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All Journal Jurnal Mandiri IT Journal of Artificial Intelligence and Digital Business
Firmansyah, Muchamad Aries
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Computer Science & IT Economics, Econometrics & Finance Electrical & Electronics Engineering Engineering Library & Information Science Mathematics

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Penerapan Metode Fuzzy Tsukamoto untuk Prediksi Jumlah Produksi PT Wings Padaharja Firmansyah, Muchamad Aries; Murtopo, Aang Alim; Fadilah, Nurul
RIGGS: Journal of Artificial Intelligence and Digital Business Vol. 4 No. 3 (2025): Agustus - October
Publisher : Prodi Bisnis Digital Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/riggs.v4i3.2173

Abstract

Penerapan sistem prediksi produksi berbasis kecerdasan buatan menjadi solusi penting dalam menjawab tantangan ketidakpastian pada sektor manufaktur, khususnya di lingkungan usaha mikro seperti PT Wings Padaharja. Penelitian ini bertujuan untuk membangun model prediksi jumlah produksi harian dengan memanfaatkan metode Fuzzy Tsukamoto guna meningkatkan efisiensi pengambilan keputusan operasional. Penelitian ini menggunakan pendekatan kuantitatif terapan dengan metode eksperimen, di mana data historis produksi tahun 2024 yang mencakup empat variabel utama—penjualan, permintaan, persediaan, dan retur—dianalisis melalui tahapan fuzzyfikasi, penetapan aturan IF–THEN, inferensi fuzzy, dan defuzzifikasi menggunakan metode rata-rata tertimbang. Hasil penelitian menunjukkan bahwa model prediksi yang dikembangkan mampu menghasilkan estimasi produksi dengan tingkat kesalahan yang masih dalam batas wajar, ditunjukkan oleh nilai MAE sebesar 65,21, MSE sebesar 15.698,8, dan RMSE sebesar 92,02. Temuan ini menunjukkan bahwa metode Fuzzy Tsukamoto efektif dalam menangani ketidakpastian dan kompleksitas data produksi, serta dapat diimplementasikan sebagai sistem pendukung keputusan bagi pelaku industri skala kecil hingga menengah; selanjutnya, pengembangan model lanjutan dapat diarahkan pada integrasi variabel eksternal dan penggunaan algoritma yang lebih kompleks seperti ANFIS untuk peningkatan akurasi prediktif
Implementation of the Fuzzy Tsukamoto method to determine the amount of beverage production Surorejo, Sarif; Firmansyah, Muchamad Aries; Arif, Zaenul; Gunawan, Gunawan
Jurnal Mandiri IT Vol. 13 No. 1 (2024): July: Computer Science and Field
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/mandiri.v13i1.302

Abstract

Optimization of the amount of beverage production by applying the Fuzzy Tsukamoto Method at PT. Sariguna Primatirta Tbk. This study aims to develop a predictive model that can assist companies in determining the optimal amount of beverage production, minimizing production costs, and maximizing customer satisfaction. The research method uses a quantitative approach with a combination design of experimental methods, quantitative analysis, and model validation, including the collection of historical data on production, market demand, and raw material availability, data pre-processing, selection of input and output variables, implementation of the Fuzzy Tsukamoto algorithm, and model evaluation with Mean Absolute Error (MAE) and Root Mean Squared Error (RMSE) metrics. The results showed that the Fuzzy Tsukamoto Method succeeded in determining the amount of beverage production with good accuracy, with an MAE of 0.25 and RMSE of 0.274 after the data was understated, proved effective in handling the uncertainty of market demand and providing optimal production recommendations based on fuzzy rules from expert knowledge. The implications of this research contribute to the scientific literature in the field of computer science and industrial management, as well as practical benefits for  PT. Sariguna Primatirta Tbk in improving its production effectiveness, with the potential to be adopted by similar industries to improve operational efficiency.
Co-Authors Aang Alim Murtopo Arif, Zaenul Gunawan Gunawan Nurul Fadilah, Nurul Sarif Surorejo