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SPATIAL INTERPOLATION OF RAINFALL INTENSITY IN JAVA ISLAND USING ORDINARY KRIGING Auliyazhafira, Shabira A.; Putri, Fariza A.; Nauli, Theresia S.; Al Madani, Aulia R.; Jaya, I Gede Nyoman Mindra; Falah, Annisa N.; Ruchjana, Budi Nurani
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 19 No 3 (2025): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol19iss3pp1791-1804

Indonesia, situated between two continents and two oceans, experiences a complex climate system influenced by global warming. Climate change has disrupted weather patterns, making it increasingly difficult to predict the rainy and dry seasons and rainfall intensity. However, neighboring regions often exhibit similar weather characteristics, which can be leveraged for prediction. As Indonesia’s economic center, Java Island displays distinct yet interconnected weather patterns, making accurate rainfall prediction crucial for various sectors. This study utilizes 10 years of average rainfall data from NASA’s Power database, covering 64 observation points across Java. Ordinary point kriging is the estimation of a value at a given point and is often used in spatial interpolation analysis in general. Through ordinary point kriging analysis, this study aims to find an accurate kriging equation for predicting rainfall in various regions of Java Island. To achieve this, semivariogram modeling was performed to determine the best theoretical model for spatial interpolation. From 53 sampled regions, 1,378 sample pairs were used to calculate the experimental semivariogram obtained using the R programming language. Next, the theoretical semivariogram was determined using the sill parameter derived from the variance of the sampled data. Three theoretical semivariogram models were considered: spherical, exponential, and Gaussian. The results indicated that the exponential model was the most suitable as it had the smallest SSE value. The results of this analysis enrich our understanding of climate patterns in Indonesia and will contribute to developing mitigation and adaptation strategies related to climate change in the future. The Kriging equation obtained can provide highly accurate prediction results on the test data with a MAPE (Mean Absolute Percentage Error) error measure of 4.85% and RMSE (Root Mean Square Error) of 18.17, which indicates that the prediction results obtained are highly accurate predictions.

Community Participation and Mosquito Breeding Sites in Cimahi City: Current Conditions and Challenges in Dengue Fever Control Faridah, Lia; Angga, Anggisti Nurdinda Chaerany Putri; Fauziah, Nisa; Jaya, I Gede Nyoman Mindra
Global Medical & Health Communication (GMHC) Vol 13, No 1 (2025)
Publisher : Universitas Islam Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29313/gmhc.v13i1.14241

In 2021, Cimahi City recorded the 5th highest dengue fever (DF) cases among 27 districts/cities in West Java. Efforts to control DF have been going on for several decades, with one strategy being to involve community participation in eliminating mosquito breeding sites. This research evaluated community participation in Cimahi city by identifying mosquito breeding locations inside and outside the home. Samples were taken from 15 sub-districts in Cimahi city. The research population involved houses in 15 sub-districts, with a total sample of 1,560 houses representing each sub-district. Larval sampling was carried out in various water reservoirs, both natural and artificial, around residential areas. The successfully taken larvae were then identified and counted in the laboratory. The research showed that the most dominant mosquito breeding place was in bucket-type containers, namely 130 units (3.2%). Entomological data produced a free larva index (FLI) of 79.23%, a house index (HI) of 20.7%, a container index (CI) of 8.07%, and a Breteau index (BI) of 20.5%. This finding indicated a lack of community involvement in preventing vector-borne diseases by eliminating breeding sites. Cimahi city still had the potential to spread vector-borne diseases.

Community Participation and Mosquito Breeding Sites in Cimahi City: Current Conditions and Challenges in Dengue Fever Control Faridah, Lia; Angga, Anggisti Nurdinda Chaerany Putri; Fauziah, Nisa; Jaya, I Gede Nyoman Mindra
Global Medical & Health Communication (GMHC) Vol 13, No 1 (2025)
Publisher : Universitas Islam Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29313/gmhc.v13i1.14138

In 2021, Cimahi City recorded the 5th highest dengue fever (DF) cases among 27 districts/cities in West Java. Efforts to control DF have been going on for several decades, with one strategy being to involve community participation in eliminating mosquito breeding sites. This research evaluated community participation in Cimahi city by identifying mosquito breeding locations inside and outside the home. Samples were taken from 15 sub-districts in Cimahi city. The research population involved houses in 15 sub-districts, with a total sample of 1,560 houses representing each sub-district. Larval sampling was carried out in various water reservoirs, both natural and artificial, around residential areas. The successfully taken larvae were then identified and counted in the laboratory. The research showed that the most dominant mosquito breeding place was in bucket-type containers, namely 130 units (3.2%). Entomological data produced a free larva index (FLI) of 79.23%, a house index (HI) of 20.7%, a container index (CI) of 8.07%, and a Breteau index (BI) of 20.5%. This finding indicated a lack of community involvement in preventing vector-borne diseases by eliminating breeding sites. Cimahi city still had the potential to spread vector-borne diseases.

MODEL KOEFISIEN REGRESI VARIASI SPASIAL UNTUK PREDIKSI HOTSPOT STUNTING DI INDONESIA Ijonu, Ukhti Nurfajriah Sasmita; Jaya, I Gede Nyoman Mindra; Arisanti, Restu
Jurnal Penelitian Pendidikan IPA Vol 10 No 10 (2024): October
Publisher : Postgraduate, University of Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jppipa.v10i10.8270

Stunting is a significant issue, particularly in the context of Indonesia. Identifying crucial risk factors is crucial for mitigating and developing effective strategies to control stunting. A Bayesian approach was employed to develop a regression model that incorporates spatial variation, allowing risk factors to vary across different districts and cities. The aim was to obtain the most optimal regression model. The analysis revealed that the impact of immunization varies across districts and cities in Indonesia when it comes to explaining the differences in stunting prevalence. The hotspot prediction results indicate that most urban districts in Indonesia remain hotspot areas, with a stunting risk exceeding 20%. The government must ensure the effective implementation of the immunization program in order to mitigate the prevalence of stunting in Indonesia. The novelty of this research lies in the use of Bayesian approaches to spatial analysis in identifying and understanding stunting risk factors as well as the prediction of stunting hotspots in Indonesia. This approach provides in-depth insight into local variations in the prevalence of stunting and the effectiveness of health interventions, which supports more effective and targeted policy development.

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