Sistem Pendukung Keputusan Menentukan Peserta Jamkesmas Dengan Metode Simple Additive Weighting

  • Ardi Ardi Universitas Pembinaan Masyarakat Indonesia Medan
  • Dasril Aldo STMIK GICI Batam
  • Ahmadi Ahmadi STMIK Bina Nusantara Jaya Lubuklinggau
Keywords: Decision Support System, Decision, Simple Additive Weighting, Jamkesmas

Abstract

The government based on Article 28 of the 1945 Constitution provides health services to ensure access of the poor by issuing Jamkesmas. However, the Jamkesmas program currently has problems in determining the Jamkesmas recipient residents. Because in decision making there are still subjectivities and the selection process runs less quickly. As an auxiliary media in determining eligible participants to get Jamkesmas (Community Health Insurance) as well as testing the SAW method (Simple Additive Weighting) to provide recommendations for participants who deserve the Jamkesmas program. The selection process uses the SAW method for several criteria from BPS (Central Bureau of Statistics). Furthermore, the criteria are processed using an application built using php and mysql programming languages ​​to test these criteria. The processing stages are poverty criteria based on the condition of the residents in the form of Floor Area per Capita, Type of Floor, Availability of Clean Water, Latrine Type, Asset Ownership, Income, Expenditures, and Consumption of Side Dishes. The results of the decision stating that there was 1 participant, namely the total number of women with a total value of 0.475, was declared eligible because the mother was the number 1 out of 10 candidates selected using the SAW method. This system proved to be helpful in determining participants who were entitled and deserving of JAMKESMAS. And also this system is only a tool for decision makers, the final decision remains in the hands of decision makers.

 

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References

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Published
2019-08-01
How to Cite
Ardi, A., Aldo, D., & Ahmadi, A. (2019). Sistem Pendukung Keputusan Menentukan Peserta Jamkesmas Dengan Metode Simple Additive Weighting. Jurnal RESTI (Rekayasa Sistem Dan Teknologi Informasi), 3(2), 94 - 99. https://doi.org/10.29207/resti.v3i2.802
Section
Artificial Intelligence