Judul: Potensi Sumber Daya Ikan Selar Kuning, Tembang, dan Tongkol di Selat Sunda yang Didaratkan di PPP Labuan, Banten
Abstrak: Pelagic fishery potential in the Sunda Strait is the highest compared to other fisheries. The dominant pelagic fish caught were yellowstripe scad, fringescale sardinella, and thonine orientale. Pelagic fish is a economic important, that facing arrest are increasing every year and it is feared to overfishing. The aims this study are to assess the utilization condition of pelagic fish in PPP Labuan, Banten especially about biological and economic aspects. The method used to determine potential is through the selection correctly of surplus production. Maximum sustainable yield (MSY) and maximum economic yield (MEY) are 1875.02 ton/year dan 1874.71 ton/year for yellowstripe scad, 3311 ton/year dan 3303 ton/year for fringescale sardinella, also 1721.17 ton/year and 1710.64 ton/year for thonine orientale. Actual catche efforts of yellowstripe scad, fringescale sardinella, and thonine orientale has greater than optimum efforts, so that indicated has been biological and economic overfishing. Economic rent on the actual condition of the third kind of fish is lower than the economic rent of MSY and MEY conditions. This condition can be caused by the rate exploitation of the three kinds of fish exceeding the optimum exploitation (> 0.5) so it had overexploited. Economic rent on the actual condition is lowest because degradation of the fish resources has increased every year. The better utilization is MEY condition because these have maximum benefit. Management plan of pelagic fish in PPP Labuan are reduction fishing effort, selectivity of fishing gear, and setting size of the fish can be caught.
Keyword: Sunda Strait., pelagic fish, overexploited, exploitation rate, degradation rate

Judul: Kajian Stok Sumber Daya Ikan Selar Kuning Selaroides leptolepis (Cuvier 1833) di Perairan Selat Sunda yang didaratkan di PPP Labuan, Banten
Abstrak: Yellowstripe Scad is one of pelagic fishes has the value of economically important fish catches and is dominant in PPP Labuan. Population of yellowstripe scade feared will decline arrest of conducted in continous. The purpose of this study was to assess the condition of yellowstripe scad in Sunda Strait that include of growth, mortality and exploitation rate. The study is done at PPP Labuan on Juny-October 2013. Fish samples observed reach a 752 with length range between 81-168 mm. Yellowstripe scad have allometric negative growth and a size of first maturity 157 mm. Parameter growth allegedly used method Ford Walford showed growth yellowstripe scade female faster than male with growth rate each of 0,42 and 0,36. The exploitation of yellowstripe scad has exceeded the optimum exploitation rate that yellowstripe scad in Sunda Strait has over exploited. Optimum efforts allegedly used Schaefer model showing of 1089 trip/year with maksimum sustainable yield (MSY) of 1977 tonnes/year and total allowable catch 1423 tonnes/year. Management that can be suggested is setting fishing effort and mesh size more than 6 cm.
Keyword: Yellowstripe scad., maksimum sustainable yield (MSY), xploitation, growth

Judul: Quantum Convolutional Neural Network (QCNN) for Classification Brain Tumor MRI Image
Abstrak: Penelitian ini bertujuan untuk mengembangkan model deteksi tumor otak menggunakan citra MRI dengan metode Quantum Convolutional Neural Network. Data yang digunakan adalah citra MRI otak yang terdiri dari citra tumor otak glioma, meningioma, hipofisis, dan negatif tumor yang dibagi kedalam data latih dan uji dengan rasio 80:20. Selanjutnya data latih dilakukan penyeimbangan dengan teknik oversampling. Dilakukan pengembangan model untuk mendeteksi tumor otak (biner), dan juga model untuk mengklasifikasikan jenis tumor otak (multiclass). Parameter yang digunakan dalam pengembangan model adalah jumlah ukuran filer = 2 dan kedalaman = 4, dengan qubit 4, dan dilatih dengan jumlah epoch sebanyak 10. Data akan diproses dengan metode Quantum Convolutional Neural Network yang terdiri dari lapisan quantum convolution, lapisan flatten, dan lapisan dense. Model multiclass mendapatkan akurasi 52%, setelah data latih diseimbangkan akurasi model meningkat menjadi 62%, sedangkan model biner mendapatkan akurasi 88%, setelah data latih diseimbangkan akurasi model meningkat menjadi 89%.
Keyword: Citra MRI, Klasifikasi Citra, QCNN, Tumor Otak