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All Journal Djtechno: Jurnal Teknologi Informasi Jurnal Nasional Holistic Science Jurnal Asimilasi Pendidikan
Amalia, Sisti Nadia
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Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Languange, Linguistic, Communication & Media Mathematics Social Sciences Other

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KLASIFIKASI RISIKO GIZI BURUK PADA IBU HAMIL MENGGUNAKAN METODE RANDOM FOREST Ramadhani, Fanny; Septiana, Dian; Amalia, Sisti Nadia; Fadilah, Putri Maulidina; Satria, Andy
Djtechno: Jurnal Teknologi Informasi Vol 5, No 2 (2024): Agustus
Publisher : Universitas Dharmawangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46576/djtechno.v5i2.4815

Abstract

Penelitian ini bertujuan untuk mengidentifikasi ibu hamil yang berisiko mengalami gizi buruk menggunakan metode klasifikasi machine learning, khususnya Random Forest, dengan memanfaatkan data dari RISKESDAS 2018. Dataset yang digunakan mencakup informasi demografi dan pola makan, termasuk usia, pendidikan, pekerjaan, status ekonomi, pola makan, dan akses ke layanan kesehatan. Data tersebut diolah melalui proses preprocessing yang meliputi penanganan nilai yang hilang, transformasi variabel kategori menggunakan OneHotEncoder, dan normalisasi fitur numerik. Model Random Forest kemudian dilatih dan dievaluasi menggunakan metrik akurasi, precision, recall, dan F1-score, serta confusion matrix untuk memahami kinerja klasifikasi. Hasil penelitian menunjukkan bahwa model Random Forest memiliki akurasi sebesar 0.67, precision sebesar 0.6, recall sebesar 0.67, dan F1-score sebesar 0.63 dalam mengklasifikasikan risiko gizi buruk pada ibu hamil. Confusion matrix memperlihatkan distribusi prediksi yang benar dan salah, sedangkan feature importance analysis mengidentifikasi fitur pola makan dan status ekonomi sebagai yang paling berpengaruh dalam prediksi risiko gizi buruk. Model Random Forest ini dapat digunakan sebagai alat yang efektif untuk mengidentifikasi ibu hamil yang berisiko tinggi mengalami gizi buruk, memungkinkan intervensi dini dan terarah dalam program kesehatan ibu hamil, sehingga dapat membantu meningkatkan kesehatan ibu dan anak. Penelitian ini juga menyediakan dasar untuk studi lanjutan yang dapat menggunakan dataset yang lebih luas dan beragam untuk memperbaiki akurasi dan generalisasi model.
The Relationship Between the Human Development Index (HDI) and Poverty Rate in North Sumatra in 2023: Spearman Correlation Analysis Hutapea, Risca Octaviyani; Triyunita, Gizka; Amalia, Sisti Nadia
Holistic Science Vol. 5 No. 2 (2025): Jurnal Nasional Holistic Sciences
Publisher : Lembaga Riset Mutiara Akbar NOMOR AHU-0003295.AH.01.07 TAHUN 2021

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56495/hs.v5i2.1133

Abstract

This study aims to analyze the relationship between the Human Development Index (HDI) and poverty levels in 33 regencies/cities across North Sumatra Province in 2023. The background of this research is rooted in the regional disparities in welfare and the strategic role of human development in poverty alleviation efforts. The data used are secondary data sourced from Statistics Indonesia (BPS), comprising HDI scores and poverty rates. The analytical methods applied include descriptive analysis, the Shapiro-Wilk normality test, and the Spearman rank correlation test, which is appropriate for non-normally distributed data. The findings reveal a significant negative correlation between HDI and poverty with a Spearman correlation coefficient of -0.5936 and a p-value of 0.0003. This indicates that regions with higher HDI tend to have lower poverty rates. The results highlight the importance of improving education quality, healthcare services, and living standards as key strategies in reducing poverty. This study is expected to contribute to the formulation of inclusive regional development policies that prioritize human well-being.
A Structural Equation Modeling Approach to Exploring the Role of Emotional Factors in Student Anxiety amid Public Demonstrations Amalia, Sisti Nadia; Zahra, Hafizha; Amry, Zul
JURNAL ASIMILASI PENDIDIKAN Vol. 4 No. 2 (2026): Jurnal Asimilasi Pendidikan
Publisher : LEMBAGA PENELITIAN DAN PENDIDIKAN (LPP) ARROSYIDIN

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61924/jasmin.v4i2.100

Abstract

This study investigates the role of emotional factors in student anxiety amid public demonstrations using a Structural Equation Modeling (SEM) approach. The study focuses on emotional intensity and emotional regulation as key psychological constructs within a socio-political context. The sample consisted of approximately 202 students from the Mathematics Department of the Faculty of Mathematics and Natural Sciences at Universitas Negeri Medan, selected through stratified random sampling. Data were collected using standardized instruments, including the Affect Intensity Measure (AIM), the Emotion Regulation Questionnaire (ERQ), and an adapted student anxiety scale measured on a five-point Likert scale. The SEM analysis indicates that the proposed model achieved an acceptable level of fit based on established goodness-of-fit criteria. However, the findings reveal that environmental stressors related to public demonstrations, emotional intensity, and emotional regulation do not have a significant direct effect on student anxiety. These results suggest the presence of adaptive psychological mechanisms, such as resilience and desensitization, among students in response to recurring socio-political disturbances. This study highlights the importance of considering contextual and psychological complexity when modeling student anxiety using SEM.
Co-Authors Amry, Zul Andy Satria Dian Septiana Fadilah, Putri Maulidina Hutapea, Risca Octaviyani Ramadhani, Fanny Triyunita, Gizka Zahra, Hafizha