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Vol. 4 No. 1 (2023) • Articles
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ANALISIS PENENTUAN POLA DATA PENDUDUK BERHAK MENDAPAT BANTUAN MENGGUNAKAN ALGORITMA APRIORI

Siti Aliyah
Universitas Potensi Utama
Efani Desi
Universitas Potensi Utama
M. Irfan Aldy Nasution
Universitas Potensi Utama
Published: January 25, 2023 Pages: 327-334
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Abstract

Data collection is a process of proving a research result which is used as the basis for studies and opinions. The problem of poverty has always been a fundamental problem that continues to be faced by society. With the problems that exist, the researcher uses a set of data by analyzing a number of population data in the database using data mining with the a apriori algorithm method to produce information. The a apriori algorithm calculation performed by the author retrieved 150 population data to be processed. the results of the research and discussion that have been carried out by researchers that the analysis process of determining population data patterns is entitled to assistance using the a apriori algorithm method can be seen based on a combination of 2 itemsets with a tendency value on unstable income and cement floors in houses with a minimum support value of 70% and minimum value of 84% confidence.

Keywords:
Population Data Apriori Algorithm Association Rule Data Mining
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Author Biographies
Siti Aliyah Universitas Potensi Utama

Program Studi Sistem Informasi, Fakultas Teknik dan Ilmu Komputer, Universitas Potensi Utama, Kota Medan, Provinsi Sumatera Utara, Indonesia

Efani Desi Universitas Potensi Utama

Program Studi Sistem Informasi, Fakultas Teknik dan Ilmu Komputer, Universitas Potensi Utama, Kota Medan, Provinsi Sumatera Utara, Indonesia

M. Irfan Aldy Nasution Universitas Potensi Utama

Program Studi Informatika, Fakultas Teknik dan Ilmu Komputer, Universitas Potensi Utama, Kota Medan, Provinsi Sumatera Utara, Indonesia

