Judul: Mapping Mangrove Distribution Using Remote Sensing Technology in Harapan, Kelapa, and Pamegaran Islands, Kepulauan Seribu National Park
Abstrak: Keberadaan ekosistem mangrove semakin terancam akibat pesatnya pembangunan destinasi wisata dan bertambahnya jumlah penduduk di Pulau Harapan, Kelapa, dan Pamegaran sehingga perlu dilakukan pemantauan ekosistem mangrove. Tujuan penelitian untuk memetakan sebaran mangrove menggunakan teknologi penginderaan jauh di Pulau Harapan, Kelapa, dan Pamegaran. Metode klasifikasi maximum likelihood digunakan untuk mengklasifikasikan vegetasi mangrove dan non mangrove. Normalized Difference Vegetation Index (NDVI) merupakan algoritma untuk menduga indeks vegetasi dari citra satelit. Klasifikasi Citra Sentinel-2A menghasilkan 3 kelas kerapatan mangrove yakni kelas kerapatan rapat, sedang, dan jarang, dengan kelas dominan adalah kelas kerapatan rapat. Luas total mangrove di Pulau Pamegaran pada tahun 2015 sebesar 1,81 ha dan luas total mangrove di tahun 2021 sebesar 2,97 ha. Luas sebaran mangrove di Pulau Harapan dan Kelapa pada tahun 2015 sebesar 4,1 ha dan pada tahun 2021 sebesar 6,56 ha. Hasil uji akurasi sebaran kerapatan mangrove menggunakan confusion matrix pada klasifikasi citra dengan survey lapang menghasilkan akurasi sebesar 82,95%., The existence of mangrove ecosystems is increasingly threatened due to the rapid development of tourist destinations and the increasing number of residents in Harapan, Kelapa, and Pamegaran islands so that monitoring of mangrove ecosystems is necessary. The purpose of the research to map the distribution of mangroves using remote sensing technology in Harapan, Kelapa, and Pamegaran Islands. The maximum likelihood classification method is used to classify mangrove and non-mangrove vegetation. Normalized Difference Vegetation Index (NDVI) is an algorithm for guessing vegetation indexes from satellite imagery. Sentinel-2A image classification produces 3 classes of mangrove density, namely tight, medium, and rare density classes, with the dominant class being the tight density class. The total mangrove area on Pamegaran Island in 2015 amounted to 1,81 ha and the total mangrove area in 2021 amounted to 2,97 ha. The area of mangrove distribution in Harapan and Kelapa Island in 2015 amounted to 4,1 ha and in 2021 amounted to 6,56 ha. Mangrove density distribution accuracy test results using confusion matrix in image classification with field survey resulting in accuracy of 82,95%.
Keyword: Density, Mangrove, NDVI, Remote sensing, Sentinel-2A

Judul: Monitoring Mangrove Area and Density Using Landsat Satellite on Lancang Island, Kepulauan Seribu
Abstrak: Mangrove adalah tumbuhan yang hidup di lingkungan pesisir dengan salinitas rendah. Ekosistem mangrove dapat tumbuh di zona intertidal dan zona supratidal. Monitoring ekosistem mangrove secara langsung tidak mudah karena sulitnya memetakan kawasan mangrove sehingga dibutuhkannya teknologi penginderaan jauh sebagai metode alternatif. Penelitian ini bertujuan mengkaji perubahan luasan dan kerapatan mangrove secara temporal menggunakan citra Landsat. Metode yang digunakan adalah klasifikasi terbimbing dengan algoritma maximum likelihood classification dan indeks vegetasi Normalized Difference Vegetation Index (NDVI). Pada tahun 2000 hingga 2010, luasan ekosistem mangrove mengalami peningkatan seluas 5,31 ha atau 131,11% dari luasan sebelumnya. Pada rentang waktu berikutnya yaitu tahun 2010 hingga 2021, luasan ekosistem mangrove mengalami peningkatan kembali seluas 6,3 ha atau 67,30% dari luasan sebelumnya. Hasil klasifikasi kerapatan mangrove di Pulau Lancang terbagi menjadi tiga kelas yaitu jarang, sedang, dan rapat. Pada tahun 2000, 2010, dan 2021 kerapatan mangrove kelas jarang dan sedang mengalami penurunan, sedangkan kerapatan mangrove kelas rapat mengalami peningkatan. Peningkatan luasan dan kerapatan mangrove di Pulau Lancang, Kepulauan Seribu dikarenakan tidak adanya gangguan secara berlebihan dari masyarakat setempat, adanya unsur hara yang menyuplai ekosistem mangrove, dan memiliki jenis substrat berlumpur yang optimal bagi habitat mangrove. Hasil uji akurasi klasifikasi citra tutupan lahan sebesar 85,45%., Mangroves are plants that live in coastal environments with low to mid range salinity. Mangrove ecosystems can grow in the intertidal zone and supratidal zone. Monitoring mangrove ecosystems directly is not easy because of the difficulty of mapping mangrove areas. So, remote sensing technology is needed as an alternative method. This research purposed to examine temporary changes in an area and density of mangroves using Landsat imagery. Method that used in this research was supervised classification with the maximum likelihood classification algorithm and Normalized Difference Vegetation Index (NDVI) vegetation index. In 2000 to 2010, mangrove ecosystem area expanded by 5.31 ha or 131,11% from previous area. In the next time span between 2010 to 2021, mangrove ecosystem area expanded by 6.3 ha or 67,30% from previous area. Mangrove density on Lancang Island specified into three classes that was sparse, moderate, and concentrated. In 2000, 2010, and 2021, sparse and moderate density of mangroves area has been degradated, while concentrated mangroves area has been expanded. The expanding area and density of mangroves on Lancang Island, Kepulauan Seribu Regency was due to the absence of excessive disturbance from local community, the presence of nutrients that supplied the mangrove ecosystem, and optimal type of muddy substrate for mangrove habitat. The results of accuracy test on land cover image classification were 85.45%.
Keyword: Area, Canopy Cover, Density, Mangrove, NDVI

Judul: Bifurkasi Hopf pada Model Siklus Bisnis Kaldor Kalecki tanpa dan dengan Waktu Tunda
Abstrak: Business cycle model is one of dynamical system models in economic. One of the business cycles model is Kaldor-Kalecki model. Kaldor-Kalecki business cycle model that is written in delayed defferential equations, is a business cycle model that involves gross product and capital stock of a company. In this paper Kaldor-Kalecki business cycle model is analyzed using both nondelay and delay in time of capital stock. By Taylor expansion for the time delayed model, an analysis of stability around the fixed points has been done. Furthermore, by using Hopf bifurcation theorem, it can be shown that there exists periodic orbits and limit cycle. In the nondelayed model, changing the parameter of goods market could lead to the occurrence of Hopf bifurcation and the existence of limit cycle. Similarly, for the delayed model, it has been shown that changing the time delay parameter may result in the occurrence of Hopf bifurcation and limit cycle.
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