Article Per Year (5 Year)
p-Index From 2020 - 2025
0.23
P-Index
This Author published in this journals
All Journal JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika)
Puteri, Nurhidayah
Unknown Affiliation
Computer Science & IT Education

Published : 1 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search

 1 
ANALYZING TEMPEARTURE ANOMALIES IN MONITORING DATA USING CONVOLUTIONAL NEURAL NETWORK Puteri, Nurhidayah; Astuti, Widi; Ihsan, Aditya Firman
JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Vol 10, No 1 (2025)
Publisher : STKIP PGRI Tulungagung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29100/jipi.v10i1.5616

Abstract

Temperature is a tool that shows the degree or measure of how hot or cold an object is. Incorrect temperature measurement can be fatal and cause various problems. Abnormal temperatures can prevent the temperature detection system from running optimally. Therefore, it is necessary to classify temperatures into normal and anomalous. Machine learning can be used as an alternative for temperature classification. By utilizing machine learning methods, one of which is Convolutional Neural Network. 3688569 temperature data were tested, dividing the results into 80% training data and 20% testing data. Accuracy, Precision, Recall, and F1 Score get a score of 100% and the CNN model graph is very good.
Co-Authors Aditya Firman Ihsan Widi Astuti