Vocabulary becomes the main problem that encountered by the students in SMP Negeri 14 Kendari. Less motivation and interest are factors that affect students in learning vocabulary. The research question of this study was “Is there any significant effect of semantic feature analysis on students’ vocabulary achievement at the second grade students of SMP Negeri 14 Kendari?” The objective of this study was to find out whether semantic feature analysis has an effect on students’ vocabulary achievement at the second grade students of SMP Negeri 14 Kendari. The population of this study was all students at second grade of SMP Negeri 14 Kendari who registered on second semester in academic year 2017/2018 with the total number of students’ were 205 students. The samples of this study were all students at class VIII.2 with total number of students are 30 and it taken by using simple random sampling. The instrument of this study was vocabulary test which consisted of 25 items (5 items matching with the synonym, 10 items matching with the meaning, 5 items complete the sentences and 5 items fill in the blank test). They were administered into two groups as the pre test and post test. The researcher used Paired Sample T-test in SPSS 16 to analyze the result of the research whether there is a significant effect of semantic feature analysis on students’ vocabulary achievement after analyzed the normality of the data in experiment class. Based on the analysis result of pre-test and post-test through SPSS in form of test, it found that the probability (Sig. 1-tailed) was 0.000 (ρ < 0.05) and the calculation of tcount (10.070) was higher than ttable (1.699) in the level of significance 0.05, df = 29. It indicated that null hypothesis (H0) was totally rejected and the alternative hypothesis (H1) was completely accepted. Therefore, it can be concluded that there is enough evidence to claim that semantic feature analysis strategy has significant effect on students’ vocabulary achievement at the second grade students of SMP Negeri 14 Kendari.Keyword: Vocabulary, Semantic Feature Analysis
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