Pramoedya, Erlangga Candra (2026) Analisis Periode Balik Gelombang Signifikan di Perairan Pulau Jawa Menggunakan Metode Annual Maxima–Generalized Extreme Value dan Peak Over Threshold–Generalized Pareto Distribution Berbasis Data ERA5 ECMWF. Masters thesis, Institut Teknologi Sepuluh Nopember.
![[thumbnail of 6016251030-Master_Thesis.pdf]](http://repository.its.ac.id/style/images/fileicons/text.png) |
Text
6016251030-Master_Thesis.pdf - Accepted Version Restricted to Repository staff only Download (6MB) | Request a copy |
Abstract
Perairan Pulau Jawa merupakan salah satu kawasan maritim tersibuk di Indonesia, mencakup perairan selatan yang berbatasan dengan Samudra Hindia dan perairan utara di Laut Jawa, sehingga membutuhkan informasi tinggi gelombang desain yang akurat dan terdistribusi spasial untuk perencanaan infrastruktur pesisir. Penelitian ini menganalisis periode balik gelombang signifikan (Hs) menggunakan dua metode nilai ekstrem secara paralel, yaitu Annual Maxima–Generalized Extreme Value (AM–GEV) dan Peak Over Threshold–Generalized Pareto Distribution (POT–GPD), berbasis data time series Hs per jam dari reanalisis ERA5 ECMWF resolusi 0,5° × 0,5° pada 161 titik grid periode 2001–2020. Parameter distribusi diestimasi menggunakan Maximum Likelihood Estimation (MLE) dan diverifikasi melalui uji Kolmogorov-Smirnov dan Q-Q Plot, kemudian dipetakan secara spasial untuk periode ulang T = 2, 5, 10, 25, 50, dan 100 tahun menghasilkan 12 peta distribusi gelombang desain. Hasil menunjukkan kontras tajam antara Selatan Jawa (high-energy zone, Hs mean 1,78–1,92 m, return level T=100 sebesar 4,30–4,78 m) dan Utara Jawa (fetch-limited zone, Hs mean 0,40–0,42 m, T=100 sebesar 1,27–3,76 m). Metode AM–GEV konsisten dengan POT–GPD pada 86,9% dari 161 stasiun (selisih <10%), dan tetap konsisten terhadap data independen 2021–2025 pada periode ulang pendek hingga menengah. Selain itu, ENSO terbukti berpengaruh lebih dominan terhadap Hs ekstrem dibandingkan IOD (21,1% vs 1,9% stasiun signifikan). Hasil penelitian ini dapat dimanfaatkan sebagai dasar informasi gelombang desain bagi perencanaan infrastruktur pesisir di sekeliling Pulau Jawa.
=========================================================================================================================================
Java Island's waters constitute one of Indonesia's busiest maritime regions, encompassing the southern coast bordering the Indian Ocean and the northern coast within the Java Sea, requiring accurate, spatially distributed design wave height information for coastal infrastructure planning. This study analyzes significant wave height (Hs) return periods using two parallel extreme value methods, Annual Maxima–Generalized Extreme Value (AM–GEV) and Peaks-Over-Threshold–Generalized Pareto Distribution (POT–GPD), based on hourly Hs time-series from the ERA5 ECMWF reanalysis at 0.5° × 0.5° resolution across 161 grid points for 2001–2020. Distribution parameters were estimated via Maximum Likelihood Estimation (MLE) and verified through the Kolmogorov-Smirnov test and Q-Q Plots, then spatially mapped for return periods of T = 2, 5, 10, 25, 50, and 100 years, producing 12 design wave height distribution maps. Results reveal a sharp contrast between southern Java (high-energy zone, mean Hs 1.78–1.92 m, T=100 return level of 4.30–4.78 m) and northern Java (fetch-limited zone, mean Hs 0.40–0.42 m, T=100 of 1.27–3.76 m). AM–GEV remained consistent with POT–GPD at 86.9% of the 161 stations (difference <10%), and stayed consistent against independent 2021–2025 data at short-to-medium return periods. ENSO also showed a more dominant influence on extreme Hs than IOD (21.1% vs 1.9% of stations significant). These findings provide a basis for design wave information supporting coastal infrastructure planning around Java Island.
| Item Type: | Thesis (Masters) |
|---|---|
| Uncontrolled Keywords: | Analisis Nilai Ekstrem, Analisis Ambang Batas, ENSO dan IOD, Infrastruktur Berkelanjutan, Infrastruktur Tangguh, Extreme Value Analysis, ENSO and IOD, Resilient Infrastructure, Sustainable Infrastructure, Threshold Selection Analysis |
| Subjects: | G Geography. Anthropology. Recreation > GC Oceanography > GC205 Waves Q Science > QA Mathematics > QA273.6 Weibull distribution. Logistic distribution. Q Science > QC Physics > QC871 Meteorology--Observations. |
| Divisions: | Faculty of Civil, Planning, and Geo Engineering (CIVPLAN) > Geomatics Engineering > 29101-(S2) Master Thesis |
| Depositing User: | Erlangga Candra Pramoedya |
| Date Deposited: | 31 Jul 2026 09:47 |
| Last Modified: | 31 Jul 2026 09:47 |
| URI: | http://repository.its.ac.id/id/eprint/140492 |
Actions (login required)
 |
View Item |