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All Journal EKSAKTA: Journal of Sciences and Data Analysis JURNAL MATEMATIKA STATISTIKA DAN KOMPUTASI Unisda Journal of Mathematics and Computer Science (UJMC) EIGEN MATHEMATICS JOURNAL Square : Journal of Mathematics and Mathematics Education Jurnal Statistika dan Aplikasinya JAMBURA JOURNAL OF PROBABILITY AND STATISTICS LOSARI: Jurnal Pengabdian Kepada Masyarakat Journal Of Human And Education (JAHE) Journal Focus Action of Research Mathematic (Factor M) Journal of Data Insights Emerging Statistics and Data Science Journal Amalgamasi: Journal of Mathematics and Applications Scientific Journal of Computer Science
Ihsan Fathoni Amri
Universitas Muhammadiyah Semarang
Agriculture, Biological Sciences & Forestry Humanities Chemical Engineering, Chemistry & Bioengineering Chemistry Computer Science & IT Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Environmental Science Health Professions Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Physics Public Health Social Sciences Transportation Other

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Journal : EIGEN MATHEMATICS JOURNAL

 1 
Forecasting the Volatility of Tuna Fish Prices in North Sumatra using the ARCH Method in the Period January - April 2024 Multiyaningrum, Riska; Amri, Ihsan Fathoni; Haris, M. Al; Salsabilla, Havinka Angel; Ginasputri, Heppy Nur Asavia; Sintya, Salsabila Dhea
Eigen Mathematics Journal Vol 7 No 2 (2024): December
Publisher : University of Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/emj.v7i2.236

Abstract

Tuna (Euthynnus affinis) is one of the most important fisheries commodities in Indonesia with significant economic value, especially in its contribution to fisheries export revenue. However, the price of tuna experiences significant fluctuations that can affect local and national economic stability. This study analyzes the daily price fluctuations of tuna in the North Sumatra market from January 1, 2024 to April 29, 2024 using a time series analysis approach. Daily price data were collected and analyzed to identify existing price patterns and volatility. The Autoregressive Conditional Heteroskedasticity (ARCH) model was selected to address the heteroscedasticity in the data, which suggests that the volatility of tuna prices can be well predicted based on past price behavior. The analysis steps include identifying the optimal ARCH model using the Autocorrelation Function (ACF) and Partial Autocorrelation Function (PACF), as well as testing parameter significance and normality assumptions to validate the model fit. The results show that the ARMA (1,0,0) model is the optimal one to model the price volatility of yellow tuna with the MAPE obtained of 2.382. compared to the ARMA-ARCH method with the MAPE value obtained of 2,747. Because it still contains heteroskedasticity effects, even though the results are good, the prediction results do not closely match the original data. The model is effective in improving price forecasting accuracy, which is important to support decision-making in risk management and economic planning in the fisheries sector. The findings contribute to understanding the dynamics of the yellowtail market and optimizing strategies for fisheries management.
The ARIMA-GARCH Method in Case Study Forecasting the Daily Stock Price Index of PT. Jasa Marga (Persero) Amri, Ihsan Fathoni; Wulan Sari; Widyasari, Velia Arni; Nurohmah, Nufita; Haris, M. Al
Eigen Mathematics Journal Vol 7 No 1 (2024): June
Publisher : University of Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/emj.v7i1.174

