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Turnover intention is widely recognized as one of the earliest indicators of potential employee resignation, which in turn can generate considerable organizational challenges such as increased operational costs, the erosion of organizational knowledge, and declining productivity levels. While a significant body of international research has explored the antecedents of turnover intention, studies that specifically provide a narrative synthesis within the Indonesian workforce context remain scarce. Recognizing this gap, the present study seeks to identify the dominant factors that influence turnover intention in Indonesia by conducting a narrative literature review. The review focused on nine selected articles published between 2018 and 2023 in nationally indexed journals. To ensure rigor, the selection was based on predefined criteria: the articles had to employ empirical designs involving full-time employees, apply quantitative research methodologies, and explicitly examine the relationships between independent variables and turnover intention. The data extracted from the studies were analyzed thematically to identify recurring patterns and dominant themes. The analysis revealed four key factors that consistently shaped turnover intention across the reviewed literature. First, job stress was found to be a critical determinant, where prolonged work pressure and role overload significantly increased employees’ desire to leave. Second, job satisfaction emerged as a central variable, with dissatisfaction related to compensation, recognition, and career development strongly linked to turnover intention. Third, leadership style played an important role, as authoritarian or unsupportive leadership approaches heightened employees’ intention to resign. Finally, the leader’s role in fostering workplace relationships and support systems was identified as a factor influencing employee attachment and loyalty. In conclusion, this study contributes theoretically by mapping the dominant factors of turnover intention within the Indonesian context and highlights their interconnections.

Burns can cause infection, hinder healing, and increase the risk of long-term complications. Staphylococcus aureus and Pseudomonas aeruginosa often infect burn wounds in general, infections are treated with antibiotics, but continued use of antibiotics can cause bacterial resistance. Binahong leaves (Anredera cordifolia) have potential as a substitute for antibiotics because of their antibacterial properties from active compounds such as alkaloids, polyphenols, tannins, saponins and ascorbic acid. This research aims to activate the antibacterial ability of binahong leaf ethanol extract against S. aureus and P. aeruginosa. This research uses an experimental method with a control group design using diffusion and dilution methods at varying concentrations. Statistical analysis of the inhibition zone showed that there was a significance difference of <0.05 between treatment groups. In the solid diluted method, S. aureus obtained an MIC value of 10.5% and a MBC of 11.5%, whereas P. aeruginosa had an MIC of 14.5% and a MBC of 15%. The results showed that the ethanol extract of binahong leaves was more sensitive to S. aureus than P. aeruginosa.  

Urological examinations using Multi Slice Computed Tomography (MSCT) often require the use of diuretic agents to enhance the visualization of the urinary tract system. However, the use of synthetic pharmacological agents may sometimes lead to undesirable side effects. The aim of this study was to evaluate the effectiveness of ginger extract (Zingiber officinale) as a natural diuretic alternative in MSCT urological examinations. This research utilized an experimental design, comparing two groups: one that was given ginger extract before the examination and another control group that did not receive any additional treatment. Key parameters observed included the degree of urinary tract distension, MSCT image quality, and the smoothness of contrast media excretion. The results indicated that the administration of ginger extract significantly increased the degree of ureteral and urinary bladder distension, leading to improved image visualization quality compared to the control group. These findings suggest that ginger extract can serve as a promising natural diuretic alternative for MSCT urological examinations. However, further studies with larger sample sizes are necessary to confirm the validity and reproducibility of these results. Ginger extract offers an innovative and potentially safer approach to improving the effectiveness of MSCT scans without the side effects associated with synthetic diuretics.

This study investigates the influence of an online attendance system and digital literacy on teacher discipline and performance in elementary schools. A quantitative explanatory research approach was employed to provide empirical evidence regarding these relationships. The research population consisted of 170 elementary school teachers in Bojong District, Pekalongan Regency, who were selected using proportional stratified random sampling to ensure representativeness. Data were collected through a structured questionnaire using a 5-point Likert scale, and analyzed with Structural Equation Modeling (SEM) through the Partial Least Squares (PLS-SEM) approach using SmartPLS 4.0 software. The measurement model evaluation demonstrated strong reliability and validity across all constructs. Cronbach’s Alpha values ranged between 0.820 and 0.872, Composite Reliability between 0.881 and 0.911, and Average Variance Extracted (AVE) between 0.649 and 0.718. Discriminant validity was confirmed based on both the Fornell-Larcker Criterion and the Heterotrait-Monotrait Ratio (HTMT). The structural model showed good predictive relevance with a Goodness-of-Fit (GoF) value of 0.366, indicating a large effect. Hypothesis testing results supported all proposed relationships. Digital literacy was found to positively influence teacher performance, while the online attendance system significantly affected both teacher discipline and teacher performance. Furthermore, teacher discipline was proven to have a positive effect on teacher performance. Mediation testing revealed that teacher discipline acted as a significant partial mediator in the relationships between digital literacy, online attendance systems, and teacher performance. The findings provide empirical validation for the Task-Technology Fit Theory and the TPACK Framework in the context of educational human resource management. This study confirms that digital transformation, through strengthening digital literacy and online systems, represents an effective strategy to improve teacher professionalism and enhance academic quality in elementary schools.  

