Judul: Monitoring Perubahan Luasan Lamun di Pulau Beralas Pasir dan Beralas Bakau Menggunakan Citra Sentinel-2 dan Unmanned Surface Vehicle
Abstrak: Perairan sekitar Pulau Bintan, memiki keberadaan padang lamun yang cukup luas. Salah satu citra satelit yang relatif baru dan memiliki kualitas spasial untuk monitoring kondisi dan perubahan terhadap suatu ekosistem wilayah pesisir adalah Citra Sentinel-2 dengan nilai resolusi spasial 10x10 m/pixel. Pengambilan data lapang dimudahkan dengan penggunaan Unmanned Surface Vehicle (USV). Penelitian ini melalui beberapa tahapan seperti Pra-Pengolahan citra, Koreksi Kolom Perairan, Masking, Klasifikasi Unsupervised, dan deteksi perubahan luasan lamun. Data yang didapatkan dari USV menjadi data untuk uji akurasi. Didapatkan luasan lamun di perairan Pulau Beralas Pasir dan Beralas Bakau sebesar 45.76 ha (2016), 48.8 ha (2019) dan 43.13 ha (2021). Perubahan luasan lamun yang terjadi dari lamun menjadi non-lamun adalah sebesar 26.72 ha (2016-2019) dan 29.09 ha (2019-2021). Sementara perubahan luasan dari non-lamun ke lamun adalah sebesar 27.64 ha (2016-2019) dan 24.23 ha (2019-2021). Perhitungan luasan perubahan menghasilkan nilai kelas lamun sedang meningkat sebesar 2.64 ha (2016-2019) dan berkurang 7.93 ha (2019-2021), lamun padat bertambah sebesar 0.4 ha (2016-2019) dan 2.26 ha (2019-2021). Uji akurasi data klasifikasi citra tahun 2019 dengan data USV menghasilkan nilai overall accuracy sebesar 64.91%., The Bintan Island has a quite large seagrass ecosystems area. One satellite image that is relatively new and has good spatial quality for monitoring conditions and changes of coastal systems is Sentinel-2 with a spatial resolution value of 10x10 m / pixel. Field data retrieval was equip with Unmanned Surface Vehicle (USV). This research went through several stages such as image pre-processing, water column correction, masking, unsupervised classification, and detection of changes of seagrass area. The data obtained from the USV was use for the accuracy test in the supervised classification. The amount of seagrass area obtained in the Beralas Pasir and Beralas Bakau Island was 45.76 ha (2016), 48.8 ha (2019) dan 43.13 ha (2021). Detection of seagrass to non-seagrass area changed resulting 26.72 ha (2016-2019) and 29.09 (2019-2021). In the other hand the changes of non-seagrass to seagrass area was 27.64 ha (2016-2019) and 24.23 ha (2019-2021). The calculation of the changed area resulting the meadows seagrass increasing 2.64 ha (2016-2019) and decreasing 7.93 ha (2019-2021), dense seagrass increasing by 0.4 ha (2016-2019) and 2.26 ha (2019-2021). The accuracy test of 2019 image classification and USV data resulting overall accuracy at 64.91%.
Keyword: Seagrass, Sentinel-2, Beralas Pasir, Beralas Bakau, USV

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
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