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Journal of Natural Sciences and Mathematics Research Published by Faculty of Science and Technology Universitas Islam Negeri Walisongo Semarang Jl Prof. Dr. Hamka Kampus III Ngaliyan Semarang 50185 Website: https://journal.walisongo.ac.id/index.php/JNSMR Email:jnsmr@walisongo.ac.id
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Journal of Natural Sciences and Mathematics Research
Published by Universitas Islam Negeri Walisongo Semarang
ISSN : 26146487     EISSN : 24604453     DOI : https://doi.org/10.21580/jnsmr
Core Subject : Science, Agriculture,
Agriculture, Biological Sciences & Forestry Biochemistry, Genetics & Molecular Biology Chemistry Materials Science & Nanotechnology Physics
Journal of Natural Sciences and Mathematics Research, an international journal, provides a forum for publishing the original research articles, review articles from contributors, and the novel technology news related to natural sciences and mathematics research. Scientific articles dealing with fundamental sciences, material sciences, mathematics, materials characterization, etc. are particularly welcome. The journal encompasses research articles, original research report, reviews, short communications and scientific commentaries in fundamental sciences and mathematics including: fundamental sciences, fundamental physics, fundamental chemistry, fundamental biology, mathematics, applied sciences, applied physics, applied chemistry,applied biology,applied mathematics and materials characterization.
Arjuna Subject : Umum - Umum
Articles 10 Documents
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Search results for , issue "Vol. 11 No. 2 (2025): December" : 10 Documents clear
Kombucha origin clustering based on 16S metabarcoding datasets analysis Nugroho, Imam Bagus; Darmawan Ari Nugroho; Abdul Rahman Siregar
Journal of Natural Sciences and Mathematics Research Vol. 11 No. 2 (2025): December
Publisher : Faculty of Science and Technology, Universitas Islam Negeri Walisongo Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21580/jnsmr.v11i2.23949

Abstract

Consumers of fermented products increasingly demand detailed information on product ingredients, quality, health benefits, and origin. Herein, we have chosen kombucha as a model for a fermented product. This study aims to establish the origin information of kombucha using clustering analysis of 16S metabarcoding datasets. We have downloaded and analysed datasets of kombucha 16Smetabarcoding originating from 5 distinct places: Brazil, the United States, the United Kingdom, Turkey, and Thailand. We randomly selected datasets from the collection (n = 32) and analysed them on the SHAMAN server to develop an initial microbiome profile. We implemented hierarchical agglomerative Clustering and found that Ward's method and the Chao distance produced the best cluster tree, which consistently separates kombucha into five distinct clades, reflecting their origin. We have extended our examination to include more datasets (n=13) to build the final cluster tree (total n = 45). We have also assessed the uncertainty of the final Clustering by pvclust in R. The pvclust cluster tree is comparable in topology to the final cluster tree built using Ward's method and Chao distance. The pvclust cluster tree features stable clades that are highly supported by AU (Approximately Unbiased) values (p-value ≥ 95%). Each kombucha was also placed correctly and consistently according to its respective origin. We have successfully conducted analyses and demonstrated that a simple clustering method, combining Ward's method and the Chao distance, is the most effective for classifying kombucha by origin using a 16S metabarcoding dataset.
Null Bézier Curves in Minkowski 3-Space Arfah
Journal of Natural Sciences and Mathematics Research Vol. 11 No. 2 (2025): December
Publisher : Faculty of Science and Technology, Universitas Islam Negeri Walisongo Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21580/jnsmr.v11i2.25323

Abstract

In this paper, we define and investigate the properties of null Bézier curves in Minkowski 3-space. The method applied is a theoretical literature study, applying the definitions of Bézier curves and the geometric framework of null curves in semi-Riemannian geometry. We establish several fundamental characteristics of these curves, including the causal nature of their tangent vectors at endpoints and their Frenet frame apparatus when parametrized by pseudo-arc length. Furthermore, we define the concept of a null Bertrand pair for such curves and prove that if a null Bézier curve of degree n≥3 admits a Bertrand mate, then both curves are necessarily helices. Finally, we provide a conclusive parametric representation of any null Bézier curve in terms of a single non-constant function. This representation offers a powerful tool for explicitly constructing null Bézier curves within this geometric setting.
Efficient Numerical Method for Generating Closed Form Solution for Nonlinear Bratu Differential Equations Otaide, Ikechukwu Jackson; Ekuma-Okereke Enyinnaya
Journal of Natural Sciences and Mathematics Research Vol. 11 No. 2 (2025): December
Publisher : Faculty of Science and Technology, Universitas Islam Negeri Walisongo Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21580/jnsmr.v11i2.26950

