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Esther Ria Matulessy
Faculty of Mathematics and Science, Universitas Papua, Manokwari, West Papua
Humanities Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Engineering Environmental Science Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Public Health Social Sciences

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The Application of VECM (Vector Error Correction Model) for Rainfall Modeling in Manokwari Regency Esther Ria Matulessy
Indonesian Journal of Multidisciplinary Science Vol. 2 No. 6 (2023): Indonesian Journal of Multidisciplinary Science
Publisher : International Journal Labs

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55324/ijoms.v2i6.483

Abstract

This study aims to determine the modeling of rainfall in Manokwari Regency with a Vector Error Correction Model (VECM) based on the period January 2012 to December 2017. In the modeling used temperature, humidity, and solar irradiation models. The research begins by looking at data stationary, if the data is not stationary, a differencing stage will be carried out to station the data. Then an optimal lag is determined and then a cointegration test is performed to determine whether there is a long-term relationship between variables on rainfall as a condition to proceed to VECM modeling. Based on VECM (1) obtained there are two relationships to changes in rainfall, namely the long-term and short-term relationships. In the long term relationship, changes in rainfall are only influenced by changes in the irradiation period of 1 (one) previous period. In the long term relationship, changes in rainfall are influenced by rainfall and irradiation period of 1 (one) previous period. In the short term relationship, changes in rainfall are only affected by changes in the irradiation period of 1 (one) previous period. When compared to ARIMA (1, 0, 2), VECM (1) can predict rainfall better because it has validation values smaller models than ARIMA (1, 0, 2).
Presenting of Special Express Mail’s Production and Revenue Data of 2022 Using Descriptive Statistics Antonio Vaticano Lekahena; Esther Ria Matulessy
Indonesian Journal of Multidisciplinary Science Vol. 2 No. 7 (2023): Indonesian Journal of Multidisciplinary Science
Publisher : International Journal Labs

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55324/ijoms.v2i7.487

Abstract

The author wants to know the results of a descriptive statistical analysis based on income and production of postal shipments in 2021 and 2022 from 3 types of services including Special Express Mail, Special Express Packages, and Corporate. Descriptive analysis is a form of research data analysis to test the generalization of research results based on one sample. There are three main things contained in statistics, namely; data, treatment of data in the form of collection, processing/analysis, analysis and drawing conclusions, and numbers. Descriptive statistics is a part of statistics that discusses how to collect and present data so that it is easy to understand and provides useful information. The conclusions that can be drawn from the results of the descriptive statistical analysis of each service are; the highest Outoging production in 2022 comes from Special Express Packages with a total production of 14,095 units or 97% of the total production, the highest outog delivery revenue in 2022 comes from Special Express Packages with a total revenue of Rp. 1.138.614.776.- or 97% of the total revenue, the highest incoming shipping production in 2022 comes from Special Express Packages with a total production of 21,235 units or 96% of the total production, the highest incoming delivery income in 2022 comes from Special Express Packages with total income of Rp. 2.650.031.160,- or 88% of the total income.
Co-Authors Antonio Vaticano Lekahena