Deteksi Pola Kunjungan Pasien Berdasarkan Status Kesehatan Menggunakan Algoritma DBSCAN - Razaq, Faisal; Muliono, Rizki (Mahesa Research Institute, 2025)
This study identified eight visit clusters grouped into four service profiles: Acute (Clusters 1 5; 1,186/3,000 ≈ 39.5%; mean age 22.8 years; peaks on Saturday at 19:00 and Thursday at 08:00; predominant diagnoses: dengue fever, typhoid, acute respiratory infection, influenza, and gastroenteritis), Chronic (Clusters 3 4; 924/3,000 ≈ 30.8%; mean age 66–67 years; peaks on Thursday at 08:00 and Friday at 13:00; predominantly COPD, type 2 diabetes mellitus, heart failure, hypertension, and kidney failure), Routine Follow-up (Clusters 2 7; 590/3,000 ≈ 19.7%; mean age 41–42 years; peaks on Thursday at 11:00 and Friday at 15:00; including post-operative follow-up, annual check-ups, adult vaccination, cholesterol screening, and nutrition counseling), and Emergency (Clusters 0 6; 300/3,000 = 10%; mean age 44–46 years; peaks at 22:00 on Thursdays and Sundays; predominantly ischemic stroke, myocardial infarction, road-traffic injuries, appendicitis, and asthma exacerbations). The age–time–diagnosis patterns indicate a distinct segmentation of service needs: acute cases are concentrated among younger patients and peak on weekends and weekday mornings; chronic cases cluster among older adults with morning–midday weekday peaks.