Membandingkan Tingkat Efisiensi Metode Tsukamoto dan Sugeno untuk kasus Pneumonia

Elyza Gustri Wahyuni

Abstract


There are three methods that can be used to implement the Fuzzy Inference System (FIS), namely Tsukamoto, Mandani and Sugeno. Each of the three methods has its own characteristics and advantages. Several third studies used this method to compare the efficiency level of different cases. This study also aims to see the most efficient method by comparing the two FIS methods, namely Tsukamoto and Sugeno, based on medical cases from previous studies that have tested the validity of the results from pulmonary specialists. The data used are the same data as previous studies, namely regarding the diagnosis of pneumonia. The analytical method used is Mean Absolute Percantage Error (MAPE) to get the accuracy value of how close a measurement result is to the actual number. Based on the cases tested, the key from the Sugeno method resulted in a smaller MAPE than Tsukamoto, namely 3.15%, which means that the Sugeno method results closer to the pneumonia score/actual value.

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References


S. Kusumadewi, Analisis dan Desain Sistem Fuzzy menggunakan Tool Box Matlab, edisi pertama, Jakarta: Graha Ilmu, 2002.

E. G. Wahyuni and A. Ramadhan, "Aplikasi Diagnosis Tingkatan Pneumonia dan Saran Pengobatan dengan Fuzzy Tsukamoto," JNTETI (Jurnal Nasional Teknik Elektro dan Teknologi Informasi), pp. 115-122, 2019.

E. G. Wahyuni and A. Ramadhan, "Application for the diagnosis of pneumonia based on Pneumonia Severity Index (PSI) values," in International Conference on Electrical Engineering, Computer Science and Informatics (EECSI), Malang, Indonesia, 2018.

A. Triyanto, F. B. Kesuma and S. Puspasari, "Studi Perbandingan Metode Fuzzy Tsukamoto Dan Fuzzy Mamdani Untuk Seleksi Pegawai Teladan Pada Pt Gracia Pharmindo," in STMIK GI MDP, 2014.

L. P. Ayuningtias, M. irfan and Jumadi, "Analisa Perbandingan Logic Fuzzy Metode Tsukamoto, Sugeno, dan Mamdani (Studi Kasus: Prediksi Jumlah Pendaftar Mahasiswa Baru Fakultas Sains Dan Teknologi Universitas Islam Negeri Sunan Gunung Djati Bandung)," Jurnal Teknik Informatika, pp. 9-16, 2017.

S. Widaningsih, "Analisis Perbandingan Metode Fuzzy Tsukamoto, Mamdani dan Sugeno dalam Pengambilan Keputusan Penentuan Jumlah Distribusi Raskin di Bulog Sub. Divisi Regional (Divre) Cianjur," Jurnal Informatika dan Manajemen STMIK, vol. 11, no. 1, pp. 51-65, 2017.

D. P. P. Astuti and Mashuri, "Penerapan Metode Fuzzy Tsukamoto Dan Fuzzy Sugeno Dalam Penentuan Harga Jual Sepeda Motor," UNNES Journal of Mathematics, vol. 9, no. 2, pp. 74-84, 2020.

A. Saelan, "Logika Fuzzy," Makalah If 2091 Struktur Diskrit, no. 1, 2009.

S. Kusumadewi and H. Purnomo, Aplikasi logika fuzzy untuk mendukung keputusan, Yogyakarta: Graha ilmu, 2004.

W. Budiharto and D. Suhartono, Artificial Intelligence Konsep dan Penerapannya, Yogyakarta: ANDI, 2014.

Marimin, Teori dan aplikasi sistem pakar dalam tehnologi manajerial, Bogor: IPB – Press, 2005.

A. Triyanto, B. K. Febri and P. Shinta, "Studi Perbandingan Metode Fuzzy Tsukamoto dan Fuzzy Mamdani Untuk Seleksi Pegawai Teladan Pada PT Gracia Pharmindo," Jurnal STMIK GI MDP, 2010.

A. H. Agustin, G. K. Gandhiadi and T. B. Oka, "Penerapan Metode Fuzzy Sugeno untuk Menentukan Harga Jual Sepeda Motor Bekas," E-Jurnal Matematika, vol. 178, 2016.

Y. Yudihartanti, "Analisis Komparasi Metode Fuzzy Mamdani dan Sugeno dalam Penjadwalan Mata Kuliah," Progresif, vol. 7, no. 2, pp. 731-780, 2012.

A. H. Hutasuhut, W. Anggraeni and R. Tyasnurita, "Pembuatan Aplikasi Pendukung Keputusan untuk Peramalan Persediaan Bahan Baku Produksi Plastik Blowing dan Inject Menggunakan Metode ARIMA (Autoregressive Integrated Moving Average) di CV. Asia," Jurnal Teknik ITS, vol. 3, no. 2, pp. 169-174, 2014.

M. Fine, T. Auble, D. Yealy, B. Hanusa, L. Weissfeld, D. Singer, C. Coley, T. Marrie and W. Kapoor, "A prediction rule to identify low-risk patients with community acquired pneumonia," N Engl J Med, vol. 336, no. 4, p. 243–250, 1997.

M. Williams, S. A. Flanders and W. F. Whitcomb, "Comprehensive hospital medicine: an evidence-based approach," Elsevier Health Sciences, vol. 273, 2007.




DOI: http://dx.doi.org/10.24014/coreit.v7i2.15085

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