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All Journal Epsilon: Jurnal Matematika Murni dan Terapan Prosiding Seminar Nasional Official Statistics
Anggi Septiawan
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Humanities Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Social Sciences Transportation

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DETERMINAN TINGKAT PARTISIPASI ANGKATAN KERJA PEREMPUAN DI INDONESIA TAHUN 2015-2019 MENGGUNAKAN MODEL REGRESI DATA PANEL Anggi Septiawan; Siti Haiyinah Wijaya
Seminar Nasional Official Statistics Vol 2020 No 1 (2020): Seminar Nasional Official Statistics 2020
Publisher : Politeknik Statistika STIS

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (188.704 KB) | DOI: 10.34123/semnasoffstat.v2020i1.387

Abstract

Female labor force participation rate (LFPR) in Indonesia is relatively smaller than male LFPR, in fact the difference is very far and never conical. In addition, the trend of female LFPR has stagnated at around 50 percent over the past decade. Therefore, this study aims to determine the determinants of female LFPR in Indonesia in 2015-2019. The analytical method used is inference analysis with panel data regression models. Fixed efffect model (FEM) with seemingly unrelated regression (SUR) method was chosen as the best model for estimating panel data regression models. The results of this study inddicate that higher mean years of schooling for women, female wage rate, manufacturing employment share, agricultural employment share, and gross regional domestic product at constants prices can increase the female LFPR in Indonesia. Meanwhile, the higher number of population taking care of households can reduce female LFPR in Indonesia.
ESTIMASI VALUE AT RISK (VAR) DENGAN METODE MONTE CARLO UNTUK MENGUKUR RISIKO KERUGIAN PETANI KETIMUN DI KABUPATEN KAPUAS HULU Arsanti, Resti; Sulistianingsih, Evy; Septiawan, Anggi
EPSILON: JURNAL MATEMATIKA MURNI DAN TERAPAN (EPSILON: JOURNAL OF PURE AND APPLIED MATHEMATICS) Vol 18, No 2 (2024)
Publisher : Mathematics Study Program, Faculty of Mathematics and Natural Sciences, Lambung Mangkurat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20527/epsilon.v18i2.11433

Abstract

Measurement of an estimated loss needs to be done by every business actor. The measurement can be done by calculating the Value at Risk (VaR). VaR is an estimate of the maximum loss that is assumed to be experienced in a certain period at the confidence interval used. Three forms of calculation methods can be used in calculating VaR estimates, namely parametric methods, methods with Monte Carlo simulation approaches, and Historical Simulation Methods. The data used is the average monthly producer price data of cucumber commodities with a period range starting from January 2020 to December 2022. The VaR calculation method in this analysis is the Monte Carlo simulation approach method which has the condition that the return data from the average producer price is normally distributed. The results of the VaR calculation with the Monte Carlo simulation method show that after generating return data with repetition 1000 times for an investment of 1 rupiah, the probability that cucumber farmers in Kapuas Hulu Regency, West Kalimantan Province will experience maximum losses is 5.79% for a confidence level of 80%, 9.08% for a confidence level of 90%, 11.39% for a confidence level of 95%, and 14.81% for a confidence level of 99%.
Co-Authors Arsanti, Resti Evy Sulistianingsih Siti Haiyinah Wijaya