Abstract

This study presents a numerical solution of the Bratu differential equations (BDE) using the Sumudu transform series decomposition technique (STSDT). The process combines the Adomian polynomials (AP), series expansion (SE), and Sumudu transform (ST), and it ultimately converges perfectly to the exact solution. Examining four test problems demonstrates that the strategy converges more effectively than the literature-based approach. Calculations were performed using Maple 2022 software.
Potential of local material SiO2 water Hyacinth for semiconductor materials Hidayat, Sony; Ahmad Ziyan Nafis; Muhammad Noorman Perdana; Upik Nurbaiti
Journal of Natural Sciences and Mathematics Research Vol. 11 No. 2 (2025): December
Publisher : Faculty of Science and Technology, Universitas Islam Negeri Walisongo Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21580/jnsmr.v11i2.27406

Abstract

This study aims to examine the potential of local SiO₂ material synthesized from water hyacinth biomass waste as a candidate for semiconductor materials. Synthesis was carried out through a calcination process at temperatures above 600 °C to remove cellulose, lignin, and other impurities. Material characterization was carried out using UV-Vis spectroscopy, X-ray Diffraction (XRD), and Raman Spectroscopy. The results of UV-Vis spectroscopy showed that the water hyacinth derived SiO₂ exhibited an unusually reduced optical band gap of approximately 2.3 eV, likely influenced by impurity phases.. XRD tests indicated the presence of two crystal phases, namely the trigonal structure of SiO₂ and the monoclinic structure of the CaH₁₂O₁₇Si₂U₂ compound. Raman analysis confirmed the presence of functional groups such as Si, amorphous SiO2, CH₂/CH₃ and vibration signals from irregular sp² carbon. This combination of structures is thought to cause a lower band gap value compared to pure SiO₂. This finding indicates that SiO₂ from water hyacinth has potential as an intermediate semiconductor material, although further purification is still needed to increase the purity of the SiO₂ phase.
Forecasting the unemployment rate in West Java Province using VARX and SVR methods Kusuma Wardani, Yuniar; Sugiman
Journal of Natural Sciences and Mathematics Research Vol. 11 No. 2 (2025): December
Publisher : Faculty of Science and Technology, Universitas Islam Negeri Walisongo Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21580/jnsmr.v11i2.27602

Abstract

This study discusses the forecasting of the Open Unemployment Rate (OUR) in West Java Province using two time series approaches: Vector Autoregressive with Exogenous variables (VARX) and Support Vector Regression (SVR). The dataset consists of monthly observations from 2018 to 2023, including variables such as OUR, the Labor Force Participation Rate (LFPR), Gross Regional Domestic Product (GRDP), and the Human Development Index (HDI). Based on the optimal lag selection using the AIC, the VARX model produced the best lag configuration of (5,2), consisting of five lags for endogenous variables and two for exogenous variables. Meanwhile, the SVR model was developed through Grid Search to find the best parameter combination, resulting in a linear kernel with  and . The evaluation results showed that the SVR model performed better than VARX, with MSE, RMSE, and MAPE values of 0.24, 0.49, and 6%, respectively, lower than those of the VARX model, which reached 0.68, 0.82, and 8.4%. SVR was selected as the best model and used to forecast the OUR until the end of 2025. The forecast results indicated a spike in OUR at the beginning of 2024 at 8.52%, followed by a declining trend that continues and stabilizes in the range of 7.96%-8.12% by the end of 2025. In conclusion, SVR outperforms VARX in predictive accuracy, while VARX remains useful for analyzing inter-variable relationships.
Seismicity analysis of the Southern Java region (2020-2024) based on the b-value and a-value using the maximum Likelihood method Apriyanti, Syafrida Dwi; Fatmasari, Nurvita; Wijayanto, Mirda Prisma; Achmad, Arifin; Muflihatun
Journal of Natural Sciences and Mathematics Research Vol. 11 No. 2 (2025): December
Publisher : Faculty of Science and Technology, Universitas Islam Negeri Walisongo Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21580/jnsmr.v11i2.27765

