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4 results on '"Anwar Putri, Masayu Rahmia"'

1. Growth and Mortality Models of Mozambique Tilapia (Oreochromis mossambicus; Peters, 1852) Wildly Enter Inside the Fish Farming Ponds in Tarakan City, North Kalimantan.

Author

Salim, Gazali, Mujiyanto, Mujiyanto, Sugianti, Yayuk, Suryanti, Zahidah, Nawir, Daud, Hartinah, Sitti, Nurjanah, Dewi, Rose, Iranda, Rama, Wirawan Arief, Mochamad Candra, Anwar Putri, Masayu Rahmia, Rahman, Abdur, Indarjo, Agus, Ransangan, Julian, Jose, Ariel E. San, and Rozi

Subjects
FISH farming, MARINE ecology, FISHERIES, FISHERS
Abstract

Exploring the length-weight relationship of fish and characterising growth parameters is essential in fisheries as they offer fundamental biology and population dynamics data to establish good management strategies for fisheries resources. This study examines the growth and mortality patterns of Oreochromis mossambicus. Data was collected between September and December 2022 using quantitative descriptive survey sampling. The study involved 20 repeats and deliberate random sampling of 30-50 fish per sample, emphasising total length, weight, and sex parameters. Based on 726 samples of O. mossambicus (352 fish identified as male and 374 fish identified as female). The growth model study revealed the typical negative allometric growth for both sexes (male and female). Male individuals attained a length of 33.449 cm after 37 days has a growth trend ± 0.3265 year-1, and females reached 21.150 cm in 34 days with a growth rate around 0.3135 year-1, as per the von Bertalanffy growth model. There were complex mortality patterns, with males contributing to most total deaths. This study emphasizes the complex biology of tilapia and its untapped potential in the aquaculture pond system ecology in Tarakan. [ABSTRACT FROM AUTHOR]

Published
2024
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2. Spatial and Temporal Distribution of Water Plant Based on Satellite Imagery and the Effect in Jatiluhur Reservoir

Author

Rahman, Arip, Anwar Putri, Masayu Rahmia, Purnamaningtyas, Sri Endah, Astuti, Lismining Pujiyani, Warsa, Andri, Rahman, Arip, Anwar Putri, Masayu Rahmia, Purnamaningtyas, Sri Endah, Astuti, Lismining Pujiyani, and Warsa, Andri

Abstract

Water vegetation in lakes or reservoirs can change the water's ecology. Water vegetation in Jatiluhur Reservoirs is dominated by water hyacinth (Eichhornia crassipes). Water hyacinth in lakes or reservoirs becomes an invasive weed that can cause ecological degradation. Jatiluhur Reservoir is one of the water bodies affected by the uncontrolled growth of water vegetation. The study was conducted to determine the spatial and temporal distribution patterns of water vegetation and its effect on Jatiluhur Reservoir. Water vegetation's spatial and temporal distribution was analyzed using Sentinel-2A satellite image data. The Normalized Difference Vegetation Index (NDVI) algorithm was used to see the distribution of water vegetation in the reservoir waters. The observations show that the movement of water vegetation starts from the inlet area and then moves along with the flow of water to the center of the reservoir. Finally, it accumulates in the outlet area. The correlation between vegetation cover area and month of observation obtained the equation y=662.5x + 128.1. Based on the equation, the increasing vegetation cover area in the Jatiluhur Reservoir is predicted to reach 128.1 ha per month. The physical method used for controlling the growth and distribution of vegetation (water hyacinth) in Jatiluhur Reservoir by taking in the waters. Efforts to control vegetation physically must notice the increasing rate of water hyacinth distribution., Water vegetation in lakes or reservoirs can change the water's ecology. Water vegetation in Jatiluhur Reservoirs is dominated by water hyacinth (Eichhornia crassipes). Water hyacinth in lakes or reservoirs becomes an invasive weed that can cause ecological degradation. Jatiluhur Reservoir is one of the water bodies affected by the uncontrolled growth of water vegetation. The study was conducted to determine the spatial and temporal distribution patterns of water vegetation and its effect on Jatiluhur Reservoir. Water vegetation's spatial and temporal distribution was analyzed using Sentinel-2A satellite image data. The Normalized Difference Vegetation Index (NDVI) algorithm was used to see the distribution of water vegetation in the reservoir waters. The observations show that the movement of water vegetation starts from the inlet area and then moves along with the flow of water to the center of the reservoir. Finally, it accumulates in the outlet area. The correlation between vegetation cover area and month of observation obtained the equation y=662.5x + 128.1. Based on the equation, the increasing vegetation cover area in the Jatiluhur Reservoir is predicted to reach 128.1 ha per month. The physical method used for controlling the growth and distribution of vegetation (water hyacinth) in Jatiluhur Reservoir by taking in the waters. Efforts to control vegetation physically must notice the increasing rate of water hyacinth distribution.

Published
2024

3. Age and Growth Estimation of Bigeye Tuna, Thunnus obesus (Lowe, 1839) in the Eastern Indian Ocean Deduced from Otolith Microstructure.

Author

Wujdi, Arief, Nugroho, Suciadi C., Zedta, Raymon R., Hartaty, Hety, Anwar Putri, Masayu Rahmia, Rochman, Fathur, Rintar Pandapotan Tampubolon, Prawira Atmaja, Kurniawan, Roy, Pramurdya, Yesika Nanda, and Setyadji, Bram

Subjects
OTOLITHS, BIGEYE tuna, AKAIKE information criterion, OCEAN, FISHERY management, AGE
Abstract

Age-based stock assessment of globally important species, like bigeye tuna Thunnus obesus (Lowe, 1839), is urgently required to develop appropriate management plans for fisheries sustainability. This study aimed to estimate age and growth parameters using annual increments count of sectioned-otoliths, which effectively employed for age determination of tunas. Samples were collected from Indonesian tuna longline catch landed in the Port of Benoa from March until December 2017. Multi-models were employed to obtain robust growth parameters, and Akaike Information Criterion (AIC) was relied for the best fit model selection among those evaluated. Growth band formation was validated using marginal analysis (MI), indicating that one ring is deposited yearly and slow growth peaked during July (Australian winter). The von Bertalanffy growth model was selected as the best model fitting growth parameters from raw age data, as expressed as Lt = 183.49 (1-e-0.134(t+2.991)). Large variances in growth were detected at the same age, with the oldest age of 15. Over 50% of fish in the Indonesian catch were <5 years old, that may have implications for fisheries sustainability. [ABSTRACT FROM AUTHOR]

Published
2023
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