Implementation Data Mining using Decision Tree Method-Algorithm C4.5 for Postpartum Depression Diagnosis
Postpartum depression is a serious problem that needs to be addressed because it has negative effects on family, child welfare, cognitive, and mother child interactions. Diagnosis is done based on psychological condition, blood pressure, respiration, body temperature, and classification data extract...
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
EDP Sciences
2018-01-01
|
| Series: | E3S Web of Conferences |
| Subjects: | |
| Online Access: | https://doi.org/10.1051/e3sconf/20187312012 |
| _version_ | 1818919847174602752 |
|---|---|
| author | Supriyanto Aris Suryono Suryono Susesno Jatmiko Endro |
| author_facet | Supriyanto Aris Suryono Suryono Susesno Jatmiko Endro |
| author_sort | Supriyanto Aris |
| collection | DOAJ |
| description | Postpartum depression is a serious problem that needs to be addressed because it has negative effects on family, child welfare, cognitive, and mother child interactions. Diagnosis is done based on psychological condition, blood pressure, respiration, body temperature, and classification data extract by decision tree C4.5 algorithm method. Results of this study in the form of an online information system that can identify the level of depression more quickly and precisely. The results showed the greatest gain on the psychological variables of 0.57 node 1, blood pressure 0.54 node 2, body temperature 0,54 node 3, means that the three variables are more influential on the condition of depressed patients, and should be given priority treatment. Test results from 50 patients with 50 examinations showed 62% prevalence, 65.62% sensitivity, specificity 77.77%, negative predictive value of 56%, and positive predictive value 84%, and |
| first_indexed | 2024-12-20T01:12:21Z |
| format | Article |
| id | doaj.art-1d39a15659084802a8ea9fcf89bca7d7 |
| institution | Directory Open Access Journal |
| issn | 2267-1242 |
| language | English |
| last_indexed | 2024-12-20T01:12:21Z |
| publishDate | 2018-01-01 |
| publisher | EDP Sciences |
| record_format | Article |
| series | E3S Web of Conferences |
| spelling | doaj.art-1d39a15659084802a8ea9fcf89bca7d72022-12-21T19:58:40ZengEDP SciencesE3S Web of Conferences2267-12422018-01-01731201210.1051/e3sconf/20187312012e3sconf_icenis18_12012Implementation Data Mining using Decision Tree Method-Algorithm C4.5 for Postpartum Depression DiagnosisSupriyanto Aris0Suryono Suryono1Susesno Jatmiko Endro2Magister Program of Information System, School of Postgraduate Studies, Diponegoro UniversityDepartement of Physics, Science and Mathematics Faculty, Diponegoro UniversityDepartement of Physics, Science and Mathematics Faculty, Diponegoro UniversityPostpartum depression is a serious problem that needs to be addressed because it has negative effects on family, child welfare, cognitive, and mother child interactions. Diagnosis is done based on psychological condition, blood pressure, respiration, body temperature, and classification data extract by decision tree C4.5 algorithm method. Results of this study in the form of an online information system that can identify the level of depression more quickly and precisely. The results showed the greatest gain on the psychological variables of 0.57 node 1, blood pressure 0.54 node 2, body temperature 0,54 node 3, means that the three variables are more influential on the condition of depressed patients, and should be given priority treatment. Test results from 50 patients with 50 examinations showed 62% prevalence, 65.62% sensitivity, specificity 77.77%, negative predictive value of 56%, and positive predictive value 84%, andhttps://doi.org/10.1051/e3sconf/20187312012postpartum depressiondecision treealgorithm C4.5online information system |
| spellingShingle | Supriyanto Aris Suryono Suryono Susesno Jatmiko Endro Implementation Data Mining using Decision Tree Method-Algorithm C4.5 for Postpartum Depression Diagnosis E3S Web of Conferences postpartum depression decision tree algorithm C4.5 online information system |
| title | Implementation Data Mining using Decision Tree Method-Algorithm C4.5 for Postpartum Depression Diagnosis |
| title_full | Implementation Data Mining using Decision Tree Method-Algorithm C4.5 for Postpartum Depression Diagnosis |
| title_fullStr | Implementation Data Mining using Decision Tree Method-Algorithm C4.5 for Postpartum Depression Diagnosis |
| title_full_unstemmed | Implementation Data Mining using Decision Tree Method-Algorithm C4.5 for Postpartum Depression Diagnosis |
| title_short | Implementation Data Mining using Decision Tree Method-Algorithm C4.5 for Postpartum Depression Diagnosis |
| title_sort | implementation data mining using decision tree method algorithm c4 5 for postpartum depression diagnosis |
| topic | postpartum depression decision tree algorithm C4.5 online information system |
| url | https://doi.org/10.1051/e3sconf/20187312012 |
| work_keys_str_mv | AT supriyantoaris implementationdataminingusingdecisiontreemethodalgorithmc45forpostpartumdepressiondiagnosis AT suryonosuryono implementationdataminingusingdecisiontreemethodalgorithmc45forpostpartumdepressiondiagnosis AT susesnojatmikoendro implementationdataminingusingdecisiontreemethodalgorithmc45forpostpartumdepressiondiagnosis |