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Jurnal Biometrika dan Kependudukan (Journal of Biometrics and Population)
Published by Universitas Airlangga
ISSN : 2302707X     EISSN : 25408828     DOI : -
Core Subject :
Jurnal Biometrika dan Kependudukan is a journal that contains articles about the development of statistical methods in the field of health, the application of statistical methods on solving health problems, the development of demography and demography, solving reproductive health problems, solving the problems of maternal and child health as well as the themes surrounding the development of biostatistics and population. This journal is published twice a year in July and December.
Arjuna Subject : -
Articles 229 Documents
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FACTORS INFLUENCING MATERNAL MORTALITY IN EAST JAVA USING GENERALIZED POISSON REGRESSION Lully Hanni Endarini; Hardian Bimanto
Jurnal Biometrika dan Kependudukan Vol. 15 No. 1 (2026): JURNAL BIOMETRIKA DAN KEPENDUDUKAN
Publisher : Universitas Airlangga

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20473/jbk.v15i1.2026.117-127

Abstract

Elevated maternal mortality rates underscore the limited effectiveness of maternal health improvement efforts to date. In East Java Province, data from 2020 revealed more maternal deaths than the previous year. This increase was partly due to the COVID-19 pandemic, which limited antenatal care visits and made it harder to monitor high-risk pregnancies. This study set out to find the factors that influence maternal mortality in East Java. Researchers used district and city-level data from the 2020 East Java Provincial Health Report and analyzed it as secondary data. They applied Poisson regression analysis, and because the data showed overdispersion, they also used the Generalized Poisson Regression (GPR) model. The main variable studied was the number of maternal deaths (Y), while the independent variables were The availability ratio of healthcare workers (X₁), The rate of complications during obstetric care (X₂), and The availability of health centers (X₃). The results showed overdispersion in the maternal mortality data. Results from the Poisson regression model indicated that every independent variable significantly influenced maternal deaths. In the GPR model, only The availability ratio of healthcare workers (p=0.001) and The rate of complications during obstetric care (p=0.018) were statistically significant. The study determines that the Generalized Poisson Regression model is better for examining maternal mortality factors in East Java, as it fits the data more accurately, as shown by a lower AIC value.
DETERMINANTS OF HEALTH INSURANCE OWNERSHIP AMONG THE WORKING-AGE POPULATION IN EAST NUSA TENGGARA, 2023 Arista Marlince Tamonob; Anugrah Jordan; Farly Oktriany Haning; Ganesha Lapenangga Putra; Maria Lobo
Jurnal Biometrika dan Kependudukan Vol. 15 No. 1 (2026): JURNAL BIOMETRIKA DAN KEPENDUDUKAN
Publisher : Universitas Airlangga

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20473/jbk.v15i1.2026.44-51

Abstract

Universal Health Coverage (UHC) aims to ensure that all individuals have equitable access to quality and affordable health services. Although coverage under Indonesia’s National Health Insurance (Jaminan Kesehatan Nasional/JKN) program has continued to increase, disparities in health insurance ownership persist, particularly in less developed regions such as East Nusa Tenggara (Nusa Tenggara Timur/NTT) Province. Health insurance coverage in NTT remained below the national UHC target in 2023, especially among the working-age population. This study aims to evaluate the achievement of UHC in NTT Province based on health insurance ownership and to analyze factors associated with health insurance ownership among the working-age population using a binary logic regression approach. The results of this study demonstrate that age, education level, self-medication, outpatient or inpatient care, savings accounts ownership, and business sector are significantly associated with health insurance ownership (? − ????? ≤ 0.05) with the Nagelkerke R Square value of 3.8%. In contrast,  area of residence, gender, marital status, employment status, and health complaints were not significantly associated with health insurance ownership  (? −????? > 0.05). These findings are expected to provide evidence-based input for policymakers in designing more targeted strategies, particularly those focusing on education, financial access, and employment sectors, to increase health insurance coverage among the working-age population in regions with low UHC achievement.
THE INFLUENCE OF SOCIO-ECONOMIC FACTORS ON DISABILITY STATUS AMONG OLDER ADULTS IN INDONESIA Martha Budi Wardani; Febri Wicaksono
Jurnal Biometrika dan Kependudukan Vol. 15 No. 1 (2026): JURNAL BIOMETRIKA DAN KEPENDUDUKAN
Publisher : Universitas Airlangga