Dyslipidemia is a lipid metabolism disorder characterized by elevated levels of total cholesterol, triglycerides, and low-density lipoprotein (LDL) accompanied by decreased levels of high-density lipoprotein (HDL). This condition is a major risk factor for atherosclerosis, coronary heart disease, and stroke. One plant with potential as an antidyslipidemic agent is bay leaves (Syzygium polyanthum). These leaves are known to contain active compounds such as flavonoids, saponins, tannins, alkaloids, and polyphenols that have antioxidant and hypolipidemic activities. The potential of natural compounds from medicinal plants to reduce blood cholesterol levels has gained significant attention in recent years. This study aims to evaluate the effectiveness of microencapsulated ethanol extract of bay leaves in reducing total cholesterol levels in white rats (Rattus norvegicus) induced by a high-cholesterol diet. The experimental study design employed was a laboratory-based true experimental method with a post-test control group design. A total of 25 male rats were used and divided into six groups: normal control, negative control (high cholesterol diet without therapy), positive control (simvastatin), and three groups treated with bay leaf extract microencapsulates at doses of 0.25%, 0.5%, and 0.75%. The treatment was given for 14 days, then total cholesterol levels were measured using an enzymatic method. The results showed that the group with a dose of 0.75% experienced the highest decrease in total cholesterol levels, namely -70 mg/dL, greater than the simvastatin group (-49 mg/dL). Statistical analysis using One Way ANOVA showed a significant difference compared to the negative control (p < 0.001). These findings indicate that the 0.75% dose of microencapsulated Syzygium polyanthum extract demonstrated an effect equal to or greater than simvastatin. Thus, it can be concluded that bay leaf ethanol extract microencapsulates are effective in reducing total cholesterol levels in hypercholesterolemic rats. This suggests that Syzygium polyanthum microencapsulation has the potential to be developed as an alternative phytotherapy for cholesterol reduction.

Dyslipidemia is a health problem characterized by impaired fat metabolism in the body, characterized by changes in blood lipid levels, either increasing or decreasing. This condition is generally seen through increased levels of total cholesterol, low-density lipoprotein (LDL), triglycerides, and decreased levels of high-density lipoprotein (HDL). This imbalance in the lipid profile, if persisted over the long term, has the potential to accelerate the formation of atherosclerotic plaque on artery walls, which can lead to cardiovascular disease. This study aims to determine the effectiveness of papaya leaf (Carica papaya L.) ethanol extract microcapsules in reducing cholesterol levels in white rats induced by a high-fat diet. The high-fat diet is formulated from a mixture of beef fat, eggs, and lard to increase cholesterol levels in a controlled manner. After the induction phase, the rats were divided into six treatment groups: a negative control group, a positive control group (simvastatin 0.36 mg), and three treatment groups with doses of papaya leaf ethanol extract microcapsules of 0.25%, 0.50%, and 0.75%. The treatment was given orally for 14 consecutive days. Total cholesterol levels were measured before and after treatment to evaluate the effectiveness of the intervention. The results showed that administration of papaya leaf extract microcapsules significantly reduced cholesterol levels. The 0.50% dose provided the most optimal effect, with a reduction reaching 77 mg/dL, greater than the simvastatin group. However, increasing the dose to 0.75% did not show a significant additional reduction effect, indicating an optimal dose-response point. Therefore, the 0.50% concentration can be considered the most effective dose and has the potential to be developed as an alternative natural cholesterol-lowering therapy. These findings also strengthen the potential use of papaya leaves as a bioactive source to support efforts to prevent and control dyslipidemia.  

