Application of Data Mining in FP Growth Algorithm to Determine Customer Purchasing Patterns of Geprek Chicken

Puji Yulianti; Luzi Dwi Oktaviana; Desty Rakhmawati

doi:10.35877/454RI.jinav2793

Puji Yulianti Department of Information System, Amikom Purwokerto University, Banyumas City, 53127, Indonesia (ID)
Luzi Dwi Oktaviana Department of Information System, Amikom Purwokerto University, Banyumas City, 53127, Indonesia (ID)
Desty Rakhmawati Department of Information System, Amikom Purwokerto University, Banyumas City, 53127, Indonesia (ID)

https://doi.org/10.35877/454RI.jinav2793

Keywords: Data Mining, FP Growth, Algorithm, Ayam Geprek Purwokerto, Frequent Itemsets

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Abstract

The FP-Growth data mining algorithm used in the study to determine customer shopping patterns at Ayam Geprek Purwokerto shop. Focusing on identifying repeat purchase events, this research aims to improve the marketing strategy and operational efficiency of Ayam Geprek Purwokerto shop. With an in-depth understanding of customer preferences and shopping habits, this research provides valuable insights for business owners in customizing menu offerings and layouts that can significantly increase sales. The results of this purchase analysis provide an in-depth understanding of consumer preferences and help determine the right course of action to improve Ayam Geprek Purwokerto's business. This study shows that using the FP-Growth algorithm to analyze customer buying patterns can significantly improve the efficiency and effectiveness of Ayam Geprek Purwokerto. By understanding common buying patterns, business owners can increase inventory design more effective promotion strategies, and improve customer satisfaction. The research shows that this can be a useful guide for business owners to create more targeted and effective marketing strategies to increase business. Thus, this research significantly increases the understanding of consumer shopping habits in the food industry, especially in the Ayam Geprek Purokerto shop.The results of this study are expected to be the basis for developing smarter and more effective marketing strategies to improve the competitiveness of food companies. In addition, this research encourages further use of data mining in optimizing inventory management and marketing strategies for the food industry.

References

Arta, I. K. J., Indrawan, G., & Dantes, G. R. (2016). Data Mining Rekomendasi Calon Mahasiswa Berprestasi Di Stmik Denpasar Menggunakan Metode Technique for Others Reference By Similarity To Ideal Solution. JST (Jurnal Sains Dan Teknologi), 5(2), 746–760. https://doi.org/10.23887/jst-undiksha.v5i2.8549

Azis, Y. A. (2023). Studi Pustaka: Pengertian, Tujaun, Sumber dan Metode. Deepublishstore.

Dewi, M. U. (2022). Data Mining Dalam Bisnis E-Commerce. Sistem Informasi Universitas Stekom.

Dewi, S. D., & Suarna, N. (2024). Penerapan Data Mining Dalam Algoritma Fp Growth Untuk Menentukan Pola Pembelian Pelanggan Online Shop Cirebon Laku. JATI (Jurnal Mhs. Tek. Inform, 08(01), 1180–1186.

Fariza, A. N. (2022). Lakukan Data Cleaning, Langkah Pengolahan Data Agar Lebih Rapi. Skawan Media.

FTIK. (2024). 3 Tantangan Utama Dalam Data Minning dan Cara Mengatasinya. FTIK Teknokrat. https://ftik.teknokrat.ac.id/3-tantangan-utama-dalam-data-mining-dan-cara-mengatasinya/

Harahap, S. Z., & Nastuti, A. (2019). Teknik Data Mining Untuk Penentuan Paket Hemat Sembako. Jurnal Ilmiah Fakultas Sains Dan Teknologi, 7(3), 111–119.

Iqbal, M. (2011). Perkembangan Teknologi dalam Industri Makanan dan Bagaimana Kita Menyikapinya? Kompasiana.Com.

Jagoan Hosting Team. (2023). Data Mining: Pengertian, Fungsi, Metode & Penerapannya. Jagoan Hosting.

Karsito, K., & Sari, W. M. (2018). Prediction of Potential Sales of Delifrance Products with the Naive Bayes Method at Pt. Pangan Lestari. Jurnal Teknologi Pelita Bangsa, 9(1), 67–78. https://jurnal.pelitabangsa.ac.id/index.php/sigma/article/view/465

Lestari, L. M. (2023). Penerapan Algoritma FP-Growth Untuk Menentukan Pola Penjualan Toko Ellia Umami. Jurnal Sekolah Tinggi Ilmu Ekonomi Trianandra, 1(3), 367–378.

Munanda, E., & Monalisa, S. (2021). Penerapan Algoritma FP-Growth Pada Data Transaksi Penjualan Untuk Penentuan Tataletak. Jurnal Ilmiah Rekayasa Dan Manajemen Sistem Informasi, 7(2), 173–184.

Mustofa, Z. (2021). Data Mining: Pengertian,Proses, Manfaat, Dan 3 Contoh Penerapannya. Teknik Informatika Universitas Stekom.

Nurfadilah, A. (2022). Tahapan Proses Data Mining/Knowledge Discovery (KDD). Kompasiana.Com.

Oliver, A. (2023). Bikin Data Lebih Mudah Dibaca, Yuk, Kenalan dengan Data Preprocessing. Glints.Com.

Qotrun, A. (2024). Pengertian Metode Observasi dan Contohnya. Gramedia.

Suhada, S., Ratag, D., Gunawan, G., Wintana, D., & Hidayatulloh, T. (2020). Rediksi Potensi Penjualan Produk Delifrance Dengan Metode Naive Bayes Di Pt. Pangan Lestari. Jurnal Swabumi, 8(2), 118–126.

Utama, K. M. R. A., Umar, R., & Yudhana, A. (2020). Penerapan Algoritma FP-Growth Untuk Penentuan Pola Pembelian Transaksi Penjualan Pada Toko Kgs Rizky Motor. Dinamik, 25(1), 20–28. https://doi.org/10.35315/dinamik.v25i1.7870