Hendradi, Aulia Ihza (2022) Rancang Bangun Modul Skrining Deteksi Risiko Stroke Dengan Rule-Based System Untuk Aplikasi Apadok. Other thesis, Institut Teknologi Sepuluh Nopember.
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Abstract
Stroke merupakan salah satu penyakit kronis. Akan tetapi penanganan stroke di Indonesia masih dapat dihitung tidak cukup baik, dibuktikan dengan peningkatan prevalensi faktor risiko dan capaian skrining risiko stroke yang masih rendah. Didasari hal tersebut, Tugas Akhir ini diupayakan untuk meningkatkan capaian skrining dan edukasi stroke dengan cara menyediakan akses ke skrining stroke yang lebih mudah dalam bentuk modul skrining stroke yang merupakan bagian dari aplikasi Apadok yang berbasis Android. Saat ini aplikasi skrining stroke yang dapat digunakan adalah Stroke Riskometer, dimana skrining yang diterapkan tidak terintegrasi dengan modul skrining penyakit lain. Modul yang akan dikembangkan terintegrasi dengan modul skrining deteksi risiko stroke, diabetes, dan kardiovaskular. Dalam pembangunan modul skrining deteksi risiko stroke Apadok dilakukan tahapan-tahapan dimulai dari tahapan pertama dengan merancang aturan yang dibutuhkan untuk algoritma. Tahapan kedua dilakukan penyesuaian terhadap aturan-aturan yang sudah dirancang. Tahapan ketiga dirancang alur serta pseudocode algoritma berdasarkan aturan yang sudah disesuaikan dengan kebutuhan klien. Tahapan keempat diimplementasikan perangkat lunak yang siap digunakan. Modul skrining deteksi risiko stroke akan menghasilkan keluaran berupa tingkat risiko penyakit stroke yang akan ditampilkan pada layar pengguna. Tingkat risiko penyakit stroke akan diperoleh dari jawaban skrining yang diisi oleh pengguna ketika melakukan skrining. Algoritma Rule-Based System yang dibangun untuk deteksi risiko stroke memiliki nilai akurasi sebesar 85,71%.
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Stroke is a chronic disease. However, stroke management in Indonesia can still be counted as not good enough, as evidenced by the increasing prevalence of risk factors and the low achievement of stroke risk screening. Based on this, this final project seeks to improve stroke screening and education outcomes by providing easier access to stroke screening in the form of a stroke screening module which is part of the Android-based Apadok application. Currently, the stroke screening application that can be used is the Stroke Riskometer, where the applied screening is not integrated with other disease screening modules. The module to be developed is integrated with the screening module for stroke, diabetes, and cardiovascular risk detection. In the development of the Apadok stroke risk detection screening module, stages were carried out starting from the first stage by designing the rules needed for the algorithm. The second stage is adjustments to the rules that have been designed. The third stage is designing the flow and pseudocode algorithm based on rules that have been adapted to the client's needs. The fourth stage is the implementation of ready-to-use software. The stroke risk detection screening module will produce output in the form of a stroke risk level which will be displayed on the user's screen. The level of risk of stroke will be obtained from the screening answers filled in by the user when doing the screening. The Rule-Based System algorithm which was built for stroke risk detection has an accuracy value of 85.71%.
| Item Type: | Thesis (Other) |
|---|---|
| Additional Information: | RSIf 005.276 2 Hen r-1 2022 |
| Uncontrolled Keywords: | Stroke, Skrining, Risiko, Rule-Based System, Apadok. Stroke, Screening, Risk, Rule-Based System, Apadok. |
| Subjects: | Q Science > QA Mathematics > QA76.9.I58 Recommender systems (Information filtering) |
| Divisions: | Faculty of Intelligent Electrical and Informatics Technology (ELECTICS) > Informatics Engineering > 55201-(S1) Undergraduate Thesis |
| Depositing User: | Mr. Marsudiyana - |
| Date Deposited: | 26 May 2026 01:58 |
| Last Modified: | 26 May 2026 01:58 |
| URI: | http://repository.its.ac.id/id/eprint/133418 |
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