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: Kajian Algoritma Watershed dan Mean-Shift dalam Segmentasi Penutupan Tajuk Hutan Lahan Kering: Studi Kasus di Kabupaten Boven Digoel
Abstrak: Penelitian ini mengkaji perbandingan teknik klasifikasi berbasis objek untuk mendeteksi penutupan tajuk hutan lahan kering di PT. Inocin Abadi, Kabupaten Boven Digoel, antara algoritma watershed dan mean-shift. Algoritma watershed menghasilkan nilai akurasi yang lebih tinggi dibandingkan algoritma mean-shift, tetapi dalam waktu pemrosesan algoritma mean-shift lebih efisien daripada algoritma watershed. Algoritma watershed menghasilkan nilai KA terbesar pada algoritma watershed 70,83% dan OA sebesar 94% pada kombinasi parameter (5-5-20) dengan waktu 1 jam dan 2 menit, lalu algoritma mean-shift memiliki nila KA terbesar 69,32% dan OA sebesar 94,22% pada kombinasi parameter (5-20-10) dengan waktu 3 menit 40 detik. This study examined two algorithms of the object-based classification techniques, i.e., namely the watershed and the mean shift, to detect dryland forest canopy cover at PT. Inocin Abadi, Boven Digoel Regency. The study shows that the watershed algorithm provided a higher accuracy value than the mean-shift algorithm; however, the processing time of the mean-shift algorithm is more efficient than the watershed algorithm. The watershed algorithm shows a KA value of 70.83% and OA of 94% with the parameter combination of 5-5-20 with a processing time of 1 hour and 2 minutes, while the mean-shift algorithm provided a KA value of 69.32% and OA of 94.22% with the combination of parameters 5-20-10 with a processing time of 3 minutes and 40 seconds.
Keyword: Akurasi Kappa, mean-shift, segmentasi, tajuk, 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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