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All Journal Pendidikan Geografi INSIST (International Series on Interdisciplinary Research) Jurnal Siger Matematika
Eri Setiawan
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Earth & Planetary Sciences Education Mathematics Other

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EVALUASI KESESUAIAN LAHAN UNTUK TANAMAN KOPI DAN KARET DI DAERAH ALIRAN SUNGAI JAMBANGAN KABUPATEN KARANGANYAR TAHUN 2011 Setiawan, Eri
Pendidikan Geografi Vol 1, No 1 (2013)
Publisher : Pendidikan Geografi

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (711.779 KB)

Abstract

ABSTRACTThe research is aimed to : (1) to know sub-class level of actual land suitability for coffee and rubber plant, (2) know sub-class of potential land suitability for coffee and rubber plant, and (3) know coffee and rubber productivity at Jambangan Watersheed in Karanganyar Regency.Based on the result of the research it can concluded as follows: (1) there are 9 subclass actual land suitability for coffe plant, those are : S2 w,r,f,n,s/m,e (0,51%), S3n(7,59%), S3r,n(5,24%), N1r(12,84%), N1r,s/m(14,99%), N1r,e(1,63%), N2r (9,59%), N2s/m (12,45%) and N2s/m,e(0,9%); There are 12 subclass actual land suitability for peanut plant, those are: S3w,n(12,47%), S3w,r,n(8,61%), S3t,w,n (0,84%), N1r (7,70%), N1r,e(1,63%), N1r,s/m (20,77%) ,N2s/m(0,66%), N2w (19,79%), N2s/m,e(0,90%), N2w,r(2,51%), N2w,s/m(10.46%), and N2w,r,s/m(4,90%); (2) Potential land suitability for coffe plant with a medium management level produced eight land suitability subclass include: S2r,s/m, S2w,r,f,n, S2w,r,f,n,s/m, S3r,n; S3r,s/m, S3r,n,s/m, S3r,s/m,e and N1s/m; Potential land suitability for coffe plant with a high management level prodused nine land suitability subclass include S2s/m, S2w,r,f,n, S2w,r,f,n,s/m, S3s/m, S3r,n, S3n,s/m, S3 r,s/m, N1s/m and N1r,s/m; Potential land suitability for rubber plant with medium management level produced 7 subclass suitability include: S2t,w,n, S3r, S3t, S3w,r,n, S3t,w,r,n,s/m,e, N1s/m, N1r,s/m; and Potential land suitability for rubber plant with a high management level prodused six land suitability subclass include: S2t,n, S2w,r,n,s/m, S3t, S3w,r,n, S3t,w,n,s/m and N1s/m.(3) Highest productivity of coffe plants get on land suitability subclass N1r,s/m which is 896 kgs/Ha/year and have the lowest productivity of coffe plants get on land suitability subclass N2s/m is 47 kgs/Ha/year; Highest productivity of Rubber plants get on land suitability subclass S3w,n which is 2137 Kgs/Ha/year and have the lowest productivity of rubber plants get on land suitability subclass N2w,s/m is1618 kgs/Ha/year.Kata kunci : Kesesuaian Lahan, Daerah Aliran Sungai,Tanaman Kopi dan Karet
Modeling Stock Return Data Using Asymmetric Volatility Models: A Performance Comparison Based On the Akaike Information Criterion and Schwarz Criterion Nisa, Khoirin; Setiawan, Eri; Herawati, Netti
INSIST Vol 3, No 2 (2018)
Publisher : Universitas Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/ins.v3i2.160

Abstract

The Generalized Autoregressive Conditional Heteroscedasticity (GARCH) model has been widely used in time series forecasting especially with asymmetric volatility data. As the generalization of autoregressive conditional heteroscedasticity model, GARCH is known to be more flexible to lag structures. Some enhancements of GARCH models were introduced in literatures, among them are Exponential GARCH (EGARCH), Threshold GARCH (TGARCH) and Asymmetric Power GARCH (APGARCH) models. This paper aims to compare the performance of the three enhancements of the asymmetric volatility models by means of applying the three models to estimate real daily stock return volatility data. The presence of leverage effects in empirical series is investigated. Based on the value of Akaike information and Schwarz criterions, the result showed that the best forecasting model for our daily stock return data is the APARCH model.
Analisis Regresi Komponen Utama Robust dengan Metode Minimum Covariance Determinant – Least Trimmed Square (MCD-LTS) Siska Diah Ayu Larasati; Khoirin Nisa; Eri Setiawan
Jurnal Siger Matematika Vol 1, No 1 (2020): Jurnal Siger Matematika
Publisher : FMIPA Universitas Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (381.312 KB) | DOI: 10.23960/jsm.v1i1.2472

Abstract

Principal Component Regression (PCR) is a method used to overcome multicollinearity problems by reducing the dimensions of independent variables to obtain new simpler variables without losing most of the information contained in the  variables. If the data analyzed contain outliers, a robust method on PCR is required. In this paper we use a robust method which is a combination of Robust Principal Component Analysis using the Minimum Covariance Determinant (MCD) method and Robust Regression Analysis using Least Trimmed Square (LTS) method. The purpose of this study is to examine the robust PCR analysis using the MCD-LTS method and to know the robustness of the method by looking at its sensitivity to outliers. For this purpose  we compared the MCD-LTS PCR  to the classic PCR based on the bias and Mean Square Error (MSE) values on several different sample sizes and percentages of outliers. The results of this study indicate that robust PCR using MCD-LTS is effective and efficient in overcoming the problem of multicollinearity and outliers in regression analysis. 
Model EGARCH dan TGARCH untuk Mengukur Volatilitas Asimetris Return Saham Sofalina Nodra Brilliantya; Khoirin Nisa; Subian Saidi; Eri Setiawan
Jurnal Siger Matematika Vol 3, No 2 (2022): Jurnal Siger Matematika
Publisher : FMIPA Universitas Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/jsm.v3i2.3111

Abstract

Model Generalized Autoregressive Conditional Heterocedasticity (GARCH) merupakan salah satu pemodelan data deret waktu yang digunakan untuk mengukur data yang memiliki varians residual yang tidak konstan atau bersifat heteroskedastisitas.  Heteroskedastisitas terjadi karena data deret waktu memiliki volatilitas yang tinggi.  Model Exponential GARCH (EGARCH) dan Threshold GARCH (TGARCH) adalah model-model GARCH yang dapat mengatasi efek asimetris pada volatilitas.  Data yang digunakan pada penelitian ini adalah data return saham harian PT KB Bukopin Tbk (BBKP).  Penelitan ini bertujuan untuk menerapkan model EGARCH dan TGARCH serta mendapatkan  model terbaik dalam mengukur volatilitas asimetris data return saham harian.  Pemilihan model terbaik didasarkan pada nilai Akaike Information Criterion (AIC) terkecil.  Hasil analisis menunjukan bahwa model EGARCH (2,1) adalah model terbaik untuk mengukur dan meramalkan volatilitas asimetris return saham yang digunakan.
Co-Authors Khoirin Nisa Khoirin Nisa Netti Herawati Saidi, Subian Siska Diah Ayu Larasati Sofalina Nodra Brilliantya