MARKET BASKET ANALYSIS OF ADMINISTRATIVE PATTERNS DATA OF CONSUMER PURCHASES USING DATA MINING TECHNOLOGY

Lukman  Samboteng; Rulinawaty Rulinawaty; M.Rachmat  Kasmad; Mutmainnah  Basit; Robbi Rahim

doi:10.5937/jaes0-32019

Lukman Samboteng Politeknik STIA LAN Makassar, Makassar, Indonesia
Rulinawaty Rulinawaty Universitas Terbuka, Indonesia
M.Rachmat Kasmad Universitas Negeri Makassar, Makassar, Indonesia
Mutmainnah Basit Universitas Negeri Makassar, Makassar, Indonesia
Robbi Rahim Sekolah Tinggi Ilmu Manajemen Sukma, Medan, Indonesia

DOI: https://doi.org/10.5937/jaes0-32019

Keywords: apriori algorithms, transaction data, data mining, associations, consumer patterns

Abstract

Food is the ingredient that enables people to grow, develop, and achieve. For this reason, food quality and types of food must be considered so that they are safe for consumption and managed. Some plant-based foodstuffs are often processed and consumed by the community, even the most needed in food processing. In this case, the research was carried out using data mining with market basket analysis algorithms to obtain very valuable information to decide the inventory of the type of material needed. Market Based Analysis method is used to analyze all data and create patterns for each data. One method of Market Based Analysis in question is the association rule with a priori algorithm. This algorithm produces sales transactions with strong associations between items in the transaction which are used as sales recommendations that help users (owners) get recommendations when users see details of the itemset purchased. From the results of the trials in this study, it was found that the greater the minimum support (minsup) and minimum confidence (minconf), the less time it takes to produce recommendations and the fewer recommendations are given, but the recommendations given come from transactions that often appear.

References

Djamaludin, I.; Nursikuwagus, A. (2017). Analisis Pola Pembelian Konsumen Pada Transaksi Penjualan Menggunakan Algoritma Apriori, Simetris : Jurnal Teknik Mesin, Elektro Dan Ilmu Komputer, Vol. 8, No. 2, 671. doi:10.24176/simet.v8i2.1566

Jayapana, R. D.; Rahayu, Y. (2015). Analisis pola pembelian konsumen dengan algoritma apriori pada apotek rahayu jepara, UG Jurnal, Vol. Vol. 8, 1–6

Hartama, D.; Perdana Windarto, A.; Wanto, A. (2019). The Application of Data Mining in Determining Patterns of Interest of High School Graduates, Journal of Physics: Conference Series, Vol. 1339, No. 1. doi:10.1088/1742-6596/1339/1/012042

Windarto, A. P.; Indriani, U.; Raharjo, M. R.; Dewi, L. S. (2020). Bagian 1: Kombinasi Metode Klastering dan Klasifikasi (Kasus Pandemi Covid-19 di Indonesia), Jurnal Media Informatika Budidarma, Vol. 4, No. 3, 855. doi:10.30865/mib.v4i3.2312

Jatnika, H.; Huda, M.; Amelia, R. R.; Manuhutu, M. A. (2021). Analysis of Data Mining in the Group of Water Pollution Areas using the K-Means Method in Indonesia Analysis of Data Mining in the Group of Water Pollution Areas using the K-Means Method in Indonesia, Journal of Physics: Conference Series PAPER. doi:10.1088/1742-6596/1783/1/012014

Aprianti, W.; Hafizd, K. A.; Rizani, M. R. (2017). Implementasi Association Rules dengan Algoritma Apriori pada Dataset Kemiskinan, Limits: Journal of Mathematics and Its Applications, Vol. 14, No. 2, 57. doi:10.12962/limits.v14i2.2933

Author, F.; Author, S.; Author, T. (2021). Analysis of Library Book Borrowing Patterns Using Apriori Association Data Mining Techniques ( Case : SMK ABC ). doi:10.18421/TEMxx-xx

Ge, Z.; Song, Z.; Ding, S. X.; Huang, B. (2017). Data Mining and Analytics in the Process Industry: The Role of Machine Learning, IEEE Access, Vol. 5, 20590–20616. doi:10.1109/ACCESS.2017.2756872

Aprilla Dennis. (2013). Belajar Data Mining dengan RapidMiner, Innovation and Knowledge Management in Business Globalization: Theory & Practice, Vols 1 and 2, Vol. 5, No. 4, 1–5

