Article Per Year (5 Year)
p-Index From 2019 - 2024
0
P-Index
This Author published in this journals
All Journal BIMASTER Journal on Mathematics Education (JME) JURNAL DERIVAT: JURNAL MATEMATIKA DAN PENDIDIKAN MATEMATIKA
Dwipa, Nendra Mursetya Somasih
Unknown Affiliation
Decision Sciences, Operations Research & Management Education Mathematics

Published : 3 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 3 Documents
Search

 1 
DEVELOPING BILINGUAL SCIENTIFIC-WORKSHEET FOR INDEFINITE INTEGRAL Sagita, Laela; Widagsa, Rudha; Dwipa, Nendra Mursetya Somasih
Journal on Mathematics Education Vol 9, No 2 (2018)
Publisher : Department of Doctoral Program on Mathematics Education, Sriwijaya University

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (386.497 KB) | DOI: 10.22342/jme.9.2.5401.249-258

Abstract

The purpose of this research was to develop a valid, practice and effective a bilingual scientific-worksheet of the indefinite integrals. This research is development research with 1) Preliminary investigation phase, 2) Prototyping phase, 3) Assessment phase. Data were collected from test and questionnaire and analyzed to examine validity, practicality, and effectiveness the worksheet. The result of this research was producing bilingual scientific-worksheet of indefinite integral materials that oriented for learning achievement improvement. The validity obtained content, language, and illustration from expert judgment. The practicality was on the relation, attention, belief, and student satisfaction. The effectiveness based on the result of achievement test on indefinite integral.
PERAMALAN VALUE AT RISK MENGGUNAKAN METODE GENERALIZED AUTOREGRESSIVE CONDITIONAL HETEROSCEDASTIC Dwipa, Nendra Mursetya Somasih
Bimaster : Buletin Ilmiah Matematika, Statistika dan Terapannya Vol 5, No 02 (2016): BIMASTER
Publisher : FMIPA Universitas Tanjungpura

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (550.317 KB) | DOI: 10.26418/bbimst.v5i02.16312

Abstract

Data return saham merupakan salah satu jenis data runtun waktu yang memiliki volatilitas tinggi dan varians yang berbeda di setiap titik waktunya. Data tersebut berfluktuatif, membentuk pola asimetris, memiliki model yang nonstasioner, dan mempunyai variansi residual yang tidak konstan (heteroskedastisitas). ARCH dan GARCH merupakan model runtun waktu yang dapat menjelaskan keheteroskedastisitasan data. Selanjutnya model GARCH ini digunakan untuk mengestimasi nilai VaR sebagai kerugian maksimum yang akan didapat selama periode waktu tertentu pada tingkat kepercayaan tertentu. Tujuan dari penelitian ini adalah  untuk mengetahui model peramalan terbaik dari nilai Indeks Harga Saham gabungan (IHSG). Model yang digunakan dalam penelitian ini adalah ARCH, dan GARCH. Hasil dari penelitian ini menunjukkan bahwa GARCH(1,1) adalah model terbaik nilai log likelihood 1551.711 dan nilai kriteria informasi AIC = -2.5340; BIC = -2.5088; SIC = -2.5340; dan HQIC = -2.5245. Model ini mendapatkan nilai Value at Risk (VaR)  satu periode dengan taraf kepercayaan 95% Rp 3.622.420,50. untuk dana investasi Rp 500.000.000,00. Kata Kunci: Peramalan, volatilitas, GARCH, VaR
Identifikasi Model I-Garch (Integrated Generalized Autoregressive Conditionally Heterocedastic) Untuk Peramalan Value At Risk Dwipa, Nendra Mursetya Somasih
Jurnal Derivat: Jurnal Matematika dan Pendidikan Matematika Vol 3, No 1 (2016): Jurnal Derivat (Juli 2016)
Publisher : Pendidikan Matematika Universitas PGRI Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (377.233 KB) | DOI: 10.31316/j.derivat.v3i1.626

Abstract

A stock returns data are one of type time series data who has a high volatility and different variance in every point of time. Such data are volatile, seting up a pattern of asymmetrical, having a nonstationary model, and that does not have a constant residual variance (heteroscedasticity). A time series ARCH and GARCH model can explain the heterocedasticity of data, but they are not always able to fully capture the asymmetric property of high frequency. Integrated Generalized Autoregresive Heteroskedascticity (IGARCH) model overcome GARCH weaknesses in capturing unit root. Furthermore IGARCH models were used to estimate the value of VaR as the maximum loss that will be obtained during a certain period at a certain confidence level. The aim of this study was to determine the best forecasting model of Jakarta Composite Index (JSI). The model had used in this study are ARCH, GARCH, and IGARCH. From the case studies were carried out, the result of forecasting volatility of stock index by using IGARCH(1,1) obtained log likelihood values that 3857,979 to the information criteria AIC = -6,3180; BIC = -6,3013; SIC = -6,3180; dan HQIC = -6,3117. Value of VaR movement of the JCI if it becomes greater the investment is Rp.500,000,000.00 with a confidence level of 95% on the date of July 2, 2015 using a model IGARCH (1,1) is Rp7.166.315,00.
Co-Authors Laela Sagita Rudha Widagsa