Elevated blood cholesterol levels are known to be a major risk factor for cardiovascular disease. Hypercholesterolemia can trigger atherosclerosis, which in turn increases the risk of coronary heart disease and stroke. One approach to managing cholesterol levels is through the use of natural ingredients with antihyperlipidemic activity. White turmeric (Curcuma zedoaria Rosc) is an herbal plant long used in traditional medicine and contains bioactive compounds such as curcuminoids and essential oils. These compounds are reported to have antioxidant and anti-inflammatory activities, as well as potential as agents for lowering blood lipid levels. Herbal-based therapies are increasingly considered as safe alternatives to synthetic drugs in managing hyperlipidemia. This study aims to evaluate the effectiveness of a microencapsulated preparation of white turmeric ethanol extract in reducing total cholesterol levels in male rats (Rattus norvegicus) induced by a high-fat diet. The study was conducted experimentally using 25 rats divided into six treatment groups. The groups consisted of normal controls, negative controls, positive controls using simvastatin, and three treatment groups given white turmeric extract microcapsules at concentrations of 0.25%, 0.50%, and 0.75%. The microencapsulation technique was applied to improve the stability and bioavailability of the turmeric extract. Cholesterol levels were measured before and after treatment. The results showed that the treatment group with the 0.25% concentration produced the most significant cholesterol reduction, from 110 mg/dL to 59 mg/dL. These findings indicate that even at a relatively low concentration, microencapsulated turmeric extract can significantly reduce cholesterol levels in vivo. Therefore, it can be concluded that white turmeric extract in microcapsule form is effective in lowering total cholesterol levels, especially at the 0.25% dose. This suggests that Curcuma zedoaria microcapsules hold promise as a natural therapeutic option for managing hypercholesterolemia and reducing cardiovascular risk.  

Dyslipidemia is a lipid metabolism disorder characterized by an increase or decrease in blood plasma fat levels. This condition includes high levels of total cholesterol, low-density lipoprotein (LDL), and triglycerides, as well as decreased levels of high-density lipoprotein (HDL). In general, dyslipidemia is divided into two types: primary, which is influenced by genetic factors, and secondary, which is caused by other diseases or an unhealthy lifestyle. Dyslipidemia is one of the major risk factors for cardiovascular disease, making its prevention and treatment very important. In this study, male white mice were used and induced with a high-fat diet to trigger dyslipidemia. The test animals were then divided into six groups: a negative control, a positive control (given simvastatin at a dose of 0.36 mL/day), and three treatment groups with microcapsules of Chinese betel leaf herb ethanol extract (EEHSC) at concentrations of 0.25%, 0.5%, and 0.75%. The treatment was administered orally for 14 days. Cholesterol levels were measured before and after treatment using a digital cholesterol tester and laboratory analysis to ensure more accurate results. The results showed a decrease in cholesterol levels with varying percentages in each group. The negative control decreased by 24.8%, the positive control by 36.1%, the 0.25% EEHSC by 24.1%, the 0.5% EEHSC by 34.7%, and the 0.75% EEHSC by 45.5%. This indicates that the 0.5% EEHSC treatment produced cholesterol reductions almost comparable to simvastatin. Interestingly, the highest effect was observed in the 0.75% group, indicating a dose-dependent response. In contrast, the 0.25% concentration only produced a less than optimal effect. Thus, microcapsules of ethanol extract of the Chinese betel leaf herb have potential as an alternative agent for lowering cholesterol levels, particularly in dyslipidemia. These findings suggest that natural-based therapies could complement conventional treatments in managing lipid disorders.

The pitcher plant (Nepenthes sp.) is a type of predatory plant typically found in tropical regions and has a pitcher structure designed to attack insects. The pitcher's structure acts as a small ecosystem that supports a variety of microorganisms, both those living on the surface (epiphytes) and those within the tissue (endophytes). This study aimed to extract and identify microorganisms present on the surface and interior of the pitcher plant. Samples were taken from peat swamps and separated using Nutrient Agar (NA) for bacteria and Potato Dextrose Agar (PDA) for fungi. The discovery process involved examining morphological characteristics both visually and under a microscope. The results revealed differences in the types of microorganisms between the outside and inside of the pitcher, influenced by the microenvironmental conditions in each area. These findings can serve as a foundation for further study of the bioactive potential of microorganisms from the pitcher plant.

Digital image processing is a rapidly developing branch of computer science and has many applications in everyday life. One of the fields that most often utilizes this technique is object detection and color identification in images and videos. This study specifically aims to implement the thresholding method in the HSV (Hue, Saturation, Value) color space to detect three basic colors, namely red, green, and blue, in digital images. The research process begins with uploading images using the Google Colab platform, a cloud-based computing environment that makes it easy for users to run Python programs without requiring additional software installation. After the image is uploaded, the next step is to convert it from the RGB (Red, Green, Blue) color space to the HSV color space. This conversion is important because the HSV color space is more suitable for use in the color segmentation process. The Hue value represents the type of color, Saturation shows the level of saturation, while Value describes the level of brightness. Once the image is in the HSV color space, the next step is to determine the HSV value range for each basic color. This range is determined based on experimental results and references from related literature. Using this range, masking is performed to extract the appropriate pixels so that only the red, green, or blue portions of the image are visible, while the other colors are reduced. The results show that the thresholding method in the HSV color space is capable of detecting primary colors with a good level of visual accuracy, especially in simple images with contrasting backgrounds. The implementation of this program is relatively lightweight, easy to run directly in Google Colab, and does not require high-spec hardware. Therefore, this method is very suitable for use as basic learning material for digital image processing, both for students and novice researchers.

