Jurnal SINTA 2
Prediksi Tinggi Muka Air (TMA) Untuk Deteksi Dini Bencana Banjir Menggunakan SVR-TVIWPSO
Jurnal Teknologi Informasi dan Ilmu Komputer (JTIIK) · Vol. 2 No. 2 (2015) · pp. 79–86
- ISSN
- 2528-6579, 2355-7699
- Published
- 2015-07-22
- Publisher
- Fakultas Ilmu Komputer, Universitas Brawijaya
- Language
- en
Abstract
Abstrak Banjir merupakan salah satu jenis bencana alam yang tidak dapat diprediksi kedatangannya, salah satu penyebabnya adalah adanya hujan yang terus – menerus(dari peristiwa alam). Faktor penyebab banjir dari segi meteorologi yaitu curah hujan yang tinggi dan air laut yang sedang pasang sehingga mengakibatkan tinggi permukaan air meningkat. Analisis terhadap data curah hujan serta tinggi permukaan air setiap periodenya dirasa masih belum dapat menyelesaikan permasalahan yang ada. Oleh karena itu, pada penelitian ini diusulkan teknik integrasi metode Time Variant Inertia Weight Particle Swarm Optimization(TVIWPSO) dan Support Vector Regression(SVR). Implementasi memadukan metode Regresi yaitu SVR untuk forecasting TMA, sedangkan TVIWPSO digunakan untuk mengoptimalisasi parameter – parameter yang digunakan di dalam SVR untuk memperoleh kinerja yang maksimal dan hasil yang akurat. Harapannya sistem ini akan dapat membantu mengatasi permasalahan untuk pendeteksian dini bencana banjir karena faktor cuaca yang tidak menentu. Hasil pengujian yang didapat dari 10 data bulanan yang berbeda menunjukkan bahwa didapatkan nilai error terkecil sebesar 0.00755 dengan menggunakan Mean Absolute Error untuk data Juni 2007 dengan menggunakan integrasi metode SVR-TVIWPSO. Kata Kunci: Support Vector Regression, Tinggi Muka Air, Time Variant Inertia Weight Particle Swarm Optimization. Abstract Flood is one type of natural disaster that can not be predicted its arrival, one reason is the rain that constantly occurs (from natural events). Factors that cause flooding in terms of meteorology are high rainfall and sea water was high, resulting in high water level increases. Analysis of rainfall data and water level in each period it is still not able to solve existing problems. Therefore, in this study the method proposed integration techniques Time Variant Inertia Weight Particle Swarm Optimization (TVIWPSO) and Support Vector Regression (SVR). Implementation combines regression method for forecasting TMA is SVR, while TVIWPSO used to optimize parameters that used in the SVR to obtain maximum performance and accurate results. Hope this system will be able to help solve the problems for the early detection of floods due to erratic weather. The result of forecasting experiment in water level forecasting from 10 monthly different data show that the smallest error rate is amount to 0.00755 using Mean Absolute Error for June 2007 with the integration method SVR-TVIWPSO. Keywords: Support Vector Regression, water level, Time Variant Inertia Weight Particle Swarm Optimization.
Collaboration network of the authors
40 authors · 110 co-authorship links · 6 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
- Institut Teknologi Sepuluh Nopember
- 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 |
|---|---|---|
| Daneswara Jauhari | University of Brawijaya | 3 |
| Dhimas Anjar Prabowo | University of Brawijaya | 3 |
| Nurul Hidayat | University of Brawijaya | 3 |
| Canny Amerilyse Caesar | University of Brawijaya | 3 |
| Latifah Hanum | University of Brawijaya | 3 |
| Dahnial Syauqy | University of Brawijaya | 3 |
| Sutrisno . | Affiliation unknown | 2 |
| Muhammad Fhadli | University of Brawijaya | 2 |
| Anang Hanafi | University of Brawijaya | 2 |
| Listiya Surtiningsih | University of Brawijaya | 2 |
| Fitra Abdurrachman Bachtiar | University of Brawijaya | 2 |
| Fitri Utaminingrum | University of Brawijaya | 2 |
| Hurriyatul Fitriyah | University of Brawijaya | 2 |
| Rizal Maulana | University of Brawijaya | 2 |
| Muhammad Ali Fauzi | University of Brawijaya | 2 |
| Rekyan Regasari Mardi Putri | University of Brawijaya | 2 |
| Agus Zainal Arifin | Institut Teknologi Sepuluh Nopember | 1 |
| Naser Jawas | Institut Teknologi Sepuluh Nopember | 1 |
| Ahmad Afif Supianto | University of Brawijaya | 1 |
| Candra Dewi | University of Brawijaya | 1 |
| Rina Christanti | University of Brawijaya | 1 |
| Budi Darma Setiawan | University of Brawijaya | 1 |
| Lailil Muflikhah | University of Brawijaya | 1 |
| Muhammad Syafiq | University of Brawijaya | 1 |
| Achmad Jafar Al Kadafi | University of Brawijaya | 1 |
| Rizka Husnun Zakiyyah | University of Brawijaya | 1 |
| Wanda Athira Luqyana | University of Brawijaya | 1 |
| Uswatun Hasanah | Universitas Amikom Purwokerto | 1 |
| Lintang Resita Mayangsari | University of Brawijaya | 1 |
| Andhica Pratama | University of Brawijaya | 1 |
| Mochammad Ainun Najib | University of Brawijaya | 1 |
| Handika Agus Fauzi | University of Brawijaya | 1 |
| Nurulita Purnama Putri | Affiliation unknown | 1 |
| Adhi Harmoko Saputro | Affiliation unknown | 1 |
| Ratih Prasetya | Affiliation unknown | 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.