Lung Disease Prediction Using Voting Feature Intervals 5 With Feature Weighting Non Uniform
Prediksi Penyakit Paru Menggunakan Algoritme Voting Feature Intervals 5 dengan Bobot Fitur Tidak Seragam
View/ Open
Date
2012Author
Ceria, Disty Tata
Kustiyo, Aziz
Noviati, Tri
Metadata
Show full item recordAbstract
Bronchitis and pulmonary tuberculosis have symptoms that are very similar. The symptoms are coughing, coughing up blood, shortness of breath, chest pain, body weakness, decreased appetite, weight loss, night sweats without activity. In this study Voting Feature Intervals 5 classification algorithm perform two types of lung disease which are bronchitis and pulmonary tuberculosis. Data collected through the interview process on new patients in the lung poly District General Hospital Pasar Rebo. The question is given in the form of common symptoms of lung disease that has consulted with dr. Tri Novianti, MARS and conducted training and testing process using Voting Feature Intervals 5 algorithms. The use of algorithms Voting Feature Intervals 5 in bronchitis and pulmonary tuberculosis classifies good results, and similar symptoms in both diseases can be proved after the visits of the intervals generated by each symptom in the training and the final normalization of the entire experiment. Penyakit paru mempunyai gejala yang sangat mirip misalnya pada Bronkitis dan Tuberkulosis Paru, gejala tersebut adalah batuk, batuk darah, sesak nafas, sakit dada, badan lemah, nafsu makan berkurang, berat badan turun, berkeringat malam walaupun tanpa kegiatan. Pada penelitian ini algoritme VFI5 melakukan klasifikasi dua jenis penyakit paru yaitu Bronkitis dan Tb Paru. Pengumpulan data dilakukan dengan proses wawancara pada pasien baru di poli paru Rumah Sakit Umum Daerah Pasar Rebo. Pertanyaan yang diberikan berupa gejala umum penyakit paru yang telah dikonsultasikan dengan dr. Tri Novianti, MARS dan dilakukan proses pelatihan dan pengujian menggunakan algoritme Voting Feature Intervals 5. Penggunaan algoritme VFI 5 dalam mengklasifikasi Bronkitis dan Tb Paru cukup memberikan hasil yang baik dan miripnya gejala pada kedua penyakit ini dapat dibuktikan setelah dilihat dari selang-selang yang dihasilkan oleh setiap gejala pada pelatihan dan pada normalisasi akhir seluruh percobaan.
Collections
- UT - Computer Science [2322]
Related items
Showing items related by title, author, creator and subject.
-
Object retrieval in video using feature quantization of scale Invariant Feature Transform (SIFT)
Sriyasa, I Wayan | Nurdiati, Sri | Wijaya, Sony Hartono (2010)Identification of objects in an image/video database is becoming a hot issue and very interesting to investigate because of the emergence of visual objects that may highly vary along with the difference in viewpoint and ... -
The Identification of Infant Cries by Using Codebook as Feature Matching, and MFCC as Feature Extraction
Renanti, Medhanita Dewi | Buono, Agus | Kusuma, Eng Wisnu Ananta (2013)In this paper, we focused on automation of Dunstan Baby Language. This software uses MFCC as feature extraction and codebook as feature matching. The codebook of clusters is made from the proceeds of all the baby’s cries ... -
Infant Cries Identificaton by Using Codebook As Feature Matching, And MFCC As Feature Extraction
Renanti, Medhinita Dewi | Buono, Agus | Kusuma, Wisnu Ananta (2005)In this paper, we focused on automation of Dunstan Bab) Language. This system uses MFCC as feature e\lraetion and codebook as ti!oture matching. The codebook or clusters is made from the proceeds of all the buhy's cries ...