Spatial Autoregressive Quantile Regression Modeling of the Distribution of Drug Users in the District Karo

Authors

Nanda , Macrani Adi Putri Siregar

DOI:

10.29303/jpm.v19i2.6545

Published:

2024-03-19

Issue:

Vol. 19 No. 2 (2024): March 2024

Keywords:

Drug Abuse Factors; Karo District; SARQR

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Nanda, & Siregar, M. A. P. (2024). Spatial Autoregressive Quantile Regression Modeling of the Distribution of Drug Users in the District Karo. Jurnal Pijar Mipa, 19(2), 248–253. https://doi.org/10.29303/jpm.v19i2.6545

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Abstract

BNN data shows that an average of 50 people die from drugs every day, and Karo Regency is in second place for the distribution of drug abuse in North Sumatra after Medan City. Variables that have this risk include drug factors, namely availability and ease of obtaining drugs, individual factors, environmental factors, family factors, and social factors. Based on this, a model is needed to determine the development of the case. The SARQR model combines SAR modeling with quantile regression (QR). Combining the SAR model with quantile regression produces a model that is good for overcoming the problems of dependency and heterogeneity in modeling spatial data and is resistant to outlier data. This research aims to determine the Spatial Autoregressive Quantile Regression Model for the distribution of drug users in the Karo Regency. The type of research used is quantitative research. The data type used is secondary data, namely, the kind of data already existing, and the data source used in this research is drug users in the Karo district. The research results show that the Spatial Autoregressive Quantile Regression model for the distribution of drug users in Karo Regency obtained estimation results for the distribution parameters of drug users using a significance test. This model explains that the factors that significantly influence drug abuse are age, gender, occupation, and other underlying factors.

References

Purbanto, H., & Hidayat, B. (2023). Systematic Literature Review: Penyalahgunaan Narkoba di Kalangan Remaja dalam Perspektif Psikologi dan Islam. Al-Hikmah: Jurnal Agama dan Ilmu Pengetahuan, 20(1), 1-13.

Banjar, H., Narkoba dari Masa ke Masa. Medan: Mitra Medan, 2019.

Lukman, G. A., Alifah, A. P., Divarianti, A., & Humaedi, S. (2021). Kasus narkoba di Indonesia dan upaya pencegahannya di kalangan remaja. Jurnal Penelitian Dan Pengabdian Kepada Masyarakat (JPPM), 2(3), 405-417.

Zulkarnain, A. (2020). Fenomenologi terhadap Kalangan Pemuda Penyalahgunaan Narkoba di Perumnas Wekke’e Kota Parepare (Doctoral dissertation, IAIN Parepare).

Saputra, H., & Chalim, M. A. (2018). Penerapan sistem pemidanaan terhadap pelaku tindak pidana penyalahgunaan narkoba (Studi kasus di Polda Jateng). Jurnal Daulat Hukum, 1(1).

Santi, G. A. N., Yuliartini, N. P. R., & Mangku, D. G. S. (2019). Perlindungan Hukum Terhadap Korban Tindak Pidana Penyalahgunaan Narkotika di Kabupaten Buleleng. Jurnal Komunitas Yustisia, 2(3), 216-226.

Wirasila, A.A.N. dan Purwani, S.P.M.E., Tindak Pidana Narkotika Dan Penanggulangan (Bagian Hukum Pidana), Universitas Udayana, Bali, 2017.

Wardani, R. A. (2018). Pemodelan Regresi Kuantil Spasial Autoregresif (Sarqr) untuk Mengatasi Efek Spasial Pada Data Yang Mengandung Outlier (Studi Kasus Pada Data Tingkat Kriminalitas Provinsi Jawa Tengah). Universitas Negeri Semarang.

Yasin, H., Waryanto, B., & Hakim, A. R. (2020). Regresi Spasial (Aplikasi dengan R). Ponorogo: WADE Group.

Arum, P. R., Gautama, R. P., Fitriani, I., & Naza, F. (2023). Identifying Factors that Influence Life Expectancy in Central Java Using Spatial Regression Models. Jurnal Ilmiah Toeri dan Aplikasi Statistik, 16(2) : 606-613.

Rizki, M. I., Sadida, H. Q., & Fauziah, A. N. (2021, December). Pemodelan Spatial Autoregressive Quantile Regression pada Tingkat Kemiskinan di Provinsi Jawa Barat. In E-Prosiding Seminar Nasional Statistika| Departemen Statistika FMIPA Universitas Padjadjaran (Vol. 10, pp. 1-7).

Rizki, M. I., & Ammar, T. (2022, May). Pemodelan Spatial Autoregressive Quantile Regression Pada Faktor Yang Memengaruhi Tingkat Incident Rate Demam Berdarah Dengue di Jawa Barat. In Prosiding Seminar Nasional Matematika dan Statistika (Vol. 2).

Taqiyyuddin, T. A., & Irfan, M. Faktor Penyebab Kemiskinan di Provinsi Jawa Barat Menggunakan Spatial Autoregressive Quantile Regression. Jurnal Sains Matematika dan Statistika, 8(1), 59-69.

Siyoto, S., & Sodik, M. A. (2015). Dasar metodologi penelitian. literasi media publishing.

Japany, A. M., & Firnanda, A. (2022, November). Analisis Spasial Upah Minimum Kabupaten/Kota di Provinsi Jawa Tengah Tahun 2017-2021 dengan Model SAR-RE. In Seminar Nasional Official Statistics (Vol. 2022, No. 1, pp. 731-740).

Zebua, H. I. (2023). SPATIAL AUTOREGRESSIVE QUANTILE REGRESSION PADA KASUS TUBERKULOSIS DI KOTA BANDUNG. Journal of Analytical Research, Statistics and Computation, 2(2).

Bunsaman, S. M., & Krisnani, H. (2020). Peran orangtua dalam pencegahan dan penanganan penyalahgunaan narkoba pada remaja. Prosiding Penelitian dan Pengabdian kepada Masyarakat, 7(1), 221-228.

Lusiana, E. D., Pramoedyo, H. E. N. N. Y., & Sudarmawan, B. N. (2022). Spatial quantile autoregressive model: case study of income inequality in Indonesia. Sains Malaysiana, 51(11), 3795-3806.

Zebua, H. I., & Jaya, I. G. N. M. (2022). Spatial Autoregressive Model of Tuberculosis Cases in Central Java Province 2019. CAUCHY: Jurnal Matematika Murni dan Aplikasi, 7(2), 240-248.

Author Biographies

Nanda, Mathematics Study Program, Universitas Islam Negeri Sumatera Utara

Macrani Adi Putri Siregar, Mathematics Study Program, Universitas Islam Negeri Sumatera Utara

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