decision-making, operational efficiency, and gaining a competitive edge, many SMEs struggle due to financial constraints, limited technical expertise, and concerns over data security and privacy. This paper explores the challenges SMEs encounter in adopting Big Data and identifies the opportunities it provides for growth and innovation. A mixed-methods approach is employed, combining qualitative interviews with SME managers and quantitative surveys from 150 SMEs to gather comprehensive data. The findings reveal that SMEs face barriers such as high implementation costs and lack of skilled personnel, but they also recognize the potential for Big Data to enhance customer insights, improve business processes, and foster new business models. Recommendations include exploring cost-effective solutions, investing in employee training, strengthening data security, and adopting modular systems that integrate easily with existing operations. This study underscores the importance of overcoming these challenges and leveraging Big Data as a key driver of digital transformation for SMEs, ultimately helping them to compete more effectively in an increasingly data-driven marketplace.
Efficient Machine Learning Acceleration with Randomized Linear Algebra for Big Data Dwi Cahyono; Apriani Sijabat; Kamal Arif Al-Farouqi
CORISINTA Vol 3 No 1 (2026): February
Publisher : Pandawan Sejahtera Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/v3i1.163

Abstract

The rapid growth of big data has significantly increased the computational complexity of machine learning models, particularly due to intensive linear algebra operations that limit scalability and efficiency. This study aims to investigate the effectiveness of Randomized Linear Algebra (RLA) as an acceleration strategy for machine learning in large scale data environments. The research adopts an experimental methodology by integrating randomized techniques such as matrix sketching and random projection into standard machine learning pipelines and evaluating their performance against deterministic baseline approaches. Experiments are conducted on large dimensional datasets using multiple machine learning models, with performance assessed in terms of computational time, memory usage, model accuracy, and scalability. The results demonstrate that the proposed RLA based approach substantially reduces computational cost and memory consumption while maintaining comparable predictive accuracy to conventional methods. These findings indicate that randomized techniques provide an effective trade off between efficiency and accuracy, enabling scalable machine learning for big data applications. In conclusion, this study contributes to the advancement of efficient Artificial Intelligence (AI) systems by demonstrating that RLA can serve as a practical and scalable solution for accelerating machine learning computations in big data contexts, aligning with the growing demand for resource efficient and high performance AI infrastructures.
Co-Authors A. Asrizal Abdul Razak Abdul Razak Ady Frenly Simanullang Agung Lorenzo Andi Rahmah Andi Sri Rezky Wulandari Anita Debora Simangunsong Anton Luvi Siahaan Aprido Bernando Simamora Arianto Munthe Asima Rohana Sinaga Asrizal Asrizal Astri Ananta Girsang Aswadi Jaya, Aswadi Belsasar Sihombing Belsasar Sihombing Berkat Kasih Situmorang Christa Voni R Sinaga Christa Voni Sinaga Christian Neni Purba David Berthony Manalu Delhi, Ariana Derlina . Dina, Aulia Rahma Dwi Cahyono Dwi Julianingsih Eduward Situmorang Eka Seprianti Sihaloho Elisabet Pebrina Br.Ujung Ertina Sabarita Barus Eva Pasaribu Eva Pratiwi Pane Evi Syuriani Harahap F. Festiyed Faturahman, Adam Febri Yanti Festiyed Festiyed Fine Eirine Siahaan Girsang, May Liza Putri Golda Novatrasio Sauduran Grace Tessalonika Juliarta Handoco, Ewin Hardeli Hardeli Herlina Hotmadia Sianipar Herna Febrianty Sianipar Herna Febrianty Sianipar Herna Febrianty Sianipar Herna Febrianty Sianipar Herna Febrianty Sianipar Herna Febrianty Sianipar Herna Febrianty Sianipar Herna Febrianty Sianipar Herna Febrianty Sianipar Herna Febrianty Sianipar Ilwandri Immanuel D. B. Silitonga Insenalia Sampe Roly Hutagalung Juanta, Palma Jumaria Sirait Kalvin Sinaga Kamal Arif Al-Farouqi Kasih Patricia Gultom Lampola Sitorus P Lampola Sitorus P Leonie, Natasha Lestari Maria Esterlina Silalahi Lisbet Novianti Sihombing Lufri Lufri Lumbangaol, Sudirman T. P Lumbangaol, Sudirman T.P Lumbangaol, Sudirman T.P. Makkah HM Manik, Heber Marbun, Juliaster Marbun, Lastri Evati Mori Maria Gultom Marlince NK Nababan Marlince NK Nababan Marthin Fransisco Manihuruk Martua Reynhat Sitanggang Gusar Mawar Febrianti Irene Manurung Melda Veby Ristella Munthe Motlan . Muktar Bahruddin Panjaitan Mungkap Mangapul Siahaan Nanich Framulya Natalina Purba Nelly Suka Sihite Novia Carla Purba Nurliani Manurung Okta Fiani Simamora Osco P Sijabat Osco Parmonangan Siajabat Palma Juanta Palma Juanta Palma Juanta Palma Juanta Palma Juanta Palma Juanta Partohap S.R Sihombing Pasaribu, Sunggul Peniel Sam Putra Sitorus Purba, Rudiarman Putri Giovani Rajagukguk Rajagukguk, Marta Jesika Agustina Ramzi Zainum Ikhsan Refi Verolika Napitupulu Revalina Permata Sari Sihombing Revi Gina Gunawan Rina Devi Romauli Siahaan Rina Siahaan Ronald Hasibuan Roulina, Christa Voni Ruth Angelina Pardede Ruth Angelya Hutapea Sahat Renol HS - -, Sahat Renol HS - Samosir, Hottua Samuel Albert Simanjuntak Sanggam Magda Lasmaria Siahaan Sanggam Siahaan Santi Mareta Saragih, Yesa Rohjayani Sauduran, Golda Novatrasio Siahaan, Fine Eirene Siahaan, Rina Devi Siahaan, Theresia Monika Siahaan, Vaisal Sianipar, Julia Sianipar, Rizky Anadora SIANTURI, TAMBOS AUGUST Sidabutar, Ropinus Sijabat, Desi Sijabat, Osco Parmonangan Simamora, Benny Leonardo Simamora, Rianita Simangunsong, Anita Debora Br. Simanjuntak, Bernard Simanjuntak, Tarida Simatupang, Leo Fernando Simbolon, Ricky Alexcius Sinaga, Mardame Pangihutan Sirait, Esti Marlina Siti Imroatul Maslikah SITINJAK, ERNI KUSRINI Sitorus, Ester Skunda Diliarosta Sotarduga Sihombing Srinatalia Silaen Sudirman TP Lumban gaol Sudirman TP Lumbangaol Susy Alestriani Sibagariang Terizla, Rizky Fredrin Tumpal Manahara Siahaan Uli Martina Benedicta Purba Welmar Olfan Barat, Welmar Olfan Winri Sidabutar Yerimadesi Yohandri Yoko Manurung Zainarthur, Henry