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All Journal EKSAKTA: Journal of Sciences and Data Analysis Indonesian Journal of Statistics and Its Applications Variance : Journal of Statistics and Its Applications REKA ELKOMIKA: Jurnal Pengabdian kepada Masyarakat
Fajar Indrayatna
Actuarial Science, Department Of Statistics, Universitas Padjadjaran, Indonesia
Chemical Engineering, Chemistry & Bioengineering Chemistry Computer Science & IT Control & Systems Engineering Earth & Planetary Sciences Electrical & Electronics Engineering Industrial & Manufacturing Engineering Materials Science & Nanotechnology Mathematics Other

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 1 
Utilization Copula in Determination of Shallot Insurance Premium Based on Regional Harvest Results Hasna Afifah Rusyda; Achmad Zabar Soleh; Lienda Noviyanti; Anna Chadidjah; Fajar Indrayatna
EKSAKTA: Journal of Sciences and Data Analysis VOLUME 1, ISSUE 2, August 2020
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20885/EKSAKTA.vol1.iss2.art11

Abstract

Abstract: Shallot is one of the highest-yielding horticultural crops in Indonesia and has the tendency to increase the profits of farmers in Indonesia. But until now in Indonesia there is no insurance for horticultural crops other than corn, whereas the shallot farmers face various sources of risk such as weather changes, pest attacks, or other technical factors that ultimately lead to uncertainty of agricultural yields (revenue risk). To overcome this loss, insurance companies can make products based on shallot yields and shallot market prices. Therefore it is essential to grasp the distribution of risk variables (shallot yields and shallot market prices) that interact simultaneously, not separate from one another. Omitting dependencies among risk variables can cause biased risk estimation. Copula can model the non-linear dependencies and can identify the structure of the dependencies between variables. The suitable copula for modeling yield and price risk of shallot is simulated to compute the premium. Result show that clayton copula is suitable for dependence modelling between risk variables.
Estimation of Value at Risk by Using GJR-GARCH Copula Based on Block Maxima Hasna Afifah Rusyda; Fajar Indrayatna; Lienda Noviyanti
Indonesian Journal of Statistics and Applications Vol 5 No 2 (2021)
Publisher : Departemen Statistika, IPB University dengan Forum Perguruan Tinggi Statistika (FORSTAT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29244/ijsa.v5i2p405-414

Abstract

This paper will discuss the risk estimation of a portfolio based on value at risk (VaR) using a copula-based asymmetric Glosten – Jagannathan – Runkle - Generalized Autoregressive Conditional Heteroskedasticity (GJR-GARCH). There is non-linear correlation for dependent model structure among the variables that lead to the inaccurate VaR estimation so that we use copula functions to model the joint probability of large market movements. Data is GEV distributed. Therefore, we use Block Maxima consisting of fitting an extreme value distribution as a tail distribution to count VaR. The results show VaR can estimate the risk of portfolio return reasonably because the model has captured the data properties. Data volatility can be accommodated by GJR-GARCH, Copula can capture dependence between stocks, and Block maxima can accommodate extreme tail behavior of the data.
Ergonomics Analysis of Computer Use in Distance Learning during the Pandemic of COVID-19 Anindya Apriliyanti Pravitasari; Mulya Nurmasnsyah Ardisasmita; Fajar Indrayatna; Intan Nurma Yulita
REKA ELKOMIKA: Jurnal Pengabdian kepada Masyarakat Vol 3, No 1 (2022): REKA ELKOMIKA
Publisher : Institut Teknologi Nasional, Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26760/rekaelkomika.v3i1.9-19

Abstract

One impact of the COVID-19 pandemic on education is the mandated learning from home or distance learning (DL) in both state and private education institutions to prevent the transmission of COVID-19. DL may require long periods of time in front of a computer screen, which can create ergonomic issues such as eye, shoulder or neck problems, low back pain, and fatigue or stress. This study was structured to look at the ergonomic behavior of students in the statistics department at Padjadjaran University. The data were gathered using questionnaire, and there were 146 respondents who were willing to answer and send back the questionnaire. The results of the analysis show that the majority of students do not have knowledge about ergonomics when using computers. However, students agree that wrong posture can affect health conditions, especially those related to musculoskeletal disorders. The real impact felt by students is the health condition around their neck, shoulders, waist, bottoms, and wrists.
Estimation of Value at Risk by Using GJR-GARCH Copula Based on Block Maxima Hasna Afifah Rusyda; Fajar Indrayatna; Lienda Noviyanti
Indonesian Journal of Statistics and Applications Vol 5 No 2 (2021)
Publisher : Departemen Statistika, IPB University dengan Forum Perguruan Tinggi Statistika (FORSTAT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29244/ijsa.v5i2p405-414

