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All Journal Jurnal Rekayasa dan Manajemen Sistem Industri Journal of Engineering and Management in Industrial System
Tuhfah, Riesa Aliya
Unknown Affiliation
Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Industrial & Manufacturing Engineering Mathematics

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ANALISIS KUALITAS PELAYANAN PELANGGAN DENGAN METODE SERVQUAL DAN IPA PADA RUMAH SAKIT UMUM DAERAH Tuhfah, Riesa Aliya; Andriani, Debrina Puspita
Jurnal Rekayasa dan Manajemen Sistem Industri Vol. 12 No. 1 (2024):
Publisher : Program Studi Teknik Industri Fakultas Teknik Universitas Brawijaya

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Abstract

Jika membutuhkan abstrak atau isi jurnal silahkan menghubungi author melalui e-mail riesaaliyat@gmail.com atau debrina@ub.ac.id Dipublikasikan tanggal: 21 Maret 2024
ANALYSIS OF HEALTHCARE SERVICE QUALITY IN GOVERNMENT HOSPITALS USING CLUSTERING METHODS Tuhfah, Riesa Aliya; Novareza, Oyong; Andriani, Debrina Puspita
JEMIS (Journal of Engineering & Management in Industrial System) Vol. 13 No. 1 (2025)
Publisher : Industrial Engineering Department, Faculty of Engineering, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21776/

Abstract

Hospitals play a crucial role in delivering healthcare services, directly influencing public health and overall well-being. Evaluating service quality is essential for enhancing patient satisfaction, as healthcare institutions must meet patient expectations to ensure effective service delivery. This study assesses hospital service quality using the Servqual model and clustering techniques to analyze patient perceptions. The Servqual framework evaluates five dimensions: tangibility, reliability, responsiveness, assurance, and empathy. A structured questionnaire was used to gather patient responses, utilizing a Likert scale to measure expectations and perceptions. Clustering techniques, including K-Means and Fuzzy C-Means, were applied to segment patient perception data, revealing four service quality categories: "Very Bad" (5%), "Bad" (40%), "Good" (14%), and "Very Good" (40%). Both clustering methods produced identical classifications, highlighting key areas requiring improvement. Among the service attributes assessed, parking area conditions received the lowest ratings, identifying them as a priority for enhancement. To address these issues, recommendations include resurfacing parking areas, implementing clear parking markings, and improving directional signage to enhance accessibility and overall patient experience. This study demonstrates the effectiveness of integrating Servqual with clustering methods in identifying service gaps and prioritizing improvements. By adopting a data-driven approach, hospitals can enhance service delivery, optimize resource allocation, and improve patient satisfaction. The findings provide valuable insights for hospital management and contribute to future research on healthcare service quality enhancement.
Co-Authors Debrina Puspita Andriani Oyong Novareza