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All Journal E-Journal Widya Kesehatan dan Lingkungan Jurnal Ilmiah Widya BAREKENG: Jurnal Ilmu Matematika dan Terapan Jurnal Aplikasi Statistika & Komputasi Statistik Prosiding Seminar Nasional Official Statistics Jurnal Ekonomi Kependudukan dan Keluarga
Sarni Maniar Berliana, Sarni Maniar
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Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Energy Engineering Environmental Science Mathematics Mechanical Engineering Physics Public Health Social Sciences Transportation Other

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FAKTOR-FAKTOR YANG MEMENGARUHI KELAHIRAN PREMATUR DI INDONESIA: ANALISIS DATA RISKESDAS 2013 Sulistiarini, Dwi; Berliana, Sarni Maniar
E-Journal Widya Kesehatan dan Lingkungan Vol. 1 No. 2 (2018)
Publisher : E-Journal Widya Kesehatan dan Lingkungan

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (32.475 KB)

Abstract

Prematuritas is the second leading cause of death in babies after pneumonia and is the leading cause of neonatal mortality. Thirty-five percent of the world's neonatal death was caused by complications of premature birth (WHO: 2012). The purpose of this research is to know the characteristics of the sosiodemografi affect the incidence of premature birth in Indonesia. This research uses data Basic Health Research (Riskesdas) 2013. The unit of analysis in this research is the whole live births that occurred from January 2010 to June 2013. Binary logistic regression methods were used to figure out the tendencies of a woman experiencing premature birth events. The results showed that out of the 36% of females there 48336 mother who experienced premature birth. Logistic regression results indicate that all free variables used are significantly affecting the incidence of preterm birth. Women with childbirth when young age characteristics, lower-educated, living in rural areas, do not have a history of miscarriage, gave birth to their first child, do not do the complete pregnancy examination, and experienced complications while pregnant tend to be greater risk experienced premature birth. The last three factors give the greatest influence on the incidence of preterm birth, It is recommended that appropriate recommendations for pregnancy examinations program should be further promoted and qualified health care personnel and facilities should be available in all regions of Indonesia, especially in rural areas.
FAKTOR-FAKTOR YANG MEMENGARUHI JAM KERJA TENAGA KERJA WANITA BERSTATUS KAWIN DALAM SEMINGGU DI INDONESIA (ANALISIS DATA SAKERNAS 2014) Berliana, Sarni Maniar; Purbasari, Lukmi Ana
Jurnal Ilmiah Widya Vol 4 No 3 (2018)
Publisher : Lembaga Layanan Pendidikan Tinggi Wilayah III Jakarta