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20473/jbk.v15i1.2026.52-62

Abstract

Indonesia is currently experiencing population aging, characterized by an older adult population that exceeds 10 percent of the total population. The proprotion of older adults continues to increase each year and is expected to raise new challenges, particularly the rising prevalence of disability among older adults. Government health policies should address this issue and reduce the risk of disability among older adults. However, according to the BPS-Statistics Indonesia data between 2010 and 2022, the prevalence of disability among older adults has generally increased. This increase has the potential to place a greater burden on families, communities, and the state. Therefore, this study aimed to identify the socioeconomic factors associated with disability status among older adults in Indonesia. The study used data from the  2023 Indonesia’s National Socio-Economic Survey (SUSENAS), comprising a sample of 129,individuals aged 60 years and above. Binary logistic regression was employed for data analysis. The results showed that welfare level, age, gender, marital status, place of residence, and education level were significantly associated with disability status among older adults. These findings are expected to support preventive measures and early intervention efforts and assist the government ino developing effective policies and programs to promote healthy aging and reduce the prevalence of disability among older adults in the future.
ANALYSIS OF FACTORS ASSOCIATED WITH UNMET NEED FOR FAMILY PLANNING AMONG WOMEN OF REPRODUCTIVE AGE Sharfina Haslin; Dewi Risma Uli Br Bancin; Elisa Aritonang; Juneris Aritonang
Jurnal Biometrika dan Kependudukan Vol. 15 No. 1 (2026): JURNAL BIOMETRIKA DAN KEPENDUDUKAN
Publisher : Universitas Airlangga

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20473/jbk.v15i1.2026.97-104

Abstract

Unmet need for contraception is a significant demographic phenomenon that affects the success of family planning programs. A high prevalence of unmet need contributes to unintended pregnancies, which can adversely affect maternal and child health. This study aimed to analyze the factors associated with unmet need for family planning among women of reproductive age in Mekar Sari Village, Deli Serdang Regency. A quantitative cross-sectional design was employed. The study population consisted of 155 married women of reproductive age, from whom 61 respondents were selected using accidental sampling . Bivariate analysis using the chi-square test revealed significant associations between unmet need and family income (p=0.001), husband’s support (p=0.004), and women's knowledge (p=0.002). Among these variables, family income showed the strongest association with unmet need. These findings suggest that addressing economic, spousal support, and educational factors is essential for reducing unmet need among women of reproductive age. Efforts to reduce unmet need should therefore include strengthening family economic well-being, improving women's knowledge of contraception, and enhancing husband involvement in family planning programs.
PATIENTS' HEALTH HISTORY AND LIFE EXPERIENCES REGARDING HYPERTENSION CONTROL: THE MODERATING ROLE OF SELF-CARE AGENCY Fitriah Fitriah; Mustofa Haris; Rodiyatun Rodiyatun; Zakkiyatus Zainiyah
Jurnal Biometrika dan Kependudukan Vol. 15 No. 1 (2026): JURNAL BIOMETRIKA DAN KEPENDUDUKAN
Publisher : Universitas Airlangga

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20473/jbk.v15i1.2026.105-116

Abstract

Hypertension is a major cause of cardiovascular disease and premature death worldwide. This study aimed to analyze the influence of patient health history and life experiences on hypertension control moderated by self-care agency in fulfilling Activities of Daily Living (ADL). The study design was a cross-sectional observational analytical study. The independent variables were health history, life experiences, and the dependent variable was hypertension control. The sample was hypertension patients at the Heart Disease Clinic and Internal Medicine Clinic of Anna Medika Madura Hospital and Syamrabu Bangkalan Hospital. 200 patients were selected using purposive sampling for 2 months. Self-care agency data were collected using the Self-Care Agency Questionnaire (SCAQ), health history questionnaires, life experiences based on the development of WHO step instruments, and short-form health surveys. Hypertension control variables were measured using a manual sphygmomanometer and questionnaires. Data analysis used descriptive statistics and logistic regression. The results of the logistic regression statistical test showed an interaction between current medical history and self-care agency with p values = 0.004, OR: 3.439 CI: (1.44-8.26) and an interaction between life experience and self-care agency with p values = 0.012 <0.05, OR: 2.674, CI: (1.22-5.90), so the influence of health history on hypertension control becomes stronger if self-care agency is high. Likewise, self-care agency strengthens the relationship between life experience and hypertension control. Increasing self-care agency can strengthen the positive impact of health history and life experience on hypertension control.
PREVALENCE AND ASSOCIATED FACTORS OF ANEMIA AMONG PREGNANT WOMEN AT SANGKRAH COMMUNITY HEALTH CENTER IN SURAKARTA, CENTRAL JAVA: A CROSS-SECTIONAL STUDY Emma Anastya Puriastuti; Nur Anisah Rahmawati; Nina Rini Suprobo
Jurnal Biometrika dan Kependudukan Vol. 15 No. 1 (2026): JURNAL BIOMETRIKA DAN KEPENDUDUKAN
Publisher : Universitas Airlangga

