Judul: Study of Watershed Segmentation  Method on Classification of Mangrove Crown Closure: a Case Study in West  Kalimantan
Abstrak: Penelitian ini menguji teknik klasifikasi berbasis objek (OBIA) algoritma watershed dalam mendeteksi penutupan tajuk dan gap pada hutan mangrove. Pendekatan OBIA dinilai lebih unggul dari klasifikasi berbasis piksel karena tidak hanya mempertimbangkan aspek spektral tetapi juga spasial. Algoritma watershed adalah salah satu algortima yang digunakan secara luas dalam klasifikasi digital. Untuk mengetahui keterhandalan klasifikasi OBIA, penelitian ini menggunakan pengujian Overall Accuracy (OA) dan Kappa Accuracy (KA). Penelitian ini menemukan bahwa segmentasi dengan citra asli lebih baik daripada menggunakan citra yang difilter dengan low pass filter. Hasil segmentasi citra tanpa filter rata-rata menghasilkan dihasilkan oleh kombinasi K-10 dengan nilai Overall Accuracy sebesar 96,68% dan nilai Kappa Accuracy sebesar 65,98%. Sementara itu, pengujian segmentasi pada citra dengan filter rata-rata dihasilkan oleh K-06 dengan nilai Overall Accuracy sebesar 94,22% dan nilai Kappa Accuracy sebesar 50,01%., This study examined the watershed algorithm of object-based classification (OBIA) to detect canopy cover and gaps in mangrove forests. The OBIA approach is considered superior to the pixel-based classification because it not only considers spectral but also spatial aspects. The examined watershed algorithm is a method for image segmentation that is widely used for digital classification. To evaluate the segmentation performance, the study applied the Overall Accuracy (OA) and Kappa Accuracy (KA). The study found that the use of the original image is better than using the filtered image with a low pass filter. The use of image segmentation without an mean filter was provided by the K-10 with an Overall Accuracy value of 96.68% and a Kappa Accuracy value of 65.98%. Meanwhile, the image segmentation test with the filtered-images was obtained from the K-06 combination with an Overall Accuracy value of 94.22% and a Kappa Accuracy value of 50.01%.
Keyword: algoritma watershed, hutan mangrove, penutupan tajuk, segmentasi

Judul: Segmentation of Dry Land Forest  Crown Closure using High Resolution Imagery and Very High Resolution Imagery
Abstrak: Penelitian ini mengkaji teknik klasifikasi berbasis objek (OBIA) dengan menggunakan citra resolusi tinggi dan sangat tinggi dalam mendeteksi penutupan tajuk hutan pada hutan lahan kering dalam membedakan tajuk dan gap di PT. Bina Balantak Raya, Sulawesi Selatan. Segmentasi yang dilakukan menggunakan algoritma Watershed, namun algoritma Watershed mempunyai kelemahan yaitu adanya over segmentation sehingga diperlukan proses filtering yaitu dengan Mean Filter pada citra SPOT 6 dan citra Worldview 2 sebelum proses segmentasi. Hasil uji akurasi didapatkan bahwa segmentasi dengan citra SPOT 6 lebih baik menggunakan filter rata-rata dengan kombinasi parameter (10-0,5,0,5) dengan nilai OA sebesar 88,1% dan nilai KAsebesar 59,8%, sedangkan untuk hasil segmentasi citra Worldview 2 lebih baik tanpa filter rata-rata dengan nilai akurasi OA 84,5% dan KA sebesar 60,43% dengan kombinasi parameter (15-0,4,0,6)., This study examines object-based classification (OBIA) techniques using high and very high resolution imagery in detecting dry forest canopy in distinguishing canopy and gap in PT. Bina Balantak Raya, South Sulawesi. Segmentation is carried out using the Watershed algorithm, but the Watershed algorithm has a weakness, namely the existence of segmentation so that a filtering process is needed, namely the Mean Filter on the SPOT 6 image and the Worldview 2 image before the segmentation process. The results of the accuracy test show that segmentation with SPOT 6 images is better using an average filter with a combination of parameters (10-0.5,0.5) with an OA value of 88.1% and a KA value of 59.8%, while for The results of Worldview 2 image segmentation are more unfiltered with an average accuracy of OA of 84.5% and KA of 60.43% with a combination of parameters (15-0.4,0.6).
Keyword: Crown, Kappa Accuracy, Mean filter, Segmentation, Watershed

Judul: Pengaruh Pairing pada Isotop Sn dengan Menggunakan Pemodelan Sembilan Tingkat Energi
Abstrak: Formation of the neutron-rich tin isotopes (Sn isotopes) is the one of the interesting topics in the field of nuclear reaction, especially regarding the stability of the heavy nuclei. Calculations of total energy using the BCS approach using five energy levels can only calculate the total energy up to Sn50132. On the other hand, the experiment continues and has exceeded the formation of isotopes. Therefore, there is need for a new model to accomadate more neutrons. In this research, Sn isotopes is modelled using nine energy levels and constant interaction potential to explain the pairing phenomenon up to Sn50154. However, to obtain more accurate results, other methods to minimize the differences with the experimental results are clearly needed here.
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