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All Journal CAUCHY: Jurnal Matematika Murni dan Aplikasi BAREKENG: Jurnal Ilmu Matematika dan Terapan
Zhafira, Azizah Atsariyyah
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Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Energy Engineering Mathematics Mechanical Engineering Physics Transportation

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Modelling Factors Affecting the Middle Income Trap in Indonesia Using Generalized Additive Models (GAM) Amelia, Dita; Suliyanto, Suliyanto; Zhafira, Azizah Atsariyyah; Ramadhanti, Aulia; Suyono, Billy Christandy; Hizbullah, Firqa Aqila
CAUCHY: Jurnal Matematika Murni dan Aplikasi Vol 11, No 1 (2026): 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.v11i1.35119

Abstract

Indonesia is currently facing a significant challenge known as the Middle Income Trap (MIT), a condition where economic growth stagnates after reaching middle-income status, hindering progress toward becoming a high-income country. This study aims to identify and model the socio-economic factors influencing MIT at the provincial level in Indonesia during the 2020–2023 period. The Generalized Additive Model (GAM) is employed to estimate nonlinear relationships between predictors and the response variable while capturing complex patterns in panel data. GRDP per capita is used as an indicator of MIT, with six predictor variables: life expectancy, poverty rate, informal employment share, secondary education completion rate, food insecurity prevalence, and population density. The results showed that the best model was obtained based on the minimum GCV and AIC values of the Gaussian family with an identity link function and 5 knot points with the highest correlation of 99,9%. Five variables show nonlinear effects, while food insecurity exhibits a significant negative linear impact. The findings provide a valuable reference for designing inclusive and adaptive eco nomic policies based on each region’s socio-economic characteristics to mitigate MIT risks and also supports the achievement of Sustainable Development Goal (SDG) 8, which promotes decent work and sustained economic growth.
SPATIAL EXTRAPOLATION OF MALARIA CASES IN CENTRAL PAPUA USING CO-KRIGING BASED ON RAINFALL AND OBSERVATIONAL DATA FROM PAPUA PROVINCE Saifudin, Toha; Chamidah, Nur; Zhafira, Azizah Atsariyyah; Budijono, Gabriella Agnes; Sihite, Rivaldi; Baihaqi, Mochamad; Januarta, R. Arya
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 20 No 2 (2026): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol20iss2pp1485-1500

Abstract

Malaria is an infectious disease that remains a significant health burden in Indonesia, particularly in Papua Province. This province has the highest malaria incidence rate nationally, influenced by various environmental factors such as rainfall. This study aims to estimate the number of malaria cases in districts/cities of Central Papua Province that do not have direct observation data, by utilizing the Co-Kriging method based on rainfall as a secondary variable and malaria cases as a primary variable from Papua Province. The secondary data used in this study were obtained from the official website of the Badan Pusat Statistik (BPS) of Papua Province, which includes the number of malaria cases in districts/cities as well as rainfall data from meteorological stations in the same region, collected in 2023. Three types of semivariogram models-spherical, exponential, and gaussian-were used to select the best model through statistical evaluation using Mean Squared Error (MSE) and Mean Absolute Percentage Error (MAPE). The results showed that the Gaussian semivariogram model provided the most optimal prediction results with an MSE of 10.895 and an MAPE of 4.67%. The estimates show that malaria cases in Central Papua are relatively uniform, with the highest incidence in Puncak Jaya district (219/1000 population) and the lowest in Mimika district (211/1,000 population). This approach is expected to be an important tool in spatially based disease planning and control and support the achievement of Sustainable Development Goals (SDGs), especially goals 3 (Good Health and Well-Being) and 13 (Climate Action).
Co-Authors Baihaqi, Mochamad Budijono, Gabriella Agnes Dita Amelia Hizbullah, Firqa Aqila Januarta, R. Arya Nur Chamidah Ramadhanti, Aulia Sihite, Rivaldi Suliyanto Suliyanto Suyono, Billy Christandy Toha Saifudin