Penentuan Tingkat Produksi Optimal dengan Metode Fuzzy Mamdani Berdasarkan Kapasitas Mesin pada CV Wangun Mandiri

Fajar Wisnu Nugraha; Iikh Nurazizah; Iwan Maulana; Shifni Mafaza

doi:10.61132/jupiter.v2i6.614

Authors

Fajar Wisnu Nugraha IPB University
Iikh Nurazizah IPB University
Iwan Maulana IPB University
Shifni Mafaza IPB University

DOI:

https://doi.org/10.61132/jupiter.v2i6.614

Keywords:

Demand, Forecasting, Fuzzy

Abstract

CV Wangun Mandiri is a manufacturing company that produces tapioca flour. In order to achieve maximum profit targets and smooth production activities, the company is faced with problems relating to the amount of tapioca flour products due to the uncertainty of its demand that tends to fluctuate and the imbalance of machine capacity. Therefore, it is required to plan the amount of production using the forecasting and fuzzy inference system approach as an effective method to determine the optimal production level. This research relies on the availability of datasets to determine the appropriate forecasting method and fuzzy method. The Fuzzy Mamdani method concludes that CV Wangun Mandiri can produce 82.9 tons to maximize existing demand and the capacity of its machines.

References

Andini, S., Hidayati, N., Larasati, & Pratiwi, E. A. (2024). Application of fuzzy logic to determine the amount of rice production based on supply data and amount of demand (RRJS distributor case study). Journal of Engineering, Computing, and Data Science (JECDS), 1(1), 7-13. Retrieved from https://e-jurnal.mediainsancreative.org/index.php/jecds/article/view/42

Ansar, K. R., Salim, & Khudriah, E. (2023). Implementasi fuzzy inference system menggunakan metode fuzzy Mamdani untuk optimalisasi produksi tahu. G-Tech: Jurnal Teknologi Terapan, 8(1), 276–285. https://doi.org/10.33379/gtech.v8i1.3650

Awanda, R., & Oktafianto, K. (2021). Peramalan permintaan paving menggunakan metode weighted moving average dan exponential smoothing. MathVision: Jurnal Matematika, 3(1), 14–18. https://doi.org/10.55719/mv.v3i1.252

Haque, D. M. (2023). Penerapan logika fuzzy Mamdani untuk optimasi persediaan stok makanan hewan. Media Online, 4(1), 427–437. https://doi.org/10.30865/klik.v4i1.1160

Lusiana, A., & Yuliarty, P. (2020). Penerapan metode peramalan (forecasting) pada permintaan atap di PT X. Industri Inovatif: Jurnal Teknik Industri, 10(1), 11–20. https://doi.org/10.36040/industri.v10i1.2530

Mada, G. S., Dethan, N. K. F., & Maharani, A. E. S. H. (2022). The defuzzification methods comparison of Mamdani fuzzy inference system in predicting tofu production. Jurnal Varian, 5(2), 137–148. https://doi.org/10.30812/varian.v5i2.1816

Nasution, V. M., & Prakarsa, G. (2020). Optimasi produksi barang menggunakan logika fuzzy metode Mamdani. Jurnal Media Informatika Budidarma, 4(1), 129. https://doi.org/10.30865/mib.v4i1.1719

Nugroho, A. N. (2014). Pengaruh jumlah persediaan bahan baku, kapasitas mesin, dan jumlah tenaga kerja terhadap volume produksi pada CV Sanyu Paint, Tropodo-Sidoarjo. Surabaya: Mitra Sumber Rejeki.

Nurfadilah, A., Budi, W., Kurniati, E., & Suhaedi, D. (2022). Penerapan metode moving average untuk prediksi indeks harga konsumen. Jurnal Matematika, 21(1), 19–25. Retrieved from https://journals.unisba.ac.id/index.php/matematika/article/view/337

Nurpaizun. (2024). Pengaruh persediaan bahan baku dan kapasitas mesin terhadap volume produksi di pabrik kelapa sawit PT. Tamora Agro Lesyari Kuansing. Jurnal Ilmiah Mahasiswa Merdeka EMBA, 3(2), 1345–1353. https://doi.org/10.59603/masman.v1i4.149

Putri, N. H., Sari, N. S., & Rahmah, N. (2022). Faktor-faktor yang mempengaruhi proses riset konsumen: Target pasar, perilaku pembelian dan permintaan pasar (literature review perilaku konsumen). Jurnal Ilmu Manajemen Terapan, 3(5), 504–514. Retrieved from https://dinastirev.org/JIMT/article/view/998

Rachman, R. (2018). Penerapan metode moving average dan exponential smoothing pada peramalan produksi industri garment. Jurnal Informatika, 5(2), 211–220. https://doi.org/10.31311/ji.v5i2.3309

Ramlan, R., Cheng, A. P., Chan, S. W., & Ngadiman, Y. (2016). Implementation of fuzzy inference system for production planning optimisation. Proceedings of the International Conference on Industrial Engineering and Operations Management, 8-10 March 2016, 2151–2158.

