PRIANUS HALAWA, NPM 2109400175 (2025) PENGGUNAAN BIG DATA UNTUK PREDIKSI TREN PASAR DALAM INDUSTRI RETAIL. Tugas_Akhir (Artikel) Jurnal Sistem Informasi, Teknik Komputer dan Teknologi Pendidikan, 4 (1). pp. 32-36. ISSN 2828-7921 (e-ISSN)
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Abstract
Perkembangan teknologi digital telah mengubah lanskap industri retail secara signifikan, terutama dalam cara perusahaan memahami dan merespons permintaan pasar. Big Data, sebagai salah satu elemen utama dalam transformasi digital, menawarkan kemampuan analisis data dalam skala besar yang mampu memberikan wawasan lebih mendalam terkait perilaku konsumen, pola pembelian, dan tren pasar yang dinamis. Penelitian ini mengeksplorasi penerapan Big Data dalam memprediksi tren pasar di industri retail, meliputi analisis preferensi konsumen, perilaku belanja multikanal, dan proyeksi permintaan di masa depan. Dengan memanfaatkan teknik seperti machine learning, data mining, dan analisis prediktif, Big Data memungkinkan perusahaan retail mengidentifikasi pola tersembunyi yang mendasari perubahan tren pasar secara real-time. Hasil analisis Big Data juga dapat digunakan untuk merancang strategi pemasaran yang lebih tepat sasaran, mengoptimalkan manajemen persediaan, serta meningkatkan pengalaman pelanggan. Selain itu, studi ini membahas berbagai tantangan yang dihadapi dalam implementasi Big Data, seperti integrasi data dari berbagai sumber, pengolahan data yang besar dan kompleks, serta kebutuhan akan infrastruktur teknologi yang memadai. Dampak positif dari penggunaan Big Data meliputi peningkatan efisiensi operasional, pengurangan risiko bisnis, serta peningkatan kepuasan pelanggan melalui personalisasi layanan. Dengan semakin kompetitifnya industri retail, hasil penelitian ini diharapkan dapat memberikan panduan strategis bagi perusahaan dalam memaksimalkan potensi Big Data untuk menciptakan keunggulan kompetitif yang berkelanjutan. Kata Kunci : Big Data, Prediksi Tren Pasar, Industri Retail, Analisis Data, Machine Learning, Data Mining ========================================================================== The development of digital technology has significantly changed the landscape of the retail industry, especially in the way companies understand and respond to market demands. Big Data, as one of the key elements in digital transformation, offers data analytics capabilities at scale that can provide deeper insights into consumer behavior, purchasing patterns, and dynamic market trends. This research explores the application of Big Data in predicting market trends in the retail industry, including analysis of consumer preferences, multi-channel shopping behavior, and future demand projections. By leveraging techniques such as machine learning, data mining, and predictive analytics, Big Data allows retail companies to identify hidden patterns underlying changing market trends in real-time. The results of Big Data analysis can also be used to design more targeted marketing strategies, optimize inventory management, and improve customer experience. In addition, this study discusses various challenges faced in the implementation of Big Data, such as the integration of data from various sources, large and complex data processing, and the need for adequate technological infrastructure. The positive impacts of using Big Data include improving operational efficiency, reducing business risks, and increasing customer satisfaction through service personalization. With the increasingly competitive retail industry, the results of this research are expected to provide strategic guidance for companies in maximizing the potential of Big Data to create a sustainable competitive advantage. Keywords : Big Data, Market Trend Prediction, Retail Industry, Data Analysis, Machine Learning, Data Mining
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | Big Data, Prediksi Tren Pasar, Industri Retail, Analisis Data, Machine Learning, Data Mining ============================== Big Data, Market Trend Prediction, Retail Industry, Data Analysis, Machine Learning, Data Mining |
| Subjects: | Z Bibliography. Library Science. Information Resources > ZA Information resources Z Bibliography. Library Science. Information Resources > ZA Information resources > ZA4050 Electronic information resources |
| Divisions: | Fakultas Sains Dan Teknologi > Sistem Informasi |
| Depositing User: | Unnamed user with email repository@ulb.ac.id |
| Date Deposited: | 30 Apr 2025 09:17 |
| Last Modified: | 30 Apr 2025 09:17 |
| URI: | http://repository.ulb.ac.id/id/eprint/1316 |
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