Sri Adikadarsih, Ihwanudien Hasan Robbani, Heri Prabowo
Sesame (Sesamum indicum L.), otherwise known as sesamum or benniseed, member of the family Pedaliaceae, is one of the most ancient oilseeds crop known to mankind. Based on Food and Agriculture Organization of the United Nations (FAO) projections, sesame number of world consumption will increase to about 500 tons per year until 2012. Therefore, it is necessary to study inheritance of sesame seed coat color for improving quality. One was to get the highest quality sesame is by plants breeding. In germplasm sesame, seed coat colour of sesame is commercially an important trait and it can also indicate the general quality. Research on seed coat color inheritance is mostly through qualitative observations. Qualitative research conducted by separating the sesame seeds manually based on the seed coat color. The results of qualitative observations need to be compared with quantitative observations. Grouping process based on color or other properties ca be done using cluster analysis. The cluster analysis algorithm used in this study is K-Means (KM). Grouping of sesame seed based on seed coat color properties of the KM cluster analysis method are not significantly different when compared with the results of previous research. So this method can be used as a alternative method (model) to grouping the sesame seed based on seed coat color properties. The results of this research able to be the validation of the results of previous research that considered not using the method (model) as appropriate. From this research it is known that grouping on previous research using a quantitative approach performed the results are not significantly different from the results of grouping of in this study. © 2018 ISISnet: Innovative Scientific Information Services Network. All rights reserved.
Indonesian Sweetener and Fiber Crops, Research Institute, Indonesia; Faculty of Computer Science, Brawijaya University, Indonesia
