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All Journal Jurnal Informatika Upgris Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Jurnal Abdimas BSI: Jurnal Pengabdian Kepada Masyarakat Jurnal Informatika JURNAL MEDIA INFORMATIKA BUDIDARMA Indonesian Journal of Artificial Intelligence and Data Mining JITK (Jurnal Ilmu Pengetahuan dan Komputer) Dinamisia: Jurnal Pengabdian Kepada Masyarakat SELAPARANG: Jurnal Pengabdian Masyarakat Berkemajuan Jurnal ICT : Information Communication & Technology Vygotsky: Jurnal Pendidikan Matematika dan Matematika Infotekmesin Society : Jurnal Pengabdian dan Pemberdayaan Masyarakat Jurnal Ilmiah Teknik Mesin, Elektro dan Komputer (JURITEK) Jurnal Komunikasi Global Jurnal Informatika: Jurnal Pengembangan IT Prosiding Seminar Nasional Pemberdayaan Masyarakat (SENDAMAS)
Primandani Arsi
Universitas Amikom Purwokerto
Agriculture, Biological Sciences & Forestry Arts Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Health Professions Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Mathematics Mechanical Engineering Medicine & Pharmacology Nursing Public Health Social Sciences Other

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Journal : Infotekmesin

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Komparasi Model Prediksi Kurs Pada Masa Pandemi Covid-19 Menggunakan Neural Network Berbasis Genetic Algorithm dan Particle Swarm Optimization Ali Nur Ikhsan; Primandani Arsi; Jali Suhaman
Infotekmesin Vol 13 No 1 (2022): Infotekmesin: Januari, 2022
Publisher : P3M Politeknik Negeri Cilacap

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35970/infotekmesin.v13i1.938

Abstract

Data from Bank Indonesia shows that the rupiah exchange rate against dollar weakened at the beginning of the Covid-19 pandemic. This exchange rate volatility is an important problem in the Indonesian economy. Therefore, the prediction model for the exchange rate against the dollar is needed during the Covid-19 pandemic to predict the exchange rate during the Covid-19 Pandemic. This study is proposed to compare the prediction of the rupiah exchange rate against the dollar using the GA-based Neural Network algorithm and the PSO-based Neural Network algorithm. Initially the data was collected in the period 2019 to 2021, then the data is preprocessed. Validation used the k-fold validation technique with a ratio of 70:30, while the evaluation is carried out with the output of RMSE. The results showed that the performance of PSO and GA was the same, namely 0.020 +/- 0.006.
Co-Authors Akhmad Mustolih Aldi Setia Pambudi Ali Nur Ikhsan Andi Dwi Riyanto Arbangi Puput Sabaniyah Azizan Nurhakim Azizan Nurhakim Bagus Adhi Kusuma Berlilana Berlilana Desta Nur Efika Ardini Desty Rakhmawati Dewi Fortuna Dwi Krisbiantoro Faridatun Nida Iphang Prayoga Irma Darmayanti Jali Suhaman Joko Prayogi Khoirul Abbi Rokhman Laili Nur Hidayati Mohammad imron Muhammad Hasyim Asyari Nurhopipah, Ade Oman Somantri Prasetyo, Agung Pungkas Subarkah Raditya Danar Dana Retno Waluyo Rizki Wahyudi Rosana Fadilla Sari Saeful Karim Septi Fajarwati Septi Oktaviani Nur Hidayah Sulis waningsih Tri Astuti Trian Damai Wawa Maisa Yuni Novita Yusyida Munsa Idah