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All Journal Indonesian Journal of Statistics and Its Applications Xplore: Journal of Statistics
Hari Wijayanto
Department of Statistics, IPB University, Indonesia
Computer Science & IT Decision Sciences, Operations Research & Management Engineering Mathematics Other

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STUDY ON EMD METHOD FOR PREDICTING THE PRICE OF CURLY RED CHILI IN INDONESIA Zilrahmi Zilrahmi; Hari Wijayanto; Farit M Afendi; Rizal Bakri
Indonesian Journal of Statistics and Applications Vol 4 No 2 (2020)
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.v4i2.600

Abstract

The fluctuations of curly red chili price affect the inflation rate in Indonesia. So that, the basic characteristics of price movement and correctly prediction for curly red chili price become concern in various studies. Empirical Mode Decomposition (EMD) method helps to examine behavioral characteristics of curly red chili prices in Indonesia easily. Ensemble EMD (EEMD) and modified EEMD are the decomposition method of time series which is development of EMD method. The decomposed data with EMD methods can also used for price forecast. The forecasting with ARIMA and trend polynomial performed to assess the effect of decomposition with EMD methods for forecast stability of curly red chili price in Indonesia under various conditions. The results show the most influence factor for price fluctuation of curly red chili in Indonesia is season and growing season. In this case, the ability of a decomposition method to produce the actual components that describe the pattern of data signals affect the accuracy of the predicted value obtained using the model. The predicted value using the decomposed data by modified EEMD always better than EEMD on the overall condition.
A Study on Accuracy of Paddy Harvest Area Estimation on Area Sampling Frame Method: Kajian Ketepatan Pendugaan Luas Panen Padi pada Metode Pengambilan Kerangka Sampel Area Mulianto Raharjo; Anang Kurnia; Hari Wijayanto
Indonesian Journal of Statistics and Applications Vol 6 No 1 (2022)
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.v6i1p41-49

Abstract

There was unsynchronized national rice data until 2017, which indicating that influenced by the differences in calculation methods between government agencies. The Indonesian Central Bureau of Statistics (BPS Statistics), the most responsible agency for national rice data, collected rice plant areas data using the paddy statistical assessment method (SP-Padi). Subjective elements from various parties potentially influenced the result of this assessment method. The development of a new method to overcome this matter has been started by the government since 1993. In 2018 the method, which is named the Area Sample Frame (ASF) method, was officially used by the government under the coordination of BPS. The ASF method divides the area into grids: blocks, segments, and sub-segments. This new method has several issues related to the methodology used in determining the sampling method. This study was conducted to evaluate the accuracy of paddy harvest area estimation on the ASF method through a sampling simulation process of the ASF method with various scenarios. With 20 simulated scenario combinations, it was found that the difference percentage average between the harvested area of the population and the harvested area of the sample to the sub-district area was 0.00062%, and the mean square error (MSE) was 0.0041%. So it can be concluded that the ASF methodology is an unbiased method and is good enough to accommodate various strata diversity in any region.
Identifikasi Faktor-Faktor yang Memengaruhi Prestasi Mahasiswa Menggunakan Regresi Logistik Ordinal dan Random Forest Ordinal: Studi Kasus Mahasiswa FMIPA IPB Angkatan 2015-2017 Zuhdiyah Izzatun Nisa'; Agus M Soleh; Hari Wijayanto
Xplore: Journal of Statistics Vol. 10 No. 1 (2021)
Publisher : Department of Statistics, IPB

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (267.829 KB) | DOI: 10.29244/xplore.v10i1.465

Abstract

Student achievement is the result of student learning processes and efforts. This research was conducted through a survey of students of the 2015-2017 FMIPA IPB with the selection of respondents using stratified random sampling. The purpose of this study is to identify the factors that influence the achievements of the 2015-2017 FMIPA IPB students using ordinal logistic regression and ordinal random forest. The response variable used is the PPKU GPA category and the last even semester GPA which is categorized based on the predicate of IPB graduation. The results of ordinal logistic regression get 7 explanatory variables that influence the PPKU GPA and 7 explanatory variables that influence the last even semester GPA. Explanatory variables that have a significant effect on ordinal logistic regression and become 10 variables with the highest level of importance in the ordinal random forest for both response variables are department, mother’s education, internet access in a day for games, activity in the class, and active work on a group assignment.
Co-Authors Agus M Soleh Anang Kurnia Farit M Afendi Mulianto Raharjo Rizal Bakri Zilrahmi Zilrahmi Zuhdiyah Izzatun Nisa'