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20473/jbk.v15i1.2026.63-73

Abstract

Pregnancy complications are often associated with anemia, which remains a critical public health problem, particularly in developing countries. Anemia during pregnancy increases the risk of adverse maternal and fetal outcomes, yet effective prevention remains a challenge. This study aimed to explore the prevalence and associated factors of anemia among pregnant women at the Sangkrah Community Health Center in Surakarta, Central Java, Indonesia. This cross-sectional study was conducted in 2025 and involved 96 pregnant women attending antenatal care, selected via purposive sampling. Data were collected using questionnaires and maternal and child health record books, covering sociodemographic, obstetric, and social-environmental factors. Data analysis was performed using descriptive and bivariate statistical tests. The results showed that the prevalence of anemia among pregnant women is 12.5%. Factors significantly associated with anemia were parity, abortion experience, number of living children, and history of blood transfusion (p<0.05). Conversely, other factors such as age, education, occupation, trimester, pregnancy spacing, history of previous births, previous birth complications, planned pregnancy, chronic diseases before pregnancy, drug allergies, Body Mass Indeks (BMI), drug consumption, history of relapse, family support, distance to health facilities, family reminders on supplement adherence, regular exercise and pregnancy information-seeking were significantly associated (p>0.05). These findings highlight the importance of monitoring maternal obstetric history and prior medical conditions as part of anemia prevention efforts during pregnancy. Strengthening antenatal care services and providing targeted Information, Education, and Communication (IEC) at the community health center level are essential to reduce the risk of anemia among pregnant women.
MODEL FOR PREDICTING PREVENTIVE BEHAVIOR AGAINST HYPERTENSION AMONG ISLAMIC STUDENTS USING MACHINE LEARNING APPROACH Ida Srisurani Wiji Astuti; Kuntoro Kuntoro; Mochammad Bagus Qomaruddin; Krish Naufal Anugrah Robby
Jurnal Biometrika dan Kependudukan Vol. 15 No. 1 (2026): JURNAL BIOMETRIKA DAN KEPENDUDUKAN
Publisher : Universitas Airlangga

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20473/jbk.v15i1.2026.33-43

Abstract

The prevalence of hypertension is currently increasing among adolescents. Despite numerous efforts to improve hypertension prevention, there are still limited approaches capable of accurately predicting hypertension prevention behaviors. Machine learning is needed to develop predictive models that can identify key predictors. This study aimed to develop and evaluate a machine learning model for predicting hypertension prevention behaviors among students in Islamic boarding schools. A cross-sectional design was employed in this study. Primary quantitative data were collected through validated questionnaires from 378 students, aged 15–18 years at three Islamic boarding schools in Jember, Indonesia. The data were analyzed using a machine learning approach involving data preprocessing, selection of indicator variables, and division of the dataset into training and testing datasets to develop and evaluate a predictive model of hypertension prevention behavior. The results showed that the machine learning–based predictive model of hypertension prevention behavior performed well, achieving an area under the curve (AUC) of 0.72, an accuracy of 95%, and a precision of 70%. The model identified competence, autonomy, and subjective norms as the main predictors and adequately distinguished between students with good and poor hypertension prevention behaviors. The machine learning approach performs better by providing a preprocessing phase, comprehensive model performance evaluation metrics, and new or previously unseen data to assess the model's generalizability. Future studies should extend the study to various settings and populations to improve generalizability. The predictive model can be used to predict hypertension prevention behavior using a number of independent variables.
THE INFLUENCE OF SPIRITUAL INTELLIGENCE ON COPING EFFORTS: THE MEDIATING ROLE OF COGNITIVE APPRAISAL AMONG PATIENTS WITH TYPE 2 DIABETES MELLITUS Kun Ika Nur Rahayu; Chatarina Umbul Wahyuni; Mochammad Bagus Qomaruddin; Muhammad Atoillah Isfandiari
Jurnal Biometrika dan Kependudukan Vol. 15 No. 1 (2026): JURNAL BIOMETRIKA DAN KEPENDUDUKAN
Publisher : Universitas Airlangga

