APPLICATION OF FUZZY TSUKAMOTO METHOD IN DETERMINING THE STOCK OF COCONUT SHELL CRAFT GOODS

Authors

  • Yasinta Esti Pratiwi Informatika, Universitas PGRI Yogyakarta
  • Fishilia Saqila Istanti Informatika, Universitas PGRI Yogyakarta

DOI:

https://doi.org/10.61677/jth.v2i2.343

Keywords:

Fuzzy Tsukamoto, inventory management, coconut shell crafts, production optimization

Abstract

This research applies the Fuzzy Tsukamoto Method to optimize the inventory management of coconut shell handicraft products in Bantul Regency, Indonesia. The aim is to develop a predictive system to determine production quantities based on market demand and inventory levels, so as to overcome challenges such as over- and under-stocking. Data was collected from Marem.id's production records between January and April 2024, which included demand, inventory, and production variables. Fuzzy modeling is performed with three variables: two inputs (demand and inventory) and one output (production). The system integrates fuzzification, inference, and defuzzification processes to calculate the optimal production level. The results show that for April 2024, a production quantity of 92,432 units is recommended to meet demand and maintain efficient inventory levels. This approach improves operational efficiency, reduces costs, and increases competitiveness in local and international markets. 

References

Afandi, A., Farida, I. N., & Mahdiyah, U. (2022). Penerapan algoritma apriori dan metode moving average untuk prediksi stok barang. Prosiding Seminar Nasional Inovasi dan Teknologi (INOTEK), 6(2), 421–426.

Asy Aria, T., Julkarnain, M., & Hamdani, F. (2023). Penerapan algoritma K-Means clustering untuk data obat. KLIK: Kajian Ilmiah Informasi dan Komputer, 4(1), 649–657.

Darmawan, A., & Puspita, D. (2021). Implementation of fuzzy inference system in forecasting production needs in dynamic markets. Jurnal Teknologi dan Sistem Komputer, 9(1), 12–19. https://doi.org/10.14710/jtsiskom.9.1.12-19

Mahendra, Y. P., & Siahaan, R. F. (2024). Penerapan metode fuzzy Tsukamoto dalam menentukan jumlah produksi opak pada home industri Tegar Jaya. Jurnal Pelita Ilmu Pendidikan, 2(1), 39–46. https://doi.org/10.69688/jpip.v2i1.60

Nugroho, R., & Rachman, F. (2023). Decision support system for stock prediction using fuzzy logic. Journal of Computer Science and Artificial Intelligence, 5(1), 10–17. https://doi.org/10.31098/jcsa.v5i1.244

PILENDIA, D. (2020). Pemanfaatan Adobe Flash sebagai dasar pengembangan bahan ajar fisika: Studi literatur. Jurnal Tunas Pendidikan, 2(2), 1–10. https://doi.org/10.52060/pgsd.v2i2.255

Putri, M. F., & Azizah, A. (2023). Hybrid fuzzy and seasonal model to forecast demand in creative industries. Jurnal Sistem Informasi dan Bisnis Kreatif, 6(2), 55–62.

Rahmawati, L., & Hidayat, A. (2022). Model prediksi stok berbasis fuzzy-Tsukamoto. Jurnal Teknologi dan Sistem Informasi, 6(1), 34–41.

Saputra, F. R., & Suyono, H. (2022). A fuzzy Tsukamoto method approach in determining the optimal stock of raw materials in MSMEs. Jurnal Ilmiah Teknologi dan Rekayasa, 25(2), 233–241. https://doi.org/10.31294/jitr.v25i2.15001

Siregar, E. B., & Utami, S. (2021). Fuzzy-based production planning for small industries. Jurnal Sistem Cerdas, 4(3), 99–107.

Tim Industri. (2022). Definisi industri berdasarkan UU No. 5 tahun 1984. Lumbung Inovasi: Jurnal Pengabdian kepada Masyarakat, 7(2), 82–96. https://journal-center.litpam.com/index.php/linov

Widodo, A., & Putra, M. H. (2020). Penggunaan fuzzy dalam optimasi rantai pasok. Jurnal Logistik Indonesia, 3(2), 45–52.

Published

2025-04-30

How to Cite

Esti Pratiwi, Y., & Saqila Istanti, F. (2025). APPLICATION OF FUZZY TSUKAMOTO METHOD IN DETERMINING THE STOCK OF COCONUT SHELL CRAFT GOODS . JTH: Journal of Technology and Health, 2(2), 94 ~ 104. https://doi.org/10.61677/jth.v2i2.343