Abstract

PT Jasa Marga is a large company in Indonesia that develop and operation the toll roads and is known as one of the blue chip companies with LQ45 shares. However, share prices have high volatility or rise and fall quickly so their value is always changing. Therefore, forecasting is needed to predict the share price of PT Jasa Marga in the future in order to know the movement of its share price. The Autoregressive Integrated Moving Average (ARIMA) method is a method that can predict data with high volatility, but has the disadvantage of residuals containing heteroscedasticity. So, the addition of the Generalized Autoregressive Conditional Heteroskedasticity (GARCH) model was carried out to overcome the heteroscedasticity problem that was initially caused by the ARIMA model so it could predict data with high volatility more optimally. Therefore, this research applies the ARIMA-GARCH method to find the best model for forecasting the daily share price index of PT Jasa Marga. The data used comes from the daily closing stock price index of PT Jasa Marga (Persero) for the period January 2015 to May 2023. The measurement of forecasting accuracy uses the Mean Absolute Percentage Error (MAPE). The forecasting results show that the best model uses ARIMA (2,1,1) - GARCH (1,3) with a MAPE value of 6.825728%, which indicates very good forecasting results because the MAPE value is <10%.
Survival Analysis Using Kaplan-Meier and Cox Regression in Hypertension Patients at Kefamenanu Regional Hospital Khikman, Muhammad Alvaro; Multiyaningrum, Riska; Kholifah , Revika Inta Nur; Sa'adah , Lydia Nur; Safira, Elfina Latifah; Sarah, Albertus Dion; Amri, Ihsan Fathoni; Haris, M. Al
Eigen Mathematics Journal Vol 8 No 2 (2025): December
Publisher : University of Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/emj.v8i2.270

Abstract

Hypertension is a chronic disease with a steadily increasing global prevalence and is one of the leading causes of serious complications. Indonesia is among the countries with a high prevalence of hypertension, necessitating an understanding of the factors influencing patient treatment duration to enhance the effectiveness of healthcare services. This study aims to analyze differences in the survival rates of hypertensive patients at Kefamenanu Hospital based on gender. The Kaplan-Meier method was used to estimate patient survival rates, while Cox Proportional Hazards regression was used to evaluate the influence of gender on survival time. The Kaplan-Meier analysis results showed that female patients had a higher probability of survival than male patients during hospitalization. However, the Cox Proportional Hazards regression analysis indicated that this difference was not statistically significant. These findings suggest that while there are differences in survival patterns, gender is not the primary determinant of the duration of care for hypertensive patients. The results of this study are expected to provide input for hospitals in designing more effective care strategies that focus on other factors that may influence patient survival time.
Co-Authors Abdul Ghufron Abidah, Khansa Ni'mal Adhwaningrum, Arullah Salsabila Ainurrofiah, Safira Al Haris, M Alwan Fadlurohman Amri, Saeful Angelina, Lea Ariska Fitriyana Ningrum Arsusma, Jesicha Arya, Abimanyu Asrirawan Astuti, Sofi Anggi Aura Hisani, Zahra Ayu Wulandari Azzahrani, Rahma Dewi Bisoumi, Yan Nazala Dannu Purwanto Daud, Khamidah Arsyad Dawi, Herculianus Rowa Dhani, Oktaviana Rahma Diani, Nandini Lova Dwi Saputri, Atika Dwi Sulistiani Ginasputri, Heppy Nur Asavia Haris, M. Al Hartanto, Raka Nurhaq Mulya Hikmah Nur Rohim, Febrian Irawan, Alfian Chandra Kaia Raissa Akmalia Khikman, Muhammad Alvaro Kholifah , Revika Inta Nur Laila Qadrini M. Al Haris Masichah, Firochul Mostfa, Ahmed A. Muhammad Fahmuddin Muhammad Ivan Ardiansyah Multiyaningrum, Riska mutiah, siti Nakib, Arman Mohammad Nisa, Rofiah Ainun Nudyawati, Elsa Nur Mahmudah Nurohmah, Nufita Nurul Azka, M. Ilham Permata, Alia Pranandira Rilvandri, Quinsy Pratama, Rifin Fadilla Priambodo, Danu Puspitasari, Linda Rahma Dhani, Oktaviana Rakhmawati, Muji Silvi Ramadhan, Wulan Nur Rohim, Febrian Hikmah Nur Sa'adah , Lydia Nur Safira, Elfina Latifah Salsabilla, Havinka Angel Saputra, Farid Sam Saputri, Atika Dwi Sarah, Albertus Dion Sintya, Salsabila Dhea Suherdi, Andri Sulistiya, Indah Supriyanto Syaharani, Nabbila Dyah Tiani Wahyu Utami Wahid, Siti Nurasriyanti Wardani, Amelia Kusuma Watur, Annisa Cahyaningrum Widyasari, Velia Arni Wulan Sari Yolan Triky Zahra Aura Hisani