Trihelmina, Febriola Rania (2022) Faktor-Faktor Yang Mempengaruhi Stunting Menggunakan Regresi Probit Biner Dengan Pendekatan Synthetic Minority Oversampling Technique Di Puskesmas Jelbuk Kabupaten Jember. Other thesis, Institut Teknologi Sepuluh Nopember.
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Abstract
Stunting merupakan kondisi gagal tumbuh akibat kekurangan gizi di seribu hari pertama kehidupan anak atau biasa disebut dengan 1000 HPK. Stunting mengakibatkan kerugian besar dari segi ekonomi. Pemerintah telah menetapkan target untuk menjadi kekuatan ekonomi terbesar kelima di dunia pada tahun 2045, yang didukung adanya bonus demografi dengan banyaknya usia produktif dalam beberapa dekade mendatang. Tetapi jika stunting tetap pada level saat ini, lebih dari seperempat dari angkatan kerja tersebut akan kurang sehat dan produktif daripada yang seharusnya, sehingga sumber daya manusia yang ada di Indonesia akan kurang berkualitas. Penelitian-penelitian terdahulu memberikan inspirasi untuk melihat eksistensi kasus stunting di Indonesia, namun beberapa memiliki hasil yang kurang maksimal, sehingga dilakukan analisis kasus stunting dengan data individu pada studi kasus puskesmas. Data yang digunakan merupakan data status stunting anak usia 0-59 bulan di Wilayah Kerja Sukowiryo Puskesmas Jelbuk Kabupaten Jember yang merupakan kabupaten dengan prevalensi kasus stunting tertinggi kedua di Jawa Timur. Metode yang digunakan yaitu regresi probit biner Synthetic Minority Oversampling Technique. Persentase status stunting anak usia 0-59 bulan di Wilayah Kerja Sukowiryo sebesar 19%, sehingga perlu dilakukan penanganan data Imbalance dengan SMOTE. Faktor yang signifikan memengaruhi status stunting pada anak usia 0-59 bulan dari hasil pemodelan regresi probit biner synthetic minority oversampling technique adalah variabel riwayat bblr, pemberian asi eksklusif, konsumsi pil penambah darah pada ibu, imunisasi dasar lengkap, dan tingkat pendidikan ayah, dengan ketepatan model dalam mengklasifikasikan status stunting anak usia 0-59 bulan adalah 84,19%.
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Stunting is a condition of failure to grow due to malnutrition in the first thousand days of a child's life or commonly referred to as 1000 HPK. Stunting results in huge losses from an economic point of view. The government has set a target to become the world's fifth-largest economic power by 2045, supported by a demographic bonus with a large number of productive ages in the coming decades. But if stunting remains at its current level, more than a quarter of the labor force will be less healthy and productive than it should be, so the human resources in Indonesia will be less qualified. Previous studies have inspired the existence of stunting cases in Indonesia, but some have less than optimal results, so an analysis of stunting cases was carried out with individual data in puskesmas case studies. The data used is data on the stunting status of toddlers in the Sukowiryo Working Area of the Jelbuk Health Center, Jember Regency, which is the district with the second highest prevalence of stunting cases in East Java. The method used is the regression of the Synthetic Minority Oversampling Technique binary probit. The percentage of stunting status of toddlers in the Sukowiryo Work Area is 19%, so it is necessary to handle Imbalance data with SMOTE. Significant factors affecting stunting status in toddlers from the results of binary progression regression modeling synthetic minority oversampling technique are variables of bblr history, exclusive breastfeeding, consumption of blood-enhancing pills in mothers, complete basic immunization, and father’s education level, with the accuracy of the model in classifying stunting status of toddlers is 84.19%.
Item Type: | Thesis (Other) |
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Additional Information: | RSSt 519.536 Tri f 2023 |
Uncontrolled Keywords: | Anak, Regresi Probit Biner, SMOTE, Stunting, Binary Probit Regression, Toddlers |
Subjects: | H Social Sciences > HA Statistics > HA31.3 Regression. Correlation. Logistic regression analysis. |
Divisions: | Faculty of Science and Data Analytics (SCIENTICS) > Statistics > 49201-(S1) Undergraduate Thesis |
Depositing User: | Anis Wulandari |
Date Deposited: | 16 Sep 2025 02:40 |
Last Modified: | 16 Sep 2025 02:46 |
URI: | http://repository.its.ac.id/id/eprint/128250 |
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