PERANCANGAN PERBAIKAN KUALITAS AIR MINUM PRODUKSI IPA BABAKAN DI PDAM TIRTA KERTA RAHARJA MENGGUNAKAN PENDEKATAN PETA KENDALI MULTIVARIAT

Abstract

Abstrak

Air merupakan sumber kehidupan yang penting bagi seluruh makhluk hidup. Air digunakan untuk konsumsi dan kebutuhan sehari-hari seperti memasak, mandi, dan mencuci. Kualitas air menjadi faktor utama dalam kesehatan masyarakat. PDAM Tirta Kerta Raharja menilai kualitas air melalui kadar sisa klor sebagai indikator efektivitas disinfeksi. Pemantauan menunjukkan ketidakstabilan kadar sisa klor, dengan 35% sampel tidak memenuhi baku mutu sesuai peraturan pemerintah. Tingginya kadar sisa klor dapat menimbulkan iritasi dan risiko penyakit kronis, sedangkan kadar rendah meningkatkan risiko pertumbuhan mikroorganisme patogen. Penelitian ini menggunakan metode Statistical Process Control (SPC) dengan peta kendali multivariat MEWMA (Multivariate Exponentially Weighted Moving Average) untuk mengendalikan dan meningkatkan kestabilan proses pengolahan air. Hasil menunjukkan metode MEWMA efektif untuk mendeteksi perubahan kecil dan mengidentifikasi variabel penyebab ketidakteraturan proses.

Kata kunci: Kualitas Air; Pengendalian Kualitas;Peta Kendali Multivariat; Stastistical Process Control

Abstract

Water is a vital source of life for all living beings, used for consumption and daily needs such as cooking, bathing, and washing. Water quality is a key factor in public health. PDAM Tirta Kerta Raharja assesses water quality through residual chlorine levels, which serve as indicators of disinfection effectiveness. Monitoring shows instability in residual chlorine levels, with 35% of samples failing to meet quality standards set by government regulations. High residual chlorine levels may cause irritation and increase the risk of chronic diseases, while low levels increase the risk of pathogenic microorganism growth. This study employs Statistical Process Control (SPC) using the Multivariate Exponentially Weighted Moving Average (MEWMA) control chart to control and improve the stability of the water treatment process. The results demonstrate that the MEWMA method effectively detects small changes and identifies variables causing process irregularities, thereby enhancing the quality and stability of the treated water.

Keywords: Water Quality; Quality Control; Multivariate Control Chart; Statistical Process Control