Claim Missing Document
Check
Articles

Found 4 Documents
Search

Analisis Keanekaragaman dan Kelimpahan Plankton di Sungai Way Awi dan Hubungannya dengan Kualitas Air Pertiwi, Tina; Tugiyono, Tugiyono; Nugroho Susanto, Gregorius
Environmental Science Journal (esjo) : Jurnal Ilmu Lingkungan 2024: Volume 3 Nomor 1 Desember 2024
Publisher : Universitas PGRI Palembang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31851/esjo.v2i2.16628

Abstract

Plankton serves as a bioindicator that can be used as a marker for water quality related to water saprobity index. Way Awi River is a river flowing from the Susunan Baru area, passing through the Tandjungkarang region, and reaching the Garuntang area. Liquid waste from households is often directly discharged into the river, without passing through a containment system such as a septic tank, resulting in river pollution. To understand this relationship, this research was conducted to determine the biological condition of the Way Awi River based on plankton community structure, including abundance index, diversity index, evenness index, and dominance index, as well as its correlation with water quality using Pearson correlation test. The research was conducted in the Way Awi River with sampling taken at five different stations from October to December 2023. Water samples were analyzed using physical parameters including water temperature and turbidity, while chemical parameters observed were pH, DO, BOD, and COD. Based on the analysis of plankton community structure, it was found that the water of Way Awi River is in a moderately polluted condition.
Pembuatan Lubang Resapan Biopori Dalam Upaya Konservasi Air Tanah Di Dalam Pekarangan Rumah Eka Lestari, Devi; Tugiyono; Nugroho Susanto, Gregorius; Lestari, Elly
AMMA : Jurnal Pengabdian Masyarakat Vol. 3 No. 11 : Desember (2024): AMMA : Jurnal Pengabdian Masyarakat
Publisher : CV. Multi Kreasi Media

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Banjar Agung Udik village is an area in Pugung Sub-District, Tanggamus Regency, which is located close to Mount Tanggamus. This activity aims to provide training on making biopore infiltration holes in an effort to conserve groundwater in the yard, with the aim of increasing the absorption of rainwater into the soil. This training is expected to reduce the risk of flooding due to rainwater and increase the amount of clean water reserves in the soil. This activity was held on August 6, 2024, at the Banjar Agung Udik village hall, with participants from various age groups, both men and women. The activity began with problem analysis through field surveys, followed by the preparation of an activity plan, training implementation, and ended with socialization and guidance on making biopore infiltration holes in an effort to conserve groundwater in home yards. With continuous training, it is expected that participants will gain knowledge and skills that can be used to reduce the risk of flooding due to overflowing rainwater and to increase the amount of clean water reserves in the soil.
Pola Distribusi Mikroba dan Pengaruhnya Terhadap Pembenihan Larva Udang Vanamei Di Hatchery Pantai Ketang Lampung Sarwoko, Jonathan Puji; Sumardi; Tugiyono; Nugroho Susanto, Gregorius; Irawan, Bambang
Jurnal Ekologi, Masyarakat dan Sains Vol 5 No 1 (2024): Jan-Jun 2024
Publisher : ECOTAS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55448/f9ymg556

Abstract

Abstract: The microbial distribution pattern or dispersion of microbes in a water environment was the primary focus of this research. The study aimed to analyze the total density of Vibrio sp., coliform, and plankton in seawater, as well as the relationship between microbes and the hatching of vanamei shrimp larvae. The research was conducted from April to August 2022 at Pantai Ketang, Kalianda, Lampung, in the Microbiology and Zoology laboratory of the Faculty of Mathematics and Natural Sciences, Lampung University. The research employed an exploratory survey method, including the calculation of total Vibrio, coliform, plankton, and survival rates. Data analysis was carried out using analysis of variance, followed by the Duncan test (? = 0.05) for identifying significant differences among groups. Additionally, the microbial relationship was analyzed using Pearson correlation (? = 0.05). The results revealed that the highest Vibrio density occurred in May (3 CFU/ml) and in larval shrimp rearing water (M) (5 CFU/ml). Coliform density was less than < 3 MPN/100ml, and the highest plankton density was observed in August (2×102 ind/L) and in high tide seawater (P) (1×104 ind/L). However, there was a very low correlation between microbial density and the survival rate of vanamei shrimp larvae.
Performance evaluation of feature extraction to improve the classification of PTM in C-glycosylation using XGBoost Damayanti, Damayanti; Rosyking Lumbanraja, Favorisen; Junaidi, Akmal; Sutyarso, Sutyarso; Nugroho Susanto, Gregorius; Hendrastuty, Nirwana
Bulletin of Electrical Engineering and Informatics Vol 14, No 2: April 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v14i2.8466

Abstract

Protein function is regulated by an important mechanism known as post-translational modification (PTM). Covalent and enzymatic protein modifications are added during protein biosynthesis, and such alterations significantly influence the regulation of gene activity and the functionality of proteins. Glycosylation, one type of PTM, involves adding sugar groups to a protein's structure. Numerous illnesses, such as diabetes, cancer, and the flu, have been linked to glycosylation. Therefore, it is critical to predict the presence of glycosylation, whether it occurs or not. Currently, predicting glycosylation sites is still done manually using biological methods, which require repeated experiments and a significant amount of time. To address these challenges, it is essential to rapidly develop computational data models using machine learning methods. In this study, the extreme gradient boosting (XGBoost) method is implemented, and C-glycosylation data is obtained from the publicly accessible UniProt website. The objective is to enhance the accuracy of C-glycosylation prediction using the XGBoost method. Feature extraction is performed using amino acid index (AAindex), composition, transition, and distribution (CTD), solvent AccessiBiLitiEs (SABLE), hydrophobicity, and pseudo amino acid composition (PseAAC) to improve accuracy. The minimum redundancy maximum relevance (MRMR) method is applied for feature selection. The findings of the study demonstrate that the PTM C-glycosylation prediction achieved 100%.