Abstract

This paper will discuss the risk estimation of a portfolio based on value at risk (VaR) using a copula-based asymmetric Glosten – Jagannathan – Runkle - Generalized Autoregressive Conditional Heteroskedasticity (GJR-GARCH). There is non-linear correlation for dependent model structure among the variables that lead to the inaccurate VaR estimation so that we use copula functions to model the joint probability of large market movements. Data is GEV distributed. Therefore, we use Block Maxima consisting of fitting an extreme value distribution as a tail distribution to count VaR. The results show VaR can estimate the risk of portfolio return reasonably because the model has captured the data properties. Data volatility can be accommodated by GJR-GARCH, Copula can capture dependence between stocks, and Block maxima can accommodate extreme tail behavior of the data.
Parents' Understanding of the Safety and Comfort in Using Gadgets for Children Anindya Apriliyanti Pravitasari; Mulya Nurmansyah Ardisasmita; Fajar Indrayatna; Intan Nurma Yulita; Triyani Hendrawati; Gumgum Darmawan
REKA ELKOMIKA: Jurnal Pengabdian kepada Masyarakat Vol 4, No 2 (2023): REKA ELKOMIKA
Publisher : Institut Teknologi Nasional, Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26760/rekaelkomika.v4i2.151-160

Abstract

The utilization of technology among children has significantly increased since the outbreak of the Covid 19 pandemic. Therefore, the use of gadgets among children requires special attention from parents, since under incorrect ergonomic circumstances, it could endanger the health of children. This webinar was designed with parents in mind, giving them valuable information on how to use kid-friendly technology. Additionally, a pre- and post-test was assigned to evaluate parents’ knowledge about ergonomic conditions (safety and comfort) when using gadgets, both before and after the webinar. The results indicated a substantial increasement in parental knowledge among the webinar participants as well as the heightened desire and willingness to apply the right ergonomic conditions for their children’s gadget use at home.
RETURN PORTOFOLIO OPTIMAL DENGAN PENDEKATAN SINGLE INDEX MODEL, TREYNOR BLACK MODEL, DAN BLACK-LITTERMAN MODEL Adri Arisena; Lienda Noviyanti; Achmad Zanbar Soleh; Fajar Indrayatna
VARIANCE: Journal of Statistics and Its Applications Vol 5 No 2 (2023): VARIANCE: Journal of Statistics and Its Applications
Publisher : Statistics Study Programme, Department of Mathematics, Faculty of Mathematics and Natural Sciences, University of Pattimura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/variancevol5iss2page117-130

Abstract

Membentuk portofolio optimal adalah metode yang dapat membantu para investor meminimalkan risiko dan mengoptimalkan keuntungan. Beberapa model untuk portofolio optimal termasuk Single Index Model (SIM), Treynor Black Model (TBM), dan Black-Litterman Model (BLM). SIM didasarkan pada pengamatan bahwa harga sekuritas berfluktuasi sejalan dengan indeks pasar. Pada TBM, seorang investor dapat melihat bahwa model ini kurang fokus pada nilai beta tetapi lebih berfokus pada risiko tidak sistematis. BLM menggabungkan elemen data historis dan pandangan investor untuk membentuk prediksi baru tentang portofolio sebagai dasar pemodelan. Prediksi pandangan dalam penelitian ini menggunakan pendekatan time series ARIMA dan GARCH. Tujuan dari penelitian ini adalah untuk membentuk tingkat pengembalian portofolio optimal dengan menggunakan SIM, TBM, dan BLM berdasarkan pandangan tunggal investor serta kombinasi pandangan beberapa investor dengan pendekatan ARIMA dan GARCH.
Co-Authors Achmad Zabar Soleh Achmad Zanbar Soleh Adri Arisena Anindya Apriliyanti Pravitasari Anna Chadidjah Gumgum Darmawan Hasna Afifah Rusyda Intan Nurma Yulita Lienda Noviyanti Mulya Nurmansyah Ardisasmita Mulya Nurmasnsyah Ardisasmita Triyani Hendrawati