Eksplorasi Social Media Mining Dalam Analitik Big Data: Metode Dan Implementasi

Authors

  • Lukas Umbu Zogara Universitas Utpadaka Swastika

DOI:

https://doi.org/10.56995/sintek.v5i2.168

Keywords:

Big Data Analytics, Social Media Mining, IoT, Analitik Data, Keputusan

Abstract

Perkembangan big data terus menunjukkan peningkatan yang signifikan seiring dengan kemajuan teknologi Internet of Things (IoT). Salah satu perangkat yang paling umum digunakan dalam kehidupan sehari-hari adalah ponsel, terutama jenis smartphone. Melalui aplikasi media sosial yang tersedia di dalamnya, smartphone menjadi sumber utama penghasil data dalam jumlah besar setiap detik. Data yang dihasilkan ini banyak dimanfaatkan dalam berbagai penelitian yang berkaitan dengan analitik big data. Teknik analisis yang digunakan pun bervariasi tergantung pada jenis data dan tujuan studi. Penelitian ini bertujuan untuk mengulas konsep analitik big data, khususnya pada ranah social media mining, beserta teknik-teknik analisis yang digunakan. Pendekatan yang digunakan adalah studi literatur terhadap jurnal ilmiah dan buku yang relevan dengan topik ini. Berdasarkan hasil kajian, ditemukan bahwa media sosial berperan penting dalam menyuplai data yang dapat dimanfaatkan dalam pengambilan keputusan melalui analitik big data. Setiap teknik analitik memiliki keunggulan dan keterbatasan tersendiri, sehingga integrasi beberapa metode dianjurkan guna meningkatkan akurasi hasil analisis. Penelitian ini diharapkan dapat memperluas pemahaman pembaca yang tertarik pada bidang social media mining.

Downloads

Download data is not yet available.

References

A. Gandomi and M. Haider, "Beyond the hype: Big data concepts, methods, and analytics," Int. J. Inf. Manage., vol. 35, no. 2, pp. 137–144, Apr. 2015, doi: 10.1016/j.ijinfomgt.2014.10.007.

M. Batty et al., "Smart cities of the future," Eur. Phys. J. Spec. Top., vol. 214, no. 1, pp. 481–518, Dec. 2012, doi: 10.1140/epjst/e2012-01703-3.

M. A. Carlos, M. Nogueira, and R. J. Machado, "Analysis of dengue outbreaks using big data analytics and social networks," in Proc. 4th Int. Conf. Systems and Informatics (ICSAI), 2017, vol. 2018-Jan., pp. 1592–1597, doi: 10.1109/ICSAI.2017.8248538.

Anonymous, "Sentiment Analysis On Social Media Big Data With Multiple Tweet Words," Int. J. Innov. Technol. Explor. Eng., doi: 10.35940/ijitee.J9684.0881019.

M. M. ElQadi, M. Lesiv, A. G. Dyer, and A. Dorin, "Computer vision-enhanced selection of geo-tagged photos on social network sites for land cover classification," Environ. Model. Softw., vol. 128, Mar. 2020, Art. no. 104696, doi: 10.1016/j.envsoft.2020.104696.

D. Wu and Y. Cui, "Disaster early warning and damage assessment analysis using social media data and geo-location information," Decis. Support Syst., vol. 111, pp. 48–59, 2018, doi: 10.1016/j.dss.2018.04.005.

G. G. Monkman, M. J. Kaiser, and K. Hyder, "Text and data mining of social media to map wildlife recreation activity," Biol. Conserv., vol. 228, pp. 89–99, 2018, doi: 10.1016/j.biocon.2018.10.010.

W. Alhalabi et al., "Social mining for terroristic behavior detection through Arabic tweets characterization," Future Gener. Comput. Syst., vol. 116, pp. 132–144, 2021, doi: 10.1016/j.future.2020.10.027.

T. Hu, B. She, L. Duan, H. Yue, and J. Clunis, "A systematic spatial and temporal sentiment analysis on geo-tweets," IEEE Access, vol. 8, pp. 8658–8667, 2020, doi: 10.1109/ACCESS.2019.2961100.

M. Kolahkaj, A. Harounabadi, A. Nikravanshalmani, and R. Chinipardaz, "A hybrid context-aware approach for e-tourism package recommendation," Electron. Commer. Res. Appl., vol. 42, Feb. 2020, Art. no. 100978, doi: 10.1016/j.elerap.2020.100978.

