Jupiter
Vol 14 No 2-c (2022): Jupiter Edisi Oktober 2022

Optimasi Fuzzy Time Series Chen Pada Prediksi Kasus Covid-19 Di Sumatera Selatan Menggunakan Particle Swarm Optimization

HAFIZH SHAFWAN RAFA (Universitas Sriwijaya)
Dian Palupi Rini (Teknik Informatika Universitas Sriwijaya)
Mastura Diana Marieska (Teknik Informatika Universitas Sriwijaya)

Article Info

Publish Date
16 Feb 2023

Abstract

At the beginning of its appearance, COVID-19 made the whole community become worried about the possibility that would happen in the future. Prediction of COVID-19 cases is a solution that can be done to reduce this worry. This study uses the Fuzzy Time Series Chen method to predict COVID-19 cases in the future, but on the other hand this method has shortcomings in determining the length of the interval which can result in the prediction accuracy being less good, so a Particle Swarm Optimization algorithm is needed to optimize the length. intervals that will later be used to predict cases of COVID-19, so that the results of the predictions will be better. Prediction accuracy is calculated using Mean Absolute Percentage Error. Based on testing the MAPE error value generated from Fuzzy Time Series Chen which is optimized for 26.380%, while for predictions without optimization it produces a value of 30.057%.

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Journal Info
Jupiter
Website

Abbrev

jupiter

Publisher

Politeknik Negeri Sriwijaya

Subject

Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Industrial & Manufacturing Engineering Library & Information Science

Description

Tentang Jurnal Ini Fokus dan Ruang Lingkup Bidang kajian yang dapat dimuat pada jurnal Jupiter meliputi dan tidak terbatas pada: Mobile Computing Image Processing Computer Graphic Artificial Intelligence Information Retrieval Computer Vision Algorithm & Complexity Data Mining Information System ...