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Deteksi Kejadian Depresi Post Partum dengan Algoritma Naïve Bayes Fadhiyah Noor Anisa; Sarkiah Sarkiah; Ahmad Hidayat
DINAMIKA KESEHATAN: JURNAL KEBIDANAN DAN KEPERAWATAN Vol 12, No 1 (2021): Dinamika Kesehatan: Jurnal Kebidanan dan Keperawatan
Publisher : Universitas Sari Mulia

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (811.272 KB) | DOI: 10.33859/dksm.v12i1.678

Abstract

Latar Belakang, Depresi postpartum banyak dialami ibu setelah persalinan  yang disebabkan oleh gangguan emosional. Kejadian depresi postpartum terjadi dalam enam bulan setelah melahirkan menurut WHO tahun 2018. Lebih dari 300 juta orang menderita depresi postpartum, secara global berkisar 0.5% hingga 60.8% dan di Indonesia angka kejadian depresi postpartum sebanyak 22.4%. Peneliti tertarik untuk mendeteksi kejadian Depresi Postpartum.Tujuan, mendeteksi kejadian depresi postpartum dengan Algoritma Naïve BayesMetode, penelitian ini menggunakan algoritma naïve bayes untuk mendeteksi kejadian depresi postpartum dengan teknik Accidental Sampling sebanyak 261 responden.Hasil penelitian, jumlah yang terdeteksi depresi postpartum ringan sebanyak 170 responden dan yang mengalami depresi berat sebanyak 91 responden, faktor-faktor yang mempengaruhi depresi postpartum berupa pekerjaan didapatkan ibu yang tidak bekerja yang mengalami berjumlah 66 responden, pada usia perkawinan 15-23 tahun yang terdeteksi depresi berat sebanyak 55 responden, sedangan responden dengan usia perkawinan 24-38 tahun yang terdeteksi depresi berat sebanyak 9 responden. Faktor umur ibu yang terdeteksi depresi berat di umur 20 tahun dan 35 tahun sebanyak 144 responden, faktor cara persalinan normal yang mengarah depresi berat terdapat 73 responden, sedangkan dilihat dari faktor pendidikan terdapat pada sekolah menangah dan perguruan tinggi yang terdeteksi depresi berat sebanyak 69 responden.Kesimpulan, faktor yang dapat mendeteksi depresi postpartum pada faktor pekerjaan yang tidak bekerja, pada usia perkawinan di usia 15-23 tahun, pada faktor usia ibu saat ini di usia 20 s.d 35 tahun, faktor paritas pada multipara, faktor cara persalinan normal dan pada pendidikan ditemukan pada sekolah menengah dan perguruan tinggi yang mengarah pada depresi berat. Kata Kunci: Depresi Postpartum, Algoritma Naïve Bayes Detection of Post Partum Depression Events with Naïve Bayes AlgorithmBackground: Postpartum depression is widely experienced by mothers after childbirth caused by emotional disorders. The incidence of postpartum depression occurred within six months of giving birth according to who in 2018. More than 300 million people suffer from postpartum depression, globally ranging from 0.5% to 60.8%, and in Indonesia, the incidence of postpartum depression is 22.4%. Researchers are interested in detecting the incidence of Postpartum Depression.Objective: detecting postpartum depressive events with Naïve Bayes AlgorithmThis method: this study used the naïve Bayes algorithm to detect the incidence of postpartum depression with the Accidental Sampling technique as many as 261 respondents.Result: the number detected mild postpartum depression as many as 170 respondents and who experienced severe depression as many as 91 respondents, factors that influence postpartum depression in the form of work obtained by non-working mothers who experienced a total of 66 respondents, at the age of marriage 15-23 years detected severe depression as many as 55 respondents, while respondents with a marriage age of 24-38 years detected severe depression as many as 9 respondents. Maternal age factor detected severe depression in the age of 20 years and 35 years as many as 144 respondents, factors of normal delivery that leads to severe depression there are 73 respondents, while seen from educational factors found in winning schools and colleges detected severe depression as many as 69 respondents.Conclusion: factors that can detect postpartum depression in factors of work that do not work, at the age of marriage at the age of 15-23 years, in the current maternal age factor at the age of 20 to 35 years, parity factor in multipara, factors of normal delivery and in education found in secondary schools and colleges that lead to severe depression. Keywords: Postpartum Depression, Naïve Bayes Algorithm
Deteksi Kejadian Depresi Post Partum dengan Algoritma Naïve Bayes Fadhiyah Noor Anisa; Sarkiah Sarkiah; Ahmad Hidayat
DINAMIKA KESEHATAN: JURNAL KEBIDANAN DAN KEPERAWATAN Vol 12, No 1 (2021): Dinamika Kesehatan: Jurnal Kebidanan dan Keperawatan
Publisher : Universitas Sari Mulia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33859/dksm.v12i1.678

