Annisa Hadyana Fadhilah, . (2025) PREDIKSI RISIKO GANGGUAN KESEHATAN MENTAL MENGGUNAKAN ALGORITMA RANDOM FOREST DENGAN PENERAPAN MODEL BERBASIS APLIKASI MOBILE. Skripsi thesis, Universitas Pembangunan Nasional Veteran Jakarta.
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Abstract
Mental health issues have received increasing attention in recent years, in line with the rising number of mental disorder cases. To support early detection and prevention of mental health problems, this study developed a risk prediction model using the Random Forest algorithm. The dataset was obtained from the DASS-21 questionnaire, which includes various psychological symptoms related to three risk categories: stress, anxiety, and depression. The model training process involved data preprocessing, handling class imbalance using the SMOTE method, and tuning the model's hyperparameters. The results showed that the Random Forest algorithm achieved good predictive performance with an accuracy of 91% for depression, 86% for anxiety, and 84% for stress. In addition, the precision, recall, and F1-score also demonstrated strong and balanced results. This model has proven effective in predicting the risk level of mental health disorders and can be utilized as a decision support system for early detection and prevention of more severe mental health issues.
| Item Type: | Thesis (Skripsi) |
|---|---|
| Additional Information: | [No. Panggil: 2110511142] [Pembimbing 1: Nur Hafifah Matondang] [Pembimbing 2: Kharisma Wiati Gusti] [Penguji 1: Widya Cholil] [Penguji 2: Muhammad Adrezo] |
| Uncontrolled Keywords: | Mental Health Disorders, Mental Health, Machine Learning, Prediction, Random Forest |
| Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science Q Science > QA Mathematics > QA76 Computer software T Technology > T Technology (General) |
| Divisions: | Fakultas Ilmu Komputer > Program Studi Informatika (S1) |
| Depositing User: | ANNISA HADYANA FADHILAH |
| Date Deposited: | 06 Aug 2025 02:34 |
| Last Modified: | 06 Aug 2025 02:34 |
| URI: | http://repository.upnvj.ac.id/id/eprint/38040 |
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