Fuzzy Tsukamoto Untuk Merekomendasikan Pembelian Barang Berdasarkan Data Penjualan
DOI:
https://doi.org/10.30865/jurikom.v12i3.8631Keywords:
Fuzzy Tsukamoto, Recommendation System, Inventory Management, MATLAB, Futsal ShoesAbstract
The development of the sports industry, especially in futsal shoe sales, requires an inventory management strategy that is able to anticipate fluctuations in market demand. The main problem in this study is how to overcome the uncertainty of futsal shoe demand caused by variables such as trends, competition seasons, and changing consumer preferences. This study aims to develop a fuzzy logic-based purchase recommendation system using the Fuzzy Tsukamoto method to improve stock management efficiency. This study uses a quantitative approach with fuzzy method stages consisting of fuzzification, rule formation, inference, and defuzzification. The tools used are MATLAB software that supports the creation of fuzzy inference systems and graphic modeling. The study was conducted at the Pasifik Club Sports Sibolga Futsal Shoe Store by processing 1,098 historical sales data. The results of the study showed that the system built was able to recommend futsal shoe purchases with good accuracy, indicated by the Mean Absolute Percentage Error (MAPE) value of 15%. This system not only provides a popularity value for each shoe variant, but also helps stores avoid excess or shortage of stock. Thus, the Fuzzy Tsukamoto method is proven to be feasible to be used as a decision-making tool in retail inventory management.
References
M. A. N. Shobah, E. Santoso, and Sutrisno, “Aplikasi Penentuan Lokasi untuk Usaha Lapangan Futsal di Kecamatan Bangil Menggunakan Metode Fuzzy Tsukamoto,” J. Pengemb. Teknol. Inf. dan Ilmu Komput. Univ. Brawijaya, vol. 2, no. 7, pp. 2465–2470, 2018.
L. Rohimah, “Prediksi Nilai Ekspor Sepatu Kulit HS 6403 ke Jepang dengan Metode Mamdani, Sugeno dan Tsukamoto,” J. Ilmu Pengetah. Dan Teknol. Komput., vol. 4, no. Februari, pp. 239–244, 2019.
A. Widana, V. Sihombing, and I. R. Munthe, “Sistem pendukung keputusan pemilihan pelatih kegiatan ekstrakurikuler menggunakan metode moosra,” J. TEKINKOM, vol. 6, no. 02, pp. 532–539, 2023, doi: 10.37600/tekinkom.v6i2.1018.
I. Irmayansyah and A. N. Rossdiana, “Penerapan Metode Fuzzy Tsukamoto untuk Prediksi Jumlah Produksi Tanaman Cabai,” Teknois J. Ilm. Teknol. Inf. dan Sains, vol. 11, no. 1, pp. 27–38, 2021, doi: 10.36350/jbs.v11i1.98.
K. Sari and R. Siregar, “Evaluasi Kinerja Karyawan Kontrak Menggunalan Metode Fuzzy Tsukamoto,” J. Media Inform. Budidarma, vol. 6, no. 1, p. 525, 2022, doi: 10.30865/mib.v6i1.3441.
H. Quddustiani, U. Athiyah, M. R. Kartika, R. Hidayat, and L. R. Nabila, “Penentuan Jurusan Siswa Sekolah Menengah Atas menggunakan Metode Fuzzy Tsukamoto,” J. Dinda Data Sci. Inf. Technol. Data Anal., vol. 1, no. 2, pp. 82–87, 2021, doi: 10.20895/dinda.v1i2.205.
W. C. Runtukahu, D. Trisnawarman, F. T. Informasi, and U. Tarumanagara, “Perancangan basis data sistem penentuan harga optimal daster dengan fuzzy logic,” vol. 7, pp. 812–819, 2024, doi: 10.37600/tekinkom.v7i2.1834.
