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All Journal Elkom: Jurnal Elektronika dan Komputer Jurnal Pengabdian Bersama Masyarakat Indonesia
Reni, Reni Utami
Unknown Affiliation
Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Languange, Linguistic, Communication & Media Public Health

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Planning and Organization of High School Activities with Google Classroom Asysyakirin Tangerang Islamic High School Training Participants Reni, Reni Utami; Ari Hidayatullah
Jurnal Pengabdian Bersama Masyarakat Indonesia Vol. 2 No. 3 (2024): Juli : Jurnal Pengabdian Bersama Masyarakat Indonesia
Publisher : CV. Aksara Global Akademia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59031/jpbmi.v2i3.414

Abstract

The PKM implemented aims to train high school students to use Google Classroom media for the teaching and learning process in the current hybrid era, after the Covid-19 pandemic. With this training, students and teachers can optimize their use of Google Classroom more optimally and efficiently because they have previously used it. The first stage was to explore problems related to the potential of e-learning during the Covid-19 pandemic. 3 years ago, this activity resulted in an increase in students' knowledge about e-learning and skills in using Google Class Room in the current era. Classes are an online learning medium that is interactive and fun in the teaching process and collecting assignments
The Prediksi Curah Hujan Pada Stasiun BMKG (CITEKO) Menggunakan Metode Backpropogation Neural Network Reni, Reni Utami; Ari Hidayatullah
Elkom : Jurnal Elektronika dan Komputer Vol 17 No 1 (2024): Juli : Jurnal Elektronika dan Komputer
Publisher : STEKOM PRESS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/elkom.v17i1.1921

Abstract

Accurate rainfall prediction is needed to improve the performance of land that always uses rainfall data. Data mining or often called knowledge discovery in databases (KDD) is an activity that includes collecting, using historical data to find regularities, patterns or relationships in large data. In predicting rainfall, there are several conditions that can be observed as reference data to predict rainfall, namely wind speed, temperature, and air humidity. In this research, a backpropagation artificial neural network prediction method is developed that can be used in predicting future rainfall. The backpropogation artificial neural network method that was built produced an accuracy value of 95.36%, a precision value of 90.50%, a recall value of 97.50% and an f-measure value of 92.00%
The Prediksi Curah Hujan Pada Stasiun BMKG (CITEKO) Menggunakan Metode Backpropogation Neural Network Reni, Reni Utami; Ari Hidayatullah
Elkom: Jurnal Elektronika dan Komputer Vol. 17 No. 1 (2024): Juli : Jurnal Elektronika dan Komputer
Publisher : STEKOM PRESS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/elkom.v17i1.1921

Abstract

Accurate rainfall prediction is needed to improve the performance of land that always uses rainfall data. Data mining or often called knowledge discovery in databases (KDD) is an activity that includes collecting, using historical data to find regularities, patterns or relationships in large data. In predicting rainfall, there are several conditions that can be observed as reference data to predict rainfall, namely wind speed, temperature, and air humidity. In this research, a backpropagation artificial neural network prediction method is developed that can be used in predicting future rainfall. The backpropogation artificial neural network method that was built produced an accuracy value of 95.36%, a precision value of 90.50%, a recall value of 97.50% and an f-measure value of 92.00%
Co-Authors Ari Hidayatullah