How to Cite
Aliyah, S., Desi, E., & Nasution, M. I. A. . (2023). ANALISIS PENENTUAN POLA DATA PENDUDUK BERHAK MENDAPAT BANTUAN MENGGUNAKAN ALGORITMA APRIORI. Jurnal Indonesia : Manajemen Informatika Dan Komunikasi, 4(1), 327-334. https://doi.org/10.35870/jimik.v4i1.185
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References
Total: 19 References
  1. Rao, K.P., 2019, July. A Comparative Study On Apriori And Reverse Apriori In Generation Of Frequent Item Set. In 2019 1st International Conference on Advances in Information Technology (ICAIT) (pp. 337-341). IEEE. DOI: 10.1109/ICAIT47043.2019.8987430
  2. Kesarwani, S., Goel, A. and Sardana, N., 2017, August. MSD-Apriori: Discovering borderline-rare items using association mining. In 2017 Tenth International Conference on Contemporary Computing (IC3) (pp. 1-4). IEEE. DOI: 10.1109/IC3.2017.8284319
  3. Cong, Y., 2020, October. Research on data association rules mining method based on improved apriori algorithm. In 2020 International Conference on Big Data & Artificial Intelligence & Software Engineering (ICBASE) (pp. 373-376). IEEE. DOI: 10.1109/ICBASE51474.2020.00085
  4. Zheng, L., 2020, January. Research on E-commerce potential client mining applied to apriori association rule algorithm. In 2020 international conference on intelligent transportation, big data & smart city (ICITBS) (pp. 667-670). IEEE. DOI: 10.1109/ICITBS49701.2020.00146
  5. Feng, D., Zhu, L. and Zhang, L., 2016, October. Research on improved Apriori algorithm based on MapReduce and HBase. In 2016 IEEE Advanced Information Management, Communicates, Electronic and Automation Control Conference (IMCEC) (pp. 887-891). IEEE. DOI: 10.1109/IMCEC.2016.7867338
  6. Pandey, K.K. and Shukla, D., 2018, December. Mining on relationships in big data era using improve apriori algorithm with MapReduce approach. In 2018 International conference on advanced computation and telecommunication (ICACAT) (pp. 1-5). IEEE. DOI: 10.1109/ICACAT.2018.8933674
  7. Zhou, N., Qiao, M. and Zhou, J., 2019, July. BI_Apriori algorithm: research and application based on battery production data. In 2019 IEEE 9th International Conference on Electronics Information and Emergency Communication (ICEIEC) (pp. 1-5). IEEE. DOI: 10.1109/ICEIEC.2019.8784491
  8. Karimtabar, N. and Fard, M.J.S., 2020, April. An Extension of the Apriori Algorithm for Finding Frequent Items. In 2020 6th International Conference on Web Research (ICWR) (pp. 330-334). IEEE. DOI: 10.1109/ICWR49608.2020.9122282
  9. Verma, N.K., Kumar, S., Kumar, M. and Saxena, P., 2020, December. An Alternate Approach to Improve Access Time for Defining Frequent Item Set through ‘A-Apriori’in Textual Data Set. In 2020 5th IEEE International Conference on Recent Advances and Innovations in Engineering (ICRAIE) (pp. 1-6). IEEE. DOI: 10.1109/ICRAIE51050.2020.9358344
  10. Salam, A. and Sholik, M., 2018. Implementasi Algoritma Apriori untuk Mencari Asosiasi Barang yang Dijual di E-commerce OrderMas. Techno. com, 17(2), pp.158-170. DOI: https://doi.org/10.33633/tc.v17i2.1656.
  11. Valerian, A. and Hakim, L., 2018. Implementasi Algoritma Apriori Untuk Prediksi Stok Peralatan Tulis Pada Toko XYZ. Jurnal Ilmiah Teknologi Infomasi Terapan, 5(1), pp.18-22.
  12. Ristianingrum, S, 2017. Implementasi Data Mining Menggunakan Algoritma Apriori, SINTAK, ISBN: 978-602-8557-20-7.
  13. Sianturi, F.A., 2018. Penerapan Algoritma Apriori Untuk Penentuan Tingkat Pesanan. Jurnal Mantik Penusa, 2(1).
  14. Adiwihardja, C., Hardi, N Widyastuty, W., 2019. Implementasi Data Mining Penjualan Kosmetik Pada Toko Zahrani Menggunakan Algoritma Apriori, Jurnal Speed, 11(2), pp. 1-7.
  15. Susilo, A.A.T., Sunardi, L. and Waruwu, Y., 2019. Penerapan Algoritma Apriori Pada Data Penjualan Kosmetik di Toko Sharly Kota Lubuklinggau. JUTIM (Jurnal Teknik Informatika Musirawas), 4(2), pp.92-100.
  16. Miftahuddin, Y. and Raihan, F.M., 2022. Penerapan Algoritma Aprioti Pada Riwayat Data Kecelakaan Lalu Lintas. INFOTEK, 5(1), pp. 62-71. DOI: 10.29408/jit.v5i1.4402.
  17. Aprianti, W., Hafizd, K.A. and Rizani, M.R., 2017. Implementasi Association Rules dengan Algoritma Apriori pada Dataset Kemiskinan. Limits: Journal of Mathematics and Its Applications, 14(2), pp.145-155. DOI: http://dx.doi.org/10.12962/limits.v14i2.2933.
  18. Anas, A., 2020. Implementasi Algoritma Apriori Untuk Menentukan Strategi Promosi STIE-Graha Karya Muara Bulian. Jurnal Ilmiah Media Sisfo, 14(1), pp.64-70. DOI: https://doi.org/10.33998/mediasisfo.2020.14.1.790.
  19. Risdianti, R., Nasution, A.K., Oktaviandi, R. and Buâ, E., 2021, October. Penerapan Algoritma Apriori Untuk Mengetahui Pola Jenis Kejahatan Yang Sering Terjadi (Studi Kasus: Polsek Percut Sei Tuan). In Seminar Nasional Sains dan Teknologi Informasi (SENSASI) (Vol. 3, No. 1, pp. 117-120).
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