Article Sidebar

Download
PDF (Bahasa Indonesia)
Statistic
Read Counter : 68 Download : 84

Downloads

Download data is not yet available.

Main Article Content

Abstract

At this time the transaction data at the UD Garam Kustono store has decreased, this shows that there is an increase in sales competition followed by an increase in applying information technology. To overcome these problems, a very appropriate sales strategy is needed to use the availability of useful data and information. Data mining is a technique that can be used to process transaction data more efficiently. The method used by researchers is the a priori algorithm. The aim of this study is to apply a data mining system to find information on interrelationships between products that can support sales strategies from transaction data. The result of this study will show that the system built can run well, as evidenced by the result of the analysis using the Apriori algorithm, the system is able to find out the shape of the combination between product that have been found in previous sales. This information can assist in making decisions in developing product promotion strategies that will be offered to buyer.

Article Details

How to Cite
Rizki Gunawan, & Wildan Toyib. (2023). Aplikasi Market Base Analitik Untuk Mempelajari Pola Belanja Masyarakat pada Toko UD Garam Kustono Menggunakan Algoritma Apriori. Jurnal Teknik Informatika Dan Komputer, 2(1), 30–36. https://doi.org/10.22236/jutikom.v2i1.11438
Download Citation
Endnote/Zotero/Mendeley (RIS)
BibTeX

References

  1. Achmad, Y. F. (2020). Pengujian Sistem Pendukung Keputusan Menggunakan Black Box Testing Studi Kasus E-Wisudawan Di Institut Sains Dan Teknologi Al-Kamal. Jurnal Ilmu Komputer, 42
  2. Adri, A. (2021). Implementasi Data Mining Menggunakan Algoritma Apriori. Paper Knowledge . Toward a Media History of Documents, 1-77
  3. Anggraini, Y. (2020). Sistem Informasi Penjualan Sepeda Berbasis Web Menggunakan Framework Codeigniter (Studi Kasus : Orbit Station). Jurnal Teknologi dan Sistem Informasi (JTSI), 64-70
  4. Febrianti, D. S. (2021). Perancangan Sistem Informasi Penjualan Tanaman Pada Koperasi Kemima (Keluarga Mitra Manunggal) Tanggerang Selatan. PROSISKO: Jurnal Pengembangan Riset dan Observasi Sistem Komputer, 33-40
  5. Herman Mawengkang, D. B. (2019). Pengembangan Algoritma Apriori Untuk Pengambilan Keputusan. Keputusan the Development Apriori Algorithm for Decision-, 110-121. https://doi.org/10.1109/ICACSIS.2016.7872744
  6. Qoniah, I. (2020). Analisis Market Basket Untuk Menentukan Asossiasi Rule Dengan Algoritma Apriori (Studi Kasus: Tb. Menara). Jurnal Teknologi dan Sistem Informasi, 26-33.
  7. Rahmawati, M. (2019). Sistem Informasi Usaha Dagang Berbasis Desktop (Studi
  8. Kasus: Toko Sobana Ii). Jurnal Teknologi Informatika dan Komputer, 135-146.
  9. Riszky, A. R. (2019). Data Mining Menggunakan Algoritma Apriori untuk Rekomendasi Produk bagi Pelanggan. Jurnal Teknologi dan Sistem Komputer, 103-108.
  10. Takdirillah, R. (2020). Penerapan Data Mining Menggunakan Algoritma Apriori Terhadap Data Transaksi Sebagai Pendukung Informasi Strategi Penjualan. Edumatic : Jurnal Pendidikan Informatika, 4(1), 37–46. https://doi.org/10.29408/edumatic.v4i1.2081
  11. Wahyuningsih, S. (2018). Perancangan Sistem Informasi Perencanaan Produksi Pt Katolec Indonesia Berbasis Web. 1-69