S. Sriani and Y. Rizky, “Klasifikasi Kualitas Daun Tembakau Menggunakan Glcm (Gray Level Co-Occurrence Matrix) Dan Svm (Support Vector Machine),” J. Inform. dan Tek. Elektro Terap., vol. 12, no. 3, pp. 3342–3349, 2024, doi: 10.23960/jitet.v12i3.4599.
K. Muflihunna and M. Mashuri, “Penerapan Metode Fuzzy Mamdani dan Metode Fuzzy Sugeno dalam Penentuan Jumlah Produksi,” Unnes J. Math., vol. 11, no. 1, pp. 27–37, 2022, doi: 10.15294/ujm.v11i1.50060.
P. Handayani, S. Deni Rizky, and H. Syahputra, “Perancangan Sistem Informasi Persediaan Stok Dan Pemesanan Beras Dengan Menggunakan Bahasa Pemrograman Php Dan Database Mysql (Studi Kasus : Huller Armaini),” J. Sains Inform. Terap., vol. 3, no. 1, pp. 11–15, 2024, doi: 10.62357/jsit.v3i1.220.
B. Muttaqi et al., “Penerapan Logika Fuzzy Mamdani dalam Sistem Penyiraman Cerdas untuk Pertanian,” vol. 8, no. 2, pp. 111–120, 2024.
A. Fathana, C. H. Simanjuntak, and S. R. Andani, “Jurnal JPILKOM ( Jurnal Penelitian Ilmu Komputer ) Penerapan Fuzzy Sugeno dalam Pemilihan Minuman Kemasan Yang Rendah Kafein,” vol. 2, no. 1, 2024.
I. Irawan, Z. Azmi, and M. Hutasuhut, “Iot Pada Sistem Monitoring Kecepatan Air Sungai Babura Sebagai Peringatan Dini Banjir Berbasis Node Mcu,” J. Sist. Komput. Triguna Dharma (JURSIK TGD), vol. 3, no. 3, pp. 80–87, 2024, doi: 10.53513/jursik.v3i3.9289.
H. T. Bowo, D. R. Trinadi, and B. Martapuse, “Fuzzy Mamdani untuk Rekomendasi Produksi Beras Berdasarkan Data Persediaan dan Jumlah Permintaan ( Studi Kasus PT XYZ ),” vol. 1, no. 1, pp. 11–23, 2024.
W. Ilham, N. Fajri, and K. Cirebon, “Menggunakan Metode Fuzzy Tsukamoto Pada,” Semin. Inform. Apl. Polinema 2020, vol. 10, no. 1, pp. 71–82, 2020.
A. Suherman and D. Widyaningrum, “Implementasi Fuzzy Tsukamoto pada Sistem Internet of Things Budidaya Tanaman Bayam,” Smatika J., vol. 14, no. 01, pp. 195–204, 2024, doi: 10.32664/smatika.v14i01.1332.
M. Furqan, A. Halim Hasugian, M. Siddik Hsb, and F. Sains dan Teknologi, “Penentuan Kualitas Bibit Padi Menggunakan Metode Fuzzy Mamdani,” J. Sains Komput. Inform. (J-SAKTI, vol. 5, no. 2, pp. 529–539, 2021.
A. D. Putri, “Penerapan Logika Fuzzy Mamdani untuk Memperkirakan Pembelian Tas Branded Wanita di Batam,” pp. 30–43, 2025.
A. Syalsabilla and A. Ramadhanu, “Hybrid intelligence system for image classification of fruit types,” vol. 9, no. 3, pp. 5029–5035, 2025.
M. D. Ahmilurrizqi, B. Darmawan, and I. M. Ginarsa, “Sistem Pengenalan Wajah Menggunakan Library Matlab Deep Learning Toolbox Pada Aplikasi Matlab,” vol. 6, no. 3, 2024.
Additional Files
Published
How to Cite
Issue
Section
License
Copyright (c) 2025 Siti Aisyah Purba, Sriani

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