Risanty, R. D., Meilina, P., & Hasni, N. A. (2016). Perancangan sistem pendukung keputusan prediksi jumlah produksi dan tenaga kerja menggunakan metode fuzzy Sugeno. Prosiding Semnastek, November, 1–6.

Santosa, S. H., Sulaeman, S., Hidayat, A. P., & Ardani, I. (2020). Fuzzy logic approach to determine the optimum nugget production capacity. Jurnal Ilmiah Teknik Industri, 19(1), 70–83. https://doi.org/10.23917/jiti.v19i1.10295

Sari, I. P. (2018). Perencanaan jumlah produksi bubuk cabai dengan metode fuzzy Mamdani berdasarkan perkiraan permintaan pada PT Ganesha Abaditama. Jurnal Ilmiah Teknologi Dan Rekayasa, 23(2), 133–145. https://doi.org/10.35760/tr.2018.v23i2.2463

Shoplogix. (2024, May 13). Production capacity: Best strategies for manufacturers to increase their processes. Retrieved from https://shoplogix.com/production-capacity-in-manufacturing/

Sofyan, D. K. (2013). Perencanaan dan pengendalian produksi. Yogyakarta: Graha Ilmu.

Susetyo, J., Asih, E. W., & Raharjo, H. (2020). Optimalisasi jumlah produksi menggunakan fuzzy inference system metode min-max. Jurnal Rekayasa Industri (JRI), 2(1), 8–14. https://doi.org/10.37631/jri.v2i1.126

Sutrisno, N., Faradila, R., Faradila, R., Sirait, E. P., & Sirait, E. P. (2024). Pengaruh kapasitas mesin dan jumlah persediaan bahan baku terhadap volume produksi. Jurnal Akuntansi Dan Bisnis, 10(01), 15. https://doi.org/10.47686/jab.v10i01.680

Utami, Y., Vinsensia, D., & Panggabean, E. (2024). Forecasting exponential smoothing untuk menentukan jumlah produksi. Jurnal Ilmu Komputer Dan Sistem Informasi (JIKOMSI), 7(1), 154–160. https://doi.org/10.55338/jikomsi.v7i1.2853

Vorster, S. (2024, April 13). Demand, price & quantity | DP IB economics revision notes 2020. Save My Exams. Retrieved from https://www.savemyexams.com/dp/economics/ib/22/hl/revision-notes/2-microeconomics/2-1-demand/demand-price-and-quantity/

Wahyudi, A. T., Giyanti, I., & Kritiana, B. V. (2023). Studi penentuan jumlah produksi botol kemasan minuman yang optimal dengan fuzzy time series Markov chain dan fuzzy inference system. JISI: Jurnal Integrasi Sistem Industri, 10(2), 99. https://doi.org/10.24853/jisi.10.2.99-110

Wiharja, A. F., & Ningrum, H. F. (2020). Analisis prediksi penjualan produk PT. Joenoes Ikamulya menggunakan 4 metode peramalan time series. Jurnal Bisnisman: Riset Bisnis Dan Manajemen, 2(1), 43–51. https://doi.org/10.52005/bisnisman.v2i1.23

Yanti, N. P. L. P., Tuningrat, I. M., & Wiranatha, A. A. P. A. S. (2016). Analisis peramalan penjualan produk kecap pada perusahaan kecap Manalagi Denpasar Bali. Jurnal Rekayasa dan Manajemen Agroindustri, 4(1), 271–276.

Yulia, & Mardiah, A. (2018). Fuzzy logic untuk menentukan kepuasan siswa terhadap sarana dan prasarana sekolah dengan menggunakan metode Sugeno. Jurnal Ilmiah Informatika, 6(1), 32–41. https://doi.org/10.33884/jif.v6i01.430