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All Journal JURNAL MATEMATIKA STATISTIKA DAN KOMPUTASI Jurnal Ilmu Sosial dan Humaniora Jurnal Ketahanan Nasional Jurnal Ilmiah Pangabdhi Jurnal Sains Matematika dan Statistika JTAM (Jurnal Teori dan Aplikasi Matematika) Zeta - Math Journal J Statistika : Jurnal Ilmiah Teori Dan Aplikasi Statistika Jurnal Varian Jurnal ABDINUS : Jurnal Pengabdian Nusantara Inferensi Elastisitas Jurnal Ekonomi Pembangunan Journal of Mathematics Education and Science UNP Journal of Statistics and Data Science Eksponensial Jurnal Pendidikan Matematika Limits: Journal of Mathematics and Its Applications International Journal of Computing Science and Applied Mathematics-IJCSAM
Dita Amelia
Fakultas Sains Dan Teknologi, Universitas Airlangga
Humanities Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Engineering Environmental Science Industrial & Manufacturing Engineering Mathematics Social Sciences Other

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Assessment of Dietary Intervention Effects on Food Intake in Mus musculus using Repeated Measures ANOVA Suliyanto Suliyanto; Dita Amelia; Aini Divayanti Arrofah; Rindiani Ahmada Alisiah; Nuzulia Anida; Utsna Rosalin Maulidya
JTAM (Jurnal Teori dan Aplikasi Matematika) Vol 10, No 2 (2026): April
Publisher : Universitas Muhammadiyah Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31764/jtam.v9i4.32467

Abstract

The prevalence of type 2 diabetes, metabolic syndrome, along with obesity that causes disturbances in the body's metabolic processes are the main triggers of chronic liver disease or in scientific language called Non-Alcoholic Fatty Liver Disease (NAFLD), getting out of control. This makes managing this disease an increasingly serious global health challenge. One of the main factors influencing this condition is a high-fat diet and an unhealthy lifestyle. Therefore, evaluation of high-fat diet programs on metabolic parameters such as food intake patterns is important as a preventive measure. This study aims to analyze the differences in food intake levels with seven different types of dietary treatments for 28 days, which were tested on mice (Mus musculus) which have physiological and biochemical characteristics that almost resemble humans. The method used was analysis of variance (ANOVA) for longitudinal data to evaluate the dynamics of food consumption across diet groups and observation periods. The results showed that the type of dietary treatment significantly influenced food intake patterns over time, indicating that diet composition plays a crucial role in shaping eating behavior. These findings highlight the importance of both diet type and treatment duration in influencing consumption patterns. However, since this study has not yet identified the most effective dietary regimen, future research is recommended to investigate diet types with high variability, while considering additional factors such as age, sex, and physiological characteristics, as well as extending the observation period to better understand long-term impacts.
Modelling Consumer Price Index Effect on 10-year US Treasury Bond Yields using Least Square Spline Approach Julia Widiyanti; Safira Salsabila; Dwika Maya Harsanti; Dita Amelia; Marisa Rifada
JTAM (Jurnal Teori dan Aplikasi Matematika) Vol 10, No 1 (2026): January
Publisher : Universitas Muhammadiyah Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31764/jtam.v9i4.33020

Abstract

Inflation measured by the Consumer Price Index (CPI) is a critical indicator in the government bond market that directly affects the yields of long-term securities such as the 10-year US Treasury Bond. This study is an explanatory quantitative study that aims to examine the complex dynamics of this relationship using the nonparametric least square spline method. The analysis uses monthly CPI data from FRED and 10-year US Treasury bond yield data from Investing.com for the period 2013-2025. This method divides the data into simple polynomial segments that are smoothly connected at transition points (knots), enabling the modelling of nonlinear patterns without assuming an initial curve shape. The analysis results indicate that a first-degree polynomial spline model (piecewise linear) with three knots successfully represents the bond yield response to inflation shocks with R^2 = 86.48%. Model segmentation identified four regimes: (1) Post-crisis recovery phase, with a negative relationship driven by Fed monetary stimulus suppresing yields despite initial inflation emergence; (2) Policy normalization phase, with a positive relationship aligned with monetary tightening in response to moderate inflation; (3) During the COVID-19 pandemic, a negative relationship due to a surge in demand for safe-haven bonds despite rising inflation; (4) Post-pandemic, the relationship turned positive again following the Fed’s aggressive monetary tightening in response to high global inflation. These findings highlight the urgency of regime-based monitoring for investors and policymakers, while contributing concretely to SDG 8 (decent work and economic growth) through the facilitation of appropriate interest rate policies for sustainable macroeconomic stability, and supporting SDG 9 (industry, innovation, and infrastructure) through the identification of inflation patterns that strengthen shock-resistant infrastructure investment planning and financial innovation during turbulent economic transitions.
Comparative Analysis of Parametric and Nonparametric Methods in Modeling Under-Five Malnutrition Prevalence Across Indonesia Dita Amelia; Suliyanto; Adelia Putri Andini; Faya Najwatus Silma; Nafla Nara Yonay; Slavina; Dinnara Chairana Aisha
UNP Journal of Statistics and Data Science Vol. 4 No. 3 (2026): UNP Journal of Statistics and Data Science
Publisher : Departemen Statistika Universitas Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/ujsds/vol4-iss3/554

