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All Journal al-Afkar, Journal For Islamic Studies Jurnal Statistika dan Aplikasinya Xplore: Journal of Statistics
Akbar Rizki
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Agriculture, Biological Sciences & Forestry Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Engineering Mathematics Social Sciences Other

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Analisis pada Data Harga Cabai Merah Keriting Indonesia menggunakan Model ARIMAX Muhammad Ali Umar; Farit Mochamad Afendi; Akbar Rizki; Budi Waryanto
Xplore: Journal of Statistics Vol. 7 No. 3 (2018): 31 Desember 2018
Publisher : Department of Statistics, IPB

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

The model used to analyze the time series data with one variable is Autoregresive Integrated Moving Average (ARIMA). In some cases, ARIMA model is not good enough in modeling. For instance, the time series data influenced by the outside patterns of observed variable that affect the variable. One way to capture the other patterns is with Autoregressive Integrated Moving Average Exogenous (ARIMAX). The model principle of ARIMAX is by making the other variables as the independent variables in the model used. Calender variation effects are independent variables which are often used in the modeling. In this research, ARIMAX model is applied on the weekly data of red curly chili in the period of Januari 1, 2011 to April 30, 2018. The evaluation result is there are some influential variables such as the peak of rainy season, election campaign, Eid Fitr, Eid al-Adha, and also Imlek. The best ARIMAX model gained is ARIMAX(1,1,2) model with the MAPE value of 5.054 â„….
Perbandingan Kinerja Regresi Conway-Maxwell-Poisson dan Poisson-Tweedie dalam Mengatasi Overdispersi Melalui Data Simulasi Ahmad Rifai Nasution; Kusman Sadik; Akbar Rizki
Xplore: Journal of Statistics Vol. 11 No. 3 (2022): Vol. 11 No. 3 (2022)
Publisher : Department of Statistics, IPB

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (310.954 KB) | DOI: 10.29244/xplore.v11i3.1018

Abstract

Poisson regression is a standard method to model count data. Modeling count data frequently causes overdispersion which means that Poisson regression is less precise to model it as Poisson regression has the assumption of equidispersion. Overdispersion can be overcome by using Conway-Maxwell-Poisson (COM-Poisson) and Poisson Tweedie (Poisson-Tw) regression. The best model is determined based on the lowest value of RMSE, absolute bias, variance of parameter estimator, AIC, and BIC. This research uses simulation data. The response variable of simulation data is generated to follow Generalized Poisson distribution with combinations of and The result of simulation study shows that COM-Poisson and Compound Poisson-Tw are the alternatives to model overdispersed count data, but COM-Poisson is better to overcome overdispersion with higher dispersion parameter.
The Concept of Educational Management at Ma'had Aly Al Mukmin Nurdin Urbayani; Rakhmad Agung Hidayatullah; Akbar Rizki; Ahmad Fauzan; Amir Reza Kusuma
al-Afkar, Journal For Islamic Studies Vol. 8 No. 4 (2025)
Publisher : Perkumpulan Dosen Fakultas Agama Islam Indramayu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31943/afkarjournal.v8i4.1679

Abstract

Educational management is a fundamental order in the implementation of education that is applied in the development of education. So in this discussion, Islamic educational management is interpreted as the art and science of managing Islamic educational resources to achieve Islamic educational goals effectively and efficiently in planning, implementation and results. Therefore, basic knowledge is needed in order to form a perfect and in-depth understanding of the science being studied, namely, an understanding of the concept of Islamic educational management that takes the perspective of the Qur'an, As-Sunnah and applicable laws as the basis for implementing Islamic educational management. by using this research analysis method, it produces the learning method applied in Ma'had Aly Al Mukmin currently there are three methods or learning systems. Namely intracurricular, co-curricular, and extracurricular. The intracurricular learning method is the core learning method or the main learning that we can later convey to students.
COMPARISON OF SIMPLEX AND NELDER-MEAD OPTIMIZATION METHODS IN QUANTILE REGRESSION FOR BOGOR CITY RAINFALL ANALYSIS Erira, Salsa Rifda; Audina, Delia Fitri; Virgie, Meriza Immanuela; Suhaeri, ⁠Bulan Cahyani; Abyan, Muhammad Fatih; Akbar Rizki; Sartono, Bagus
Jurnal Statistika dan Aplikasinya Vol. 9 No. 2 (2025): Jurnal Statistika dan Aplikasinya
Publisher : LPPM Universitas Negeri Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21009/JSA.09203

Abstract

Predicting extreme rainfall is crucial for supporting planning in the agricultural sector, infrastructure development, and disaster mitigation in the city of Bogor. However, the asymmetric distribution of daily rainfall and the presence of outliers make linear regression methods less suitable. Quantile regression offers an alternative that captures the influence of explanatory variables across different parts of the data distribution, particularly in the extreme regions. This study compares the Simplex and Nelder-Mead methods for estimating quantile regression parameters on extreme rainfall data in Bogor. Daily rainfall data were obtained from the West Java BMKG Climate Station for the period from May 2024 to April 2025, comprising 365 observations, with four explanatory variables: average temperature, average humidity, sunshine duration, and average wind speed. Modeling was conducted at the 0.75, 0.85, and 0.95 quantiles to represent extreme rainfall. The results show that the Simplex method outperformed Nelder-Mead, as indicated by lower Pinball Loss and Mean Absolute Error (MAE) values at most quantiles. Humidity and average wind speed had a significantly positive effect on extreme rainfall intensity, while average temperature had a negative effect. Sunshine duration showed less consistent effects. Overall, the Simplex method is recommended for quantile regression optimization in extreme rainfall data due to its greater stability and accuracy in generating model parameters. However, this study is limited by the number of explanatory variables and the relatively short observation period. Incorporating additional variables such as air pressure, ENSO index, or topographical data, along with extending the observation period, could improve model accuracy and generalizability in future research.
Co-Authors Abyan, Muhammad Fatih Ahmad Fauzan Ahmad Rifai Nasution Amir Reza Kusuma Audina, Delia Fitri Bagus Sartono Budi Waryanto Erira, Salsa Rifda Farit Mochamad Afendi Kusman Sadik Muhammad Ali Umar Nurdin Urbayani Rakhmad Agung Hidayatullah Suhaeri, ⁠Bulan Cahyani Virgie, Meriza Immanuela