BibTex Citation Data :
@article{Medstat10086, author = {Moch. Mukid and Triastuti Wuryandari and Desy Ratnaningrum and Restu Sri Rahayu}, title = {BAGGING CLASSIFICATION TREES UNTUK PREDIKSI RISIKO PREEKLAMPSIA (Studi Kasus : Ibu Hamil Kategori Penerima Jampersal di RSUD Dr. Moewardi Surakarta)}, journal = {MEDIA STATISTIKA}, volume = {8}, number = {2}, year = {2015}, keywords = {}, abstract = { Preeclampsia is a spesific pregnancy disease in which hypertency and proteinuria occurs after 20 weeks of pregnancy. Classification Trees is a statistical method that can be used to identify potency of expectant women suffering from preeclampsia. This research aim to predict the risk of preeclampsia based on some individual variables. They are parity, work status, history of hypertension of preeclampsia, body mass index, education and income. To improve the stability and accuracy of the prediction were used the Bootstrap Aggregating Classification Trees method. By the method, classification accuracy reach to 86%. Keywords : Pre-eclampsia, Bagging CART, Classification Accuracy }, issn = {2477-0647}, pages = {111--120} doi = {10.14710/medstat.8.2.111-120}, url = {https://ejournal.undip.ac.id/index.php/media_statistika/article/view/10086} }
Refworks Citation Data :
Preeclampsia is a spesific pregnancy disease in which hypertency and proteinuria occurs after 20 weeks of pregnancy. Classification Trees is a statistical method that can be used to identify potency of expectant women suffering from preeclampsia. This research aim to predict the risk of preeclampsia based on some individual variables. They are parity, work status, history of hypertension of preeclampsia, body mass index, education and income. To improve the stability and accuracy of the prediction were used the Bootstrap Aggregating Classification Trees method. By the method, classification accuracy reach to 86%.
Keywords : Pre-eclampsia, Bagging CART, Classification Accuracy
Article Metrics:
Last update:
Last update: 2024-04-26 18:15:25
The Authors submitting a manuscript do so on the understanding that if accepted for publication, copyright of the article shall be assigned to Media Statistika journal and Department of Statistics, Universitas Diponegoro as the publisher of the journal. Copyright encompasses the rights to reproduce and deliver the article in all form and media, including reprints, photographs, microfilms, and any other similar reproductions, as well as translations.
Media Statistika journal and Department of Statistics, Universitas Diponegoro and the Editors make every effort to ensure that no wrong or misleading data, opinions or statements be published in the journal. In any way, the contents of the articles and advertisements published in Media Statistika journal are the sole and exclusive responsibility of their respective authors and advertisers.
The Copyright Transfer Form can be downloaded here: [Copyright Transfer Form Media Statistika]. The copyright form should be signed originally and send to the Editorial Office in the form of original mail, scanned document or fax :
Dr. Di Asih I Maruddani (Editor-in-Chief) Editorial Office of Media StatistikaDepartment of Statistics, Universitas DiponegoroJl. Prof. Soedarto, Kampus Undip Tembalang, Semarang, Central Java, Indonesia 50275Telp./Fax: +62-24-7474754Email: maruddani@live.undip.ac.id
Media Statistika
Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro
Gedung F Lantai 3, Jalan Prof Jacub Rais, Kampus Tembalang
Semarang 50275
Visitor Number:
Indexing:
