AXL tyrosine kinase plays a critical role in cancer progression, metastasis, and therapy resistance, making it a promising target for therapeutic intervention. However, traditional drug discovery methods for developing AXL inhibitors are resource-intensive, time-consuming, and often fail to provide detailed insights into molecular determinants of potency. To address this gap, we applied machine learning techniques, including Random Forest, Gradient Boosting, Support Vector Regression, and Decision Tree models, to predict the potency (pIC₅₀) of AXL inhibitors using a dataset of 972 compounds with 550 molecular descriptors. Our results demonstrate that the Random Forest model outperformed others with an R² of 0.703, MAE of 0.553, RMSE of 0.720, and PCC of 0.841, showcasing strong predictive accuracy. SHAP analysis identified critical molecular features, such as RNCG and TopoPSA(NO), as key contributors to inhibitor potency, providing interpretable insights into structure-activity relationships. These findings highlight the potential of machine learning to accelerate the identification and optimization of AXL inhibitors, bridging the gap between computational predictions and rational drug design and paving the way for effective cancer therapeutics.

Skin aging is a natural process of change in all living organisms, it is associated with cell maturation. Cells gradually lose function on exposure to factors such as sunlight, pollution, or prolonged contact with chemicals. Patchouli Essential Oil (PEO) extracted from Patchouli Plant (Pogostemon cablin Benth.) is known to have antioxidants and anti-aging properties. Therefore, this study aimed to determine the potential of PEO as an anti-aging agent using in silico methods. PEO Chemical Profiling was done using Gas Chromatography-Mass Spectrometry (GC-MS). Each PEO active molecule was subjected to ADME (Adsorption, Distribution, Metabolism, and Excretion) analysis using Lipinski's Rule of Five and LogKp (Skin Permeability) in the SwissADME database, followed by toxicity test using the ProTox-II database. Each of the selected compounds was subjected to reverse docking against skin-aging proteins known to play important roles in the aging process including MMP13 (Collagenase), MMP9 (Gelatinase), and hyaluronidase using the Autodock Vina program integrated into the PyRx software. In addition, Molecular Dynamics Simulation (MDS) was carried out using YASARA (Yet Another Scientific Artificial Reality Application) v.23.5.19 software. GC-MS analysis of PEO detected 44 compounds, out of which 26 compounds with anti-aging potential were selected based on ADME and toxicity studies. Molecular docking result showed that the compound 3, 7, 11-trimethyl-dodeca-2, 4, 6, 10-tetraenal had the lowest binding energy value (-8.2 Kcal/mol) against the MMP9 protein. MDS data also demonstrated excellent interaction between ligand molecule and MMP9 protein. These results imply that PEO compounds may inhibit the function of skin-aging proteins.

Coffee is one of the plantation commodities with a high economic value among other plantation crops and plays an important role as a source of foreign exchange. Indonesian coffee is classified into two types of coffee, namely arabica coffee and robusta coffee. According to data from the Central Bureau of Statistics of Aceh Province (2019), the area of coffee plantations in Aceh reached 123,749 ha with a production of 68,493 tons. About 85% of the land area is planted with arabica coffee, while the rest is planted with robusta coffee. This study analyzes the morphological relationships of various Arabica and Robusta coffee plant varieties at the Gayo Experimental Garden, Pondok Gajah District, Bener Meriah Regency, Aceh Province. Samples of coffee varieties were selected by purposive sampling method. The morphological characters observed were 25 on stem organs, leaves, flowers, fruits, and beans. Data analysis was conducted using the NTSYS program and presented as a dendrogram. The results showed that eleven coffee varieties were grouped into four groups. The variety that has the furthest kinship is Mocca Yaman, with a coefficient value of 0.58. The varieties with the closest kinship are C 48 and C 49, with a coefficient value of 0.84. These two varieties have similarities in the 19 observed morphological characters.

The issue of global warming is a threat to the survival of various ecosystems on earth. The purpose of the study was to determine changes in land cover of green The issue of global warming is a threat to the survival of various ecosystems on earth. The purpose of the study was to determine changes in land cover of green

Aceh is an exceptional region in Indonesia characterized by significant biodiversity and abundant natural wealth. Despite these numerous benefits, there is limited information regarding the potential of biodiversity in this region. Therefore, this research aimed to design and develop Website and Android-based applications to facilitate access to information regarding biodiversity in Aceh. In the development process, the Waterfall method was used, and the applications consisted of two main components, namely the back-end and the front-end. The users were divided into three categories, including contributors, verificators, and admins. After the development was complete, functionality testing was conducted using the black box method, and usability was examined using the Post-Study System Usability Questionnaire (PSSUQ). The results of functionality testing showed that both applications operate efficiently, thereby providing users with a satisfying experience when accessing information about Aceh biodiversity. The usability score was approximately 7 for Website-based and 6 for Android-based applications, showing a high level of usability.