Publication | Open Access
ANALISIS DATA KUALITATIF
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2019
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Data RepresentationEngineeringData VisualizationData ExplorationQualitative InterpretationData ScienceData CollectionManagementExploratory Data AnalysisData IntegrationData ReductionContent AnalysisData ManagementStatisticsAnalisis Data KualitatifKnowledge DiscoveryData WranglingQualitative AnalysisData LiteracyData Modeling
Qualitative research relies on iterative data collection and reduction, where data are sorted into conceptual units, themes, and matrices to facilitate interpretation and support conclusions. The study aims to explain how to conduct the data analysis process in qualitative research. The authors outline a five‑step framework—defining data meaning, analyzing during collection, reducing data, presenting findings, and verifying conclusions—to guide the analysis.
Data collection is interactive with data analysis, data collection is an integral part of data analysis activities. Data reduction is an attempt to deduce data, then sorting through data in certain conceptual units, certain categories, and certain themes. Data reduction results are processed in such a way as to look more fully in their figure. It may take the form of sketches, synopsis, matrices, and other forms; it is very necessary to facilitate the explanation and affirmation of conclusions. The process, not once, but interacts back and forth. The process of occurrence in qualitative research is very dependent on the complexity of the problems to be answered and the sharpness of the researchers' traceability in making comparisons during the data collection process. How can the data analysis process be operated? This paper will attempt to answer and describe the parts (1) understanding the meaning of data analysis, (2) analysis when collecting data; (3) data reduction; (4) data presentation; (5) drawing conclusions and verification.