Abstract

This study investigates the seismicity analysis of the Southern Java region using earthquake data obtained from BMKG Banjarnegara, comprising 1064 events recorded between 2020 and 2024. The study area spans coordinate 7.5°S-8.5°S and 108.31°E-109.50°E. The analysis was conducted using Microsoft Excel, ZMAP 7.0, and QGIS 3.28.2 to calculate the a-value and b-value, key parameters that describe the frequency and magnitude distribution of earthquakes. The magnitude of 2.6 was the most frequently observed, with 150 recorded events, while earthquakes occurring at a depth of 10 km were the most common, totaling 210 events. The high density of seismic occurrences reflects significant tectonic activity in the region. Using the maximum likelihood method, the b-value was determined to be approximately 1.09 ± 0.04, and the a-value was calculated at 5.754. The relatively low b-value suggests areas of elevated stress, implying potential for larger-magnitude earthquakes. Additionally, the spatial distribution of the a-value highlights regions of heightened seismic activity. These findings contribute to a deeper understanding of seismic behavior in Southern Java and offer valuable insights to support disaster risk reduction and earthquake mitigation efforts in the region.
Evaluating surface water and groundwater quality parameters in the Karst Mining Zone, Gunungkidul for environmental risk mitigation Yudhistira Zein Sanadha; Haerul Anwar; Faisal M. Jasin; Bayu Achil Sadjab
Journal of Natural Sciences and Mathematics Research Vol. 11 No. 2 (2025): December
Publisher : Faculty of Science and Technology, Universitas Islam Negeri Walisongo Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21580/jnsmr.v11i2.27773

Abstract

This study aims to characterize the physical, chemical, and microbiological water parameters of the Oya River (Bleberan Playen) and groundwater in the CV Kusuma Arga monitoring well, located in the white stone mining zone, Ponjong District, Gunungkidul Regency, Special Region of Yogyakarta, Indonesia. The importance of this research is driven by the lack of comprehensive water quality data in active karst mining areas and the potential environmental and health risks associated with contamination. Parameters tested included temperature, electrical conductivity (EC), total dissolved solids (TDS), turbidity, pH, nitrite, ammonia, chloride, sulfate, detergents, dissolved iron, dissolved lead, dissolved copper, dissolved cadmium, dissolved manganese, dissolved nickel, total coliform, and fecal coliform. Testing methods referred to the Indonesian National Standard (SNI) and Standard Methods, including the use of atomic absorption spectrophotometry (AAS) for heavy metal analysis and the membrane filter method for microbiology. The test results showed that most physical and chemical water parameters from both sources met the relevant quality standards. For example, the well water temperature of 27°C and well water pH of 6.9 were both declared to be by standards. However, analysis showed lead concentrations (0.1 mg/l in the river) and cadmium (0.010 mg/l in the river) exceeding World Health Organization (WHO) recommendations for drinking water, although initially categorized as "appropriate". Furthermore, total coliform (3000-5000 MPN/100ml) and fecal coliform (4000-4500 MPN/100ml) concentrations in both samples were very high, clearly indicating a health-risking fecal contamination, despite also being declared "appropriate" in the report. The role of Environmental Engineering science is crucial in sample collection, laboratory analysis, and interpretation of this data. This study contributes to the understanding of water quality in areas affected by mining activities and emphasizes the need for further evaluation for sustainable environmental management.
Comparative study of artificial Neural Network and Kalman Filter models for blood demand forecasting at PMI Surabaya Sofia, Ainin; Teguh Herlambang; Rizqi Putri Nourma Budiarti; Endang Sulistiyani
Journal of Natural Sciences and Mathematics Research Vol. 11 No. 2 (2025): December
Publisher : Faculty of Science and Technology, Universitas Islam Negeri Walisongo Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21580/jnsmr.v11i2.28540