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ABSTRAK: Wanita menikah memiliki peran ganda, yaitu sebagai pencari nafkah dan pengelola rumah tangga. Peran ganda wanita sebagai pencari nafkah dan pengelola rumah tangga tersebut menuntut wanita untuk dapat mengalokasikan waktu secara proporsional pada kedua peran tersebut. Tujuan penelitian ini adalah untuk mengetahui kecenderungan tenaga kerja wanita berstatus kawin di Indonesia untuk bekerja lebih dari 40 jam dalam seminggu menggunakan data Survei Ketenagakerjaan Nasional (Sakernas) tahun 2014. Pada penelitian ini terdapat 66.702 wanita berstatus kawin yang bekerja pada saat pencacahan, di mana 35% di antaranya bekerja lebih dari 40 jam dalam seminggu. Metode yang digunakan dalam penelitian ini adalah analisis deskriptif dan analisis regresi logistik biner. Hasil penelitian menunjukkan bahwa kecenderungan wanita kawin untuk bekerja lebih dari 40 jam dalam seminggu lebih tinggi pada (1) wanita yang berusia lebih muda, (2) memiliki tingkat pendidikan lebih rendah, (3) tinggal di daerah perkotaan, (4) memiliki ukuran rumah tangga lebih kecil, (5) tidak memiliki anak usia prasekolah, (6) tidak memiliki anak usia sekolah, (7) memiliki anggota rumah tangga dewasa, (8) bekerja dengan status sebagai karyawan atau wirausaha, dan (9) memiliki pasangan yang bekerja. Berdasarkan hasil ini, kami menyarankan bahwa (1) pemberdayaan perempuan melalui peningkatan pendidikan harus lebih dimajukan lagi dan (2) pencapaian program keluarga berencana, yaitu mewujudkan norma keluarga kecil merupakan faktor penting untuk memaksimalkan partisipasi wanita kawin dalam pasar kerja.Kata kunci: jam kerja, regresi logistik, sakernas ABSTRACT: Married-women have a dual role as a breadwinner and a household manager. The dual roles ……..The objective of the study is to examine the likelihood of married-women in Indonesia to work more than 40 hours a week using the 2014 Labor Force Survey (LFS) data. Among 66,702 married-women who worked within one week prior to enumeration, 35% worked more than 40 hours a week. The result showed that the likelihood of married-women to work more than 40 hours a week is higher among women who are (1) at younger age, (2) have lower educational level, (3) live in urban areas, (4) have smaller household size, (5) have no preschool-age children, (6) have no school-age children, (7) have adult household members, (8) work as employee or self-employment, and (9) have working spouse. Based on these results, we suggest that (1) women's empowerment through increasing educational level should be more advanced further and (2) the achievement of family planning programs, which realize small family size norm is an important factor to maximize married-women participation in labor market.Keywords: working hours, logistic regression, labor force survey (Sakernas)
Pemodelan Geographically Weighted Regression pada Tingkat Pengangguran Terbuka di Pulau Jawa Tahun 2020 Septiyana, Alya Nur; Fatkhurrohman, Ikbal; Fikri, Fajriana Fadhlul; S, Riabela; Prananggalih, Ahmad Tegar; Bachtiar, Aji Bagus; ML, Dhitasya Salsabila; Berliana, Sarni Maniar
Seminar Nasional Official Statistics Vol 2023 No 1 (2023): Seminar Nasional Official Statistics 2023
Publisher : Politeknik Statistika STIS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34123/semnasoffstat.v2023i1.1789

Abstract

Geographically Weighted Regression (GWR) is a regression model that takes into account spatial effects in modeling the relationship between the response variable and the independent variable due to spatial heterogeneity in the data studied. The unemployment rate by regency/municipality in Java Island shows spatial heterogeneity so that the GWR modeling appropriate to be applied in determining the factors that influence the unemployment rate. The results show that the number of residents, the number of workers in the agricultural sector, the regional minimum wage, the mean years of schooling, and the labor force participation rate have different effects for different locations, while domestic investment has no significant effect on the unemployment rate either globally as well as locally. The application of the GWR model is better than the ordinary regression model based on the Akaike information criterion.
Aplikasi Model Spatial Autoregressive untuk Analisis Prevalensi Balita Underweight di Jawa Tengah Tahun 2021 Alwanti, Natasya; Berliana, Sarni Maniar; Ayuningtyas, Agian Dila; Simbolon, Rosarina Debesti Tirdvalen; Nafiis, Faried Akbar; Pradiptha, I Gede Nyoman Setya; Rangkuti, Suifatiha
Seminar Nasional Official Statistics Vol 2023 No 1 (2023): Seminar Nasional Official Statistics 2023
Publisher : Politeknik Statistika STIS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34123/semnasoffstat.v2023i1.1893

