Product Recommendation System Application Using Web-Based Equivalence Class Transformation (Eclat) algorithm

Authors

  • Mochzen Gito Resmi SEKOLAH TINGGI TEKNOLOGI WASTUKANCANA
  • Teguh Iman Hermanto STT Wastukancana, Purwakarta, West Java
  • Miftah Al Ghozali STT Wastukancana, Purwakarta, West Java

DOI:

10.33395/sinkron.v7i3.11454

Keywords:

Market Basket Analysis, Association Rule, ECLAT

Abstract

The use of saved transaction data can provide a lot of knowledge that useful to the company in making policy and find the strategy in Alfamidi. In applying that goal, that is using Market Business Analysis. One of the techniques of Data Mining is Association Rule, which is the procedure of Market Basket Analysis to find the customer buying patterns. This pattern can be one of the ways in making policy and business strategy. One pattern determined by two parameters, they are support (support value) and confidence (certainly value). This analysis used algorithm Equivalence Class Transformation (ECLAT). One of the patterns resulted from analysis to the 30 transaction data with 12 category items. As an instance, if we buy strawberry jam then buy essence of bread with confidence value = 1%. The results obtained an also be used in helping the Alfamidi to help in determine the inventory decisions. So, the conclusion may be taken if consumers could buy strawberry jam then bought essence of bread simultaneously, then the Alfamidi should at least maintain the availability stock of both these items in order to remain the same.

GS Cited Analysis

Downloads

Download data is not yet available.

References

Alma, E., Utami, E., & Wahyu Wibowo, F. (2020). Implementasi Algoritma Apriori untuk Rekomendasi Produk pada Toko Online Implementation of Apriori Algorithms for Product Recommendations at Online Stores. Citec Journal, 7(1).

Aprizal, A., Hasriani, H., & Ningsih, W. (2016). Implementasi Data Mining Untuk Penentuan Posisi Barang pada Rak Menggunakan Metode Apriori Pada PT Midi Utama Indonesia. Techo.COM, 15(4), 335–342.

Arinda, S. (2017). Implemantasi Data Mining Menggunakan Algoritma Eclat. Prosiding SINTAK, 388–391.

Arnomo, S. A. (2021). Market Basket Analysis pada Barang Minimarket dimasa Pandemi Covid-19. Jurnal Sistem Dan Teknologi Informasi (Justin), 9(2), 127. https://doi.org/10.26418/justin.v9i2.43243

Asriningtias, Y., & Mardhiyah, R. (2014). Aplikasi Data Mining Untuk Menampilkan Informasi. Informatika, 8(1), 837–848.

Elisa, E. (2018). Market Basket Analysis Pada Mini Market Ayu Dengan Algoritma Apriori. Jurnal RESTI (Rekayasa Sistem Dan Teknologi Informasi), 2(2), 472–478. https://doi.org/10.29207/resti.v2i2.280

FAHRUDIN, N. F. (2019). Penerapan Algoritma Apriori untuk Market Basket Analysis. MIND Journal, 1(2), 13–23. https://doi.org/10.26760/mindjournal.v4i1.13-23

Lisnawita, L., & Devega, M. (2018). Analisis Perbandingan Algoritma Apriori Dan Algoritma Eclat Dalam Menentukan Pola Peminjaman Buku Di Perpustakaan Universitas Lancang Kuning. INOVTEK Polbeng - Seri Informatika, 3(2), 118. https://doi.org/10.35314/isi.v3i2.753

Maulana, A., & Fajrin, A. A. (2018). Penerapan Data Mining Untuk Analisis Pola Pembelian Konsumen Dengan Algoritma Fp-Growth Pada Data Transaksi Penjualan Spare Part Motor. Klik - Kumpulan Jurnal Ilmu Komputer, 5(1), 27. https://doi.org/10.20527/klik.v5i1.100

Muhammad Rashidi Wahab, M. F. A. (2013). Jurnal Teknologi. Jurnal Teknologi, 11, 31–39. https://doi.org/10.35134/jitekin.v1i1.001-006

Sikumbang, E. D. (2018). Penerapan Data Mining Penjualan Sepatu Menggunakan Metode Algoritma Apriori. Jurnal Teknik Komputer AMIK BSI (JTK), Vol 4, No.(September), 1–4.

Siregar, V., & Hasugian, P. M. (2020). Application of Data Mining Method Using Association Rules Apriori To Shopping Cart Analysis On Sale Transactions (Case Study Alfamidi Burnt Stone). Journal Of Computer Networks, Architecture and High Performance Computing, 2(2), 222–226. https://doi.org/10.47709/cnapc.v2i2.425

Susanto, H., & Sudiyatno, S. (2014). Data mining untuk memprediksi prestasi siswa berdasarkan sosial ekonomi, motivasi, kedisiplinan dan prestasi masa lalu. Jurnal Pendidikan Vokasi, 4(2), 222–231. https://doi.org/10.21831/jpv.v4i2.2547

Wedy, L., Setiawan, H., & Sirajuddin. (2016). Analisis Kepuasan Pelanggan Terhadap Pelayanan Pada Alfamidi Bukit Palem Cabang Kota Cilegon. Jurnal Teknik Industri, 4(1), 1–96. http://jurnal.untirta.ac.id/index.php/jti/article/view/1394/1105

Widyan, A., & Rozi, A. F. (2021). Analisis Rekomendasi Produk Menggunakan Algoritma ECLAT Berdasarkan Riwayat Data Penjualan PT XYZ. Jurnal Teknologi Dan Sistem Informasi Bisnis, 3(2), 395–411. https://doi.org/10.47233/jteksis.v3i2.296

Yuli Mardi. (2019). Data Mining : Klasifikasi Menggunakan Algoritma C4 . 5 Data mining merupakan bagian dari tahapan proses Knowledge Discovery in Database ( KDD ) . Jurnal Edik Informatika. Jurnal Edik

Downloads


Crossmark Updates

How to Cite

Gito Resmi, M., Hermanto, T. I. ., & Ghozali, M. A. . (2022). Product Recommendation System Application Using Web-Based Equivalence Class Transformation (Eclat) algorithm. Sinkron : Jurnal Dan Penelitian Teknik Informatika, 6(3), 957-961. https://doi.org/10.33395/sinkron.v7i3.11454