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Journal : VARIANSI: Journal of Statistics and Its Application on Teaching and Research

Peramalan Jumlah Produksi Kelapa Sawit Provinsi Kalimantan Timur Menggunakan Metode Singular Spectrum Analysis Siringoringo, Meiliyani; Wahyuningsih, Sri; Purnamasari, Ika; Arumsari, Melisa
VARIANSI: Journal of Statistics and Its application on Teaching and Research Vol. 4 No. 3 (2022)
Publisher : Program Studi Statistika Fakultas MIPA UNM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35580/variansiunm46

Abstract

Singular spectrum analysis (SSA) is a nonparametric method that does not rely on assumptions such as stationary nature or residual normality. SSA separates time series data into its components, which are trend, seasonality, and error (noise). This study aimed to obtain forecasting results for the amount of oil palm production in East Kalimantan Province for the period January 2021 to December 2021 using SSA. Based on the results of the data analysis, in the process of forming the forecasting model with in-sample data, the parameter window length (L) was 24, which produced a MAPE value of 0.464%, and while the forecasting model validation process used out-sample data, it produced a MAPE value of 41.172%.
PENGELOMPOKAN PROVINSI DI INDONESIA BERDASARKAN DATA JUMLAH KEJADIAN DAN DAMPAK BENCANA BANJIR MENGGUNAKAN METODE FUZZY C-MEANS Hayati, Memi Nor; Goejantoro, Rito; Siringoringo, Meiliyani; Purnamasari , Ika; Yuniarti, Desi; Nida, Khairun; Messakh, Gerald Claudio
VARIANSI: Journal of Statistics and Its application on Teaching and Research Vol. 6 No. 01 (2024)
Publisher : Program Studi Statistika Fakultas MIPA UNM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35580/variansiunm167

Abstract

Cluster analysis is a technique used to find groups of similar data objects. The Fuzzy C-Means (FCM) method is a data grouping method where the existence of each data in a cluster is determined by the degree of membership. This study aims to determine the optimal number of clusters based on the Modified Partition Coefficient (MPC) validity index and to determine the optimal grouping results of 34 provinces in Indonesia based on data on the number of events and the impact of floods in 2017-2021. The optimal number of clusters using the FCM method is based on MPC value consists of 2 clusters, namely the first cluster consisting of 27 provinces in Indonesia and the second cluster consisting of 7 provinces in Indonesia.