Jurnal SINTA 2
Aplikasi Mobile (Lide) Untuk Diagnosis Tingkat Resiko Penyakit Stroke Menggunakan PTVPSO-SVM
Jurnal Teknologi Informasi dan Ilmu Komputer (JTIIK) · Vol. 3 No. 2 (2016) · pp. 147–155
- ISSN
- 2528-6579, 2355-7699
- Published
- 2016-06-20
- Publisher
- Fakultas Ilmu Komputer, Universitas Brawijaya
- Language
- en
Abstract
AbstrakPenyakit Stroke merupakan penyakit yang umum dan menduduki peringkat kedua dalam kematian di Indonesia dengan angka 11,13%. Penyakit yang mernyerang fungsi saraf otak dengan tingkat resiko bertahap. Dengan tidak hanya menyerang pada manusia usia lanjut, kini penyakit stroke dapat menyerang siapa saja. Indikator yang dapat digunakan dalam mewaspadai tingkat stroke adalah memeriksa kolestrol tubuh, HLD, LDL, dan Trigliserida. Namun faktor umum juga menjadi masalah utama namun umum. Dengan bertambahnya umum 10 tahun dimulai dari umur 55 tahun, maka tingkat resiko penyakit stroke menjadi dua kali lipat. Tingkat kewaspadaan perlu diperhatikan, sehingga dalam sewaktu-waktu untuk memeriksakan kondisi tubuh diperlukan. Lide adalah sebuah aplikasi pada smarthphone yang berbasis Android yang mengimplementasikan perhitungan algoirtma dalam menentukan tingkat resiko penyakit stroke. Lide merupakan salah satu solusi yang dibangun dalam mengontrol tingkat resiko stroke, hanya dengan memasukkan tingkat kolestrol, LDL, HDL, dan triglieserida. Dilengkapi dengan treatment bagi para pengguna, sehingga dapat melakukan penanganan awal pada tingkat-tingkat tertentu. Dalam aplikasi bergerak ini mengimplementasikan metode Particle Swarm Optimization dan Support Vector Machine untuk klasifikasi dengan menggunakan 4 fitur (kolesterol, HDL, LDL, dan Trigliserida). Dengan menggunakan metode ini, nilai akurasi yang dihasilkan mencapai 87%.Kata kunci: Stroke, PTVPSO-SVM, Aplikasi Perangkat Bergerak, LideAbstractStroke is a common disease and was ranked second in the number of death in Indonesia with 11, 13%. This disease attacks the nerve function of brain with the level of risk. Not only attacks on old age, this disease can attacks everyone. Indicators that can be used in reasonably level stroke is cholesterol, HDL, LDL, and Triglycerides. But the common factor is also becoming a major problem, however. Increasing public 10 years starting at age 55 years, then the risk level of stroke become twice. The level of alertness to note, so in any time to check the condition of the body is required. Lide is an application on an android-based smartphone which implement algorithm calculation to determining the risk level of stroke. Lide is one of solution that is built to control the risk level of stroke, by simply entering the level of LDL, HDL, Cholesterol, and Triglycerides. It is equipped with treatment for users, so that it can perform the initial handling at certain levels. This mobile application implements the method of Particle Swarm Optimization and Supprot Vector Machine for classification by using 4 features (cholesterol, LDL, HDL, and Triglycerides). By using this method, the value of the resulting accuracy is reached 87%.Keywords: Stroke, PTVPSO-SVM, Mobile Apps, Lide
Collaboration network of the authors
40 authors · 108 co-authorship links · 3 across different organisations · showing the 40 most connected
Hover or tap a name to highlight its co-authors. Double-click to open the author's page.
- University of Brawijaya
- Universitas Amikom Purwokerto
- Affiliation unknown
- Different organisations
- Same organisation
- Affiliation unknown
- Thicker line = more joint articles · bigger circle = more articles
Show as table
| Co-author | Organisation | Joint articles |
|---|---|---|
| Dhimas Anjar Prabowo | University of Brawijaya | 4 |
| Anang Hanafi | University of Brawijaya | 4 |
| Arief Andy Soebroto | University of Brawijaya | 3 |
| Muhammad Fhadli | University of Brawijaya | 3 |
| Marji . | University of Brawijaya | 2 |
| Sutrisno . | Affiliation unknown | 2 |
| Nurul Hidayat | University of Brawijaya | 2 |
| Canny Amerilyse Caesar | University of Brawijaya | 2 |
| Latifah Hanum | University of Brawijaya | 2 |
| Listiya Surtiningsih | University of Brawijaya | 2 |
| Fitra Abdurrachman Bachtiar | University of Brawijaya | 2 |
| Candra Dewi | University of Brawijaya | 2 |
| Budi Darma Setiawan | University of Brawijaya | 2 |
| Aryeswara Sunaryo | University of Brawijaya | 2 |
| Dian Eka Ratnawati | University of Brawijaya | 1 |
| Ahmad Afif Supianto | University of Brawijaya | 1 |
| Randy Cahya Wihandika | University of Brawijaya | 1 |
| Maria Tenika Frestantiya | University of Brawijaya | 1 |
| Ziya El Arief | University of Brawijaya | 1 |
| Rina Christanti | University of Brawijaya | 1 |
| Alfian Himawan | University of Brawijaya | 1 |
| Rekyan Regasari Mardi Putri | University of Brawijaya | 1 |
| Uswatun Hasanah | Universitas Amikom Purwokerto | 1 |
| Lintang Resita Mayangsari | University of Brawijaya | 1 |
| Andhica Pratama | University of Brawijaya | 1 |
| Galang Gilang Ramadhan | University of Brawijaya | 1 |
| Mochammad Ainun Najib | University of Brawijaya | 1 |
| Handika Agus Fauzi | University of Brawijaya | 1 |
| Sutrisno Sutrisno | University of Brawijaya | 1 |
| Maryamah . | University of Brawijaya | 1 |
| Moh. Fadel Asikin | University of Brawijaya | 1 |
| Daisy Kurniawaty | University of Brawijaya | 1 |
| Novanto Yudistira | University of Brawijaya | 1 |
Affiliations come from OpenAlex; journal OAI-PMH metadata carries none. Authors without an OpenAlex ID are matched by name, which can merge or split people.