Hidayanti, Aliefia Rosa (2026) Sistem Skrining Angina Pektoris Dengan Menggunakan Algoritma Random Forest di Rumah Sakit Perkebunan Jember Klinik. Undergraduate thesis, Politeknik Negeri Jember.
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Abstract
Angina pectoris is one of the coronary heart diseases characterized by chest pain caused by reduced blood flow to the heart muscle. Delays in early screening may increase the risk of more serious complications, highlighting the need for a system that can support rapid and accurate screening. Based on a preliminary study conducted at RS Perkebunan Jember Klinik, angina pectoris was among the three most common inpatient diseases in 2024. This study aimed to develop a web-based angina pectoris screening system using the Random Forest algorithm at RS Perkebunan Jember Klinik. This study focused on the development of a machine learning model using the Cross-Industry Standard Process for Data Mining (CRISP-DM) methodology. The research utilized 357 electronic medical records of patients diagnosed with angina pectoris and non-angina pectoris. The Random Forest algorithm achieved an accuracy of 98.61%, precision of 97.50%, recall of 100.00%, F1-score of 98.73%, ROC-AUC of 0.9992, sensitivity of 1.0000, and specificity of 0.9697, resulting in a classification model that was integrated into the screening system for prediction. The system was developed using the Waterfall model. System testing was conducted using the Black Box Testing method, and the results showed that all system functions operated properly. It is recommended that RS Perkebunan Jember Klinik integrate the screening system with the Electronic Medical Record (EMR) system so that the screening results can be utilized as supporting information for clinical decision-making
| Item Type: | Thesis (Undergraduate) | ||||||
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| Uncontrolled Keywords: | Angina Pektoris, Random Forest, CRISP-DM, Waterfall, Sistem Skrining, Website. | ||||||
| Subjects: | 260 - Rumpun Ilmu Kedokteran > 270 - Ilmu Kedokteran Spesialis > 285 - Penyakit Jantung 410 - Rumpun Ilmu Teknik > 450 - Teknik Elektro dan Informatika > 458 - Teknik Informatika 340 - Rumpun Ilmu Kesehatan > 350 - Ilmu Kesehatan Umum > Sistem Informasi Kesehatan |
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| Divisions: | Jurusan Kesehatan > Prodi D4 Manajemen Informasi Kesehatan > Tugas Akhir | ||||||
| Depositing User: | Aliefia Rosa Hidayanti | ||||||
| Date Deposited: | 21 Sep 2026 00:40 | ||||||
| Last Modified: | 21 Sep 2026 00:40 | ||||||
| URI: | https://sipora.polije.ac.id/id/eprint/60308 |
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