OPTIMALISASI PENGAMBILAN KEPUTUSAN DENGAN METODE  SIMPLE ADDITIVE WEIGHTING (SAW) UNTUK SELEKSI PENYEBAB DEMAM BERDARAH

T. Irfan Fajri; Novia Hasdyna

doi:10.46576/syntax.v5i2.5538

OPTIMALISASI PENGAMBILAN KEPUTUSAN DENGAN METODE SIMPLE ADDITIVE WEIGHTING (SAW) UNTUK SELEKSI PENYEBAB DEMAM BERDARAH

T. Irfan Fajri, Novia Hasdyna

Abstract

Demam berdarah dengue (DBD) merupakan salah satu masalah kesehatan masyarakat yang signifikan di Indonesia, terutama dalam menentukan faktor risiko utama yang memengaruhi penyebarannya. Pendekatan konvensional dalam seleksi penyebab DBD sering kali mengandalkan analisis deskriptif dan pengambilan keputusan manual, yang cenderung memakan waktu dan rentan terhadap subjektivitas. Oleh karena itu, penelitian ini mengaplikasikan metode Simple Additive Weighting (SAW) untuk mengoptimalkan pengambilan keputusan berbasis data dalam seleksi faktor risiko DBD. Metode SAW memungkinkan evaluasi multikriteria, melibatkan kondisi lingkungan, perilaku masyarakat, dan data epidemiologis, dengan bobot yang ditentukan secara sistematis berdasarkan relevansi tiap kriteria. Studi ini menggunakan data kasus DBD dari wilayah tertentu, memanfaatkan proses normalisasi dan perhitungan agregasi bobot untuk mengidentifikasi faktor dominan. Hasil penelitian menunjukkan bahwa metode SAW mampu meningkatkan akurasi seleksi faktor risiko hingga 92%, serta mempercepat proses analisis secara signifikan dibandingkan pendekatan sebelumnya. Dengan demikian, metode SAW menjadi alat pendukung keputusan yang efektif, relevan, dan dapat diadaptasi dalam strategi mitigasi risiko DBD.

Kata Kunci: Demam Berdarah, Pengambilan Keputusan, Simple Additive Weighting (SAW), Faktor Risiko, Mitigasi Risiko.

ABSTRACT

Dengue fever (DF) remains a significant public health challenge in Indonesia, particularly in identifying the key risk factors influencing its spread. Conventional approaches to determining DF risk factors often rely on descriptive analysis and manual decision-making processes, which are time-consuming and prone to subjectivity. To address these limitations, this study implements the Simple Additive Weighting (SAW) method to optimize data-driven decision-making in selecting DF risk factors. The SAW method facilitates multi-criteria evaluation, incorporating environmental conditions, community behavior, and epidemiological data, with systematically assigned weights based on the relevance of each criterion. Using DF case data from specific regions, this study applies normalization processes and weight aggregation calculations to identify dominant risk factors. The findings reveal that the SAW method improves the accuracy of risk factor selection by up to 92% while significantly accelerating the analytical process compared to conventional approaches. Consequently, the SAW method serves as an effective, reliable, and adaptable decision-support tool for mitigating DF risk.

Keywords: Dengue Fever, Decision-Making, Simple Additive Weighting (SAW), Risk Factors, Risk Mitigation.

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DOI: https://doi.org/10.46576/syntax.v5i2.5538