Penerapan Algoritma Apriori Pada Prediksi Penjualan Tanaman Hias Bromelia (Studi Kasus: Karimah Flora)

Authors

  • Mufidah Karimah Universitas Pamulang
  • Wulan Pahira Universitas Pamulang

DOI:

https://doi.org/10.32493/informatika.v7i1.16135

Keywords:

Apriori Algorithm, Prediction, Decorative Plants, Bromelia

Abstract

Apriori algorithms are part of the algorithms in data mining which are often used to find data patterns. Apriori algorithms are often used in sales transaction data. In this study, the authors discussed the application of apriori to the prediction of sales of ornamental bromeliads. The author found that one of the problems is often taking care of plants. Of course this reduces the revenue at the Karimah Flora shop. From these problems the authors conducted research on sales transaction data in the last 3 months of 2020, namely August, September and October. Then the authors collect data on the sale of ornamental plants bromeliads which will then be calculated by applying the a priori algorithm formula. The calculation determines which of the 21 types of ornamental plants bromeliads will be studied, after which the authors conduct an analysis for order combination patterns of up to 4-itemsets, so that they can form an association rule. By applying the algorithm in this study, it produces a combination of ornamental bromeliads to attract consumers to buy promotional packages offered according to the pattern.

References

Buulo, E. (2020). Data Mining untuk Perguruan Tinggi. DI Yogyakarta: Deepublish.

Evinola. (2019). Mengenal Ruang Lingkup Tanaman Hias. Jawa Timur: Uwais Inspirasi Indonesia.

Kurniawati, L., Kusuma, A. E., & Dewansyah, B. (2019). Implementasi Algotima Apriori untuk Menentukan Persediaan Spare Part Compressor. Journal of Computer Engineering System and Science, IV(1), 6-10.

Pahlevi, O., Sugandi, A., & Sintawati, I. D. (2018). Penerapan Algoritma Apriori dalam Pengendalian Kualitas Produk. Sinkron, III(1), 272-278.

Panjaitan, S., Sulindawaty, Amin, M., Lindawati, S., Watrianthos, R., Sihotang, H. T., & Sinaga, B. (2019). Implementation of Apriori Algorithm for Analysis of Consumer Purchase Patterns. The International Conference on Computer Science and Applied Mathematic, 1-9.

Putra, J. L., Raharjo, M., Sandi, T. A., Ridwan, & Prasetyo, R. (2019). Implementasi Algoritma Apriori Terhadap Data Penjualan pada Perusahaan Retail. Jurnal PILAR Nusa Mandiri, XV(1), 85-90.

Sherly. (2020). Bromelia, Tanaman Hias Tak Manja. Jakarta: Bhuana Ilmu Populer.

Sianturi, F. A. (2018). Penerapan Algoritma Apriori untuk Penentuan Tingkat Pesanan. Jurnal Mantik Penusa, II(1), 50-57.

Simbolon, P. H. (2019). Implementasi Data Mining Pada Sistem Persediaan Barang Menggunakan Algoritma Apriori (Studi Kasus: Srikandi Cash Credit Elektronik dan Furniture). Jurnal Riset Komputer (JURIKOM), VI(4), 402.

Yendrizal. (2020). Data Mining Penjualan Tanaman Hias dengan Algoritma Apriori pada Toko Flores Elishabet. Jurnal Media Informatika Budidarma, IV(2), 472-478.

Jurnal Informatika Universitas Pamulang Vol. 7 No. 1 Maret 2022

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Published

2022-05-31

Issue

Vol. 7 No. 1 (2022): JURNAL INFORMATIKA UNIVERSITAS PAMULANG

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Article

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