Abstract

Latar Belakang, Depresi postpartum banyak dialami ibu setelah persalinan  yang disebabkan oleh gangguan emosional. Kejadian depresi postpartum terjadi dalam enam bulan setelah melahirkan menurut WHO tahun 2018. Lebih dari 300 juta orang menderita depresi postpartum, secara global berkisar 0.5% hingga 60.8% dan di Indonesia angka kejadian depresi postpartum sebanyak 22.4%. Peneliti tertarik untuk mendeteksi kejadian Depresi Postpartum.Tujuan, mendeteksi kejadian depresi postpartum dengan Algoritma Naïve BayesMetode, penelitian ini menggunakan algoritma naïve bayes untuk mendeteksi kejadian depresi postpartum dengan teknik Accidental Sampling sebanyak 261 responden.Hasil penelitian, jumlah yang terdeteksi depresi postpartum ringan sebanyak 170 responden dan yang mengalami depresi berat sebanyak 91 responden, faktor-faktor yang mempengaruhi depresi postpartum berupa pekerjaan didapatkan ibu yang tidak bekerja yang mengalami berjumlah 66 responden, pada usia perkawinan 15-23 tahun yang terdeteksi depresi berat sebanyak 55 responden, sedangan responden dengan usia perkawinan 24-38 tahun yang terdeteksi depresi berat sebanyak 9 responden. Faktor umur ibu yang terdeteksi depresi berat di umur 20 tahun dan 35 tahun sebanyak 144 responden, faktor cara persalinan normal yang mengarah depresi berat terdapat 73 responden, sedangkan dilihat dari faktor pendidikan terdapat pada sekolah menangah dan perguruan tinggi yang terdeteksi depresi berat sebanyak 69 responden.Kesimpulan, faktor yang dapat mendeteksi depresi postpartum pada faktor pekerjaan yang tidak bekerja, pada usia perkawinan di usia 15-23 tahun, pada faktor usia ibu saat ini di usia 20 s.d 35 tahun, faktor paritas pada multipara, faktor cara persalinan normal dan pada pendidikan ditemukan pada sekolah menengah dan perguruan tinggi yang mengarah pada depresi berat. Kata Kunci: Depresi Postpartum, Algoritma Naïve Bayes Detection of Post Partum Depression Events with Naïve Bayes AlgorithmBackground: Postpartum depression is widely experienced by mothers after childbirth caused by emotional disorders. The incidence of postpartum depression occurred within six months of giving birth according to who in 2018. More than 300 million people suffer from postpartum depression, globally ranging from 0.5% to 60.8%, and in Indonesia, the incidence of postpartum depression is 22.4%. Researchers are interested in detecting the incidence of Postpartum Depression.Objective: detecting postpartum depressive events with Naïve Bayes AlgorithmThis method: this study used the naïve Bayes algorithm to detect the incidence of postpartum depression with the Accidental Sampling technique as many as 261 respondents.Result: the number detected mild postpartum depression as many as 170 respondents and who experienced severe depression as many as 91 respondents, factors that influence postpartum depression in the form of work obtained by non-working mothers who experienced a total of 66 respondents, at the age of marriage 15-23 years detected severe depression as many as 55 respondents, while respondents with a marriage age of 24-38 years detected severe depression as many as 9 respondents. Maternal age factor detected severe depression in the age of 20 years and 35 years as many as 144 respondents, factors of normal delivery that leads to severe depression there are 73 respondents, while seen from educational factors found in winning schools and colleges detected severe depression as many as 69 respondents.Conclusion: factors that can detect postpartum depression in factors of work that do not work, at the age of marriage at the age of 15-23 years, in the current maternal age factor at the age of 20 to 35 years, parity factor in multipara, factors of normal delivery and in education found in secondary schools and colleges that lead to severe depression. Keywords: Postpartum Depression, Naïve Bayes Algorithm
Relationship between type of delivery and colostrum production from postpartum mothers at Dr.H.Moch Ansari Saleh Hospital, Banjarmasin Cantika Cantika; Fadhiyah Noor Anisa; Fitri Yuliana; Sarkiah Sarkiah
Jurnal EduHealth Vol. 14 No. 04 (2023): Jurnal eduHealt, 2023, December
Publisher : Sean Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Colostrum is a yellowish liquid that is produced from pregnancy to 4 days postpartum. However, colostrum cannot be secreted directly because levels of the hormone estrogen are still high. Delays in expressing colostrum can affect exclusive breastfeeding. The choice of type of delivery has an impact on the occurrence of colostrum production in postpartum mothers. Mothers who give birth normally have the opportunity to immediately give colostrum to their babies through the IMD process or early contact. This study aims to analyze the relationship between type of delivery and colostrum expenditure at RSUD Dr. H. Moch Ansari Saleh Banjarmasin. This type of research is quantitative with a cross sectional design. The respondents in this study were 108 postpartum mothers, taken using a purposive sampling technique as many as 37 people, then analyzed using the Chi-Square test. Data was obtained from 37 postpartum mothers based on the most age characteristics, namely <20 and >35 years (51%), multiparous parity 21 people (57%), nutritional status ≥23.5 cm (97%), basic level education as many as 25 people (67.6%), SC delivery (59.5%). The highest colostrum production is >120 minutes. The results of Chi-Square analysis obtained valuesp value0.000 (p<0.05)which means accepting the alternative hypothesis, meaning that there is a real relationship between the type of delivery and colostrum expenditure. It can be concluded that there is a relationship between the type of delivery and colostrum expenditure. This is because the SC type of delivery slows down the time of colostrum expulsion, occurring at >120 minutes.