Judul: Pemetaan Perubahan Luasan Padang Lamun Menggunakan Citra Satelit Sentinel-2A di Pulau Lancang
Abstrak: Lamun merupakan salah satu komponen utama penyusun ekosistem perairan laut dangkal. Tumbuhan lamun memiliki fungsi secara ekologis dan ekonomis diantaranya sebagai sumber utama produktivitas primer di laut dan bahan baku obat-obatan. Penyusutan areal padang lamun terjadi karena adanya aktivitas manusia di wilayah pesisir dan ancaman dari alam. Penelitian ini bertujuan memetakan dan mengetahui perubahan luasan lamun tahun 2017 dan 2022 menggunakan citra Sentinel-2A di Pulau Lancang, Kepulauan Seribu. Penelitian ini melalui beberapa tahapan seperti pengambilan data lapang, pra-pengolahan citra, koreksi kolom perairan, klasifikasi citra, dan deteksi perubahan luasan lamun. Klasifikasi lamun di Pulau Lancang terbagi menjadi tiga kelas yaitu lamun padat, lamun sedang, dan non lamun. Klasifikasi dengan metode maximum likelihood menghasilkan luas area lamun tahun 2017 sebesar 78.43 ha dan tahun 2022 sebesar 72.43 ha. Perubahan luasan lamun yang terjadi dari lamun menjadi non lamun adalah sebesar 26.78 ha. Sementara perubahan luasan dari non lamun menjadi lamun sebesar 20.78 ha., Seagrass is a crucial component of shallow marine ecosystems. These plants have ecological and economic functions, being the primary source of productivity in the sea and providing raw materials for medicine. Unfortunately, human activities in coastal areas and threats from nature cause the shrinkage of seagrass beds. The goal of this study is to map and analyze changes in the seagrass area on Lancang Island, Kepulauan Seribu, using Sentinel-2A imagery from 2017 and 2022. The research involved several stages, including field data collection, image pre processing, water column correction, image classification, and detection of changes in the seagrass area. The classification of seagrass on Lancang Island were divided into three classes, namely dense seagrass, medium seagrass, and non-seagrass. The maximum likelihood method was used for classification, resulting in an area of 78.43 ha for seagrass in 2017 and 72.43 ha in 2022. The detection of seagrass to non-seagrass area change resulted in a net loss of 26.78 ha. On the other hand, the change from non-seagrass to seagrass area was 20.78 ha.
Keyword: Lancang Island, sentinel-2, seagrass

Judul: Mapping of Changes in Seagrass Areas Using Sentinel-2A Imagery on Harapan and Kelapa Islands Waters, Kepulauan Seribu National Park
Abstrak: Lamun merupakan tumbuhan berbunga (Angiospermae) yang dapat ditemukan di pesisir pantai hingga perairan dangkal dan dapat beradaptasi terhadap perairan bersalinitas. Padang lamun memiliki fungsi penting antara lain sebagai habitat biota laut alami dan dapat memperlambat pergerakan arus serta gelombang ke darat. Aktivitas manusia seperti kegiatan perikanan, budidaya, pariwisata dan alih fungsi lahan untuk pembangunan dapat mengakibatkan kerusakan pada lamun yang berakibat pada penurunan luas padang lamun. Penelitian ini bertujuan untuk memetakan sebaran dan perubahan luas lamun di perairan Pulau Harapan dan Pulau Kelapa. Penelitian ini diawali dengan pengambilan data lapang dan pengolahan citra satelit Sentinel-2A berupa preprocessing citra dan koreksi kolom air. Selanjutnya dilakukan klasifikasi maximum likelihood pada citra sentinel-2A akuisisi 22 November 2015 dan 24 April 2021. Hasil klasifikasi citra diperoleh tiga kelas yaitu kelas non lamun, lamun padat, dan lamun sedang. Pada tahun 2015 luas area padang lamun seluas 0,92 km2 dan non lamun 1.58 km2, di tahun 2021 luas lamun seluas 0,70 km2 dan non lamun 1.79 km2. Terjadi perubahan luas area lamun menjadi non lamun seluas 0.52 km2 dan area non lamun yang menjadi lamun seluas 0.30 km2. Nilai overall accuracy yang diperoleh sebesar 74.17% sudah memenuhi standar minimal 60% dari Badan Informasi Geospasial., Seagrass is a flowering plant (Angiospermae) found on the coast in shallow waters and could adapt to salinity waters. Seagrass beds have important functions as a natural habitat for marine organisms and reduce the movement of currents and sea waves into the land. Human activities such as fishing, aquaculture, tourism, and land conversion for development can cause damage to seagrass, resulting in a decrease in the area of seagrass beds. This study was to map the seagrass distribution and detect changes in the seagrass area in the waters of Harapan and Kelapa Islands. This research begins with field data collection and processing of Sentinel-2A satellite imagery, image preprocessing, and water column correction. The next step is the maximum likelihood classification is carried out on the Sentinel-2A image with the acquisition on 22 November 2015 and 24 April 2021. The image classification results obtained are three classes: non-seagrass, dense seagrass, and medium seagrass. In 2015 the area of seagrass beds was 0.92 km2, and non-seagrass areas were 1.58 km2, while in 2021, the area of seagrass beds was 0.70 km2 and non-seagrass fields area was 1.79 km2. There was a changing area of seagrass becoming non-seagrass at about 0.52 km2, and the location of non-seagrass, which became seagrass, is 0.30 km2. The overall accuracy value obtained of around 74.17% already meets the minimum standard of 60% from the Geospatial Information Agency.
Keyword: Supervised classification, Seagrass, Area changes, Sentinel-2A imagery

Judul: Penentuan Nilai Eigen dan Vektor Eigen dari Matriks Tridiagonal 2-Toeplitz dengan Pendekatan Polinomial Chebyshev
Abstrak: The eigenvalues and eigenvectors of a matrix can be determined by finding its characteristic polynomials. The characteristic polynomials of a tridiagonal 2-Toeplitz matrix is shown to be closely connected to polynomials which satisfy the Chebyshev recurrence relationship. If the order of the matrix is odd, then the eigenvalues are found explicitly in terms of the Chebyshev zeros and the eigenvectors are found in terms of the polynomials satisfying the recurrence relationship. For even ordered matrices, the situation is more complicated. The problem in these cases is that although the Chebyshev recurrence formula is still applied, its initial values are not generating Chebyshev polynomials
Keyword: