Analisis Data Penjualan Laptop ASUS, Lenovo, dan Produk TV Berbasis Visualisasi Python
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Abstract
Penelitian ini menganalisis dan memvisualisasikan data penjualan laptop dan televisi untuk memahami tren harga, perilaku konsumen, serta distribusi geografis pembeli. Analisis dilakukan melalui perbandingan harga mingguan laptop ASUS dan Lenovo selama satu tahun, visualisasi heatmap untuk mengidentifikasi periode pembelian tertinggi, serta scatter plot untuk memetakan persebaran pembeli di Pulau Sumatera. Pada produk televisi, dilakukan analisis statistik deskriptif dan uji ANOVA untuk menguji pengaruh rating terhadap harga jual. Hasil penelitian menunjukkan adanya perbedaan signifikan antara merek dan rating terhadap harga, serta mengungkap pola pembelian yang dapat dimanfaatkan dalam strategi harga dan distribusi produk elektronik. Secara praktis, penelitian ini berkontribusi dalam pengembangan analisis data penjualan berbasis Python untuk mendukung pengambilan keputusan bisnis.
References
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[4] M. Carter dan S. Evans, “Effects of price, usage and pleasure on consumer buying behavior,” Front. Psychol., vol. 13, Art. 823890, 2022.
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[7] K. Lee, J. Kim, dan Y. Park, “Determinants of laptop prices: an empirical study using regression analysis,” Comput. Econ., vol. 58, pp. 1207–1222, 2024.
[8] E. Low, Y. Zhang, dan X. Li, “Consumer perception towards laptop quality and post‑purchase behavior,” J. Retail. Consum. Serv., vol. 72, Art. 103044, 2023.
[9] D. Moreno dan J. Li, “Correlation of product rating and sales price: an empirical study,” J. Market. Data Sc., vol. 11, no. 3, pp. 82–95, 2022.
[10] A. Park, S. Cho, dan J. Kim, “Consumer behavior in television purchasing: an empirical investigation,” Telecommun. Policy, vol. 47, no. 6, Art. 102324, 2023.
[11] S. Patel dan D. Rao, “TV advertising and online sales: intertemporal effects,” J. Retail., vol. 99, no. 1, pp. 103–119, 2023.
[12] P. Reddy dan M. Patil, “Temporal analysis of consumer purchase patterns in retail electronics,” Retail Analytics J., vol. 6, no. 1, pp. 45–59, 2024.
[13] R. Singh dan T. Sharma, “Consumer behavior and price sensitivity in electronics markets,” Asian J. Econ. Bus., vol. 7, no. 2, pp. 140–152, 2022.
[14] S. Sharma, R. Kumar, dan A. Tomar, “Analysis of laptop price influencing factors and price prediction,” Int. J. Semantic Comput., vol. 16, no. 2, pp. 275–290, 2024.
[15] H. Tan dan M. Gao, “Pricing and brand effects on laptop purchase intention: a consumer behavior study,” Electron. Commer. Res., vol. 23, pp. 45–63, 2022.
[16] J. Taylor, P. Miller, dan L. Nguyen, “The future of TV‑shopping: predicting user purchase intention,” Technol. Forecasting Soc. Change, vol. 192, Art. 122327, 2024.
[17] Y. Wang, Z. Zhang, dan Q. Li, “TV shopping for apparel: perceived information and purchase intention,” Behav. Sci. Theory Pract., vol. 28, no. 2, pp. 189–204, 2020.
[18] Y. Zhou dan S. Xu, “Heatmap-based visualization for retail time‑period analysis,” Data Vis. J., vol. 10, no. 2, pp. 110–122, 2023.
[19] L. Zhou dan S. Xu, “Purchase patterns in electronics: an empirical comparison,” J. Quant. Mark. Res., vol. 34, no. 1, pp. 89–104, 2023.
[20] N. Zhu dan K. Wong, “Machine learning approach to product rating and pricing prediction,” J. Appl. Data Sci., vol. 5, no. 3, pp. 211–227, 2021.
Published
2026-01-26
How to Cite
CHAIRUNNISA, Nanda; KAHAR, Novhirtamely.
Analisis Data Penjualan Laptop ASUS, Lenovo, dan Produk TV Berbasis Visualisasi Python.
Seminar Nasional Informatika (SENATIKA), [S.l.], p. 205-213, jan. 2026.
Available at: <https://www.ejournal.pelitaindonesia.ac.id/ojs32/index.php/SENATIKA/article/view/5360>. Date accessed: 15 feb. 2026.
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