Lisa Harsyiah
Program Studi Statistika, Universitas Mataram, Indonesia

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Regresi Komponen Utama dalam Mengatasi Multikolinieritas pada Faktor-Faktor yang Mempengaruhi Inflasi di Indonesia Salsabila Hadi Putri Ningrum; Khairatun Hisan; Triana Putri Ramdhani; Luzianawati Luzianawati; M. Daffa Rizki Zindawi; Lisa Harsyiah
Indonesian Journal of Applied Statistics and Data Science Vol. 2 No. 1 (2025): Mei
Publisher : Universitas Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/ijasds.v2i1.5827

Abstract

Inflation is a significant concern for a developing country like Indonesia. To effectively anticipate inflationary trends, it is essential to conduct statistical analysis to determine what factors can influence inflation. This study utilized Principal Component Regression (PCR) to address multicollinearity in the regression model linking inflation to various factors. The results revealed that transportation, food, electricity and household fuel factors positively correlate with inflation, while health, education and clothing show negative correlations. However, the resulting regression model proved to be inadequate, as evidenced by a very low R-square value. This highlights the necessity for further refinement of the model to provide better information in the context of inflation management in Indonesia.
Analisis Tren Sosial di Indonesia dengan Peta Kendali CUSUM (Studi Kasus: Perceraian, Kemiskinan, Pernikahan Dini, dan Tingkat Pendidikan) Navisah Navisah; Mawaddatul Fariha; Ketrin Jupina Ranti; Lita Astuti; Suwindah Puji Yarti; Lisa Harsyiah; Jihadil Qudsi
Indonesian Journal of Applied Statistics and Data Science Vol. 2 No. 1 (2025): Mei
Publisher : Universitas Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/ijasds.v2i1.6909

Abstract

Social changes in Indonesia, in the last ten years, have attracted the attention of researchers, especially related to the problems of divorce, early marriage, education levels, and poverty. For example, early marriage is still a major problem in some places. BPS, in 2022, reported that the rate of early marriage in Indonesia was very high, from 16.23% in 2022 to 17.32% in 2023. Several studies have shown a correlation between poverty levels, education levels, and early marriage rates. One effective statistical approach to monitoring changes in trends in time data is the Cumulative Sum Control Chart (CUSUM). The CUSUM control chart method, social data trends can be analyzed longitudinally, detecting significant changes, and mapping the time and magnitude of the shifts that occur. A total of 36 data from 4 variables in the 2022-2024 range were processed using the R application to obtain the CUSUM control chart. The results obtained showed that the variables of education level and early marriage showed more data that was within the limits of the CUSUM constraint map, while the variables of divorce rate and poverty rate had a lot of data that was out of control, which occurred a lot in the months of 2023.