Prediksi Penjualan Sparepart Mobil Terlaris Menggunakan Metode K-Nearest Neighbor

 Sahara Abdy (STMIK Logika, Medan, Indonesia)
 Erika Roberta Br Gultom (STMIK Logika, Medan, Indonesia)
 (*)Sri Ramadhany Mail (STMIK Logika, Medan, Indonesia)
 Afifudin Afifudin (STMIK Logika, Medan, Indonesia)

(*) Corresponding Author

Abstract

PT. GAYA MAKMUR MULIA MEDAN is a company engaged in selling spare parts and spare parts in North Sumatra. Along with the development of technology, the increasing business competition, especially regarding the sale of spare parts. This also affects the competition between brands of goods with the quality they produce. Products offered by various brands, brands influence people to buy these products. Judging from the large number of consumer requests for spare parts products based on sales over the last 2 years, predictions are needed for sales of the best-selling spare parts products, in order to make it easier for companies to provide stock. To find out the sales of best-selling spare part product, data mining techniques and K-Nearest neighbor algorithm are used to produce predictions of the best-selling sales in the Mitsubishhi division with an accuracy of 80,00% and Isuzu accuracy of 66,67% so that acquisition targets are obtained to increase the accuracy value for the classification of best-selling product sales.

PT. GAYA MAKMUR MULIA MEDAN is a company engaged in selling spare parts and spare parts in North Sumatra. Along with the development of technology, the increasing business competition, especially regarding the sale of spare parts. This also affects the competition between brands of goods with the quality they produce. Products offered by various brands, brands influence people to buy these products. Judging from the large number of consumer requests for spare parts products based on sales over the last 2 years, predictions are needed for sales of the best-selling spare parts products, in order to make it easier for companies to provide stock. To find out the sales of best-selling spare part product, data mining techniques and K-Nearest neighbor algorithm are used to produce predictions of the best-selling sales in the Mitsubishhi division with an accuracy of 80,00% and Isuzu accuracy of 66,67% so that acquisition targets are obtained to increase the accuracy value for the classification of best-selling product sales.

Keywords


Merk; Sparepart; Best Sellling; Data Mining; K-Nearest Neighbor

Full Text:

PDF


Article Metrics

Abstract view : 697 times
PDF - 524 times

References

M. Aries, H. Rarindo, Y. A. Winoko, and S. Adiwidodo, “ANALISIS PENJUALAN SPARE PART MOBIL DENGAN METODE ABC (KONSEP 80-20) PADA GUDANG SUKU CADANG DI BENGKEL PT. ASTRA INTERNASIONAL Tbk. AUTO2000 PASURUAN,” J. Ilm. Teknol. FST Undana, vol. 14, no. 2, 2020.

M. Reza Noviansyah, T. Rismawan, D. Marisa Midyanti, J. Sistem Komputer, and F. H. MIPA Universitas Tanjungpura Jl Hadari Nawawi, “Penerapan Data Mining Menggunakan Metode K-Nearest Neighbor Untuk Klasifikasi Indeks Cuaca Kebakaran Berdasarkan Data Aws (Automatic Weather Station) (Studi Kasus: Kabupaten Kubu Raya),” J. Coding, Sist. Komput. Untan, vol. 06, no. 2, pp. 48–56, 2018.

A. A. Firdaus, N. Iksan, D. N. Sadiah, L. Sagita, and D. Setiawan, “Penerapan Algoritma Apriori untuk Prediksi Kebutuhan Suku Cadang Mobil,” J. Sist. dan Teknol. Inf., vol. 9, no. 1, p. 13, 2021, doi: 10.26418/justin.v9i1.41151.

S. H. David Hartanto Kamagi, “Implementasi Data Mining dengan Algoritma C4.5 untuk Memprediksi Tingkat Kelulusan Mahasiswa,” Ultim. Vol. VI, No. 1 | Juni 2014, vol. VI, no. 1, pp. 254–260, 2014, doi: 10.1109/EPEPEMC.2016.7752007.

L. Setiyani, M. Wahidin, D. Awaludin, and S. Purwani, “Analisis Prediksi Kelulusan Mahasiswa Tepat Waktu Menggunakan Metode Data Mining Naïve Bayes : Systematic Review,” Fakt. Exacta, vol. 13, no. 1, p. 35, 2020, doi: 10.30998/faktorexacta.v13i1.5548.

