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Journal : Matrik : Jurnal Manajemen, Teknik Informatika, dan Rekayasa Komputer

COVID-19 Chest X-Ray Detection Performance Through Variations of Wavelets Basis Function I Gusti Ayu Agung Diatri Indradewi; Ni Wayan Sumartini Saraswati; Ni Wayan Wardani
MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer Vol 21 No 1 (2021)
Publisher : LPPM Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (493.383 KB) | DOI: 10.30812/matrik.v21i1.1089

Abstract

Our previous work regarding the X-Ray detection of COVID-19 using Haar wavelet feature extraction and the Support Vector Machines (SVM) classification machine has shown that the combination of the two methods can detect COVID-19 well but then the question arises whether the Haar wavelet is the best wavelet method. So that in this study we conducted experiments on several wavelet methods such as biorthogonal, coiflet, Daubechies, haar, and symlets for chest X-Ray feature extraction with the same dataset. The results of the feature extraction are then classified using SVM and measure the quality of the classification model with parameters of accuracy, error rate, recall, specification, and precision. The results showed that the Daubechies wavelet gave the best performance for all classification quality parameters. The Daubechies wavelet transformation gave 95.47% accuracy, 4.53% error rate, 98.75% recall, 92.19% specificity, and 93.45% precision.
Recognize The Polarity of Hotel Reviews using Support Vector Machine Ni Wayan Sumartini Saraswati; I Gusti Ayu Agung Diatri Indradewi
MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer Vol 22 No 1 (2022)
Publisher : LPPM Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/matrik.v22i1.1848

Abstract

A brand is very dependent on consumer perceptions of the product or services. In assessing consumer perceptions of products and services, companies are often faced with data analysis problems. One of the data that is very useful to produce a picture of consumer perceptions of the products and services is review data. So that the company's ability to process review data means that the company has a picture of the strength of the brand it has. Some of the most popular machine learning algorithms for creating text classification models include the naive Bayes family of algorithms, support vector machines (SVM) and deep learning algorithms. In this research, SVM has been proven to be a reliable method in pattern recognition. In particular, this study aims to produce a model that can be used to classify the polarity of hotel reviews automatically. The experimental data comes from review data on hotels in Europe sourced from TripAdvisor with a total of 38000 reviews. We also measure the quality of the classification engine model. The test results of the SVM model built from hotel review data are quite good. The average accuracy of the classification engine is 92.48%. Because the recall and precision values ​​are balanced, the accuracy value is considered sufficient to describe the quality of the classification.