DOI: https://doi.org/10.21456/vol13iss1pp29-36

Klasifikasi Penyakit Jantung Menggunakan Algoritma Analisis Diskriminan Linier

*Ibnu Rashad  -  Postgraduate School, Diponegoro University, JL. Imam Bardjo SH No.5 Semarang, Indonesia
R Rizal Isnanto  -  Teknik Sistem Komputer, Fakultas Teknik Universitas Diponegoro, Indonesia
Catur Edi Widodo  -  Departemen Fisika, Fakultas Sains dan Matematika Universitas Diponegoro, Indonesia
Open Access Copyright (c) 2023 JSINBIS (Jurnal Sistem Informasi Bisnis)

Citation Format:
Abstract

The number of documented deaf people continues to increase. To communicate with each other, the deaf use sign language. The problem arises when Muslims with hearing impairment or deafness need to recite the Al-Quran. Muslims recite Al-Quran using their voice, but for the deaf, there are no available means to do the reciting. Thus, learning hijaiyah letters using finger gestures is considered important to develop. In this study, we use the recognition of hijaiyah letters based on pictures as the learning model. The real-time-based recognition then uses the learning model. This study uses 4 CNN pre-trained models, namely MnetV2, VGG16, ResNet50, and Xception. The learning process shows that MnetV2, VGG16, and Xception reach the accuracy limit of 99.85% in 2, 3, and 11 s, respectively. Meanwhile, ResNet50 cannot reach the accuracy limit after processing 100 s. ResNet50 achieves 82.12% accuracy. The testing process shows that MnetV2, VGG16, and ResNet50 achieve 100% precision, recall, f1-score, and accuracy. ResNet50 shows figures 81.55%, 86.04%, 82.04%, and 82.58%. The implementing process of the learning outcomes from MnetV2 shows good performance for recognizing finger shapes in real-time.

Fulltext View|Download
Keywords: Coronary Heart Disease; Machine Learning; Linear Discriminant Analysis

Article Metrics:

Article Info
Section: Research Articles
Language : ID
Recent articles
Analisis Adopsi Sistem ERP dalam Mengoptimasi Industri Pangan Menggunakan SEM dan Model UTAUT2 Penerapan PIECES Framework dalam Analisis Kepuasan Pengguna F-Learn UKSW saat Pandemi Covid-19 Perbandingan Performa Cluster Model Algoritma K-Means Dalam Mengelompokkan Penerima Bantuan Program Keluarga Harapan More recent articles
Most cited articles
Sistem Informasi Penyebaran Penyakit Demam Berdarah Menggunakan Metode Jaringan Syaraf Tiruan Backpropagation Data Clustering Menggunakan Metodologi CRISP-DM Untuk Pengenalan Pola Proporsi Pelaksanaan Tridharma Sistem Pendukung Keputusan Penilaian Proposal Kegiatan PNPM MPd Menggunakan Metode Profile Matching dan Analytic Hierarchy Process (AHP) Perencanaan Infrastruktur Teknologi Informasi pada Bank dengan Framework TOGAF Kombinasi Balanced Scorecard dan Objective Matrix Untuk Penilaian Kinerja Perguruan Tinggi More cited articles
  1. Budiman, E., Santoso, E., Afirianto, T., 2017. Pendeteksi jenis autis pada anak usia dini menggunakan metode linear discriminant analysis (LDA). Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer 1(7), 583–592
  2. Dhuhita, WDutta, D., Sil, J., Dutta, P., 2020. A bi-phased multi objective genetic algorithm based classifier.146
  3. Ghaderyan, P., Abbasi, A., Sedaaghi, M. H., 2014. An efficient seizure prediction method using KNN-based undersampling and linear frequency measures. Journal of Neuroscience Methods 232, 134–142
  4. Hana, F. M., 2020. Perbandingan algoritma neural network dengan linier discriminant analysis (LDA) pada klasifikasi penyakit diabetes. 1, 1541– 1541
  5. Handayani, I., 2019. Application of k-nearest neighbor algorithm on classification of disk hernia and spondylolisthesis in vertebral column. Indonesian Journal of Information Systems 2(1), 57-66
  6. Mai, H., Pham, T. T., Nguyen, D. N., Dutkiewicz, E., 2018. Non-laboratory-based risk factors for automated heart disease detection. International Symposium on Medical Information and Communication Technology (ISMICT) 1–6
  7. Mutawalli, L., Zaen, M. T. A., Bagye, W., 2019. Klasifikasi teks sosial media twitter menggunakan support vector machine (studi kasus penusukan wiranto). Jurnal Informatika dan Rekayasa Elektronik 2(2), 43-51
  8. Purnama, A., 2020. Edukasi dapat meningkatkan kualitas hidup pasien yang terdiagnosa penyakit jantung koroner. Jurnal Kesehatan Indonesia 10(2), 66–71
  9. Sulistio, S., 2017. Aplikasi prediksi kelulusan mahasiswa dengan metode Linear Discriminant Analysis. Computation : Journal of Computer Science and Information Systems 1(1), 58
  10. Trajdos, P., Burduk, R., 2021. Linear classifier combination via multiple potential functions. Pattern Recognition 111, 107681
  11. Wei, J., Chen, H., 2020. Determining the number of factors in approximate factor models by twice K-fold cross validation. Economics Letters, 191, 109149

Last update:

No citation recorded.

Last update: 2024-11-20 11:58:51

No citation recorded.