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All Journal HAYATI Journal of Biosciences FORUM STATISTIKA DAN KOMPUTASI Jurnal Statistika Universitas Muhammadiyah Semarang Journal of Innovation and Applied Technology Jurnal Sumberdaya Akuatik Indopasifik JFMR (Journal of Fisheries and Marine Research) Jurnal Penelitian Pendidikan IPA (JPPIPA) Journal of Aquaculture and Fish Health Media Akuatika: Jurnal Ilmiah Jurusan Budidaya Perairan Jurnal Pijar MIPA
Supriatin, Febriyani Eka
Faculty Of Fisheries And Marine Science, Universitas Brawijaya, Malang
Agriculture, Biological Sciences & Forestry Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Computer Science & IT Decision Sciences, Operations Research & Management Earth & Planetary Sciences Education Engineering Environmental Science Materials Science & Nanotechnology Mathematics Physics

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Effect of different sodium nitrate concentrations on the growth, biomass, and biochemical composition of Tetraselmis chuii Fakhri, Muhammad; Amrulloh, Albazi Achmad; Yuniarti, Ating; Supriatin, Febriyani Eka; Arifin, Nasrullah Bai
Journal of Aquaculture and Fish Health Vol. 14 No. 1 (2025): JAFH Vol. 14 No. 1 February 2025
Publisher : Department of Aquaculture

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20473/jafh.v14i1.64564

Abstract

Nitrogen plays a significant role in the growth and metabolism of microalgae. The purpose of this study was to investigate the influences of different sodium nitrate concentrations on growth, biomass, and biochemical profile in Tetraselmis chuii. Four different nitrate concentrations, 0.5, 1.0, 1.5, and 2.0 g/L NaNO3 were applied in T. chuii culture under a batch system. It was found that a low nitrate concentration of 0.5 g/L NaNO3 produced the highest specific growth rate and biomass concentration of T. chuii. On the other hand, increasing nitrate concentration led to an increase in chlorophyll a+b and carotenoid in T. chuii, with the optimum nitrate concentration found at 1.5 g/L NaNO3. Under the nitrogen limitation condition, protein content was significantly decreased, but lipid and carbohydrate content were highly accumulated in the cells. This study provides a unique phenomenon that low nitrogen concentrations not only produce higher biomass but also accumulate high lipid and carbohydrate content.
Fish Growth Performance in RAS Pond Using Hydrocyclone Mechanical Filter Aulia Rahmawati; Febriyani Eka Supriatin; Sri Andayani; Muhammad Nasim Mubarok; Aulia Rahman
Jurnal Penelitian Pendidikan IPA Vol 10 No 4 (2024): April
Publisher : Postgraduate, University of Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jppipa.v10i4.6149

Abstract

The high feeding and the metabolic output of the fish in intensive aquaculture can cause various problem, such as poor water quality and slowing down the fish growth performance. Recirculating Aquaculture System (RAS) is a solution to maintain water quality. Unfortunately, the conventional mechanical filter in RAS such as japmat is inefficient. One strategy that can be applied is to use a hydrocyclone. This research aims to observe the fish growth performance in RAS pond using hydrocyclone mechanical filter and its comparison with the use of japmat. Research method was performed by comparing hydrocyclone and japmat in the pond with the RAS system. The research design is completely randomized design (CRD), with three replications in each treatment. The research was carried out through five stages, namely hydrocyclone set-up, RAS ponds set-up, water quality analysis, fish growth measurement, and statistical analysis. Based on the Independent Samples Test, the use of hydrocyclone mechanical filters has a significant effect (P<0.05) on the measured water quality parameters (DO, Temperature, pH, TDS, NH3) except for NO2. Hydrocyclone significantly affect Average Daily Growth and Specific Daily Growth parameters. Whilst, the Survival Rate and Feed Conversion Ratio parameters, it did not give significant effect
APPLICATION OF THE COCHRANE-ORCUTT METHOD IN ANALYZING THE IMPACT OF WATER QUALITY DYNAMICS ON THE GROWTH OF VANNAMEI SHRIMP (Litopenaeus vannamei) Febriyani Eka Supriatin; Aulia Rahmawati
Jurnal Statistika Universitas Muhammadiyah Semarang Vol 12, No 2 (2024): Jurnal Statistika Universitas Muhammadiyah Semarang
Publisher : Department Statistics, Faculty Mathematics and Natural Science, UNIMUS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26714/jsunimus.12.2.2024.%p