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20473/jbk.v15i1.2026.74-85

Abstract

Diabetes mellitus requires lifelong treatment and imposes persistent psychological stress on patients. Spiritual intelligence (has been recognized as a psychological resource that promotes resilience and adaptation; however, the role of cognitive appraisal as a mechanism linking spiritual intelligence to coping remains unclear. This study aimed to examine the mediating role of cognitive appraisal in the relationship between spiritual intelligence and coping among patients with type 2 diabetes mellitus. A cross-sectional study was conducted among 300 patients with type 2 diabetes mellitus aged 30–50 years in Kediri, Indonesia. Data were collected using the Spiritual Intelligence Self-Report Inventory (SISRI-24), the Primary Appraisal Secondary Appraisal (PASA) scale, and the Brief COPE questionnaire. Path analysis with bootstrapping was performed to examine the mediating role of cognitive appraisal. Spiritual intelligence significantly predicted cognitive appraisal (β = 0.819, p < 0.001) and coping (β = 0.335, p < 0.001). Cognitive appraisal also positively predicted coping  (β = 0.425, p < 0.001) and partially mediated the relationship between spiritual intelligence and coping, accounting for 40.28% of the total effect. The model explained 31.7% of the variance in cognitive appraisal and 45.3% of the variance in coping. These findings suggest that interventions integrating spiritual intelligence and psychological dimensions by enhancing spiritual intelligence and strengthening cognitive appraisal may improve coping capacity, treatment adherence, and long-term self-management among patients with type 2 diabetes mellitus. Future longitudinal studies are recommended to establish causal relationships and investigate demographic and clinical factors that may moderate these associations.
MACHINE LEARNING-BASED PREDICTION OF BREAST CANCER RECURRENCE Nabila Shafiya; Soenarnatalina Melaniani; Ronny Isnuwardana; Sagar Tiwari; Sigit Ari Saputro
Jurnal Biometrika dan Kependudukan Vol. 15 No. 1 (2026): JURNAL BIOMETRIKA DAN KEPENDUDUKAN
Publisher : Universitas Airlangga

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20473/jbk.v15i1.2026.86-96

Abstract

Breast cancer recurrence remains a major cause of mortality among women worldwide. Early identification is essential for improving patient outcomes, and prediction modelling has emerged as an approach to support this objective. This study aimed to develop and compare machine learning models for predicting breast cancer recurrence. A retrospective secondary analysis was conducted on data from 286 patients in the University of California, Irvine (UCI) Machine Learning Repository. Nine predictors were used to develop logistic regression (LR), artificial neural network (ANN), and extreme gradient boosting (XGBoost) models. The dataset was split into training and testing sets using a 70:30 ratio. Model performance was evaluated using the area under the receiver operating characteristic curve (ROC-AUC), Brier score, and calibration analysis, with 95% confidence intervals estimated through bootstrap resampling. LR demonstrated the best discriminatory performance, achieving a test AUC of 0.790. In contrast, XGBoost and ANN showed lower generalization performance, with test AUCs of 0.727 and 0.748, respectively. LR also achieved the highest testing recall (0.731) and F1-score (0.623), indicating superior sensitivity for identifying recurrent cases. Meanwhile, XGBoost demonstrated the highest precision (0.727), accuracy (0.756), and calibration performance. The relatively small sample size and reliance on structured clinical predictors may have contributed to the superior performance of LR in this study. In conclusion, LR demonstrated the most reliable predictive performance for this dataset.  Future research should use larger, diverse datasets and incorporate a broader range of predictors, including imaging and genomic data, to optimize the benefits of more complex machine learning models.

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