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Journal : Mathematical Journal of Modelling and Forecasting

Application of Principal Component Analysis in Identifying Factors Affecting the Human Development Index Faisal, Muhammad; Fitri, Fadhilah; Zilrahmi
Mathematical Journal of Modelling and Forecasting Vol. 2 No. 2 (2024): December 2024
Publisher : Universitas Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/mjmf.v2i2.26

Abstract

This study examines the Human Development Index (HDI) in West Sumatra Province in 2023. The HDI is an essential indicator for measuring the success of efforts to improve the quality of human life. This research aims to identify the key factors that influence the HDI. The HDI is constructed from three fundamental dimensions that indicate human quality of life: health, education, and economy. The factors within each dimension tend to be strongly correlated, as they mutually influence one another, potentially leading to multicollinearity issues. Therefore, an analysis is conducted to reduce the number of original variables into new orthogonal variables while preserving the total variance of the original variables using Principal Component Analysis (PCA). Based on this background, the study applies PCA to address multicollinearity and to identify new, more representative variables. The study findings indicate that the factors influencing the HDI are the education and economic and health welfare indexes.
Application of the K-Means Clustering Algorithm to the Case of Stunting Risk Families in Districts/Cities of West Sumatra Province in 2023 Widiyanti; Fitri, Fadhilah
Mathematical Journal of Modelling and Forecasting Vol. 2 No. 2 (2024): December 2024
Publisher : Universitas Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/mjmf.v2i2.29

Abstract

Stunting is one of the indicators of chronic nutritional status that has a long-term effect on child growth; the main contributing factors are households that do not have access to clean drinking water, proper sanitation facilities, and other factors. The adverse effects experienced by stunted children are reduced cognitive ability, learning ability, decreased endurance, and can lead to new diseases such as diabetes, heart disease, and many other diseases. This study uses the K-Means Cluster method to group the Regency / City of West Sumatra Province in 2023 regarding cases of stunting risk families. K-Means Cluster analysis is an analysis used to group data based on similar features or characteristics. From the results of the study, it can be concluded that the clustering of 19 regencies/cities in West Sumatra Province resulted in 2 groups (clusters): cluster 1 consists of 12 regency/city members, and cluster 2 consists of 7 regency/city members. The characteristic results obtained from each cluster formed are cluster 2 shows families with better conditions than cluster 1.
Comparison of the Fuzzy Time Series Chen Model and the Heuristic Model in Forecasting the Number of International Tourists in West Sumatra Rizki Akbar; Fitri, Fadhilah; Vionanda, Dodi; Mukhti, Tessy Octavia
Mathematical Journal of Modelling and Forecasting Vol. 2 No. 1 (2024): June 2024
Publisher : Universitas Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/mjmf.v2i1.20

Abstract

The Fuzzy Time Series Chen and Heuristic are two forecasting methods based on fuzzy logic used to predict values in time series. The FTS Chen and Heuristic models have almost identical forecasting processes, but the main difference lies in how they develop fuzzy logical relationships. The FTS Chen model uses Fuzzy Logical Relationship Groups obtained from the results of Fuzzy Logical Relationships for the forecasting process. On the other hand, the FTS Heuristic model uses Fuzzy Logical Relationships directly in the forecasting process. Fuzzy Logical Relationships are a collection of fuzzy logical relationships used to connect values in time series. By using Fuzzy Logical Relationships, the Heuristic model can predict values in time series more accurately and effectively. The forecasting is done to plan the development of tourism infrastructure, determine service needs, and optimize tourism promotion. The data shows that the number of foreign tourists visiting West Sumatra has continued to grow from 2006 to 2023. The comparison of the accuracy of the forecasting results of FTS Chen and Heuristic models for foreign tourists in West Sumatra yielded a MAPE of 0.241% for FTS model Chen and 0.194% for FTS model Heuristic. This indicates that the best forecasting model for foreign tourists is the Heuristic model due to its lower MAPE value.