Abstract

Blood plays a vital role in human health, making the need for donors and transfusions crucial. Currently, the Indonesian Red Cross (PMI) in Surabaya faces a balance issue between blood supply and demand. To address this, a blood demand forecasting model has been created at the PMI using ANN with a 4% error rate. The Kalman Filter algorithm is known to significantly reduce prediction errors from the prediction and correction process, while an ANN is considered capable of handling data complexity and nonlinearity. Therefore, this study aims to analyze the performance of the ANN and Kalman Filter models and compare the model performance results to determine the model with the best performance level. The modelling uses the CRISP-DM method, which starts from data understanding, data preparation, data modelling, model evaluation, and forecasting. The results of this study indicate that the Kalman Filter model successfully minimizes errors compared to the ANN prediction results, achieving a model accuracy level reaching 93.1%. These results demonstrate that the Kalman Filter model can significantly reduce prediction errors in the prediction and correction process, making it more optimal than the ANN model in forecasting blood demand at the PMI in Surabaya.
Endophytic fungi from Parijoto (Medinilla speciosa) leaves and their potential as biocontrol agents against Corn Pest Larvae Syaifudin, Andang; Wahidah, Baiq Farhatul
Journal of Natural Sciences and Mathematics Research Vol. 11 No. 2 (2025): December
Publisher : Faculty of Science and Technology, Universitas Islam Negeri Walisongo Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21580/jnsmr.v11i2.28768

Abstract

Parijoto (Medinilla speciosa) leaves are widely used for their antimicrobial properties. Endophytic fungi from these leaves show potential as entomopathogenic agents against Helicoverpa armigera larvae, a moth pest of cotton and corn.The research activities conducted in the laboratory include the isolation and characterization of endophytic fungi, as well as entomopathogenic testing against H. armigera larvae using a spraying technique with endophytic fungal extracts. In this study, 5 isolates were obtained from leaves and assessed their entomopathogenic properties. The isolate code is EP1, EP2, EP3, EP4, EP5. Bioassays were conducted to evaluate the effectiveness of these fungi in controlling H. armigera larvae. Among the tested fungi, EP5 demonstrated the highest entomopathogenic activity, significantly reducing the survival rate of the larvae. These findings indicate that EP5 holds substantial promise as a biocontrol agent for managing H. armigera populations with mortality percentage 30,78%, offering a sustainable and environmentally friendly alternative to chemical pesticides. The study underscores the potential of utilizing endophytic fungi from parijoto leaves in integrated pest management strategies.
Mineralogical classification and impact simulation of the Punggur (H7-Melt Breccia) Meteorite, Indonesia Muztaba, Robiatul; Danni Gathot Harbowo; Hakim Luthfi Malasan
Journal of Natural Sciences and Mathematics Research Vol. 11 No. 2 (2025): December
Publisher : Faculty of Science and Technology, Universitas Islam Negeri Walisongo Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21580/jnsmr.v11i2.29459

Abstract

Meteorite falls in Indonesia are rarely examined through systematic scientific analysis, resulting in limited documentation of fall events and incomplete classification of recovered specimens. The Punggur meteorite fall of 28 January 2021 reportedly produced at least five fragments. This study addresses that gap by analyzing two fragments (PM-01 and PM-02) to confirm their extraterrestrial origin and to characterize their physical, chemical, and mineralogical properties. Physical characterization involved measurements of density, magnetic susceptibility, and surface morphology. The chemical composition was determined using X-ray fluorescence (XRF), while microscopic imaging was employed to compare fusion-crust features with interior textures. A web-based meteoroid-impact modeling tool was further employed to estimate the atmospheric entry behavior and environmental effects of the fall. The result is that PM-01 has dimensions of 13 × 6.5 × 8 cm, a volume of 419 mL, a mass of 2200 g, and a density of 5.25 ± 0.26 g/cm³. PM-02 measures 25 × 23 × 16 cm, with a volume of 443 mL, a mass of 1820 g, and a density of 4.06 ± 0.06 g cm⁻³. Modeling results indicate that post-airburst fragments retained a residual velocity of approximately 16.2 km s⁻¹, while the airburst released an estimated 2.12 × 10¹⁰ J of energy (0.51 × 10⁻⁵ megatons). The shock wave reached observers 1.78 minutes after the event, accompanied by a maximum wind velocity of 0.0422 m s⁻¹ and sound levels near 25 dB—consistent with witness reports and the observed impact crater. Microscopic and XRF analyses reveal coarse-grained textures with high concentrations of Fe, Si, and Mg. PM-01 contains 23.55% Fe, 20.18% Si, and 12.48% Mg, whereas PM-02 contains 48.09% Fe, 25.06% Si, and 10.21% Mg. Thus, this finding indicates that the specimen’s mineralogy is dominated by olivine ((Mg, Fe)₂SiO₄), confirming that it aligns with the classification of an H7 melt breccia.

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