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All Journal JURNAL MATEMATIKA STATISTIKA DAN KOMPUTASI
Anisah Nabilah Ghasani
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Mathematics

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Analysis of the Effects of Light Emitting Diode (LED) Phototherapy on the Hematological and Biochemical Parameters of Rabbits Using Repeated Measures Longitudinal ANOVA Dita Amelia; Suliyanto Suliyanto; Anisah Nabilah Ghasani; Nike Meliana Rahmawati; Dwi Syarifatun Nisya’; Dinda Rahma Alya
Jurnal Matematika, Statistika dan Komputasi Vol. 22 No. 3 (2026): May 2026
Publisher : Department of Mathematics, Hasanuddin University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20956/j.v22i3.49375

Abstract

This study examined the longitudinal effects of Light Emitting Diode (LED) phototherapy on hematological (hemoglobin) and biochemical (creatinine) parameters in rabbits (Oryctolagus cuniculus). Although LED phototherapy is widely applied as a non-invasive treatment, its systemic effects in repeated-measure settings remain limited. Fourteen rabbits were randomly assigned to a control group (n = 7) and a treatment group (n = 7). The treatment group received two 12-hour LED phototherapy sessions on consecutive days, while the control group underwent identical conditions without LED activation. Hemoglobin and creatinine levels were measured at three time points and analyzed using Repeated Measures ANOVA, with assumption testing for normality, homogeneity, and sphericity; Greenhouse–Geisser correction was applied when necessary. The results showed that observation time significantly affected hemoglobin (p = 0.004967) and creatinine levels (p = 0.03577), indicating temporal physiological changes that occurred regardless of treatment exposure. However, no significant differences were observed between the control and treatment groups for hemoglobin (p = 0.936) or creatinine (p = 0.357), and no significant group–time interaction was detected, suggesting that the observed changes were independent of LED phototherapy. Post-hoc pairwise comparisons based on estimated marginal means (EMMs) with Tukey adjustment revealed a significant increase in hemoglobin from time 0 to time 1 and a significant difference in creatinine between time 1 and time 2, further supporting that these variations reflect natural physiological processes rather than treatment-induced effects. These findings indicate a lack of evidence of treatment effect under the studied conditions, although the relatively small sample size warrants cautious interpretation. Future studies with larger samples are recommended.
CO2 Emission Modeling in Asian Countries Using a Truncated Spline Nonparametric Regression Approach on Panel Data Dita Amelia; Anisah Nabilah Ghasani; Salsabilla Rusydah Putri
Jurnal Matematika, Statistika dan Komputasi Vol. 23 No. 1 (2026): September 2026
Publisher : Department of Mathematics, Hasanuddin University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20956/yee72c02

Abstract

Climate change, driven by increasing carbon dioxide (CO₂) emissions, has become a major global challenge, with Asian countries contributing nearly 50% of total worldwide emissions. This study aims to model the factors affecting CO₂ emissions in Asian countries using a truncated spline nonparametric regression approach with panel data from 2020 to 2023. The predictor variables considered are population density, primary energy consumption, and urban population, while CO₂ emissions serve as the response variable. Optimal knot points were determined using the Generalized Cross Validation (GCV) criterion. The results indicate that the model with three knots provides the best performance, yielding a GCV value of 0.00004, a Mean Square Error (MSE) of 0.005248, and a coefficient of determination (R²) of 99.99206%. The findings reveal that differences in energy consumption patterns, industrialization levels, and dependence on fossil fuels contribute significantly to variations in CO₂ emissions among countries. The thematic map analysis further shows that high emissions are not always associated with high population density or urban population. Overall, the selected predictor variables explain almost all variations in CO₂ emissions across Asian countries. These findings provide a more comprehensive understanding of emission dynamics and offer valuable insights for the development of sustainable energy and environmental policies in the Asian region.
Co-Authors Dinda Rahma Alya Dita Amelia Dwi Syarifatun Nisya’ Nike Meliana Rahmawati Salsabilla Rusydah Putri Suliyanto Suliyanto