Penentuan Pola Pembunuhan Di Nusa Tenggara Barat Menggunakan Association Rules Algoritma Apriori

Authors

  • Sri Wardiani Institut Teknologi Sepuluh November

Keywords:

Knowledge discovery in database, data mining, murder

Abstract

Murder is a crime that results in the loss of another person’s life due to certain reasons, the incident was planned or not planned. Murder cases are only in news cases about chronological events, so no new knowledge is gained. This study aims ti determine the patterns of murder that occurred in West Nusa Tenggara using the Knowledge Discovery in Database (KDD) technique which includes data mining. The data mining technique used was the a priori algorithm rules association method using data obtained from the NTB Regional Police and other integrated sources. The results show that the pattern of murder that occurs was if there was a murder of women with sharp object, then the motive for the number must be jealously which had a relationship with the perpetrator, then the perpetrator was the opposite sex.  With a confidence value (level of confidence level) of 100% that the rule was sure to happen. This research was used by parties involved in making decisions in the future.

References

Andriyanto, I 2020. Peranan Data Mining Dalam Perusahaan. Retrieved 28, from https://www.course-net.com/peranan-data-mining-dalam-perusahaan/

Dariyo, A. 2013. Mengapa Seseorang Mau Menjadi Pembunuh. Jurnal Penelitian Psikologi, Vol.04(No.01), 10-20.

Dengen, C. N., Kusrini, & Luthfi, E. T. (2019, Desember). Penentuan Association Rule Pada Kelulusan. JURTI.

Fikri, A. 2009. Penerapan Data Mining Untuk Mengetahui Tingkat Kekuatan Beton Yang Dihasilkan. 5-11.

Hahsler, M., & Chellubonia, S. 2015. Visualizing Association Rules: Introduction to the. 1-27.

Hakim, L., & Fauzy, A. 2015. Penentuan Pola Hubungan Kecelakaan Lalu Lintas Menggunakan Metode Association Rules dengan Algoritma Apriori. 1-9. Universitas Islam Indonesia.

Jaya, H., Gunawan, R., & Kustini, R. 2019. Penerapan Data Mining Untuk Memprediksi Target. Sains dan Komputer (SAINTIKOM), pp. 219~227.

Kawale, N. M., & Dahima, S. 2018. Market Basket Analysis using Apriori Algorithm in R Language. Inernational Journal of Trend in Scientic Researc and Development , Vol.2(Issue.4).

Mardi, Y. 2015. Data Mining : Klasifikasi Menggunakan Algoritma C4.5. Jurnal Edik Informatika, V2.i2(213-219)(ISSN : 2407-0491).

Riandari, F., & Simangunsong, A. 2019. Penerapan Algoritma C4.5 Untuk Mengukur Tingkat. Jurnal Mantik Penusa, pp 1-7.

Riszky, A. R., & Sadikin, M. 2019. Data Mining using Apriori Algorithm for Product Recommendation for Customers. Jurnal Teknologi dan Sistem Komputer, Vol. 7(3), Pages , 103-108.

Setianingsih, D., & Hakim, F. 2015. Penerapan Data Mining Dalam Analisis Kejadian Tanah. Prosiding Seminar Nasional Matematika dan Pendidikan Matematika UMS , 731-741.

Shivali, Birla, J., & Gurpreet. 2015. Knowledge Discovery in Data-Mining. International Journal of Engineering Research & Technology (IJERT(10), Pag. 1-5.

Simaremare, R. 2019. ISSN: 2278-0181.

Badan Pusat Statistik,2020 .Statistik Kriminal 2020.Jakarta,DKI:Penulis. Diakses dari Badan Pusat Statistik (bps.go.id)- pdf

Sugiono, Nurdiani, S., Linawati, S., Safitri, R. A., & Saputra, E. P. 2019. Pengelompokan Perilaku Mahasiswa Pada. Volume 19.

Susanto, H. 2015. Data Mining Untuk Memprediksi Prestasi Siswa. Jurnal Pendidikan Vokasi, 222-231.

Yanto, R., & Khoiriah, R. 2015. Implementasi Data Mining dengan Metode Algoritma. Citec Journal, Vol.2(No.2), Hal.102-113.

Zainafree, I. 2009. Euthanasia. KEMAS, 4(2), 183-190.

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Published

2024-07-27