S. Park, Y. Xu, L. Jiang, Z. Chen, and S. Huang, "Spatial structures of tourism destinations: A trajectory data mining approach leveraging mobile big data," Ann. Tour. Res., vol. 84, Jan. 2020, Art. no. 102973, doi: 10.1016/j.annals.2020.102973.

Y. Yan, J. Chen, and Z. Wang, "Mining public sentiments and perspectives from geotagged social media data," Appl. Geogr., vol. 123, Feb. 2020, Art. no. 102306, doi: 10.1016/j.apgeog.2020.102306.

K. Hou, T. Hou, and L. Cai, "Public attention about COVID-19 on social media: An investigation based on data mining and text analysis," Pers. Individ. Dif., vol. 175, Sep. 2020, Art. no. 110701, doi: 10.1016/j.paid.2021.110701.

M. Abdul-Rahman, E. H. W. Chan, M. S. Wong, V. E. Irekponor, and M. O. Abdul-Rahman, "A framework to simplify pre-processing location-based social media big data for sustainable urban planning and management," Cities, vol. 109, Sep. 2021, Art. no. 102986, doi: 10.1016/j.cities.2020.102986.

K. G. Blumenthal et al., "Mining social media data to assess the risk of skin and soft tissue infections," J. Allergy Clin. Immunol., vol. 144, no. 1, pp. 129–134, Jul. 2019, doi: 10.1016/j.jaci.2019.01.029.

J. A. de Bruijn, H. de Moel, B. Jongman, J. Wagemaker, and J. C. J. H. Aerts, "TAGGS: Grouping Tweets to Improve Global Geoparsing for Disaster Response," J. Geovisualization Spat. Anal., vol. 2, no. 1, 2018, doi: 10.1007/s41651-017-0010-6.

D. T. Larose and C. D. Larose, Discovering Knowledge in Data: An Introduction to Data Mining, 2nd ed. Hoboken, NJ: Wiley, 2014.

J. Han, M. Kamber, and J. Pei, Data Mining: Concepts and Techniques, 2nd ed. [Online]. Available: https://www.researchgate.net/publication/262562891_Data_Mining_Concepts_and_Techniques_2nd_Edition. [Accessed: May 22, 2021].

U. Fayyad, G. Piatetsky-Shapiro, and P. Smyth, "Knowledge Discovery and Data Mining: Towards a Unifying Framework," in Proc. 2nd Int. Conf. Knowledge Discovery and Data Mining, 1996.

M. Allahyari et al., "A Brief Survey of Text Mining: Classification, Clustering and Extraction Techniques," arXiv preprint, arXiv:1707.02919, Jul. 2017.

N. Siyam, O. Alqaryouti, and S. Abdallah, "Mining government tweets to identify and predict citizens engagement," Technol. Soc., vol. 60, 2020, Art. no. 101211, doi: 10.1016/j.techsoc.2019.101211.

C. C. Aggarwal, "An Introduction to Social Network Data Analytics," in Social Network Data Analytics, Springer US, 2011, pp. 1–15.

S. Ji, C. P. Yu, S. F. Fung, S. Pan, and G. Long, "Supervised learning for suicidal ideation detection in online user content," Complexity, vol. 2018, 2018, Art. no. 6157249, doi: 10.1155/2018/6157249.

F. Namugera, R. Wesonga, and P. Jehopio, "Text mining and determinants of sentiments: Twitter social media usage by traditional media houses in Uganda," Comput. Soc. Netw., vol. 6, no. 1, 2019, doi: 10.1186/s40649-019-0063-4.

F. F. Mailo et al., "Analisis Sentimen Data Twitter Menggunakan Metode Text Mining Tentang Masalah Obesitas di Indonesia," J. Sist. Inf. Kesehat. Masy., vol. 4, no. 1, pp. 28–36, 2019.

Downloads

Published

2025-07-24

How to Cite

Umbu Zogara, L. (2025). Eksplorasi Social Media Mining Dalam Analitik Big Data: Metode Dan Implementasi. Jurnal Sistem Informasi Dan Teknologi (SINTEK), 5(2), 194–199. https://doi.org/10.56995/sintek.v5i2.168