PENDUGAAN DATA HILANG PADA RANCANGAN ACAK KELOMPOK LENGKAP DENGAN METODE BIGGERS (Studi Kasus: Tanaman Tebu dan Simulasi Tanaman Jagung)

Nadya Fauziah, NIM. 16610035 (2021) PENDUGAAN DATA HILANG PADA RANCANGAN ACAK KELOMPOK LENGKAP DENGAN METODE BIGGERS (Studi Kasus: Tanaman Tebu dan Simulasi Tanaman Jagung). Skripsi thesis, UIN SUNAN KALIJAGA YOGYAKARTA.

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Abstract

One of the designs in the experimental design is a completely randomized block design. In the experiments that were carried out the implementation did not go as expected. Various kinds that were expected in advance to happen. This will result in incomplete data. Missing data will become a new problem in analysis because the data is incomplete, so the approach that is often taken to solve problems with missing data is by analyzing existing data or by estimating the missing data. The calculation method used is the Biggers method. If two data is missing, the Yates method is used to estimate it, whereas if there are more than two missing data, the Biggers method can be used. In principle, the Biggers method is the same as the Yates method, namely by minimizing the number of squares of error. In this study, the application was carried out in a Complete Randomized Block Design with empirical data from the measurement of herbacid levels which were suitable for controlling weeds in sugarcane where there were 4 missing data and simulated data on the yield of dry maize (Kw / ha) cobs from 8 varieties where there were 5 missing data. The data is estimated first using the Biggers method. Then the analysis uses an alternative analysis with values on group variables (0,000783***) 0,05( so that the decision is obtained that there is a group influence on the measurement results of herbacid levels which are suitable for controlling weeds in sugarcane and the values on group variables 3,92e 05*** 0,05 and on treatment variables 1,71e 15*** 0,05 so that it is obtained that there is a group and treatment effect on maize production (Kw / ha) dry cobs of 8 varieties. After the analysis of alternative variants is carried out, the Least Significant Difference test will be carried out on the group variables in the empirical data and the group and treatment variables on the simulation data.

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