Judul: Analisis Regresi Menggunakan Metode Kuantil
Abstrak: Regression analysis is applied to analyze relation between response variable with one or more predictor variable, especially to construct a model that has not been known. In order to estimate the regression parameters, certain estimation method of regression coefficients are carried out. In this paper quantile regression method is applied to asymmetric data. This method divides data into two or more groups, where existence of different estimated values at different quantiles are suspected. In this regression analysis, the regression coefficients are estimated using quantiles regression approximation properties, i.e. weighted least square approximation with all predictor variables included and the suites approximation with partial regression decomposition for certain predictor variables. Quantile regression approximation property explains that the quantile regression coefficient vector can minimize the expected value of weighted mean square error, which will give the best fit. The quantile regression with suites approximation is used to omit predictor variables which do not have influence to the model. The approximation properties of quantile regression are illustrated with the salary data from the U.S. census at 1980, 1990, and 2000. Key word: quantiles regression, asymmetric data, weighted least square, partial regression.
Keyword: 

Judul: Kajian metode pendugaan pada model regresi dengan peubah penjelas bersifat acak
Abstrak: Regression analysis is a statistical method to evaluate the relationship between a variable with other variables. Model I regression analysis describes the one-way relationship between variable X and variable Y with the value of X as fixed variable or measured without error. Model I regression analysis uses Ordinary Least Square (OLS) as an estimation method. Model II regression analysis is a regression model with predictors variable that becomes a random variable. There are two estimation methods of model II regression analysis, ordinary least product regression (Model IIA) and major axis regression (Model IIB). The convenience of using model I regression analysis with OLS estimation method causes many researchers to use this model as a model regression analysis with random predictor variables. The purpose of this study is to compare model I regression analysis (OLS estimation method) and model II regression analysis (ordinary least product estimation method and major axis regression estimation method). The data used in this research are simulation data where response variable (Y) and predictor variable (X) are random. The result of this study showed for predictor variable is random, ordinary least product regression is the best estimation method compared to the other methods because it produces the smallest value of bias and the smallest value of mean square error. In this condition, OLS can be used for the estimate parameter of simple linier regression model if the correlation value between predictor variable (X) and response variable (Y) is high (r ≥ 0.9).
Keyword: Bogor Agricultural University (IPB), Model IIB, Model IIA, Model I, mean square error, correlation

Judul: Pengelolaan Panen dan Pascapanen Bunga Lily Potong (Lilium longiflorum ‘LA Hybrid’) di Perusahaan Daily Sunshine, Heerhugowaard, Belanda Utara.
Abstrak: Kegiatan magang dilaksanakan di perusahaan penghasil bunga potong Daily Sunshine mulai 26 Februari sampai dengan 25 Mei 2018. Kegiatan magang bertujuan untuk meningkatkan kemampuan, pengetahuan dan keterampilan dalam aspek budi daya bunga potong Lilium longiflorum secara umum dan secara khusus untuk mempelajari proses pengelolaan panen dan pascapanen yang terdapat di Perusahaan Daily Sunshine. Metode yang digunakan adalah metode langsung dan tidak langsung. Metode langsung dilaksanakan dengan melakukan pengamatan secara langsung di lapang serta mengikuti semua kegiatan teknis budi daya bunga lily mulai dari penanaman sampai dengan panen. Metode tidak langsung dilaksanakan dengan memperoleh dan mempelajari data sekunder berupa arsip perusahaan, laporan dari perusahaan dan studi pustaka. Budi daya serta pengelolaan panen dan pascapanen bunga Lilium longiflorum di perusahaan Daily Sunshine sudah dilakukan dengan baik. Hal tersebut ditunjukan dengan hasil total produksi optimum sebesar 92.18 % dengan 95.60 % produksi kelas mutu A1 dan telah memenuhi standar perusahaan pada beberapa parameter yang diamati yaitu kondisi lingkungan tumbuh, pertumbuhan tanaman, umur panen, produksi, kehilangan panen, stadia panen dan standar mutu panen. Distribusi pemasaran bunga potong di Perusahaan Daily Sunshine dilakukan melalui organisasi balai lelang tanaman hias di Belanda, yaitu Royal Flora Holland dan Plantion Ede
Keyword: bunga potong, kualitas panen, Royal Flora Holland, standar mutu panen