Analisis Big Data UMKM Menggunakan Apache Hadoop-Hive dengan Metode Forecasting Time Series
Abstract
MSMEs (Micro, Small, and Medium Enterprises) play a vital role in economic growth, creating jobs, and improving people's welfare. However, MSMEs often face challenges in managing sales data and performance analysis, resulting in many businesses closing down every year. The Covid-19 pandemic has worsened this situation, with many MSMEs experiencing a decline in revenue and product demand. In the past five years, the application of big data analysis has increased rapidly, helping with fast and accurate decision-making. This technology, especially the time series forecasting method, allows predictions of future values ??based on historical data, thus supporting MSMEs in increasing productivity and competitiveness. The industrial revolution 4.0 brings big data and blockchain-based business intelligence that accelerates the supply chain and trade. This helps the government in setting regulations and making specific decisions for MSMEs. Although there are challenges in building infrastructure and deploying this technology, the benefits are enormous, such as understanding community trends through sentiment analysis on social media, improving company image, planning businesses based on consumer behavior, and making fast and accurate decisions. Apache Hadoop and Hive are efficient tools for managing and analyzing big data. In this study, MSME data in Bali Province was analyzed using the simple moving average forecasting time series method. The results of this analysis are used as a basis for providing recommendations and improving MSME management, and are expected to be a reference for better decision making.
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References
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[23] N. Buslim, B. Busman, N. S. Sinatrya, and T. S. Kania, “Analisa Sentimen Menggunakan Data Twitter, Flume, Hive Pada Hadoop dan Java Untuk Deteksi Kemacetan di Jakarta,” Jurnal Online Informatika, vol. 3, no. 1, p. 1, Jun. 2018, doi: 10.15575/join.v3i1.141.
[24] L. Febtriani, “Studi Dan Perbandingan Apache Spark Sql dan Hive Dalam Konteks Analisis Big Data,” 2018.
[25] “AWS: What is Apache Hive?”
[26] Masbullah, “Implementasi Knowledge Management Untuk Mendorong Inovasi dan Produktivitas UMKM Menggunakan Big Data Media Sosial,” Jurnal Manajemen Informatika dan Bisnis Digital, vol. 2, no. 1, pp. 12–23, 2023, doi: 10.55123/jumintal.v2i1.1887.
[27] T. Bustomi, E. Marlovia, and Achdiat, “Inisiatif Open Data Pada Usaha Mikro Kecil Menengah Kota Bandung,” Jurnal Ilmu Administrasi, vol. 12, 2021.
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[31] O. Azeroual and R. Fabre, “Processing big data with apache hadoop in the current challenging era of COVID-19,” Big Data and Cognitive Computing, vol. 5, no. 1, 2021, doi: 10.3390/bdcc5010012.
[32] S. H. Bhatti, A. Ahmed, A. Ferraris, W. M. Hirwani Wan Hussain, and S. F. Wamba, “Big data analytics capabilities and MSME innovation and performance: A double mediation model of digital platform and network capabilities,” Ann Oper Res, 2022, doi: 10.1007/s10479-022-05002-w.
[33] Kementrian Koordinator Bidang Perekonomian Republik Indonesia, “Perkembangan UMKM sebagai Critical Engine Perekonomian Nasional Terus Mendapatkan Dukungan Pemerintah,” https://www.ekon.go.id/publikasi/detail/4593/perkembangan-umkm-sebagai-critical-engine-perekonomian-nasional-terus-mendapatkan-dukungan-pemerintah, Jakarta, Oct. 01, 2022.
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[35] N. Putri and J. T. Informasi, “Optimalisasi Terhadap Infrastruktur Big Data Dengan Menggunakan Hadoop,” 2022.
[36] C. Wibawa, S. Wirawan, M. Mustikasari, and D. T. Anggraeni, “Komparasi Kecepatan Hadoop Mapreduce Dan Apache Spark Dalam Mengolah Data Teks,” Jurnal Ilmiah MATRIK, vol. 24, no. 1, 2022.
[37] I. R. Prabaswara and R. Saputra, “Analisis Data Sosial Media Twitter Menggunakan Hadoop dan Spark,” IT JOURNAL RESEARCH AND DEVELOPMENT, vol. 4, no. 2, Mar. 2020, doi: 10.25299/itjrd.2020.vol4(2).4099.
[38] I. D. N. A. Manuaba, I. B. G. Manuaba, and M. Sudarma, “Komparasi Metode Peramalan Grey dan Grey-Markov untuk mengetahui Peramalan PNBP di Universitas Udayana,” Majalah Ilmiah Teknologi Elektro, vol. 21, no. 1, p. 83, Jul. 2022, doi: 10.24843/mite.2022.v21i01.p12.
[39] Y. Pramana, R. S. Hartati, and K. Oka Saputra, “Peramalan Penerbitan Ijin Mendirikan Bangunan Dengan Single Moving Average Dan Exponential Smoothing,” Majalah Ilmiah Teknologi Elektro, vol. 18, no. 2, Jul. 2019, doi: 10.24843/mite.2019.v18i02.p13.
[40] I. G. N. G. A. Suniantara, N. Gunantara, and M. Sudarma, “Analisis Penyebaran Covid 19 Menggunakan Model SIR (Susceptible, Infected, Recovered) Di Provinsi Bali,” Majalah Ilmiah Teknologi Elektro, vol. 22, no. 1, p. 39, Jun. 2023, doi: 10.24843/mite.2023.v22i01.p05.
Published
2024-12-14
How to Cite
PERTEKA, Putu Denanta Bayuguna; GUNANTARA, I Nyoman; SWAMARDIKA, Ida Bagus Alit.
Analisis Big Data UMKM Menggunakan Apache Hadoop-Hive dengan Metode Forecasting Time Series.
Majalah Ilmiah Teknologi Elektro, [S.l.], v. 23, n. 2, p. 263-272, dec. 2024.
ISSN 2503-2372.
Available at: <https://ojs.unud.ac.id/index.php/mite/article/view/119865>. Date accessed: 08 feb. 2025.
Section
Articles
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
This work is licensed under a Creative Commons Attribution 4.0 International License