Wahidin, W.; Mugihartadi, M.; Hasanah, T.; Aviani, B.; Pratiwi, H. (2021). Application of data mining techniques using the K-Means Method on Unmet Need of Health Services by Province in Indonesia Application of data mining techniques using the K-Means Method on Unmet Need of Health Services by Province in Indonesia, Journal of Physics: Conference Series PAPER. doi:10.1088/1742-6596/1783/1/012012

Elsi, Z. R. S.; Pratiwi, H.; Efendi, Y.; Rusdina, R.; Alfah, R.; Windarto, A. P.; Wiza, F. (2020). Utilization of Data Mining Techniques in National Food Security during the Covid-19 Pandemic in Indonesia, Journal of Physics: Conference Series, Vol. 1594, No. 1. doi:10.1088/1742-6596/1594/1/012007

Anil Kumar, K. M.; Ajay, B.; Shashank, R.; Amogha Subramanya, D. A. (2019). An apriori method for topic extraction from text files, International Journal of Recent Technology and Engineering, Vol. 8, No. 2, 2516–2521. doi:10.35940/ijrte.A3068.078219

Bailey-Wilson, J. E.; Brennan, J. S.; Bull, S. B.; Culverhouse, R.; Kim, Y.; Jiang, Y.; Jung, J.; Li, Q.; Lamina, C.; Liu, Y.; Mägi, R.; Niu, Y. S.; Simpson, C. L.; Wang, L.; Yilmaz, Y. E.; Zhang, H.; Zhang, Z. (2011). Regression and data mining methods for analyses of multiple rare variants in the Genetic Analysis Workshop 17 mini-exome data, Genetic Epidemiology, Vol. 35, No. SUPPL. 1, 92–100. doi:10.1002/gepi.20657

Agustiani, N.; Suhendro, D.; Apriori, K.; Pembahasan, A. (2020). Penerapan Data Mining Metode Apriori Dalam Implementasi Penjualan Di Alfamart, Vol. 2, 300–304

Waluyo, A.; Jatnika, H.; Permatasari, M. R. S.; Tuslaela, T.; Purnamasari, I.; Windarto, A. P. (2020). Data Mining Optimization uses C4.5 Classification and Particle Swarm Optimization (PSO) in the location selection of Student Boardinghouses, IOP Conference Series: Materials Science and Engineering, Vol. 874, No. 1, 1–9. doi:10.1088/1757-899X/874/1/012024

Supriyadi, B.; Windarto, A. P.; Soemartono, T.; Mungad. (2018). Classification of natural disaster prone areas in Indonesia using K-means, International Journal of Grid and Distributed Computing, Vol. 11, No. 8, 87–98

Widyastuti, M.; Fepdiani Simanjuntak, A. G.; Hartama, D.; Windarto, A. P.; Wanto, A. (2019). Classification Model C.45 on Determining the Quality of Custumer Service in Bank BTN Pematangsiantar Branch, Journal of Physics: Conference Series, Vol. 1255, No. 012002, 1–6. doi:10.1088/1742-6596/1255/1/012002

Jantan, H.; Jamil, A. Z. M. (2019). Association rule mining based crime analysis using apriori algorithm, International Journal of Advanced Trends in Computer Science and Engineering, Vol. 8, No. 1.5 Special Issue, 18–24. doi:10.30534/ijatcse/2019/0581.52019

Yulanda, R. D.; Wahyuningsih, S.; Amijaya, F. D. T. (2019). Association rules with apriori algorithm and hash-based algorithm, Journal of Physics: Conference Series, Vol. 1277, No. 1. doi:10.1088/1742-6596/1277/1/012048

Kristiana, T.; Putri, S. A.; Nurmalasari; Handayani, R. I.; Merlina, N.; Yunita, N. (2020). Association Rule Implementation Using Algorithm Apriori to Analize Fishing Pattern in Indonesia, Journal of Physics: Conference Series, Vol. 1641, No. 1. doi:10.1088/1742-6596/1641/1/012072

Ruswati, R.; Gufroni, A. I.; Rianto, R. (2018). Associative Analysis Data Mining Pattern Against Traffic Accidents Using Apriori Algorithm, Scientific Journal of Informatics, Vol. 5, No. 2, 91–104. doi:10.15294/sji.v5i2.16199

Hanguang, L.; Yu, N. (2012). Intrusion Detection Technology Research Based on Apriori Algorithm, Physics Procedia, Vol. 24, 1615–1620. doi:10.1016/j.phpro.2012.02.238