Article Per Year (5 Year)
p-Index From 2021 - 2026
2.782
P-Index
This Author published in this journals
All Journal International Journal of Electrical and Computer Engineering Jurnal Buana Informatika JURNAL TEKNIK INFORMATIKA DAN SISTEM INFORMASI Jiko (Jurnal Informatika dan komputer) Abdi Wiralodra : Jurnal Pengabdian Kepada Masyarakat Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) Aiti: Jurnal Teknologi Informasi Jurnal Teknologi Informasi dan Komunikasi Jurnal Pendidikan Jurnal Ilmiah Wahana Pendidikan Media Bina Ilmiah Jurnal Indonesia : Manajemen Informatika dan Komunikasi Kesatria : Jurnal Penerapan Sistem Informasi (Komputer dan Manajemen)
Rissal Effendi
Universitas Kristen Satya Wacana
Religion Agriculture, Biological Sciences & Forestry Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Languange, Linguistic, Communication & Media Library & Information Science Mechanical Engineering Public Health Social Sciences Other

Published : 18 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search
Journal : International Journal of Electrical and Computer Engineering

 1 
Precipitation and water discharge for internet of things based flood disaster prediction improvement Efendi, Rissal; Widiasari, Indrastanti R.
International Journal of Electrical and Computer Engineering (IJECE) Vol 14, No 6: December 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v14i6.pp6773-6785

Abstract

Floods are a major global problem affect communities and businesses. For these effects to be mitigated and emergency measures to be improved, accurate prediction is essential. Conventional flood prediction models frequently fail because the models ignore important hydrological elements like water discharge and instead solely use rainfall data. This limitation was addressed by the combination of rainfall and water discharge data on internet of things (IoT)-based technologies. It focuses on analyzing historical records from flood-prone areas in Semarang using gated recurrent unit (GRU) models. The findings demonstrate how effectively the GRU model performs when rainfall and water discharge factors are taken into account, resulting in very accurate and dependable predictions of flood events. Precision, Recall, and F1-score are evaluation metrics that demonstrate the accuracy on which the model determines flood emergency statuses. This study advances flood prediction methods and highlights the value of integrating internet of things data to improve preparedness and resilience against flood disasters.
Co-Authors Adriyanto Juliastomo Gundo Andika Wahyu Kurniawan Angela Atik Setiyanti Ardhian Ahkim Miftahul Huda Barsalinus Milenius Dupat Desi, Desi Deslitia Rolina Hanita Yulia Indrastanti Ratna Widiasari Krismiyati Marlens Albert Nenobais Meilinda Novena Br Simanjuntak Br Simanjuntak Mila Chrismawati Paseleng Nabila, Cheysha Restu Pariama, Alberth Septian Adi Prasetyo Teguh Wahyono Toriq Lurie Annaba Tumbilung, Chresto Friedrich Winrou Wesley Purba Yoppy Beniah Pello Yuliana T. B. Tacoh