Abstract

Underweight is a form of nutritional disorder caused by an imbalance between the body's needs and nutrient intake. Underweight is more vulnerable to children under the age of five. Central Java is one of the provinces that has the highest prevalence of underweight children among other provinces on the island of Java. This study aims to determine the factors that influence the prevalence of underweight in Central Java in 2021 by considering spatial effects using data from the Central Java Health Service in 2021, the Central Java BPS in 2021, and the Central Java Data Portal in 2021. The model used in this study this is a spatial autoregressive model (SAR). The SAR model obtained shows that the percentage of infants with low birth weight, the percentage of children with complete immunization, the percentage of antenatal care visits according to program recommendations and the percentage of children under five weighed significantly affect the prevalence of underweight.
Spatial Dependencies in Environmental Quality: Identifying Key Determinants Samosir, Omas Bulan; Karim, Rafidah Abd; Fauzi, M. Irfan; Berliana, Sarni Maniar
Jurnal Aplikasi Statistika & Komputasi Statistik Vol 16 No 2 (2024): Jurnal Aplikasi Statistika & Komputasi Statistik
Publisher : Politeknik Statistika STIS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34123/jurnalasks.v16i2.802

Abstract

Introduction/Main Objectives: Environmental quality is essential to human development because it reflects the condition of our natural surroundings. Background Problems: Understanding the determinants of environmental quality is crucial for Indonesia as it helps identify the key factors influencing environmental quality. Novelty: This study seeks to identify the determinants of environmental quality in regencies and municipalities on Java Island, incorporating spatial effects into the analysis. Research Methods: The dependent variable is environmental quality index. The independent variables are GRDP in industrial sector, GRDP in agricultural sector, urban population rate, population density, and poverty rate. We applied spatially lag regression model using contiguity spatial weight matrix. Finding/Results: This study shows the spatially lag regression model outperforms the OLS model. GRDP in the industrial sector, GRDP in the agricultural sector, urban population rate, and population density have negative effects, suggesting the increases in these variables were associated with lower environmental quality.
A MACHINE LEARNING FRAMEWORK FOR SUICIDAL THOUGHTS PREDICTION USING LOGISTIC REGRESSION AND SMOTE ALGORITHM Berliana, Sarni Maniar; Samosir, Omas Bulan; Karim, Rafidah Abd; Valenzuela, Victoria Pena; Wahyuni, Krismanti Tri; Alfian, Andi
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 19 No 2 (2025): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol19iss2pp1409-1420

Abstract

Suicide, a global health challenge identified in Goal 3 of the global agenda for enhancing worldwide well-being, demands urgent attention. This study focused on predicting suicidal thoughts using machine learning, leveraging the 2021 National Women's Life Experience Survey (SPHPN) involving women aged 15 to 64. Analyzing 11,305 ever-married women, 504 (4.5%) reported experiencing suicidal thoughts. The outcome variable was binary (1 for suicidal thoughts, 0 for none). The study used seven predictors: age, education level, residence type, physical and sexual violence, smoking frequency, alcohol consumption, and depression. Ordinary logistic regression and SMOTE-based logistic regression were applied. The former identified physical violence, depression, and sexual violence as crucial factors, while the latter emphasized physical violence, sexual violence, and age. In cases of class imbalance, the SMOTE-enhanced model exhibited improved performance in terms of sensitivity, false positive rate, balanced accuracy, and Kappa statistic, with lower standard errors of parameter estimates. The findings highlight the importance of addressing violence and mental health in policies aimed at reducing suicidal thoughts among women. Policymakers can use these insights to develop targeted interventions, and healthcare providers can identify high-risk individuals for timely interventions. Community programs and public health campaigns should promote mental well-being and prevent suicidal behaviors using these findings. Future research should include more predictors, diverse populations, and longitudinal data to better understand causal relationships and timing. Interdisciplinary collaboration and advanced machine learning techniques can enhance predictive accuracy and model interpretability.
MODELING FACTORS AFFECTING EDUCATED UNEMPLOYMENT ON JAVA ISLAND USING GEOGRAPHICALLY WEIGHTED POISSON REGRESSION MODEL Wicaksono, Ditto Satrio; Nuriyah, Sinta; Fajritia, Rahajeng; Yuniarti, Ni Putu Nita; Priatmadani, Priatmadani; Amelia, Laeli; Berliana, Sarni Maniar
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 18 No 1 (2024): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol18iss1pp0615-0626

