Development of Geographic Information System (GIS) Spread of The Dangerous Diseases in Jember District

Nugroho Setyo Wibowo, Khafidurrohman Agustianto, Eva Rosdiana, Syamsiar Kautsar, Hendra Yufit Riskiawan, Dwi Putro Sarwo Setyohadi

Abstrak


Jember has an area of 3,293.34 km2 with an altitude between 0 - 3.330 masl. Climate Jember Regency is tropical with temperature range between 23oC - 32oC. Such a climate Jember is  susceptible  to  tropical  diseases  such  as  Tuberculosis,  Diphtheria,  Pertussis,  Tetanus neonatorum, Leprosy, Dengue Haemorrhagic Fever (DHF), Measles, HIV-AIDS, Malaria and Filariasis. Potential diseases that may arise in an area to be a challenge for the parties concerned to prevent and to overcome, this is related to the readiness of personnel and medical materials, as well as coverage prevention or coverage of prevention. That conditions resulted in many GIS (Geographic Information System) researches to resolve the issue. GIS is used because it has the ability to properly visualize the spread, have good visual presentation of data that more easily analyzed, interpreted and arrange a prevention strategy or handling. This study aims to develop GIS spread of disease in Jember District. So with the GIS developed research hopes to be widely used either for the general public or the government to prepare a plan for prevention or treatment of disease in Jember District.

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Referensi


A. V. Vitianingsih, D. Cahyono, and A. Choiron, “Analysis and Design of Web-Geographic Information System for Tropical Diseases-Prone Areas: A Case Study of East Java Province, Indonesia,” in 2017 4th International Conference on Information Technology, Computer, and Electrical Engineering (

N. Guizani and A. Ghafoor, “Modeling and Evaluation of Disease Spread Behaviors,” 2014 Int. Wirel. Commun. Mob. Comput. Conf., pp. 996–1003, 2014.

C. Cao, G. Li, S. Zheng, and J. Cheng, “Research On The Environmental Impact Factors of Hand-Foot-Mouth Disease in Shenzhen, China using RS and GIS Technologies,” 2012, pp. 7240–7243.

Q. Cheng and S. Zhang, “Fuzzy Weights of Evidence Method Implemented in GeoDAS GIS for Information Extraction and Integration for Prediction of Point Events,” … Symp. 2002. IGARSS’02. 2002 IEEE …, vol. 00, no. C, pp. 2933–2935, 2002.

Z. A. Latif and M. H. Mohamad, “Mapping of Dengue Outbreak Distribution Using Spatial Statistics and Geographical Information System,” in 2nd International Conf on Information Science and Security, 2015, pp. 1–5.

I. S. Klyuzhin, E. Shahinfard, M. Gonzalez, and V. Sossi, “Feasibility of Using Geometric Descriptors of Tracer Distribution for Disease Assessment,” in 2014 IEEE Nuclear Science Symposium and Medical Imaging Conference, NSS/MIC 2014, 2016, pp. 1–5.

L. Guo, Z. Sun, L. Di, and L. Lin, “Spatial Distribution and Variation Analysis of Lyme Disease in The Northeastern United States,” 2016, pp. 2–5.

D. C. Robinson, S. Mohanty, J. Young, G. Jones, and D. Wesemann, “Novel Techniques for

Mapping Infectious Diseases Using Point of Care Diagnostic Sensors,” in Physics and

Technology of Sensors (

N. Mathur, V. S. Asirvadam, S. C. Dass, and B. S. Gill, “Visualization of Dengue Incidences

Using Expectation Maximization

X. Lu, “Web GIS Based Information Visualization for Infectious Disease Prevention,” in 2009

Third International Symposium on Intelligent Information Technology Application, 2009, pp.

–151.

a. Zhang, Q. Qi, and L. Jiang, “Design and Implementation of A Web-Based Disease Control

and Emergency Response System on CNGI for Mekong Subregion,” 2011, pp. 263–266.

W. Zeng, X. Liu, X. Cui, H. Cui, and P. Wang, “Remote Sensing and GIS for Identifying and

Monitoring The Environmental Factors Associated with Vector-Borne Disease: An verview,”

in International Geoscience and Remote Sensing Symposium (

P. Pattarakavin and K. Piromsopa, “Development of Epidemiology Data Map Visualization

System,” in Proceedings of the 9th International Conference on Electronics, Computers and

Artificial Intelligence, ECAI 2017, 2017, vol. 2017–Janua, pp. 1–6.

L. Yu, “Space-Time Dynamic Analysis of Global Bird Flu based on Internet and GIS,” 2010.


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