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All Journal Rangkiang Mathematics Journal UNP Journal of Statistics and Data Science
Susrifalah, Amelia
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Computer Science & IT Decision Sciences, Operations Research & Management Mathematics Social Sciences Other

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Penerapan Algoritma Extreme Gradient Boosting dengan ADASYN untuk Klasifikasi Rumah Tangga Penerima Program Keluarga Harapan di Provinsi Sumatera Barat Susrifalah, Amelia; Vionanda, Dodi; Kurniawati, Yenni; Sulistiowati, Dwi
UNP Journal of Statistics and Data Science Vol. 3 No. 2 (2025): UNP Journal of Statistics and Data Science
Publisher : Departemen Statistika Universitas Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/ujsds/vol3-iss2/369

Abstract

Program Keluarga Harapan (PKH) is a form of social protection provided by the government to overcome poverty in Indonesia. However, challenges remain in accurately predicting eligible households. Therefore, a data-based classification method is needed to identify PKH recipients based on their factors. This research was conducted in West Sumatra Province using variables from the Data Terpadu Kesejahteraan Sosial (DTKS) variable group contained in SUSENAS 2024. Based on data from Badan Pusat Statistik (BPS) of West Sumatera Province, there are 1.790 PKH recipient households and 9.810 non-recipient households, indicating a class imbalance. Considering the large amount of data and complex variables, PKH can be analyzed using the Extreme Gradient Boosting (XGBoost) algorithm because of its ability to handle large-scale data and produce high classification performance. To address data imbalance, Adaptive Synthetic (ADASYN) was applied before analysis. The application of XGBoost with the scale_pos_weight parameter shows low classification performance, with sensitivity value of 12.3% and balanced accuracy of 55.2%. To overcome this, unbalanced data was handled using the ADASYN method. The application of XGBoost after data balancing with ADASYN showed significant performance improvement, with sensitivity value 80.4% and balanced accuracy 88.1%. In classifying PKH recipient households, the variables that make an important contribution are the age of the head of household, floor area, diploma of the head of household, floor material and number of household Members. This research shows that the combination of XGBoost and ADASYN is effective in overcoming data imbalance and improving PKH recipient classification performance.
Do Prestigious Schools Still Exist in Padang? An Exploratory Study on State Junior High School Admission 2025 in Padang Vionanda, Dodi; Wood, Raihan Attaya; Susrifalah, Amelia
Rangkiang Mathematics Journal Vol. 4 No. 2 (2025): Rangkiang Mathematics Journal
Publisher : Department of Mathematics, Universitas Negeri Padang (UNP)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/rmj.v4i2.106

Abstract

In this study, we perform an exploratory study of New Student Admission datasets for public Junior High School in Padang in 2025. We utilized tables, barplots, and boxplots to present information contained in datasets and we carried out cluster analysis using HDBSCAN algorithm. For this study we made use of admitted students’ datasets for each admission pathway of all state Junior High Schools in Padang in 2025. We carried out this study to investigate the emergence of prestigious schools among public Junior High School in Padang amid the implementation on zoning system. Our study reveals the presence of group of prestigious schools along with group of schools that admitted students mostly live nearby the schools. Hence, it is recommended for Padang Municipal government to improve the quality of schools that are not considered as prestigious schools since there are many schools that admitted students mostly live nearby the school.
Co-Authors Dodi Vionanda Dwi Sulistiowati, Dwi Wood, Raihan Attaya Yenni Kurniawati