Massangka, Aathifah Dewantari Wirya (2026) Jagajantung: Rule-Based Advisor System untuk Saran Aktivitas Fisik dan Berhenti Merokok berdasarkan Tingkat Risiko Penyakit Kardiovaskular. Other thesis, Institut Teknologi Sepuluh Nopember.
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Abstract
Penyakit kardiovaskular (CVD) merupakan penyebab kematian utama secara global yang dipengaruhi oleh gaya hidup sedenter dan kebiasaan merokok. Meskipun aktivitas fisik rutin efektif sebagai pencegahan, intensitas olahraga yang tidak sesuai profil klinis berisiko memicu kejadian fatal. Oleh karena itu, penelitian ini mengembangkan “JagaJantung”, sebuah advisor system berbasis website untuk memberikan saran aktivitas fisik dan strategi berhenti merokok yang aman dan sesuai kondisi klinis pengguna. Sistem dibangun menggunakan metode Rule Based Forward Chaining berdasarkan pedoman European Society of Cardiology (ESC). Logika komputasi memprioritaskan deteksi kondisi klinis kritis sebelum menghitung estimasi risiko fatal 10 tahun menggunakan model SCORE (Systematic Coronary Risk Evaluation), guna mengklasifikasikan pengguna ke dalam empat kategori risiko kardiovaskular (Low, Moderate, High, Very High). Evaluasi sistem mencakup validasi klinis dan pengujian penerimaan pengguna. Validasi oleh Dokter Spesialis Jantung (Sp.JP) mengonfirmasi bahwa mekanisme fleksibilitas parameter usia, perluasan kategori riwayat merokok, dan tips keamanan untuk olahraga intensitas tinggi telah aman dan sesuai standar medis. Pengujian User Acceptance Test (UAT) menggunakan System Usability Scale (SUS) pada 30 responden memperoleh skor rata-rata 86,5. Nilai tersebut menempatkan sistem pada tingkat penerimaan acceptable dengan adjective rating excellent, menegaskan bahwa JagaJantung merupakan alat bantu kesehatan digital yang user-friendly, aman, dan efektif dalam memitigasi risiko kardiovaskular masyarakat.
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Cardiovascular disease (CVD) is the leading cause of death globally, significantly influenced by a sedentary lifestyle and smoking habits. Although regular physical activity is effective for prevention, exercise intensity that is inconsistent with an individual's clinical profile risks triggering fatal events. Therefore, this research developed "JagaJantung," a website-based advisor system designed to provide safe physical activity recommendations and smoking cessation strategies tailored to the user's clinical condition. The system was built using a Rule-Based method with a Forward Chaining inference approach, referring to the European Society of Cardiology (ESC) guidelines. The computational logic prioritizes the detection of critical clinical conditions before calculating the 10-year fatal risk estimation using the SCORE (Systematic Coronary Risk Evaluation) model, thereby classifying users into four cardiovascular risk categories (Low, Moderate, High, and Very High). The system evaluation involved clinical validation and user acceptance testing. Validation by a Cardiologist confirmed that the age parameter flexibility mechanism, the expansion of smoking history categories, and
the safety tips for high-intensity exercise are safe and comply with medical standards. Furthermore, the User Acceptance Test (UAT) utilizing the System Usability Scale (SUS) on 30 respondents yielded an average score of 86,5. This score places the system at an "acceptable" level with an "excellent" adjective rating, affirming that JagaJantung is a user-friendly, safe, and effective digital health tool for mitigating cardiovascular risk in the community.
| Item Type: | Thesis (Other) |
|---|---|
| Uncontrolled Keywords: | Advisor System, Aktivitas Fisik, Forward Chaining, Rule-Based, Penyakit Kardiovaskular, SCORE, Advisor System, Cardiovascular Disease, Forward Chaining, Physical Activity, Rule-Based, SCORE |
| Subjects: | Q Science > QA Mathematics > QA76.76.E95 Expert systems |
| Divisions: | Faculty of Intelligent Electrical and Informatics Technology (ELECTICS) > Information System > 57201-(S1) Undergraduate Thesis |
| Depositing User: | Aathifah Dewantari Wirya Massangka |
| Date Deposited: | 28 Jul 2026 03:49 |
| Last Modified: | 28 Jul 2026 03:49 |
| URI: | http://repository.its.ac.id/id/eprint/138400 |
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