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All Journal Edu Komputika Journal Sistemasi: Jurnal Sistem Informasi Jurnal Eksplora Informatika Respati Jurnal Abdi Insani Community Development Journal: Jurnal Pengabdian Masyarakat Information System Journal (INFOS) Journal of Intelligent Software Systems Indo-Fintech Intellectuals: Journal of Economics and Business Journal of Future Artificial Intelligence and Technologies
Akhmad Dahlan
Universitas Amikom Yogyakarta
Agriculture, Biological Sciences & Forestry Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Health Professions Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Mathematics Public Health Social Sciences

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Journal : Journal of Intelligent Software Systems

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TEMPERATURE SENSOR DATA QUALITY ASSESSMENT IN MANUFACTURING ENVIRONMENT USING HAMPEL FILTER AND QSD P.D.P., Bambang; Andriyani, Widyastuti; Dahlan, Akhmad
Journal of Intelligent Software Systems Vol 4, No 1 (2025): Juli 2025
Publisher : LPPM UTDI (d.h STMIK AKAKOM) Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26798/jiss.v4i1.2003

Abstract

In the Industry 4.0 era, integrated temperature sensors in system production become source main data for taking decisions. However, the quality of the data produced often influenced by noise, missing values, and disturbing anomalies accuracy of analytical processes. Research This proposes a monitoring pipeline designed data quality For environment manufacturing based on the Internet of Things (IoT), with focus on usage Hampel Filter and Quality Score Delta (QSD) methods. Hampel Filter is used for detecting and handling outliers in temperature data in a way adaptive, while QSD is used for measure dynamics change data quality from time to time. Architecture system built with using Apache Kafka for data ingestion, InfluxDB For time-series storage, and Grafana for real-time visualization. Case study performed on temperature sensor data from the conveyor motor, and the results show that method. This capable detect degradation data quality in general proactive. Findings show potential big in increase reliability industrial monitoring system as well as support maintenance predictive data- based. Research This give contribution significant in developing modular and adaptive approach for management data quality in the manufacturing sector.
Co-Authors Achmad Nuruddin Safriandono Ahmad Muktamar B Ambarwati, Dwi Arini Ayu Amri Amri Amri Andriyani, Widyastuti Anggono, Eko Tri Arief Zikry Budi Witjaksana De Rosal Ignatius Moses Setiadi Ema Utami Emha Taufiq Luthfi Farah Zakiyah Rahmanti Iwan Setiawan Wibisono Lendra Lendra LILIS DWI FARIDA Lukman Lukman M. Nuraminudin Mekar Meilisa Amalia Muhammad Bitrayoga Nina Dwi Putriani Nina Dwi Putriani Nofirman Nofirman Ojugo, Arnold Adimabua P.D.P., Bambang Renaldi Renaldi Reni Reni Reni, Reni Rospita, Andri Siska Yulia Defitri Siska Yulia Defitri Susilo Suharsono Ulfani Ikhwana Purba Yoga Pristyanto Yuliana, Muhammad Rafi Nur