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Journal : Variance : Journal of Statistics and Its Applications

CLASSIFICATION OF THE GEOCHEMICAL COMPOSITION OF METEORITE OF PUNGGUR (ASTOMULYO) BY k-NEAREST NEIGHBOR ALGORITHM Triyana Muliawati
VARIANCE: Journal of Statistics and Its Applications Vol 5 No 2 (2023): VARIANCE: Journal of Statistics and Its Applications
Publisher : Statistics Study Programme, Department of Mathematics, Faculty of Mathematics and Natural Sciences, University of Pattimura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/variancevol5iss2page185-192

Abstract

The fall of a meteorite in Astomulyo Village, Punggur, Lampung Province in early 2021 is an interesting topic for further study. This rare object has been suggested to have a unique geochemical composition and a special connection with other meteorites. We aimed to trace its classification by comparing it with other well-known meteorites studied previously. We approach the classification process using the k-nearest neighbor algorithm. The database used 211 represents the geochemical data for each known meteorite group from chemical analyses of meteorites. As a result, we identified that with a k-value = 5 and the proportion of test data 5/95 (in %), the geochemical composition of this meteorite is relatively close to that of the H-type chondrite group with a value accuracy of 91.67%. These results are consistent with the fact that the meteorite of Punggur has a high total iron and metallic composition.