Iqbal Maulana Syahputra, Triase Triase, Septiana Dewi Andriana
{"title":"Implementation of Statistical Quality Control Method in Product Quality Monitoring Information System","authors":"Iqbal Maulana Syahputra, Triase Triase, Septiana Dewi Andriana","doi":"10.47709/cnahpc.v6i2.3825","DOIUrl":null,"url":null,"abstract":"The business sector faced intensifying competition due to significant advancements in information systems and technology. PT. Florindo Makmur, a leading private company in the cassava processing industry producing tapioca flour, has proven to implement quality standards to uphold product quality and ensure customer satisfaction. The product quality inspection process had to meet standards before packaging; however, reporting remained manual using paper sheets, elevating the risk of data loss and reducing monthly evaluation efficiency due to manual calculations. The aim of this research was to design an efficient information system for monitoring product quality at PT. Florindo Makmur, utilizing the Statistical Quality Control (SQC) method. The quality control monitoring system played a central role in gathering quality control data to support management decisions regarding product quality certainty. Therefore, obtaining monitoring information promptly was crucial to ensure products met quality standards and reduce rejected product quantities. The research approach included observation, interviews, and literature review as data collection strategies, while the system development method used was the waterfall method encompassing system requirement analysis, design, coding, and implementation. This information system enabled PT. Florindo Makmur to efficiently monitor its products by applying SQC concepts such as data analysis and creating control charts to swiftly identify improvements in product defects and take appropriate actions.","PeriodicalId":15605,"journal":{"name":"Journal Of Computer Networks, Architecture and High Performance Computing","volume":" 15","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal Of Computer Networks, Architecture and High Performance Computing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.47709/cnahpc.v6i2.3825","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
The business sector faced intensifying competition due to significant advancements in information systems and technology. PT. Florindo Makmur, a leading private company in the cassava processing industry producing tapioca flour, has proven to implement quality standards to uphold product quality and ensure customer satisfaction. The product quality inspection process had to meet standards before packaging; however, reporting remained manual using paper sheets, elevating the risk of data loss and reducing monthly evaluation efficiency due to manual calculations. The aim of this research was to design an efficient information system for monitoring product quality at PT. Florindo Makmur, utilizing the Statistical Quality Control (SQC) method. The quality control monitoring system played a central role in gathering quality control data to support management decisions regarding product quality certainty. Therefore, obtaining monitoring information promptly was crucial to ensure products met quality standards and reduce rejected product quantities. The research approach included observation, interviews, and literature review as data collection strategies, while the system development method used was the waterfall method encompassing system requirement analysis, design, coding, and implementation. This information system enabled PT. Florindo Makmur to efficiently monitor its products by applying SQC concepts such as data analysis and creating control charts to swiftly identify improvements in product defects and take appropriate actions.