W. C. Zheng and X. X. Wu, “Investigations of the spin Hamiltonian parameters for the trigonal Co 2+ center in ZnS0.001Se0.999 mixed crystal,” Opt. Mater. (Amst)., vol. 28, no. 4, pp. 370–373, 2006, doi: 10.1016/j.optmat.2004.12.020.

Mustakim and G. Oktaviani F, “Algoritma K-Nearest Neighbor Classification Sebagai Sistem Prediksi Predikat Prestasi Mahasiswa,” vol. 13, no. 2, pp. 195–202, 2016.

P. Simanjuntak and E. Elisa, “Data Mining Untuk Menentukan Pemilihan Celular Card Di Kota Batam,” J. Inf. Syst. Dev., vol. 4, no. 2, pp. 1–5, 2019, [Online]. Available: https://ejournal.medan.uph.edu/index.php/isd/article/view/283%0Ahttps://ejournal.medan.uph.edu/index.php/isd/article/download/283/143

I. P. Ninditama, I. P. Ninditama, W. Cholil, M. Akbar, and D. Antoni, “Klasifikasi Keluarga Sejahtera Study Kasus : Kecamatan Kota Palembang,” J. TEKNO KOMPAK, vol. 15, no. 2, pp. 37–49, 2020, [Online]. Available: https://ejurnal.teknokrat.ac.id/index.php/teknokompak/article/view/1156

D. P. Utomo and M. Mesran, “Analisis Komparasi Metode Klasifikasi Data Mining dan Reduksi Atribut Pada Data Set Penyakit Jantung,” J. Media Inform. Budidarma, vol. 4, no. 2, p. 437, 2020, doi: 10.30865/mib.v4i2.2080.

A. Rohman, “MODEL ALGORITMA K-NEAREST NEIGHBOR (K-NN) UNTUK PREDIKKELULUSAN MAHASISWA,” 2012.

H. Said, N. H. Matondang, and H. N. Irmanda, “Sistem Prediksi Kualitas Air Yang Dapat Dikonsumsi Dengan Menerapkan Algoritma K-Nearest Neighbor,” no. April, pp. 158–168, 2022.

N. Tangerang, “ALGORITMA K-NEAREST NEIGHBOR DENGAN MENGGUNAKAN METODE EUCLIDEAN DISTANCE UNTUK MEMPREDIKSI KELULUSAN UJIAN NASIONAL BERBASIS DESKTOP PADA SMA,” vol. 1, no. 1, pp. 123–129, 2018.

S. Maesaroh and Kusrini, “Sistem Prediksi Produktifitas Pertanian Padi Menggunakan Data Mining,” J. Energi, vol. 7, no. 2, pp. 25–30, 2017, [Online]. Available: eprints.dinus.ac.id/16925/1/jurnal_16115.pdf

M. Y. Putra and D. I. Putri, “Pemanfaatan Algoritma Naïve Bayes dan K-Nearest Neighbor Untuk Klasifikasi Jurusan Siswa Kelas XI,” J. Tekno Kompak, vol. 16, no. 2, pp. 176–187, 2022.

S. Marpaung, S. -, and I. -, “Penerapan Metode Naïve Bayes Dalam Memprediksi Prestasi Siswa Di SMA Negeri 1 Panombeian Panei,” J. Sist. Inf. dan Ilmu Komput. Prima(JUSIKOM PRIMA), vol. 4, no. 2, pp. 8–13, 2021, doi: 10.34012/jurnalsisteminformasidanilmukomputer.v4i2.1522.

K. S. M. I. P.-A. Sri Wahyunu, “Implementasi Rapid Miner dalam menganalisa Data Mahasiswa Drop Out,” vol. 10, pp. 421–437, 2017.

Bila bermanfaat silahkan share artikel ini

Berikan Komentar Anda terhadap artikel Prediksi Penjualan Sparepart Mobil Terlaris Menggunakan Metode K-Nearest Neighbor

Refbacks

  • There are currently no refbacks.


Copyright (c) 2022 Sahara Abdy, Erika Roberta Br Gultom, Sri Ramadhany, Afifudin

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

JURIKOM (Jurnal Riset Komputer)
Publish by Universitas Budi Darma (before STMIK BUDI DARMA (P3M))
Email: jurikom.stmikbd@gmail.com

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