Pendekatan Z-Score Dan Fuzzy Dalam Pengujian Akurasi Peramalan Curah Hujan

Abstract

Determination of rainfall is important to determine the intensity of rain that occurs in an area. Rain intensity that is too high will certainly have a bad impact. Forecasting or prediction techniques are used to determine the likelihood of intensity occurring in the following year. However, rainfall data are continuous numerical data. Measurement of accuracy becomes more difficult if the data type is like that. So, this study tests the accuracy of rainfall forecasting in the city of Denpasar from a different perspective. This test combines the Z-score method and the Fuzzy set theory to normalize and classify rainfall data. This combination determines the degree of rainfall membership divided into Upper, Middle, and Lower levels. Based on the results of rainfall accuracy testing starting in 2012-2016 obtained an average value of accuracy of 85% with training data that is data in 2007-2015. The normalization process greatly affects the value of the training data.

Implementation of Fuzzy Multi-Objective Optimization On The Basic Of Ratio Analysis (Fuzzy-MOORA) In Determining The Eligibility Of Employee Salary

“…Teori himpunan fuzzy dapat digunakan untuk memodelkan sistem yang sulit untuk didefinisikan secara tepat karena ketidak jelasan dan ketidakpastian dalam persepsi manusia [12], ketidakjelasan dan ketidakpastian ini dapat dimodelkan dengan fungsi keanggotaan [13]. Fungsi derajat keanggotaan sangat mempengaruhi teori himpunan fuzzy [14]. Salah satu cara yang dapat digunakan untuk menentukan nilai keanggotaan adalah melalui pendekatan fungsi representasi kurva, antara lain kurva linier, kurva segitiga, kurva trapesium, kurva bentuk bahu, kurva S, kurva bentul lonceng serta kurva Gauss [3], [15].…”

Sensitivitas Urutan Alternatif Keputusan Berdasarkan Prioritas Kriteria Pada Metode Analytical Hierarchy Process

“…Dalam membangun model pendukung keputusan dengan metode Analytical Hierarchy Process (AHP), analisis sensitivitas merupakan langkah penting dalam menentukan solusi optimal yang dapat diterapkan [6][7], pada penelitian ini menggunakan analisis sentivitas prioritas kriteria [8] dalam seleksi penerimaan dosen [9] dengan metode pembobotan kriteria AHP [10], metode AHP digunakan untuk menentukan bobot kriteria serta skoring data alternatif agar menghindari ketidakpastian [11] nilai data dan setiap nilai alternatif dapat dihitung dengan angka [12]. Masing-masing pendekatan penentuan bobot yang digunakan dalam AHP jarang dilakukan pengujian terhadap besaran sensitivitasnya [13].…”

Determining Tilapia Quality Using the Fuzzy Logic

“…In this study, researchers can determine the quality of fish by using several factors such as texture, flavor, size and price. These factors are then converted into fuzzy variables that can be measured with different scales (Radhitya & Sudipa, 2020). Fuzzy methods are used because they provide better results than traditional classification methods.…”