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All Journal Jurnal Riset Rumpun Matematika dan Ilmu Pengetahuan Alam (JURRIMIPA)
Rohimatul Anwar
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Mathematics

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Sample Preparation Technique for Scanning Electron Microscopy in Analyzing Shrimp Shell Biodegradation by Actinomycetes through Solid-State Fermentation Widyastuti Widyastuti; Annisa Ananda; Rohimatul Anwar; Kurniawan Shidiq
JURNAL RISET RUMPUN MATEMATIKA DAN ILMU PENGETAHUAN ALAM Vol. 4 No. 2 (2025): Agustus: Jurnal Riset Rumpun Matematika dan Ilmu Pengetahuan Alam
Publisher : Pusat riset dan Inovasi Nasional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/jurrimipa.v4i2.6342

Abstract

Shrimp shell waste is a chitin-rich biopolymer with high potential for microbial bioconversion into value-added products. This study aimed to analyze the microstructural degradation of shrimp shells by the actinomycete isolate 18D38A1 under solid-state fermentation, using Scanning Electron Microscopy (SEM). A fresh sample preparation method was applied, involving washing and immersion in 70% ethanol, followed by vacuum drying and gold sputter-coating. Fermentation was conducted over a period of 1 to 4 days. SEM analysis revealed progressive structural deterioration of the shrimp shell matrix, including increased surface erosion, pore formation, and breakdown of chitin fibers, which became more pronounced each day. These observations indicate active and time-dependent biodegradation by isolate 18D38A1. The sample preparation protocol proved effective in preserving morphological features and enhancing SEM image clarity, enabling precise visualization of degradation stages. The combination of solid-state fermentation and optimized SEM preparation provides a reliable approach to evaluate the biodegradation process of chitinous waste by actinomycetes over time. This study demonstrates a practical SEM sample preparation method for visualizing the progressive biodegradation of shrimp shell by actinomycete isolate 18D38A1 from day 1 to day 4.
Analisis Regresi Kernel Gaussian untuk Memprediksi Indeks Pembangunan Manusia (IPM) Berdasarkan Faktor Sosial-Ekonomi Provinsi di Indonesia Rohimatul Anwar; Linda Rassiyanti; Rizka Pitri
JURNAL RISET RUMPUN MATEMATIKA DAN ILMU PENGETAHUAN ALAM Vol. 4 No. 3 (2025): Desember : JURRIMIPA: Jurnal Riset Rumpun Matematika dan Ilmu Pengetahuan Alam
Publisher : Pusat riset dan Inovasi Nasional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/jurrimipa.v4i3.7017

Abstract

The Human Development Index (HDI) functions as a key indicator for assessing the level of welfare and overall quality of life of the population within a specific region. This study aims to examine the socio-economic factors influencing HDI at the provincial level in Indonesia using a Gaussian kernel regression approach. A nonparametric method is employed due to its flexibility in capturing nonlinear relationships between the response and predictor variables without the need to assume a specific functional form. The analysis utilizes secondary data, including education, poverty, per capita expenditure, expected years of schooling, open unemployment rate, and gross regional domestic product for each Indonesian province. The findings from this study indicate that educational factors, particularly mean years of schooling and expected years of schooling, exert the most significant impact on HDI improvement. The estimated Gaussian kernel regression model demonstrates a coefficient of determination of 0.9954 and a residual standard error of 0.3468, reflecting a very high predictive accuracy and relatively low error. These results suggest that Gaussian kernel regression is an effective nonparametric approach for analyzing human development in Indonesia.
Co-Authors Annisa Ananda Kurniawan Shidiq Linda Rassiyanti Rizka Pitri Widyastuti Widyastuti