Web-Based Fuzzy Mamdani System for Adaptive Cost of Production in Culinary MSMEs

Fallan Switly Fransisco Parengkuan; Chriestie Ellyane Juliet Clara Montolalu; Mahardika Inra Takaendengan

doi:10.58602/itsecs.v4i3.352

Fallan Switly Fransisco Parengkuan Universitas Sam Ratulangi
Chriestie Ellyane Juliet Clara Montolalu Universitas Sam Ratulangi
Mahardika Inra Takaendengan ^{(Corresponding Author)} Universitas Sam Ratulangi https://orcid.org/0000-0001-8622-7537

DOI: https://doi.org/10.58602/itsecs.v4i3.352

Keywords: Cost of Production, Fuzzy Mamdani, Decision Support System, Micro-Enterprises, Culinary Industry, Pricing Strategy

Abstract

Culinary micro, small, and medium enterprises frequently experience financial instability because conventional deterministic costing methods lack the flexibility to handle daily fluctuations in raw material and overhead expenses. This study develops an adaptive Cost of Production model and generates pricing recommendations using a web-based Fuzzy Mamdani decision support system. The research employs an applied quantitative case study design focusing on a single culinary micro-enterprise operating in a volatile local market. The fuzzy engine processes raw material and overhead uncertainties as linguistic inputs using MIN-MAX inference, while treating direct labor as a constant parameter. Centroid defuzzification calculates the final adaptive cost. The results demonstrate that the conventional deterministic cost was Rp27,077, whereas the Fuzzy Mamdani model adjusted this value to Rp27,532. This 1.68 percent increase functions as a calculated risk premium that protects profit margins against minor supply chain volatilities. The system subsequently generated three margin-based pricing tiers. The standard tier with a 30 percent margin demonstrated a 97.74 percent goodness of fit when compared to actual market prices. The primary contribution is the deployment of a lightweight web artifact that removes the technical barriers associated with desktop-based fuzzy simulations. This tool enables non-technical business owners to transition from heuristic guesswork to transparent, data-driven pricing strategies that inherently buffer against operational cost uncertainty.

References

J. Nasution, A. Hardana, A. Damisa, and A. Rasyid, “Pelatihan Manajemen Usaha dalam Meningkatkan Usaha UMKM Kuliner,” J. Pengabdi. Masy. Bestari, vol. 1, no. 5, pp. 271–280, 2022, doi: 10.55927/jpmb.v1i5.927.

A. Khaerunnisa and R. P. Pardede, “Analisis Harga Pokok Produksi Untuk Menentukan Harga Jual Tahu: Studi Kasus Pada Home Industry Compehu,” J. Ilm. Akunt. Kesatuan, vol. 9, no. 3, pp. 631–640, 2021, doi: 10.37641/jiakes.v9i3.1213.

S. Mulyani, B. Gunawan, and M. Nurkamid, “Pelatihan Perhitungan Harga Pokok Produksi Bagi UMKM Kabupaten Pati,” Empowerment, vol. 4, no. 2, pp. 181–187, 2021, doi: 10.25134/empowerment.v4i02.4526.

Pitrawati and A. Sanjaya, “Rekayasa Perangkat Lunak Perhitungan Harga Pokok Produksi Metode Full Costing Pada UMKM Mitra Cake di Bandar Lampung,” J. Inf. Dan Komput., vol. 9, no. 2, 2021, doi: 10.35959/jik.v9i2.243.

L. Marashi-Hosseini, S. Jafarirad, and A. M. Hadianfard, “A fuzzy based dietary clinical decision support system for patients with multiple chronic conditions (MCCs),” Sci. Rep., vol. 13, p. 12166, 2023, doi: 10.1038/s41598-023-39371-4.

F. Fauziyah, T. Afkar, U. Lasiyono, and N. Noerchoidah, “Menghitung Harga Pokok Produksi yang Tepat pada UMKM Amanah Blimbing Wuluh di Dukuh Menanggal Kecamatan Gayungan, Surabaya,” Ekobis Abdimas J. Pengabdi. Masy., vol. 2, no. 2, pp. 115–123, 2021, doi: 10.36456/ekobisabdimas.2.2.4861.

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.

K. Saleh, H. F. Siregar, and Z. Sitorus, “Analisis Fuzzy Sugeno Dalam Menentukan Pemilihan Motor Honda,” J. Teknol. Inf., vol. 5, no. 2, pp. 181–186, 2021, doi: 10.36294/jurti.v5i2.2498.

G. F. Tauhid, W. A. Wangni, R. D. Adinata, R. Dinargo, M. D. J. Saputra, and A. Rahman, “Fuzzy Logic dalam Keputusan Jumlah Produksi Berbasis Website Dengan Metode Mamdani,” J. Inov. Komput. INOKOM, vol. 1, no. 2, pp. 56–65, 2025, doi: 10.71200/inokom.v1i2.34.

M.-D. Pop, D. Pescaru, and M. V. Micea, “Mamdani vs. Takagi-Sugeno Fuzzy Inference Systems in the Calibration of Continuous-Time Car-Following Models,” Sensors, vol. 23, no. 21, p. 8791, 2023, doi: 10.3390/s23218791.

P. An, “Fuzzy Decision Support Systems to Improve the Effectiveness of Training Programs in the Field of Sports Fitness,” Int. J. Comput. Intell. Syst., vol. 17, no. 1, p. 168, 2024, doi: 10.1007/s44196-024-00555-z.

R. Navarro-Almanza, M. A. Sanchez, J. R. Castro, O. Mendoza, and G. Licea, “Interpretable Mamdani neuro-fuzzy model through context awareness and linguistic adaptation,” Expert Syst. Appl., vol. 189, p. 116098, 2022, doi: 10.1016/j.eswa.2021.116098.

Y. P. Hutomo, Awa, T. M. Ibrahim, S. A. F. Adawiyah, and A. B. Setiawan, “Pelatihan dan Pendampingan Penghitungan Harga Pokok Produksi pada UMKM Daur Ulang Limbah Kecamatan Bogor Selatan,” Educivilia J. Pengabdi. Pada Masy., vol. 6, no. 1, pp. 24–39, 2025, doi: 10.30997/ejpm.v6i1.16282.

F. A. A. Shukri, N. Ramli, M. F. Othman, and A. R. M. Shariff, “Experts’ Judgment-Based Mamdani-Type Decision System for Risk Assessment,” Math. Probl. Eng., vol. 2021, p. 6652419, 2021, doi: 10.1155/2021/6652419.

D. Sunandar, “Implementasi Logika Fuzzy Mamdani dalam Sistem Pendukung Keputusan untuk Penanganan Kesehatan Gizi Balita di RS Citra Arafiq Sawangan,” Ranah Res. J. Multidiscip. Res. Dev., vol. 7, no. 4, pp. 2311–2320, 2025, doi: 10.38035/rrj.v7i4.1465.

C. D. Mait, J. A. Watuseke, P. D. G. Saerang, and S. R. Joshua, “Sistem Pendukung Keputusan Menggunakan Fuzzy Logic Tahani Untuk Penentuan Golongan Obat Sesuai Dengan Penyakit Diabetes,” J. Media Infotama, vol. 18, no. 2, pp. 344–353, 2022, doi: 10.37676/jmi.v18i2.2936.

A. N. K. Nisa, “Penerapan Metode Full Costing dalam Penentuan Harga Pokok Produksi UKM Roti Galuh Sari,” J. Sos. Terap., vol. 3, no. 2, pp. 64–74, 2025, doi: 10.29244/yexjcq74.