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In order to determine the ripening stages of apple (Malus sylvestris L), local farmer in Malang still utilized a traditional method by examining its size and appearance. However, this method needs worker-s extensive experience causing a non-standard ripeness level that may lead to lower the economic value of the crop. Thus, to strive this problem, fast and quantitative prediction method need to be developed. UV/Vis spectroscopy has shown its capability to provide a robust prediction of several internal attributes such as, Total Solube Solid (TSS) and water content. The aim of this research is to develop a Partial Least Square (PLS) regression to predict internal parameter contained in apple. Sixty sample of apples were taken from local plantation in Bumiaji district. There were 3 stages to complete the research: (1) spectral data acquisition ranging from wavelength 340nm-800nm; (2) Internal parameters measurement (TSS, water content and firmness); (3) Performing PLS regression based on spectral data and internal parameters. The result showed that PLS model of TSS could provide a good coefficient of determination (r2 = 0,80) and for RPD, LV and RSMEP resulting 1.92, 7, 0.90 respectively. On the other hand, the model could not predict both water content and firmness; the model only provided low r2 accounting for 0.73 and 0.53 respectively. Further enhancement need to be addressed to the model for improving its capability of apple-s quality prediction.