Abstract

Vannamei shrimp (Litopenaeus vannamei) is a key commodity in aquaculture due to its high survival rate, short cultivation period, and disease resistance. Water quality plays a crucial role in shrimp growth and productivity, particularly in intensive farming systems. This study aims to analyze the effects of water quality dynamics (pH, temperature, and dissolved oxygen) on shrimp growth, measured through Average Body Weight (ABW) and Specific Growth Rate (SGR). Multiple linear regression analysis was employed, but given the time-series nature of water quality data, the assumption of non-autocorrelation was violated. To address this issue, the Cochrane-Orcutt method was applied to obtain efficient parameter estimates and valid hypothesis testing results.The findings indicate that temperature significantly affects ABW and SGR (p < 0.05), while pH and dissolved oxygen do not show a significant partial effect. The simultaneous F-test confirms that these three water quality variables collectively influence shrimp growth. The Durbin-Watson test revealed autocorrelation in the initial model, which was resolved through the Cochrane-Orcutt method. The final regression model demonstrated improved estimation accuracy without autocorrelation. This study highlights that temperature is the primary factor influencing vannamei shrimp growth, while pH and dissolved oxygen play supporting roles in maintaining an optimal environment. Furthermore, the Cochrane-Orcutt method proved effective in addressing autocorrelation, ensuring more accurate analysis results that can guide the management of intensive vannamei shrimp farming
Hildreth-Lu Model for Autocorrelation Correction in Time-Series Regression of Shrimp Growth Perfomance Febriyani Eka Supriatin; Aulia Rahmawati; Muhammad Dailami
Jurnal Statistika Universitas Muhammadiyah Semarang Vol 13, No 2 (2025): Jurnal Statistika Universitas Muhammadiyah Semarang
Publisher : Department Statistics, Faculty Mathematics and Natural Science, UNIMUS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26714/jsunimus.13.2.2025.123-133

Abstract

Autocorrelation frequently occurs in time-series regression models, leading to inefficient estimators and biased inference when ignored. This study analyzed the relationship between water quality parameters and shrimp growth performance by applying the Hildreth–Lu iterative method to correct autocorrelation. The dataset consisted of Specific Growth Rate (SGR) as the dependent variable and three water-quality parameters—temperature, pH, and dissolved oxygen (DO)—as explanatory variables, with pond type included as a dummy factor. The initial Ordinary Least Squares (OLS) estimation revealed that temperature and pH significantly affected SGR, while the Durbin–Watson (DW) value of 0.878 indicated positive autocorrelation in the residuals. After applying the Hildreth–Lu correction, the estimated autocorrelation coefficient (ρ) was 0.64, and the DW statistic improved to 2.03, confirming that serial correlation had been successfully removed. The corrected model provided more efficient and unbiased parameter estimates without requiring data transformation or loss of observations. The results confirm that temperature is the most influential factor in shrimp growth, while pH, DO, and pond type showed no significant effects. The study highlights the importance of autocorrelation diagnostics in regression analysis and demonstrates that the Hildreth–Lu method is an effective and reliable approach for improving model efficiency in small-sample time-series data
Co-Authors Aisyah, Jumrotul Alfarisi, Muhammad Asnin Alim, Muhammad Bachrun Amrulloh, Albazi Achmad Aprillianto, Riqki Yoga Arifin, Nasrullah Bai Asus Maizar Suryanto H Ating Yuniarti Aulia Rahman Aulia Rahmawati Aulia Rahmawati, Aulia Budi Susetyo Diana Arfiati Ertikasari, Nuning Faqih, Abd Raheem Febiana, Arifatus Kurnianingsih, Asmiyati Kusman Sadik M. Tanzil Furqon, M. Tanzil Maftuch Maftuch Maulana, Gilang Drajat Muammar Kadhafi Muhammad Dailami Muhammad Dailami, Muhammad Muhammad Fakhri Muhammad Musa Muhammad Musa Muhammad Musa Muhammad Nasim Mubarok Patresna, Laelatul Nisa Putra, Renanda Baghaz D.S. Rahardjo, Seto Sugianto Prabowo Rahmi Nurdiani Rohman, Ahmad Nur Samsu Rijal, Seftiawan Savira, Riza Septi Anitasari, Septi Sianturi, Andre Soaloon Sri Andayani Sri Andayani TIWI NURJANNATI UTAMI Yenny Risjani