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Analisis Perbandingan Fuzzy Tsukamoto dan Sugeno dalam Menentukan Jumlah Produksi Kain Tenun Menggunakan Base Rule Decision Tree

Jurnal Teknologi Informasi dan Ilmu Komputer ◽

10.25126/jtiik.2020701751 ◽

2020 ◽

Vol 7 (1) ◽

pp. 171

Author(s):

Tundo Tundo ◽

Riolandi Akbar ◽

Enny Itje Sela

Keyword(s):

Comparative Analysis ◽

Decision Tree ◽

Woven Fabric ◽

Production Data ◽

Actual Production ◽

Truth Value ◽

The Difference ◽

Fabric Production

Penelitian ini menerangkan tentang analisis perbandingan fuzzy Tsukamoto dan Sugeno dalam menentukan jumlah produksi kain tenun dengan menggunakan base rule decision tree. Dari hasil analisis penelitian ini, maka ditemukan beberapa perbedaan yang sangat signifikan: (1) Metode fuzzy Tsukamoto dari hasil yang diperoleh lebih mendekati dari data sesungguhnya, dibandingkan dengan fuzzy Sugeno, (2) Selisih yang diperoleh dengan menggunakan fuzzy Tsukamoto dengan data produksi sesungguhnya selalu konsisten yaitu hasil fuzzy Tsukamoto selalu lebih besar, sedangkan untuk fuzzy Sugeno tidak konsisten, (3) Hasil selisih untuk fuzzy Tsukamoto relatif mendekati dari data produksi sesungguhnya, sedangkan untuk fuzzy Sugeno relatif jauh selisih yang dihasilkan. Sehingga dapat disimpulkan bahwa metode yang paling mendekati nilai kebenaran adalah produksi yang mengunakan metode Tsukamoto dengan keakuratan yang diperoleh menggunakan base rule decision tree sebesar 83.3333 %. Abstract This study describes the comparative analysis of fuzzy Tsukamoto and Sugeno determining the amount of woven fabric production using a decision tree base rule. From the results the analysis of this study, we found several very significant differences: (1) The fuzzy Tsukamoto method of the results obtained is closer to the actual, compared to fuzzy Sugeno, (2) The difference obtained by using fuzzy Tsukamoto with actual production data is always consistent is that Tsukamoto fuzzy results are always greater, while for Sugeno's fuzzy inconsistency, (3) The difference results for fuzzy Tsukamoto are relatively close to the actual production data, whereas Sugeno fuzzy is relatively far from the difference produced. So it can be concluded that the method closest to the truth value is production using the Tsukamoto method with the accuracy obtained using the base rule decision tree of 83.3333%.

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