Judul: The sea surface salinity monsoonal and interannual variability; their implications on the catch rate of small pelagic fish, Java Sea
Abstrak: The monthly average of sea surface salinity (January 1994–December 2010 with a spatial resolution of 1o x1o) from Estimating Circulation and Climater of Ocean (ECCO) Dataset is used as a primary data, Dataset of wind (European Center For Medium Range Forecast, ECMWF) as a secondary parameter (monthly averages both for east-west (zonal) component and north-south (meridional) component, it is derived from 10 meters above sea level within period of January 1994–December 2010, with a spatial resolution of 2.5o x 2.5o) in this study. Time series analysis is conducted to obstain a complete picture of the Sea Surface Salinity (SSS) seasonal fluctuations. Results showed that SSS in the Java Sea has seasonal variability, which is shown by appearences of two SSS maximum and two SSS minimum annually. Based on monthly average in the northern part of Java Seas, the SSS is having range of 32 and 34,4 psu. In the first transitional season (March-April-May), SSS is relatively lower than the other season, i.e. NW monsoon, SE monsoon. The second transitional season (September-October-November), where it is found a low core SSS consentrated in the western part of the Java Sea and also in the south of Makassar strait. Results of the analysis shows that the catch varies according to temporal (monthly, seasonal, and annual), and to spatial in the Java Sea during the period 1990 to 1995. In the Java Sea, there are seven fishing ground of small pelagic fish, namely in the waters of north Pekalongan-Tegal, Java Karimun Islands, Bawean Island, Masalembo-Masalima Island, Matasiri Island, the southern Makassar Strait, and on the Kangean Island. Based on the total catch from the of seven regions, the average monthly percentage of the catch of round scads (Decapterus spp.), mackerels (Rastrelliger kanagurta), flat sardinella (Sardinella spp), round sardinella (Sardinella lemuru), bigeye scads (Selar crumenophthalmus), and yellowstripe scads (Selaroides leptolepis) are 48.50%, 16.97%, 14,15%, 10.80%, 8.65% and 0.93% respectively.
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Judul: Analysis of Small Pelagic Fishing Ground Using GAM Model and MaxEnt Model in Java Sea
Abstrak: Small pelagic fish are a group of potential fish resource types in the Java Sea. The high fishing effort over the last few years has led to an increase in utilization rate until it reaches an optimum level and tends to be over fishing. Purse seine and bauke-ami vessels are the dominant fishing vessels in these waters. Both types of vessels use light aids in the fishing process. The main obstacle to the success of fishing operations, apart from the dynamic movement of fish, is also caused by oceanographic factors in the waters. Fish respond differently to oceanographic factors, making it difficult for fishermen to carry out fishing operations. To help make it easier for fishermen to catch fish in the Java Sea, it is necessary to develop a better fishing area information system, so that fishing efforts can be more effective and efficient. The aim of this study was to develop a small pelagic fishing area prediction model based on oceanographic parameters, namely sea surface temperature and salinity. This study uses Generalized Additive Models (GAM) and Maximum Entropy (MaxEnt) for prediction modeling of fishing grounds in the Java Sea. The data used are Visible Infrared Imaging Radiometer Suite Boat Detection (VBD) images to determine the position and distribution of fishing vessels, sea surface temperature (SST) images, and salinity data as parameters for DPI modeling. VBD data assumed to be the location of fishing vessels to catch fish is stated as a response variable and oceanographic data is stated as a predictor variable in the development of the GAM model and the MaxEnt model. Data for 2018 is used as training data and data for 2019 is used as data validation. The analysis of the GAM model and the MaxEnt model was carried out using the same software, namely RStudio. The predictive performance of the model is assessed using the area under cover (AUC) matrix. The DPI prediction map generated from the GAM and MaxEnt modelers is expressed by the habitat suitability index (HSI) value. The GAM model for DPI prediction based on SST and salinity parameters shows that the presence of small pelagic fish is in the SST range 28 – 28.7 oC and salinity 32 – 33 psu. The MaxEnt model shows that the highest probability of fish distribution is in the range of SST 27.6 – 31.0 oC, and salinity 32 – 34 psu. Salinity is the most influential parameter in the distribution of small pelagic fish. Potential fishing areas, either based on the GAM model or the MaxEnt model, are found more in the central and eastern parts of the Java Sea closer to the southern waters of Kalimantan Island. The GAM model and MaxEnt model show accurate results in predicting small pelagic DPI in the Java Sea.
Keyword: google earth engine, salinitas, suhu permukaan laut, Laut Jawa

Judul: Katalis Zink Ferit Tersubstitusi Cu untuk Oksidasi Benzil Alkohol
Abstrak: Katalis berperan dalam menurunkan energi aktivasi. Katalis ZnFe2O4 dan ZnFe2O4 tersubstitusi Cu disintesis menggunakan metode kopresipitasi untuk digunakan dalam oksidasi benzil alkohol. Katalis dicirikan dengan spektrofotometer inframerah (FTIR) dan difraktometer sinar-X. Spektrum FTIR menunjukkan puncak serapan dari ikatan Zn-O dan Fe-O masing-masing pada rentang 559‒575 cm-1 dan 419‒447 cm-1. Difraktogram menunjukkan terbentuknya fase tunggal Zn0.6Cu0.4Fe2O4 pada katalis ZnFe2O4 tersubstitusi Cu 20%. Benzil alkohol dioksidasi dengan sistem refluks. Konversi benzil alkohol meningkat dengan meningkatnya suhu. Kadar benzaldehida yang dihasilkan dengan katalis ZnFe2O4 tersubstitusi Cu 20% lebih tinggi dibandingkan dengan katalis ZnFe2O4 yang tidak tersubstitusi dan yang tersubstitusi Cu 60 dan 80%. Hal tersebut menunjukkan bahwa katalis ZnFe2O4 tersubstitusi Cu 20% memiliki kinerja yang lebih baik dalam oksidasi benzil alkohol menjadi benzaldehida dengan kadar benzaldehida 8.763%.
Keyword: Benzil alkohol, katalis, oksidasi, ZnFe2O4