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Journal : Journal of Software Engineering, Information and Communication Technology

Analysis of Quality in Project Quality Management Based on PMBOKĀ® Didik Suwito Pribadi; Cholid Fauzi; Ardhian Ekawijana
Journal of Software Engineering, Information and Communication Technology (SEICT) Vol 3, No 2: December 2022
Publisher : Universitas Pendidikan Indonesia (UPI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17509/seict.v3i2.52460

Abstract

Quality is a vital part of a successful organization. Quality is important to a process and result. A good process produces a good product, while a good product is produced through a good process. In project management, quality is used to assess project success. Quality is the degree to which the inherent characteristics meet requirements, while project quality is the process of meeting business objectives according to the project charter. The journal entitled 'Analysis of Quality in PMBOK-Based Project Management', discusses the definition, types, and processes of quality management, intending to explain projects and the process of managing them. The benefit is to explain knowledge about quality and its management. The method used is identification, description of the concept of project quality management, analysis of the management planning process, quality control, and conclusions. This research describes the quality management process, including quality control. The main input utilized in the process including Project Charter, PM Plan, Project Documents, EEF, OPA, Approved CR, Deliverables, and Work Performance Data. The Tools and technic utilized in the process include Expert Judgement, Data Gathering, Data Analysis, Decision Making, Data Representation, Test, and Inspection Planning/ audit, Design For X, Problem Solving Quality Improvement Methods, and Meetings. The results obtained from the above process include the main results consisting of QM Plan, Quality Metrics, Quality Reports, Test Documents, CR, QC Measurements, Verified Deliverables, and Work Performance Information.
Morphological Grayscale Pre-processing to SAR Images for Reducing Noise in Ship Detection Based on YOLOv8 Pratidina, Caturiani; Safira, Decia; Gelar, Trisna; Permana, Heru; Suprihanto, Suprihanto; Syakrani, Nurjannah; Fauzi, Cholid
Journal of Software Engineering, Information and Communication Technology (SEICT) Vol 5, No 2: December 2024
Publisher : Universitas Pendidikan Indonesia (UPI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17509/seict.v5i2.75970

Abstract

The development of a ship detection system using SAR pictures loaded with noise poses issues for pictures Intelligence (IMINT). The YOLOv8 model is utilized for ship identification. The preprocessing approaches entail employing a fusion of grayscale morphology techniques and image restoration using a harmonic mean filter and a bandpass. This technique is designed to assess the effect of noise reduction to enhance the accuracy of detecting objects in SAR images. The preprocessing technique is categorized into two methods: basic grayscale morphology (GM1-GM6) and a fusion of image restoration with grayscale morphology (GHB1-GHB6). The model's performance is assessed using mAP and IoU criteria. This research discovered that ship objects were not detected successfully in the presence of several types of noise. These failures were attributed to factors such as tiny ship size, low picture quality, and inadequate preprocessing techniques for noise handling. The findings indicate a substantial enhancement in ship detection, specifically in synthetic aperture radar (SAR) images affected by sidelobe noise. There were noticeable enhancements in the accuracy of images that underwent preprocessing using GHB5. GHB5 employs a combination of image restoration, closure, and erosion techniques.