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TELKOMNIKA Telecommunication, Computing, Electronics and Control
Machine learning based lightweight interference mitigation scheme for wireless sensor network
The interference issue is most vibrant on low-powered networks like wireless sensor network (WSN). In some cases, the heavy interference on WSN from different technologies and devices result in life threatening situations. In this paper, a machine…
TELKOMNIKA Telecommunication, Computing, Electronics and Control
Classification using semantic feature and machine learning: Land-use case application
Land cover classification has interested recent works especially for
deforestation, urban are monitoring and agricultural land use. Traditional
classification approaches have limited accuracy especially for non-
heterogeneous land cover. Thus,…
deforestation, urban are monitoring and agricultural land use. Traditional
classification approaches have limited accuracy especially for non-
heterogeneous land cover. Thus,…
TELKOMNIKA Telecommunication, Computing, Electronics and Control
Prediction schizophrenia using random forest
Schizophrenia is a mental illness with a very bad impact on sufferers, attacking the part of human brain that disables the ability to think clearly. In 2018, Rustam and Rampisela classified Schizophrenia by using Northwestern University Schizophrenia…
TELKOMNIKA Telecommunication, Computing, Electronics and Control
Comparison of machine learning performance for earthquake prediction in Indonesia using 30 years historical data
Indonesia resides on most earthquake region with more than 100 active volcanoes, and high number of seismic activities per year. In order to reduce the casualty, some method to predict earthquake have been developed to estimate the seismic movement.…
TELKOMNIKA Telecommunication, Computing, Electronics and Control
Roof materials identification based on pleiades spectral responses using supervised classification
The current urban environment is very dynamic and always changes both
physically and socio-economically very quickly. Monitoring urban areas is
one of the most relevant issues related to evaluating human impacts on
environmental change. Nowadays…
physically and socio-economically very quickly. Monitoring urban areas is
one of the most relevant issues related to evaluating human impacts on
environmental change. Nowadays…
TELKOMNIKA Telecommunication, Computing, Electronics and Control
Machine learning with multistage classifiers for identification of of ectoparasite infected mud crab genus Scylla
Recently, the mud-crab farming can help the rural population economically.
However, the existing parasite in the mud-crabs could interfere the long live
of the mud-crabs. Unfortunately, the parasite has been identified to live in
hundreds of…
However, the existing parasite in the mud-crabs could interfere the long live
of the mud-crabs. Unfortunately, the parasite has been identified to live in
hundreds of…
TELKOMNIKA Telecommunication, Computing, Electronics and Control
An effective feature extraction method for rice leaf disease classification
Our society is getting more and more technology dependent day by day.
Nevertheless, agriculture is imperative for our survival. Rice is one of the
primary food grains. It provides sustenance to almost fifty percent of the world
population and…
Nevertheless, agriculture is imperative for our survival. Rice is one of the
primary food grains. It provides sustenance to almost fifty percent of the world
population and…
TELKOMNIKA Telecommunication, Computing, Electronics and Control
The importance of data classification using machine learning methods in microarray data
The detection of genetic mutations has attracted global attention. several
methods have proposed to detect diseases such as cancers and tumours. One
of them is microarrays, which is a type of representation for gene expression
that is helpful in…
methods have proposed to detect diseases such as cancers and tumours. One
of them is microarrays, which is a type of representation for gene expression
that is helpful in…
Journal of ICT Research and Applications ITB Bandung Vol. 15 No. 3 2021
Machine-Learning Classifiers for Malware Detection Using Data Features
Abstract. The spread of ransomware has risen exponentially over the past decade, causing huge financial damage to multiple organizations. Various anti-ransomware firms have suggested methods for preventing malware threats. The growing pace, scale and…
Journal of ICT Research and Applications ITB Bandung Vol. 15 No. 2 2021
A New Term Frequency with Gaussian Technique for Text Classification and Sentiment Analysis
Abstract. This paper proposes a new term frequency with a Gaussian technique (TF-G) to classify the risk of suicide from Thai clinical notes and to perform sentiment analysis based on Thai customer reviews and English tweets of travelers that use US…