Penerapan Algoritma Hash Based Terhadap Penentuan Rule Asosiasi Transaksi Penjualan Sparepart Sepeda Motor

 (*)Salmon Salmon Mail (STMIK Widya Cipta Dharma, Samarinda, Indonesia)
 Siti Lailiyah (STMIK Widya Cipta Dharma, Samarinda, Indonesia)
 Nursobah Nursobah (STMIK Widya Cipta Dharma, Samarinda, Indonesia)
 Reza Andrea (Politeknik Pertanian Negeri Samarinda, Samarinda, Indonesia)

(*) Corresponding Author

Submitted: January 26, 2024; Published: April 30, 2024

Abstract

The problem that occurs in increasing sales transactions is that the large number of sales transactions every day with many kinds of spare parts makes it difficult for sales to determine strategies for offering spare parts that are relevant and really needed by consumers. The large amount of transaction data to be analyzed is not possible to do manually. Therefore, a certain technique is needed that can carry out the association rule mining process quickly on quite large data. One technique that can be used for association rules is the Hash algorithm. Hash Based Algorithm Uses hashing techniques to filter out itemsets that are not important for generating the next itemset. Generating frequent itemsets in this research requires a minimum support value and a minimum confidence value. The minimum support value used in this research is the average frequency of spare parts sales. Development is carried out in the process of generating candidate rules using a hash table on transaction data. By using the Hash Based algorithm, the association rule mining process becomes faster and more efficient in memory usage. From the results of the association rules trial with a minimum support of 40% and a minimum confidence of 75%. 14 lists of association rules were produced that met the requirements. This list becomes a reference for sales in determining strategies for offering spare parts to consumers.

Keywords


Transaction; Sale; Rules; Association; Hash Based Algorithm

Full Text:

PDF


Article Metrics

Abstract view : 167 times
PDF - 60 times

References

A. Yani, Z. Azmi, and D. Suherdi, “Implementasi Data Mining Menganalisa Data Penjualan Menggunakan Algoritma K-Means Clustering,” J. Sist. Inf. Triguna Dharma (JURSI TGD), vol. 2, no. 2, p. 315, 2023, doi: 10.53513/jursi.v2i2.6357.

I. Rosmayati, W. Wahyuningsih, E. F. Harahap, and H. S. Hanifah, “Implementasi Data Mining pada Penjualan Kopi Menggunakan Algoritma Apriori,” J. Algoritm., vol. 20, no. 1, pp. 99–107, 2023, doi: 10.33364/algoritma/v.20-1.1259.

M. Hutasuhut, M. Gilang Suryanata, S. Kusnasari, and M. A. Lesmana, “Data Mining Untuk Menganalisa Pola Penjualan Pestisida dengan Mengunakan Algoritma FP-Growth,” J. Ris. Komputer), vol. 9, no. 6, pp. 2407–389, 2022, doi: 10.30865/jurikom.v9i6.5200.

Y. M. Kristania and S. Listanto, “Implementasi Data Mining Terhadap Data Penjualan Dengan Algoritma Apriori Pada Pt. Duta Kencana Swaguna,” J. Teknoinfo, vol. 16, no. 2, p. 364, 2022, doi: 10.33365/jti.v16i2.1973.

A. Nugraha, O. Nurdiawan, and G. Dwilestari, “Penerapan Data Mining Metode K-Means Clustering Untuk Analisa Penjualan Pada Toko Yana Sport,” JATI (Jurnal Mhs. Tek. Inform., vol. 6, no. 2, pp. 849–855, 2022, doi: 10.36040/jati.v6i2.5755.

S. P. Dewi, N. Nurwati, and E. Rahayu, “Penerapan Data Mining Untuk Prediksi Penjualan Produk Terlaris Menggunakan Metode K-Nearest Neighbor,” Build. Informatics, Technol. Sci., vol. 3, no. 4, pp. 639–648, 2022, doi: 10.47065/bits.v3i4.1408.

F. Y. Fenesia Yunika, “Market Basket Analysis Menggunakan Algoritma Hash Based Pada Data Penjualan Di O2 Swalayan,” J. Inform. Kaputama, vol. 8, no. 1, pp. 21–30, 2024, doi: 10.59697/jik.v8i1.417.

B. Nadeak and M. Sianturi, “Implementasi Algoritma Hash-Based Dalam Mengetahui Pola Penjualan Obat,” BEES Bull. Electr. Electron. Eng., vol. 3, no. 1, pp. 23–33, 2022.

Alwendi, A. S. Mandopa, and E. A. Hasibuan, “Aplikasi Data Mining Untuk Menentukan Masa Studi Mahasiswa Menggunakan Metode Association Rule,” J. Pendidik. DEWANTARA, vol. 2, no. 1, pp. 1–6, 2023.

B. V. Christioko, K. Khoirudin, and A. Nugroho, “Penentuan Pola Asosiatif Data Tracer Study Universitas Semarang dengan Algoritma Hash Based,” AITI J. Teknol. Inf., vol. 20, no. 2, pp. 150–166, 2023, doi: 10.24246/aiti.v20i2.150-166.

