Article Per Year (5 Year)
p-Index From 2021 - 2026
1.288
P-Index
This Author published in this journals
All Journal Jurnal Sains dan Seni ITS CGANT JOURNAL OF MATHEMATICS AND APPLICATIONS Sewagati Limits: Journal of Mathematics and Its Applications International Journal of Computing Science and Applied Mathematics-IJCSAM
Didik Khusnul Arif
Departemen Matematika Institut Teknologi Sepuluh Nopember Surabaya
Arts Humanities Computer Science & IT Education Engineering Languange, Linguistic, Communication & Media Mathematics Public Health Social Sciences Other

Published : 12 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 12 Documents
Search

 1   2 
State Variable Estimation of Nonisothermal Continuous Stirred Tank Reactor Using Fuzzy Kalman Filter Risa Fitria; Didik Khusnul Arif
(IJCSAM) International Journal of Computing Science and Applied Mathematics Vol. 3 No. 1 (2017)
Publisher : LPPM Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Increasing safety and product quality, reducing manufacturing cost, minimizing the impact of environment in fault detection system for Nonisothermal Continuous Stirred Tank Reactor (CSTR) are the reason why accurate state estimation is needed. Kalman filter is an estimation algorithm of the stochastic linear dynamical system. Through this work, a modification of Kalman Filter that combines with fuzzy theory, namely Fuzzy Kalman Filter (FKF) is presented to estimate the state variable of Non-Isothermal CSTR. First, we approximate the nonlinear system of CSTR as piecewise linear functions and then change the crisp variable into the fuzzy form. The estimation results are simulated using Matlab. The simulation shows the comparison results, i.e computational time and accuracy, between FKF and Ensemble Kalman Filter (EnKF). The final result of these case shows that FKF is better than EnKF to estimate the state variable of Nonisothermal CSTR. The error estimation of FKF is 72.9% smaller for estimation of reactans concentration, 39.9% smaller for tank temperature, 76.47% smaller for cooling jacket temperature and the computational time of FKF is 76.47% faster than the computational time of EnKF.
Prediksi Penyebaran Covid-19 di Indonesia dan Jawa Timur dengan Metode Extended Kalman Filter Helisyah Nur Fadhilah; Erna Apriliani; Didik Khusnul Arif
Limits: Journal of Mathematics and Its Applications Vol. 18 No. 1 (2021): Limits: Journal of Mathematics and Its Applications Volume 18 Nomor 1 Edisi Me
Publisher : Pusat Publikasi Ilmiah LPPM Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Saat ini pandemi Covid-19 telah menyebar ke seluruh dunia, tidak terkecuali Indonesia. Dalam pemodelan matematika, penyebaran Covid-19 dapat digambarkan melalui model matematika epidemiologi SIRD ( Susceptible, Infected, Recover, Death ). Pertama model non-linier SIRD didiskritkan dan selanjutnya dilakukan prediksi puncak penyebaran Covid-19 dengan menggunakan metode Extended Kalman Filter (EKF). Dengan data aktual Infected, Recover, dan Death yang merupakan data harian, modifikasi EKF dapat memprediksi puncak infeksi Covid-19 untuk satu bulan kedepan. Simulasi dilakukan dengan 3 macam pembatasan pergerakkan pada masyarakat yaitu : tanpa adanya pembatasan (100%), 75%, dan 50% pergerakkan. Hasil prediksi dengan modifikasi EKF menunjukkan dengan dilakukan pembatasan pergerakkan 50% pada masyarakat di Indonesia dan Jawa Timur dapat mempercepat terjadinya puncak infeksi dengan jumlah individu terinfeksi lebih sedikit
Co-Authors Bandung Arry Sanjoyo Budi Setiyono Dwi Ratna Sulistyaningrum Erna Apriliani Fadia Nila Sihan Novita Lutfiani Helisyah Nur Fadhilah Helisyah Nur Fadhilah Indah Rahmadhania Mardlijah - Muhammad Jirov Rexiansyah Grystnop Sutopo Nastitie Nastitie Nastitie Nastitie Prima Aditya Rifki Ilham Baihaki Risa Fitria Risa Fitria Sulthon Amar Al Aziim Valeriana Lukitosari Yunita Indriana Sari Zainullah Zuhri