Gambaran Pemberian Metode 20-20-20 Terhadap Penurunan Keluhan Gejala Computer Vision Syndrome (CVS) pada Pekerja Pengguna Komputer di PDAM Kota Makassar: Overview of the Effectiveness of the 20-20-20 Method on Reducing Symptoms of Computer Vision Syndrome (CVS) in Computer Users at PDAM Kota Makassar - Rahmadani, Rahmadani; Yusriani, Yusriani; Gafur, Abdul; Idris, Fairus Prihatin; Yuliati, Yuliati; S. , Ikhram Hardi (Postgraduate Program in Public Health, Universitas Muslim Indonesia, 2025)
ABSTRAK Latar Belakang: Berdasarkan data World Health Organization (WHO) sekitar 2,2 miliar orang mengalami gangguan penglihatan jarak dekat atau jarak jauh. Data American Optometric Association Tahun 2023 kondisi utama yang menyebabkan gangguan penglihatan jarak jauh atau kebutaan adalah katarak (94 juta), kelainan refraksi (88,4 juta), degenerasi makula terkait usia (8 juta), glaukoma (7,7 juta), retinopati diabetik (3,9 juta). Prevalensi Computer Vision Syndrome (CVS) mencapai 64-90% dengan jumlah penderita di seluruh dunia diperkirakan sebesar 60 juta orang dan setiap tahun muncul 1 juta kasus baru. Tujuan: Untuk menganalisis Pengaruh Intervensi Metode 20-20-20 Terhadap Kejadian Computer Vision Syndrome (CVS) pada Pekerja Pengguna Komputer di PDAM Kota Makassar. Metode: Penelitian ini menggunakan jenis penelitian kuantitatif dengan desain penelitian Quasi Eksperimen dengan pendekatan Pre-Post Test with Control Group Design. Teknik pengambilan sampel menggunakan teknik purposive sampling dengan jumlah kelompok eksperimen 22 responden dan kelompok kontrol 22 responden di PDAM Kota Makassar. Data penelitian dianalisis dengan uji Independent Sample T-Test dengan tingkat kepercayaan 95% (α=0,05). Hasil: Hasil uji Independent Sample T-Test menunjukkan terdapat perbedaan yang signifikan keluhan gejala Computer Vision Syndrome (CVS) antara kelompok eksperimen dan kelompok kontrol dengan nilai signifikan ρ = 0,000 (< 0,05). Saran: Diharapkan untuk instansi menerapkan metode 20-20-20 sebagai bagian dari kebijakan Kesehatan dan Keselamatan Kerja (K3) dan pekerja diharapkan secara mandiri dan konsisten menerapkan metode 20-20-20 untuk mencegah berkembangnya Computer Vision Syndrome (CVS) serta menjaga kesehatan mata selama bekerja di depan layar computer. ABSTRACT Background: Based on World Health Organization (WHO) data, approximately 2.2 billion people experience near or distance vision impairment. Data from the American Optometric Association in 2023, the main conditions that cause distance vision impairment or blindness are cataracts (94 million), refractive errors (88.4 million), age-related macular degeneration (8 million), glaucoma (7.7 million), diabetic retinopathy (3.9 million). The prevalence of Computer Vision Syndrome (CVS) reaches 64-90% with the number of sufferers worldwide estimated at 60 million people and 1 million new cases appearing every year. Objective: To analyze the Effect of the 20-20-20 Method Intervention on the Incidence of Computer Vision Syndrome (CVS) in Computer User Workers at PDAM Makassar City. Method: This study uses a type of quantitative research with a Quasi Experiment research design with a Pre-Post Test with Control Group Design approach. The sampling technique used purposive sampling technique with the number of experimental groups 22 respondents and control groups 22 respondents at PDAM Makassar City. The research data were analyzed using the Independent Sample T-Test test with a confidence level of 95% (α = 0.05). Results: The results of the Independent Sample T-Test test showed that there was a significant difference in complaints of Computer Vision Syndrome (CVS) symptoms between the experimental group and the control group with a significant value of ρ = 0.000 (<0.05). Suggestion: It is expected that agencies apply the 20-20-20 method as part of the Occupational Health and Safety (OHS) policy and workers are expected to independently and consistently apply the 20-20-20 method to prevent the development of Computer Vision Syndrome (CVS) and maintain eye health while working in front of a computer screen.