A. Triayudi and S. Sumiati, “Penerapan Algoritma Hash Based dalam Penemuan Aturan Asosiasi Penjualan Tanaman Hias,” Build. Informatics, Technol. Sci., vol. 4, no. 3, pp. 1293–1300, 2022, doi: 10.47065/bits.v4i3.2626.

A. Royzen, J. Wahyudi, E. Suryana, and U. Dehasen, “PENERAPAN METODE MARKET BASKET DENGAN ALGORITMA HASH-BASED TERHADAP DATA PENJUALAN PRODUK PADA,” J. Sci. Soc. Res., vol. 4307, no. 1, pp. 339–344, 2024.

M. A. Abdullah and R. T. Aldisa, “Data Mining Untuk Menerapkan Algoritma Hash Based Pada Penetapan Pola Tata Letak Penjualan Bakery and Cake,” J. Sist. Komput. dan Inform., vol. 4, no. 3, p. 443, 2023, doi: 10.30865/json.v4i3.5933.

R. T. Aldisa, “Penerapan Data Mining Pada Analisa Pola Pembelian Obat Menerapkan Algoritma Hash Based,” Build. Informatics, Technol. Sci., vol. 4, no. 4, pp. 1892–1898, 2023, doi: 10.47065/bits.v4i4.3142.

F. Y. Rahman, I. I. Purnomo, and N. Hijriana, “PENERAPAN ALGORITMA DATA MINING UNTUK KLASIFIKASI KUALITAS AIR,” Technologia, vol. 13, no. 3, pp. 228–232, 2022.

H. P. Doloksaribu and Y. T. Samuel, “KOMPARASI ALGORITMA DATA MINING UNTUK ANALISIS SENTIMEN APLIKASI PEDULILINDUNGI,” J. Teknol. Inf., vol. 16, no. 1, pp. 1–11, 2022.

Sekar Setyaningtyas, B. Indarmawan Nugroho, and Z. Arif, “Tinjauan Pustaka Sistematis: Penerapan Data Mining Teknik Clustering Algoritma K-Means,” J. Teknoif Tek. Inform. Inst. Teknol. Padang, vol. 10, no. 2, pp. 52–61, 2022, doi: 10.21063/jtif.2022.v10.2.52-61.

E. - and S. P. Tamba, “Penerapan Data Mining Algoritma Apriori Dalam Menentukan Stok Bahan Baku Pada Restoran Nelayan Menggunakan Metode Association Rule,” J. Sist. Inf. dan Ilmu Komput. Prima(JUSIKOM PRIMA), vol. 5, no. 2, pp. 97–102, 2022, doi: 10.34012/jurnalsisteminformasidanilmukomputer.v5i2.2407.

T. Prasetya, J. E. Yanti, A. I. Purnamasari, A. R. Dikananda, and O. Nurdiawan, “Analisis Data Transaksi Terhadap Pola Pembelian Konsumen Menggunakan Metode Algoritma Apriori,” INFORMATICS Educ. Prof. J. Informatics, vol. 6, no. 1, p. 43, 2022, doi: 10.51211/itbi.v6i1.1688.

S. Aulia Miranda, F. Fahrullah, and D. Kurniawan, “Implementasi Association Rule Dalam Menganalisis Data Penjualan Sheshop dengan Menggunakan Algoritma Apriori,” Metik J., vol. 6, no. 1, pp. 30–36, 2022, doi: 10.47002/metik.v6i1.342.

A. Anggraini and L. Sianturi, “Implementasi Data Mining Algoritma Hash-Based Untuk Mengetahui Frekuensi Itemset Penjualan Alat-Alat Listrik ( Studi Kasus : PT . Asia Sinar Inti Abadi ),” Inf. dan Teknol. Ilm., vol. 9, no. 2, pp. 36–40, 2022.

M. F. H. Lubis, “Data Mining Market Basket Analysis Menggunakan Algoritma Hash Based Pada Sistem Penjualan Produk,” 2023.

F. Panjaitan, A. Surahman, and T. D. Rosmalasari, “Analisis Market Basket Dengan Algoritma Hash-Based Pada Transaksi Penjualan (Studi Kasus: Tb. Menara),” J. Teknol. dan Sist. Inf., vol. 1, no. 2, pp. 111–119, 2020, doi: 10.33365/jtsi.v1i2.450.

A. Asran, V. Hadrianti, K. Kasmawaru, H. Hasniaty, N. P. D. T. Yuliadi, and M. Rumende, “Implementasi Data Mining Untuk Meningkatkan Penjualan Dengan Algoritma Hash – Based Pada Toko Krisna Mart,” YUME J. Manag., vol. 6, no. 1, p. 269, 2023, doi: 10.37531/yum.v6i1.3586.

Bila bermanfaat silahkan share artikel ini

Berikan Komentar Anda terhadap artikel Penerapan Algoritma Hash Based Terhadap Penentuan Rule Asosiasi Transaksi Penjualan Sparepart Sepeda Motor

Refbacks

  • There are currently no refbacks.


Copyright (c) 2024 JURNAL MEDIA INFORMATIKA BUDIDARMA

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.



JURNAL MEDIA INFORMATIKA BUDIDARMA
STMIK Budi Darma
Secretariat: Sisingamangaraja No. 338 Telp 061-7875998
Email: mib.stmikbd@gmail.com

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.