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All Journal CAUCHY: Jurnal Matematika Murni dan Aplikasi Jurnal Statistika dan Matematika (Statmat)
Putri, Nisa Akbarilah
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Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Mathematics Other

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Identification and Modelling Tuberculosis Incidence Risk Factors in West Java with Negative Binomial Mixed Model Random Forest Arisanti, Restu; Pontoh, Resa Septiani; Winarni, Sri; Putri, Nisa Akbarilah; Maurin, Stefany
CAUCHY: Jurnal Matematika Murni dan Aplikasi Vol 10, No 2 (2025): CAUCHY: JURNAL MATEMATIKA MURNI DAN APLIKASI
Publisher : Mathematics Department, Universitas Islam Negeri Maulana Malik Ibrahim Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18860/cauchy.v10i2.29750

Abstract

Tuberculosis (TB) remains a major public health problem in many parts of the world, including in West Java Province, Indonesia. By guiding targeted medication, an accurate assessment of TB risk factors can enhance overall efforts to control tuberculosis. This study introduces modelling by integrating Negative Binomial Mixed Models (NBMM) and Random Forest (RF) called the Negative binomial mixed model random forest (NBMMRF) model.  This model is used to identify and assess risk factors associated with the incidence of tuberculosis. First, utilized NBMM to add fixed effects and random effects in the model and compensate for overdispersion. Modelling count data with overdispersion is a crucial problem in epidemiological studies, and the NBMM component in this model provides a flexible. Afterward, we include a Random Forest component in the model, which helps us detect relevant predictive features and change model weights accordingly. The resulting Negative Binomial Mixed Model Random Forest (NBMMRF) has a high accuracy value of up to 0.915. In contrast to simpler models, the NBMMRF model can capture complex and nonlinear interactions between predictors and outcomes.
Multidimensional Scaling Analysis Based on Factors Affecting Under-Five Malnutrition Cases in West Java Rachman, Hallen Naafi Aliya; Putri, Nisa Akbarilah; Hendrawati, Triyani
STATMAT : JURNAL STATISTIKA DAN MATEMATIKA Vol 7 No 1 (2025)
Publisher : Math Program, Math and Science faculty, Pamulang University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32493/sm.v7i1.46533

Abstract

Malnutrition is a condition where the body's nutrition is below the average standard. Nutritional issues, particularly among toddlers, remain a serious problem in various provinces in Indonesia, including West Java. In 2022, 3.3% of toddlers in West Java experienced undernutrition, and 0.4% suffered from severe malnutrition. This study aimed to map 27 regencies/cities in West Java Province based on factors influencing toddler malnutrition in 2022, highlighting similarities among these areas. A statistical method, Multidimensional Scaling (MDS), was used to classify objects based on similar characteristics. This method illustrated the dispersion of observational units based on measured variables, creating a two-dimensional map. Nearby regencies/cities indicated similar malnutrition conditions among toddlers, suggesting that the same mitigation efforts could be applied in those areas. The analysis resulted in four quadrants. Red circles were used on the map to mark points that were very close. To test the validity, STRESS and R-Square values were calculated. The STRESS value of 0.012% indicates that the generated map is in the perfect category, demonstrating that this analysis has precise reliability and validity. The R-Square value of 99.76% shows that the variance of the data is well explained by the model. This indicates that the Multidimensional Scaling (MDS) model is acceptable for mapping purposes. The findings of this study serve as valuable information and a reference for the West Java provincial government to make more effective and targeted efforts in combating malnutrition.
Co-Authors Arisanti, Restu Hendrawati, Triyani Maurin, Stefany Rachman, Hallen Naafi Aliya Resa Septiani Pontoh Sri Winarni