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Journal : Grimsa Journal of Science Engineering and Technology

GC-MS Analysis Reveals Unique Chemical Composition of Blumea balsamifera (L.) DC in Ie-Jue Geothermal Area Maulydia, Nur Balqis; Khairan, Khairan; Tallei, Trina Ekawati; Estevam, Ethiene Castellucci; Patwekar, Mohsina; Mohd Fauzi, Fazlin; Idroes, Rinaldi
Grimsa Journal of Science Engineering and Technology Vol. 1 No. 1 (2023): October 2023
Publisher : Graha Primera Saintifika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61975/gjset.v1i1.6

Abstract

Blumea balsamifera (L.) DC. or Sembung is a flowering plant belonging to the genus Blumea of the family Asteraceae. Many pharmacological activities of this plant show potential in human therapy. In this study, an investigation was conducted on the ethanolic extract of B. balsamifera collected from a geothermal area known as Ie-Jue, in Aceh Province, Indonesia. The results showed that the ethanolic extract of B. balsamifera contained secondary metabolites of flavonoids and tannins. Chemical constituents of ethanolic extracts B. balsamifera further analysis using gas chromatography-mass spectrometry (GC-MS) show that active compounds from this plant was Proximadiol (C15H28O2) with relative area 41.76%. This research underscores the compelling potential of the Ie-Jue geothermal area as a promising reservoir of flora owing to the plant's adaptability to geothermal extremities.
Geothermal Flora and AgNPs Synergy: A Study on the Efficacy of Lantana camara and Acrostichum aureum-Infused Hand Sanitizers Harera, Cheariva Firsa; Maysarah, Hilda; Kemala, Pati; Idroes, Ghazi Mauer; Maulydia, Nur Balqis; Patwekar, Mohsina; Idroes, Rinaldi
Grimsa Journal of Science Engineering and Technology Vol. 2 No. 2 (2024): October 2024
Publisher : Graha Primera Saintifika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61975/gjset.v2i2.38

Abstract

Hand hygiene is an important factor that needs to be observed in controlling the spread of diseases transmitted through hand-to-hand contact. Synthesis of silver nanoparticles from tembelekan (Lantana camara) and paku laut (Acrostichum aureum) using the green synthesis method has good antibacterial activity against Staphylococcus aureus and Escherichia coli bacteria. Therefore, a preparation formulation was made, namely hand sanitizer, which is still rarely used. Formulations that have successfully entered the evaluation stage include organoleptic tests, homogeneity tests, spreadability tests, adhesion tests, viscosity tests, pH tests, accelerated stability tests, and irritation tests. Antibacterial activity was evaluated against bacteria Staphylococcus aureus and Escherichia coli. The hand sanitizer is formulated to contain 5% tembelekan AgNPs (F1); paku laut AgNPs 5% (F2); and a combination of 2.5% paku laut AgNPs and 2.5% tembelekan AgNPs. The resulting hand sanitizer has good organoleptic characteristics, except for the color of the preparation, which changed during the accelerated stability test. Test results for pH, adhesion, spreadability, viscosity, and homogeneity of hand sanitizer meet the requirements of a good test. Irritation tests on ten volunteers showed no irritation reaction. Antibacterial tests show that hand sanitizer has bacterial antibacterial activity with an average ± standard deviation of the inhibition zone Staphylococcus aureus is 6.605±0.459(F1); 6.665±0.615(F2); 6.380±0.282(F3) dan Escherichia coli namely 6.575 ± 0.219 (F1); 6.860 ± 0.155 (F2); 6.810 ± 0.056 (F3). Making hand sanitizer AgNPs-based ingredients from plants can be used as hand sanitizer, but stabilizers are required to prevent color changes during storage.
Fine-Tuning ChemBERTa for Predicting Activity of AXL Kinase Inhibitors in Oncogenic Target Modeling Noviandy, Teuku Rizky; Idroes, Ghazi Mauer; Patwekar, Mohsina; Idroes, Rinaldi
Grimsa Journal of Science Engineering and Technology Vol. 3 No. 2 (2025): October 2025
Publisher : Graha Primera Saintifika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61975/gjset.v3i2.98

Abstract

The development of selective kinase inhibitors remains a key objective in cancer drug discovery, where predictive computational models can significantly accelerate the identification of leads. In this study, we investigate the fine-tuning strategies of the transformer-based ChemBERTa model for quantitative structure–activity relationship (QSAR) modeling of AXL receptor tyrosine kinase inhibitors, an important therapeutic target implicated in tumor progression and metastasis. A dataset of AXL inhibitors was curated from the ChEMBL database. Three fine-tuning configurations, namely baseline, full fine-tune, and aggressive, were implemented to examine the influence of learning rate, weight decay, and the number of frozen transformer layers on model performance. Models were evaluated using accuracy, precision, recall, F1-score, and calibration metrics. Results showed that both the full fine-tune and aggressive configurations outperformed the baseline model, achieving higher precision and F1-scores while maintaining robust recall. The aggressive configuration achieved the most balanced performance, with improved calibration and the lowest expected calibration error, indicating reliable probabilistic predictions. Overall, this study highlights that controlled fine-tuning of ChemBERTa significantly enhances predictive performance and confidence estimation in QSAR modeling, offering valuable insights for optimizing transformer-based chemical language models in kinase-targeted drug discovery.