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Home > Volume 1, Number 2, December 2018 > Munawar
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Asep Rusyana
Department of Statistics, Faculty of Mathematics and Natural Sciences, Syiah Kuala University
Jalan Syech Abdurrauf No.3, Kopelma Darussalam, Banda Aceh 23111, Aceh, Indonesia
Email: jda@unsyiah.ac.id
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Pendeteksian Penyakit Diabetes di RSUD Zainoel Abidin Banda Aceh dengan Sistem Fuzzy Mamdani

Munawar Munawar, Marzuki Marzuki, Radhiah Radhiah

Abstract

Diabetes adalah salah satu penyakit kronis yang dapat menyebabkan komplikasi kesehatan yang serius. Kekerapan dan komplikasi di antara ras, negara dan kebudayaan ditemukan perbedaannya. Metode logika fuzzy mempunyai tiga tahapan proses yaitu fuzzifikasi, inferensi dan defuzzifikasi. Logika fuzzy merupakan sebuah nilai yang memiliki kesamaran antara benar dan salah. Dalam teori logika fuzzy sebuah nilai bisa bernilai benar dan salah secara bersamaan tapi berapa besar kebenaran dan kesalahan suatu nilai tergantung dari berapa besar bobot keanggotaan yang dimilikinya. Dalam teori logika fuzzy dikenal himpunan fuzzy (fuzzy set) yang merupakan pengelompokan sesuatu berdasarkan variabel bahasa (linguistic variable) yang dinyatakan dalam fungsi keanggotaan yang bernilai nol sampai dengan satu. Metode logika fuzzy Mamdani dapat digunakan untuk menentukan tingkat keakurasian untuk mendeteksi penyakit diabetes. Hasil pengujian menunjukkan bahwa semakin tua usia dan semakin sangat tinggi kolesterol seseorang maka akan semakin besar resiko terkena penyakit diabetes. Pada sistem inferensi fuzzy, metode mamdani adalah salah satu metode yang memiliki keakuratan yang tinggi.

Diabetes is a chronic disease that can cause serious health complications. The frequency and complication between race, country and culture are found to be different. Fuzzy logic method has three stages, namely fuzzification, inference and defuzzification. Fuzzy logic is a value that has the ambiguity between right and wrong. In fuzzy logic theory, a value can be true and false value simultaneously but how much truth and error of a value depends on how much weight the membership has. In the theory of fuzzy logic known as fuzzy sets which is a grouping of things based on language variables (linguistic variables) which are expressed in membership functions with value zero to one. Mamdani fuzzy logic method can be used to determine the level of accuracy to detect diabetes. The test results show that the older the age and the very high cholesterol a person has, the greater the risk of developing diabetes. In the fuzzy inference system, the mamdani method is one method that has high accuracy.

 Keywords

Diabetes; Fuzzy logic; Mamdani method

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References

Suyanto, S.. 2008. Soft Computing Membangun Mesin Ber-IQ Tinggi. Bandung: Informatika.

Zhang, C., Song, J., Wu, Z. 2009. Fuzzy Integral Be Applied to the Diagnosis of Gestational Diabetes Mellitus. Sixth International Conference on Fuzzy Systems and Knowledge Discovery. Tianjin : IEEE.

Ali, A., Mehdi, N. 2010. A Fuzzy Expert System for Heart Disease Diagnosis. Proceedings of the International MultiConference of Engineers and Computer Scientists (Vol I). Hong Kong : IMECS.

Mulyanta, E.S., 2006. Pengolahan Digital Image dengan Photoshop CS2. Yogyakarta : Andi.

Naba, E.A., 2009. Belajar Cepat Fuzzy Logic Menggunakan MATLAB. Yogyakarta: Andi.

Shaheen, A., Khan, W.A. 2009. Intelligent Decision Support System in Diabetic eHealth Care From the perspective of Elders. Thesis. Ronneby : Department of School of Computing Bleking Institute of Technology Soft Center.

Kusumadewi, S., Purnomo, H. 2010. Aplikasi Logika Fuzzy. Yogyakarta : Graha Ilmu.

Zahara, R., Hizir, H., Hermansyah, H. 2015. Jurnal Ilmu Keperawatan 3(2) : Pendidikan Kesehatan terhadap Peningkatan Pengetahuan Keluarga Penderita Skizofrenia dengan Perilaku Kekerasan. Banda Aceh : Magister Keperawatan Universitas Syiah Kuala.

Izazi. 2016. Aplikasi Logika Fuzzy untuk Mendiagnogsis Tingkat Keparahan Penyakit Jantung (Studi Kasus Di RSUDZA Banda Aceh). Skripsi. Banda Aceh : Universitas Syiah Kuala.

DOI: https://doi.org/10.24815/jda.v1i2.12612

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About The Authors

Munawar Munawar
Jurusan Statistika, FMIPA, Universitas Syiah Kuala
Indonesia

Marzuki Marzuki
Department of Statistics, Faculty of Mathematics and Natural Sciences, Syiah Kuala University
Indonesia

Radhiah Radhiah
Jurusan Statistika, FMIPA, Universitas Syiah Kuala
Indonesia

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Keywords ARIMA Analisis Regresi Aset Bank Bayesian Biplot Canonical correlation analysis Complete lingkage Computer Network Degree of poverty Forecasting Mean lingkage Multidimensional Poverty indicators RWikiStat Sensitivitas Software-defined Network Spatial Error Model Spatial Regression Structural Equation Model, Analisis Jalur, Status Gizi Remaja android pembelajaran statistika
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