Abstract

The eighth goal of the SDGs, which aim to promote sustained, inclusive and sustainable economic growth, full and productive employment and decent work for all, addresses the problem of unemployment. Indonesia, the fourth-largest country in the world, keeps on dealing with unemployment and its negative consequences. Three provinces on the island of Java have higher unemployment rates for educated people than any other provinces. The purpose of this study is to examine the variables affecting educated unemployment in Java. This study uses cross-sectional data published from BPS-Statistics Indonesia website and the Indonesia Investment Coordinating Board (BKPM) for 119 regencies/cities across six provinces on Java Island in 2021. The predictor variables are Gross Regional Domestic Product (GRDP), investment, labor force participation rate, mean years of schooling, regency/city minimum wage, and inflation. The number of working-age population is used as an exposure measure. Four models were used to analyze the factors affecting educated unemployment on Java Island: Poisson regression model and Geographically Weighted Poisson Regression (GWPR) model, both with and without an exposure. Based on the smallest AIC/AICc, the best model is the GWPR model with an exposure. This model creates 11 groups of locations based on the same predictor variables that significantly affect educated unemployment
Determinan Perilaku Swamedikasi Penduduk Jawa Tengah Utomo, Agung Priyo; Syahida, Inayati; Berliana, Sarni Maniar; Samosir, Omas Bulan; Sugiarto, Sugiarto
Jurnal Ekonomi Kependudukan dan Keluarga Vol. 2, No. 1
Publisher : UI Scholars Hub

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Abstract

Self-medication has been practiced globally for thousands of years. As a part of primary healthcare services, self-medication forms the cornerstone of a sustainable healthcare system supporting universal health coverage, which is targeted in Sustainable Development Goal 3 (SDG 3), target 3.8. This study aims to provide an overview of self-medication behaviors and the factors influencing them among residents of Central Java Province. Using data from the 2021 National Socio-Economic Survey provided by the BPS-Statistics Indonesia, the sample size of this study includes 19,998 individuals, with 82.1% engaging in self-medication. The prevalence of self-medication is higher among males (84.0%) compared to females (80.6%). Self-medication is more common among individuals who are employed, live in rural areas, are unmarried, do not have health insurance, use the internet, are not poor, or have health complaints that do not interfere with daily activities, compared to their corresponding counterparts. The proportion of self-medication decreases with increasing age or higher education levels. Further binary logistic regression analysis identifies that the propensity for self-medication is higher among males (OR=1.16; 95% CI: 1.07-1.26), employed individuals (OR=1.40; 95% CI: 1.30-1.52), unmarried individuals (OR=1.17; 95% CI: 1.07-1.28), those without health insurance (OR=1.32; 95% CI: 1.20-1.44), the poor (OR=1.16; 95% CI: 1.02-1.31), those with health complaints that do not disrupt daily activities (OR=1.54; 95% CI: 1.43-1.66). The government needs to provide education and information regarding safe and responsible self-medication practices to at-risk groups, such as those with lower education levels, those without health insurance, and the poor, to maximize the benefits of self-medication and minimize the negative impacts of self-medication behaviors.
Co-Authors Agung Priyo Utomo Alfian, Andi Alwanti, Natasya Amelia, Laeli Ayuningtyas, Agian Dila Bachtiar, Aji Bagus Dwi Sulistiarini, Dwi Fajritia, Rahajeng Fatkhurrohman, Ikbal Fauzi, M. Irfan Fikri, Fajriana Fadhlul Karim, Rafidah Abd ML, Dhitasya Salsabila Nafiis, Faried Akbar Nuriyah, Sinta Pradiptha, I Gede Nyoman Setya Prananggalih, Ahmad Tegar Priatmadani, Priatmadani Purbasari, Lukmi Ana Rangkuti, Suifatiha S, Riabela Samosir, Omas Bulan Septiyana, Alya Nur Simbolon, Rosarina Debesti Tirdvalen Sugiarto S Syahida, Inayati Valenzuela, Victoria Pena Wahyuni, Krismanti Tri Wicaksono, Ditto Satrio Yuniarti, Ni Putu Nita