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Eksakta : Berkala Ilmiah Bidang MIPA
Published by Universitas Negeri Padang
ISSN : -     EISSN : 25497464     DOI : https://doi.org/10.24036/eksakta/
Core Subject : Science, Education, Agriculture, Social, Engineering,
Agriculture, Biological Sciences & Forestry Astronomy Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Energy Engineering Environmental Science Materials Science & Nanotechnology Mathematics Mechanical Engineering
Eksakta : Berkala Ilmiah Bidang MIPA (E-ISSN : 2549-7464) is an open access journal and peer-reviewed that publishes either original article or reviews. The journal is dedicated towards dissemination of knowledge related to the advancement in scientific research. The prestigious interdisciplinary editorial board reflects the diversity of subjects covered in this journal. Under the realm of science and technology, the coverage includes environmental science, pure and applied mathematics, agricultural research and engineering, biology, biotechnology, bioinformatics, Healthcare sciences (including clinical medicine, preventive medicine & public health), physics, biophysics, computer science, chemistry and bioengineering, to name a few. This Journal Is Published at 3 Month intervals on January-Marc, April-June, July-September and October-December
Arjuna Subject : Umum - Umum
Articles 333 Documents
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Spatial-Temporal Analysis of b-value Before and After the 2018 Lombok Earthquake Using OK1993 Based on Voronoi in the Bali-NTB Region Tata Dwi Hardi Yanti; Yudha Styawan; Rizki Wulandari
EKSAKTA: Berkala Ilmiah Bidang MIPA Vol. 27 No. 03 (2026): Eksakta : Berkala Ilmiah Bidang MIPA (E-ISSN : 2549-7464) In Progress
Publisher : Faculty of Mathematics and Natural Sciences (FMIPA), Universitas Negeri Padang, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/eksakta/vol27-iss03/678

Abstract

This study is motivated by the tectonic complexity of the Bali-NTB region, which results in a heterogeneous seismic distribution and active stress dynamics. The objective is to analyze the spatiotemporal evolution of the b-value using the Ogata-Katsura maximum likelihood estimation (OK1993), combined with Voronoi tessellation as an adaptive spatial partition and the Bayesian Information Criterion (BIC) for ensemble model optimization. Spatial analysis prior to the 2018 event revealed a contradiction in the form of high b-value (>1.0) in Lombok. However, the spatiotemporal analysis successfully explains the condition by identifying a zone of low b-value (<1.0) that developed following the 2007 intermediate sized earthquake through the 2018 mainshock distinct from the 2004 local anomaly that did not progress into a major earthquake. This indicates that the persistence of low b-values is a key indicator of high stress accumulation. Following the 2018 earthquake, the high stress zone expanded across Lombok and West Nusa Tenggara (NTB). This study emphasizes the importance of evaluating statistical reliability, such as N(b) and Median Absolute Deviation (MAD), to avoid misinterpretations due to data limitations, thereby providing a more reliable framework for regional seismic hazard assessment.
Residual-Based Analysis of the Mismatch Between LoRa Channel Models and Field Measurements in Urban and Rural Environments Muhamad Bagus Fikril Alan; Pradini Puspitaningayu; Nurhayati Nurhayati; Muhammad &#039;Aamir Nashrullah; Nobuo Funabiki; Erwin Sutanto; Fahmi Fahmi
EKSAKTA: Berkala Ilmiah Bidang MIPA Vol. 27 No. 03 (2026): Eksakta : Berkala Ilmiah Bidang MIPA (E-ISSN : 2549-7464) In Progress
Publisher : Faculty of Mathematics and Natural Sciences (FMIPA), Universitas Negeri Padang, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/eksakta/vol27-iss03/683

Abstract

This study investigates discrepancies between classical propagation models (Okumura-Hata, CI, FI) and LoRa field measurements in urban and rural environments. While rural areas exhibited linear path loss trends, urban scenarios showed distinct signal saturation, resulting in significant residuals even after model optimization. To address this, a residual-based analysis using Machine Learning (Linear Regression, Decision Tree, Random Forest) was proposed to map these systematic errors. The evaluation reveals that Random Forest (RF) significantly outperforms other algorithms, achieving an of 0.961 and an RMSE of 3.291 dB. These findings demonstrate that model mismatches follow deterministic patterns driven by environmental features rather than random noise. The study concludes that integrating ML-based residual compensation is essential for accurate radio planning in heterogeneous network deployments.
Influence of Species, Growing Site, and Postharvest Leaf Handling on the Yield and Chemical Composition of Cajuput Oil (Melaleuca spp.) from Seram Island, Indonesia Imanuel Berly Delvis Kapelle; Fensia Analda Souhoka; Nini Munirah Renur
EKSAKTA: Berkala Ilmiah Bidang MIPA Vol. 27 No. 03 (2026): Eksakta : Berkala Ilmiah Bidang MIPA (E-ISSN : 2549-7464) In Progress
Publisher : Faculty of Mathematics and Natural Sciences (FMIPA), Universitas Negeri Padang, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/eksakta/vol27-iss03/687

Abstract

Cajuput (Melaleuca spp.) is a high-value non-timber forest product in Seram Island, Maluku. The quality of cajuput oil is primarily determined by its 1,8-cineole (eucalyptol) content, which is influenced by genetic, environmental, and raw material factors. This study analyzed the effects of species, growing location, and raw material condition on the yield and chemical composition of oil derived from Melaleuca leucadendra and Melaleuca cajuputi collected from Hatusua and Eti villages, using distillation and GC-MS analysis. The results showed that fresh leaves yielded higher amounts than dried leaves. The highest yield was obtained from M. leucadendra from Eti (1.022%), while the lowest yield was recorded from dried leaves (0.008%). M. leucadendra oil was dominated by eucalyptol (56.62–58.50%), whereas M. cajuputi was dominated by methyleugenol (81.61%) with a lower yield (0.1213%), reflecting differences in genetically controlled metabolic pathways. Environmental factors influenced yield and minor compounds without altering the dominant constituents. Overall, the quality and quantity of cajuput oil are determined by the interactions among genetic, environmental, and post-harvest factors. The use of fresh raw materials, appropriate species or chemotypes, and optimal growing locations is key to improving oil quality and ensuring consistent production.   

Page 34 of 34 | Total Record : 333

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