Anisa Anisa
Universitas Hasanuddin

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Nilai Risiko Terkondisi pada Return Finansial Menggunakan Metode Copula Gumbel Najiha Alimatun; Anisa Anisa; Andi Kresna Jaya
ESTIMASI: Journal of Statistics and Its Application Vol. 3, No. 1, Januari, 2022 : Estimasi
Publisher : Hasanuddin University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20956/ejsa.vi.12246

Abstract

The calculation of VaR is assumed normal distribution while the conditions in the real world distribution conditions of the return value depends on the market conditions that occurred at the time. Thus, this makes VaR estimates invalid which results in portfolio risk occurring greater than the predetermined risk. Therefore, In this study, the estimated risk value uses the Conditional Value at Risk (CVaR), which measures the expected value depending on what is the worst percentage of the risk loss, and using Copula Gumbel to model financial return in the investment data of PT. Telkomunikasi Indonesia tbk and PT. XL Axiata tbk. for the period March 11, 2019 to March 10, 2020. In this study, the CVaR estimation results for the 99% confidence level is 0.231, while for the VaR estimate it is 0.192. This indicates that risk value with CVaR estimate is better able to show higher risk than VaR.
Strengthening Junior High School Members in Maros Regency in Supporting Adiwiyata Schools Naimah Aris; Jusmawati Massalesse; Nur Erawaty; Nurdin Nurdin; Kasbawati Kasbawati; Edy Saputra; Anisa Anisa; Anna Islamiyati; Sri Astuti Thamrin; Sitti Sahriman; Ainun Mawaddah Abdal; Najhah Aris; Muralia Hustim; Afifah Afifah
JATI EMAS (Jurnal Aplikasi Teknik dan Pengabdian Masyarakat) Vol 7 No 1 (2023): Jati Emas (Jurnal Aplikasi Teknik dan Pengabdian Masyarakat)
Publisher : Dewan Pimpinan Daerah (DPD) Perkumpulan Dosen Indonesia Semesta (DIS) Jawa Timur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36339/je.v7i1.711

Abstract

Maros Regency as an area that often receives Adipura award certificates should have schools that are also capable of achieving the Adiwiyata school title, a program that collaborates education with the environment. However, according to partners, out of 76 junior high schools in Maros Regency, only 5 have received this award. Starting from this, a team of lecturers from the Mathematics, Statistics, and Environmental Engineering study programs in collaboration with the Center for Development and Control of the Sulawesi and Maluku Ecoregions held training and mentoring activities for junior high schools in Maros Regency so that they were able to get the adiwiyata school title. Several aspects of the adiwiyata school assessment include curriculum development and environment-based learning, in this case specifically for mathematics. Organize the management of land, facilities and infrastructure in the environment around the school, in order to create an atmosphere that contributes to the formation of the character of students who are environmentally sound, build an extra-curricular climate that can contribute to environmental conservation, provide creativity and innovation for school residents in environmental protection and management efforts. The target audience for this service are students, teachers, and the junior high school environment in Maros Regency. The training activities was take place at SMP Negeri 16 Mandai, Maros Regency. The methods used include lectures, FGDs accompanied by demonstrations/practices, as well as monitoring and evaluation in class.
Estimasi Model Regresi Spline Kubik Tersegmen dengan Metode Penalized Least Square Anna Islamiyati; Anisa Anisa; Raupong Raupong; Jusmawati Massalesse; Nasrah Sirajang; Sitti Sahriman; Alfiana Wahyuni
Al-Khwarizmi : Jurnal Pendidikan Matematika dan Ilmu Pengetahuan Alam Vol 10, No 2 (2022): Al-Khwarizmi : Jurnal Pendidikan Matematika dan Ilmu Pengetahuan Alam had Accre
Publisher : Prodi Pendidikan Matematika FTIK IAIN Palopo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24256/jpmipa.v10i2.3197

Abstract

Abstract:Nonparametric regression is used for data whose data pattern is non-parametric. One of the estimators that can be developed is a segmented cubic spline which is able to show several segmentation changes in the data. This article examines the estimation of segmented cubic spline nonparametric regression models using the Penalized Least Square estimation criteria. The method involves knot points and smoothing parameters simultaneously. In addition, the model is used to analyze data on BPJS claims based on patient age. The results show that the optimal model is at two-knot points, namely 26 and 52 with a smoothing parameter of 0.89. There are three segmentation changes from the cubic data, which consist of young people up to 26 years old, 26-52 years old, and 52 years and over. Abstrak:Regresi nonparametrik digunakan untuk data yang pola datanya bentuk non parametrik. Salah satu estimator yang dapat dikembangkan adalah spline kubik tersegmen yang mampu menunjukkan beberapa segmentasi perubahan pada data. Artikel ini mengkaji estimasi model regresi nonparametrik spline kubik tersegmen melalui kriteria estimasi menggunakan Penalized Least Square. Metode tersebut melibatkan titik knot dan parameter penghalus secara bersamaan. Selain itu, model digunakan untuk menganalisis data klaim BPJS berdasarkan usia pasien. Hasil menunjukkan bahwa model optimal pada dua titik knot yaitu 26 dan 52 dengan parameter penghalus sebesar 0,89. Terdapat tiga segmentasi perubahan data secara kubik, yaitu usia muda hingga 26 tahun, usia 26-52 tahun, dan usia 52 tahun ke atas. 
Analisis Value at Risk pada Portofolio Saham PT. Adaro Energy Tbk dan PT. Bukit Asam Tbk Menggunakan Metode Copula Archimedean Victor Liman; Georgina Maria Tinungki; Anisa Anisa
ESTIMASI: Journal of Statistics and Its Application Vol. 4, No. 2, Juli, 2023 : Estimasi
Publisher : Hasanuddin University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20956/ejsa.v4i2.25575

Abstract

Value at Risk (VaR) is statistical method used in risk analysis in stock investments. Stock returns that are not normally distributed cause the risk calculation to be less precise, so to overcome this, the copula method can be used. Copula is a method based on dependencies between variables. The most commonly known copula family is the Archimedean copula which consists of the Clayton, Frank, and Gumbel copula. VaR is expected to be a feasible method to use, so it is important to perform backtesting. In this research, we use data on the daily closing price of PT. Adaro Energy Tbk and PT. Bukit Asam Tbk May 11, 2020 until June 15, 2022. The best copula based on the smallest Empirical copula value is Frank copula. VaR estimates for the 90%, 95%, and 99% confidence levels respectively were 2.688%, 3.545%, and 5.014%. The higher the confidence level, the VaR value is also higher. Based on backtesting results, VaR with Frank copula method is valid at 90%, 95%, and 99% confidence levels.