Identification of Housing Eligibility Status Using Family Data in Samarinda City

Antonieta Aryuka Paskalia Nggotu ; Hamdani ; Hamdani ; Anindita Septiarini
International Journal of Applied Mathematics and C... 📅 2026 Vol 3, No 2 🔗 DOI: 10.62951/ijamc.v3i2.294
Abstract
The issue of uninhabitable houses still requires an accurate identification mechanism because the manual data collection process has the potential to be time-consuming, costly, and subject to subjectivity in determining aid priorities. This study aims to develop a classification model to identify habitable and uninhabitable houses based on family socioeconomic data using the Random Forest algorithm. The research method includes data preprocessing, data division using stratified split in three scenarios, baseline model development, and optimization through hyperparameter tuning using GridSearchCV with 3-fold cross-validation and balanced class_weight parameters. The data used includes variables such as education type, employment status, occupation type, number of family members, and family insurance type. The test results show that the 70:30 data division scenario after tuning provides the best performance with a recall value of 0.5797 for uninhabitable houses and an F1-score of 0.4746. Feature importance analysis shows that education type and employment status are the most influential variables in the classification. The results of this study show that the model built is capable of increasing sensitivity in detecting uninhabitable houses to support more objective field survey prioritization.
Keywords
Uninhabitable Housing; Random Forest; Classification; Hyperparameter Tuning; GridSearchCV
How to Cite

Antonieta Aryuka Paskalia Nggotu, et al. (2026). Identification of Housing Eligibility Status Using Family Data in Samarinda City. International Journal of Applied Mathematics and Computing, 3(2). https://doi.org/10.62951/ijamc.v3i2.294

Antonieta Aryuka Paskalia Nggotu; Hamdani, Hamdani; Anindita Septiarini, "Identification of Housing Eligibility Status Using Family Data in Samarinda City," International Journal of Applied Mathematics and Computing, vol. 3, no. 2, 2026.

Antonieta Aryuka Paskalia Nggotu; Hamdani, Hamdani; Anindita Septiarini. "Identification of Housing Eligibility Status Using Family Data in Samarinda City." International Journal of Applied Mathematics and Computing, vol. 3, no. 2, 2026.

Antonieta Aryuka Paskalia Nggotu; Hamdani, Hamdani; Anindita Septiarini. "Identification of Housing Eligibility Status Using Family Data in Samarinda City." International Journal of Applied Mathematics and Computing 3, no. 2 (2026).

Antonieta Aryuka Paskalia Nggotu, et al. (2026) 'Identification of Housing Eligibility Status Using Family Data in Samarinda City', International Journal of Applied Mathematics and Computing, 3(2). doi: 10.62951/ijamc.v3i2.294.

Antonieta Aryuka Paskalia Nggotu; Hamdani, Hamdani; Anindita Septiarini. Identification of Housing Eligibility Status Using Family Data in Samarinda City. International Journal of Applied Mathematics and Computing. 2026;3(2).

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