Abstract

Malnutrition prevalence among children under five in Indonesia varied widely across provinces in 2024, ranging from 8.70% to 37.00%. Addressing this issue supports the global Sustainable Development Goals (SDGs) agenda, particularly SDG 2 (Zero Hunger) and SDG 3 (Good Health and Well-being). While most studies rely on multiple linear regression, its strict assumption of linearity is often violated in practice. This study conducts a comparative analysis between multiple linear regression and nonparametric penalized spline regression to model the effects of professional-assisted deliveries, safe sanitation access, complete basic immunization, and households at risk of stunting across 36 Indonesian provinces. Cross-sectional data for 2024 from the Central Bureau of Statistics (BPS) were analyzed, using MSE, R², and GCV for model comparison. The multiple linear regression model yielded an MSE of 18.812 and an R²  of 53.03%. Conversely, the penalized spline model (second-order polynomial, three knot points, λ = 0.0004) achieved a substantially lower MSE of 2.653 and a higher R² of 92.31%, demonstrating its superior capability in capturing nonlinear patterns. Regarding predictor significance, both models consistently identified safe sanitation, complete basic immunization, and households at risk of stunting as influential factors. However, professional assisted deliveries showed no significant effect in the nonparametric model. These findings confirm that the penalized spline approach provides more accurate estimates and is better suited for modeling provincial level malnutrition determinants.
Comparison of Least Square Spline and Penalized Spline for Modeling Human Development Index Determinants Dita Amelia; Tyo Anugrah Putra; Slavina; Thareq Alexander Manggala Napitupulu; Layyin Gisvira; Nila Khoirun Naili Salam
UNP Journal of Statistics and Data Science Vol. 4 No. 3 (2026): UNP Journal of Statistics and Data Science
Publisher : Departemen Statistika Universitas Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/ujsds/vol4-iss3/555

