BibTex Citation Data :
@article{J.Gauss8587, author = {Restu Rahayu and Moch. Mukid and Triastuti Wuryandari}, title = {IDENTIFIKASI FAKTOR-FAKTOR YANG MEMPENGARUHI TERJADINYA PREEKLAMPSIA DENGAN METODE CHAID (Studi Kasus pada Ibu Hamil Kategori Jampersal di RSUD Dr.Moewardi Surakarta)}, journal = {Jurnal Gaussian}, volume = {4}, number = {2}, year = {2015}, keywords = {re-eclampsia, Classify, CHAID, Maternal Mortality Ratio, Accuration}, abstract = { Pre-eclampsia is a spesific pregnancy disease in which hypertency and proteinuria occurs after 20 weeks of pregnancy . This sickness is caused by many factors. To identify the factors, We lowercase a statistical analysis that can explain the characteristics of pregnant women who has pre-eclampsia. One analysis used for segmentation is CHAID ( Chi-Squared Automatic Interaction Detection ). This analysis classify and view the segmentation on nominal scale dependent variable (patient’s status). CHAID analysis result indicates that the history of hypertension is the most influential independent variable. The tree diagram shows that there are seven segments of pregnant women, this study reveals that, there are three segments that need to be concerned because these segments show a high number and high index value exceeds 100% of pregnant women with pre-eclampsia. These segments need an effort to support the reduction of MMR. The three segment are segment pregnant women who has the history of hypertension; segment pregnant women of primary school degree and who are jobless, overweight, with no history of hypertension; and segment pregnant women with elementary and junior high school degree, who has jobs, and no hypertension history. Accuration of the CHAID algorithm in classifying is 78,2%. Keywords : Pre-eclampsia, Classify, CHAID, Maternal Mortality Ratio, Accuration }, issn = {2339-2541}, pages = {383--392} doi = {10.14710/j.gauss.4.2.383 - 392}, url = {https://ejournal3.undip.ac.id/index.php/gaussian/article/view/8587} }
Refworks Citation Data :
Pre-eclampsia is a spesific pregnancy disease in which hypertency and proteinuria occurs after 20 weeks of pregnancy . This sickness is caused by many factors. To identify the factors, We lowercase a statistical analysis that can explain the characteristics of pregnant women who has pre-eclampsia. One analysis used for segmentation is CHAID (Chi-Squared Automatic Interaction Detection). This analysis classify and view the segmentation on nominal scale dependent variable (patient’s status). CHAID analysis result indicates that the history of hypertension is the most influential independent variable. The tree diagram shows that there are seven segments of pregnant women, this study reveals that, there are three segments that need to be concerned because these segments show a high number and high index value exceeds 100% of pregnant women with pre-eclampsia. These segments need an effort to support the reduction of MMR. The three segment are segment pregnant women who has the history of hypertension; segment pregnant women of primary school degree and who are jobless, overweight, with no history of hypertension; and segment pregnant women with elementary and junior high school degree, who has jobs, and no hypertension history. Accuration of the CHAID algorithm in classifying is 78,2%.
Keywords: Pre-eclampsia, Classify, CHAID, Maternal Mortality Ratio, Accuration
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