Penerapan Data Mining Untuk Memprediksi Pembelian Mobil Bekas Menggunakan Algoritma Naïve Bayes

  • Diana Yusuf Institut Teknologi dan Bisnis Ahmad Dahlan
Keywords: Database, Data Mining, Used Car, Naïve Bayes

Abstract

Database can also be interpreted as a data warehouse. The amount of data collected in the database can be processed to generate valuable knowledge for science. One popular and widely used technique for processing databases is data mining. Data mining is the process of extracting knowledge from large and complex data warehouse. Data mining encompasses various algorithm to generate knowledge, one of which is naïve bayes. The dataset used in this research, employing the naïve bayes algorithm, consists of attributes relevant to the purchase of used cars, such year, transmission, mileage, car condition, and brand. This research aims to produce patterns and additional knowledge for participants in the used car business to identify the supporting factors in purchasing used cars.

References

Budi Susanto (2007). “Data Mining Menggali Pengetahuan dari Bongkahan Data”. Edisi I. Yogyakarta. C.V ANDI OFFSET.

Dana Sulistiyo Kusumo (2003), “ Data Mining dengan Algoritma Apriori pada RDBMS ORACLE”

Defid Sarjon. 2012. “Data Mining”. (Bahan Kuliah Advance Database). Padang.

Kusrini dan Emha Taufik Luthfi (2009). “Algoritma Data Mining”. Edisi I. Yogyakarta. C.V ANDI OFFSET.

Sani Susanto dan Dedy Suryadi (2010). “Pengantar Data Mining Teknik pemenfaatan data untuk Keperluan Bisnis”. GRAHA ILMU. Feri Sulianta dan Dominikus Juju (2010). “Data Mining Meramalkan Bisnis Perusahaaan”. Edisi I. Yogyakarta. C.V ALEX MEDIA KOMPUTINDO.

Published
2023-06-13
How to Cite
Diana Yusuf. (2023). Penerapan Data Mining Untuk Memprediksi Pembelian Mobil Bekas Menggunakan Algoritma Naïve Bayes. Jurnal Sistem Informasi (JUSIN), 4(1), 29-38. https://doi.org/10.32546/jusin.v4i1.2070