Abstract

The Human Development Index (HDI) is a key indicator of national and regional development and supports the achievement of the Sustainable Development Goals (SDGs), particularly Goal 1 (No Poverty) and Goal 4 (Quality Education). However, substantial disparities in HDI remain across Indonesia’s regencies and cities due to complex and nonlinear socioeconomic relationships that cannot always be captured by conventional parametric methods. This study analyzes the determinants of HDI in 514 regencies and cities in Indonesia in 2024 using nonparametric spline regression by comparing Penalized Spline and Least Square Spline estimators. The explanatory variables include mean years of schooling, labor force participation rate, percentage of senior-high-school graduates, and poverty rate. Secondary data from BPS were analyzed through spline basis construction, smoothing parameter selection using Generalized Cross Validation (GCV), parameter estimation, significance testing, and residual diagnostics. The results show that all predictors have nonlinear relationships with HDI. Mean years of schooling and the percentage of senior-high-school graduates positively affect HDI, whereas labor force participation and poverty rate have negative effects. The second-order Penalized Spline model with four knot points achieved the best performance, yielding the lowest GCV (5.388838), the lowest MSE (4.948574), and the highest adjusted R² (86.94%). Residual diagnostics confirmed normality and zero mean but indicated autocorrelation, suggesting spatial dependence. Overall, Penalized Spline regression provides a flexible and accurate approach for modeling HDI determinants and informing evidence-based regional development policy.
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.
Co-Authors Abdillah, Adrian Wahyu Addina Nurkamila Adelia Frielady Yosifa Adelia Frielady Yosifa Adelia Putri Andini Adelia Sukma Dwiyanto Aditya Syarifudin Akbar Adma Novita Sari Aflaha, Nabila Shafa Agnes Happy Julianto Agnes Happy Julianto Ain, Dzuria Hilma Qurotu Aini Divayanti Arrofah Aini Divayanti Arrofah Alya Rahma Inneztiana Ameliatul 'Iffah Ana, Elly Andi Vania Ghalliyah Putrie Anida, Nuzulia Anisa Laila Azhar Anisah Nabilah Ghasani Annisa Putri Nayumi Antonio Nikolas Manuel Bonar Simamora Aprilia Prastyaningrum Ardi Kurniawan Ariyawan, Jovansha Aulia Ramadhanti Aulia, Niswa Faizah Azizah Atsariyyah Zhafira Azzah Nazhifa Wina Ramadhani Azzah Nazhifa Wina Ramadhani Bintang Alyaa Sabila Bryan Given Christiano Ginzel Budijono, Gabriella Agnes Cynthia Anggelyn Siburian Davina Shafa Vanisa Deby Victoria Deshinta Arrova Dewi Dinda Rahma Alya Dinnara Chairana Aisha Doni Muhammad Fauzi Dwi Syarifatun Nisya’ Dwika Maya Harsanti Dwitya, Shabrina Nareswari Dwiyanto, Adelia Sukma Dwiyanto, Adelia Sukma Elly Pusporani Faradilla Harianto Farah Fauziah Putri Faya Najwatus Silma Fery Yulian Putra Firda Aulia Pratiwi Fortunata, Regina Ghasani, Anisah Nabilah Grace Lucyana Koesnadi Hanny Valida Humaira, Edla Putri Ismi, Ferissa Maulida Isna Nurul Izza Amalia Julia Widiyanti Karina Rubita Makhbubah Karina Tri Handayani Kurniawan, Ardi Kusuma, Shalwa Oktavia Layyin Gisvira M. Fariz Fadillah Mardianto M. Nabil Saputra Made Riyo Ary Permana Mahadesyawardani, Arinda Marbun, Barnabas Anthony Philbert Maria Setya Dewanti Marisa Rifada Marthabakti, CitraWani Mochammad Baihaqi Muhammad Fikry Al Farizi Muhammad Hafidzuddin Nahar Muhammad Rizaldy Baihaqi Muhammad Rosyid Ridho Az Zuhro Muhammad Rosyid Ridho Az Zuhro Muhammad Walid Jumlat Mutyaravica, Astrid Na'imatul Lu'lu'a Nabila Rahma Na’ifa, Ariza Nadia Dwi Marwanda Nafla Nara Yonay Nahar, Muhammad Hafidzuddin Nike Meliana Rahmawati Nila Khoirun Naili Salam Nur Chamidah Nurdin, Nabila Nurrohmah, Zidni ‘Ilmatun Nuzulia Anid Nuzulia Anida Pambudi, Daffa Satrio Permana, Made Riyo Ary Pratama, Fachriza Yosa Pressylia Aluisina Putri Widyangga Previan, Anggara Teguh Putri Masyita Qomaryah Putri Nur Farida Putri, Ferdiana Friska Rahmana Putri, Refa Berliana Putu Eka Andriani Rafly Tawekal Rahmada, Indrastanto Oktodian Ramadhan, Achmad Wahyu Ramadhani, Azzah Nazhifa Wina Ramadhani, Maulana Syah Putra Rani, Lina Nugraha Rindiani Ahmada Alisiah Rohayah, Dewi Safira Salsabila Sanda Insania Dewanty Sediono, Sediono Siagian, Kimberly Maserati Siregar, Naufal Ramadhan Al Akhwal Slavina Sofia Andika Nur Fajrina Suliyanto Suliyanto Suliyanto Suryono, Alda Fuadiyah Syavrilia Alfiatur Rakhma Tagawa, Dustin Nathanael Thareq Alexander Manggala Napitupulu Toha Saifudin Tsabita Amalia Shofa, Nayla Tyo Anugrah Putra Utsna Rosalin Maulidya Victoria Anggia Alexandra Victoria Anggia Alexandra Wibawa, Yoga Setya Wieldyanisa, Ezha Easyfa Wulandari, Indana Zulfa Yanuar Ibnu Ridho Yoga Setya Wibawa Yosifa, Adelia Frielady Yuliati, Intan Zah, Alfian Iqbal Zahrani, Vista Vanadya Zhafirab, Azizah Atsariyyah