During storage and before consumption, grains often experience a decline in quality, nutritional content, and cleanliness due to pest attacks. Botanical insecticides are considered an alternative method to reduce dependence on harmful chemical pesticides. This study aimed to evaluate the effectiveness of three concentrations of silver nanoparticles (AgNPs) synthesized from the leaves of Cymbopogon citratus against Cadra cautella (Walk.) (Lepidoptera: Pyralidae) and their potential as biological control agents. The selection of C. cautella as the test organism was based on the limited number of studies examining this pest. The AgNPs used were synthesized through an eco-friendly method, and their optical and physical properties were analyzed using UV-Vis spectroscopy. The results demonstrated that AgNPs synthesized from C. citratus extract showed high effectiveness in controlling the eggs and second instar larvae of C. cautella. Egg mortality reached 80.3% at a concentration of 40 μg/ml after 24 hours of exposure, followed by 72.9% at 30 μg/ml, and 65.8% at 20 μg/ml. In contrast, the control group showed no egg mortality. Similarly, larval mortality rates were 74.9%, 65.8%, and 60.2% for concentrations of 40 μg/ml, 30 μg/ml, and 20 μg/ml, respectively. These findings indicate that higher concentrations of AgNPs lead to greater mortality in both eggs and larvae. This study highlights the potential of green-synthesized AgNPs from C. citratus leaves as an effective and eco-friendly biopesticide. Their significant impact on egg and larval mortality suggests that they can be developed as an alternative pest control strategy in stored grains, thereby reducing reliance on conventional chemical pesticides that are detrimental to human health and the environment. Further research is recommended to explore their long-term efficacy, safety, and integration into sustainable grain storage management.

Steel structure projects are increasingly favored in the construction industry due to their benefits in execution time efficiency and long-term cost savings. However, the suboptimal management of human resources (HRM) remains a significant challenge in achieving these efficiencies. This study aims to systematically review the role of HRM in enhancing time and cost efficiency in steel structure projects. A Systematic Literature Review (SLR) was conducted based on the PRISMA protocol, analyzing 35 accredited scientific articles published between 2013 and 2023. The articles were sourced from national databases such as Garuda and Neliti, and data were extracted using standardized documentation instruments. The analysis reveals that workforce planning, project-based training, performance monitoring, and inter-team coordination are key managerial aspects that consistently contribute to improving both time and cost efficiency. Visualization of topic networks using VOSviewer highlights strong interconnections between themes such as "training," "schedule control," and "performance evaluation," all of which are critical components of strategic HRM practices. This study concludes that HRM plays a crucial role in achieving efficiency in steel structure projects, especially through the integration of technical workflows and managerial control systems. Effective workforce planning ensures that the right skills are available at the right time, while performance monitoring and training programs help enhance productivity and reduce delays. The findings suggest the necessity for formulating HR policies that are based on workload analysis and the improvement of real-time workforce evaluation mechanisms. Furthermore, the study calls for further research to test integrative models for HRM practices in steel-based construction projects in Indonesia. This research opens avenues for refining HRM strategies to support the construction industry’s efficiency goals, offering insights for future studies and practical applications in the field.

In helping to support the appearance and confidence of the skin needs to be treated especially for dry skin. Having a dry facial skin causes discomfort because the cosmetics used will be difficult to stick to the skin. In addition, weather factors, the use of unsuitable cosmetics, exposed to excessive sun exposure, and unhealthy lifestyles can cause the skin to become dry. The purpose of this study was to determine the process of making gel masks from carrot extracts and seen from laboratory tests, organoleptic tests and hedonic tests. This study uses quantitative methods with an experimental approach. Data collection techniques through observation, documentation and observation sheets that can be seen from the results of laboratory tests, organoleptic tests (texture, color, aroma, adhesion) and hedonic tests (panelists). The results of the study obtained from the results of laboratory tests by looking at the pH level of each formulation are in a safe range of 4-5. In the organoleptic test, panelists declared F1 as a preparation of less thick, orange, and lack of scented in carrot. In the F2 formulation, panelists declare as a texture preparation that is thick, orange, and scented typical of carrots. In the F3 formulation, the panelists declare that the preparation is less thick, less orange, and a typical carrot scented. In the F4 formulation, panelists declare as a very thick, non -orange preparation. And very scented typical of carrots. In the adhesion of the panelist states from all formulations that F4 is very attached. In the hedonic test, the preparation that many panelists like, namely the F4 preparation, is very thick, not orange and very scented typical of carrots. Thus the gel mask of carrot extract can be used as material for making gel masks seen from laboratory tests, organoleptic tests, and hedonic tests.

Fish bekasam is one of Indonesia's traditional fermented products that involves the activity of microorganisms, especially lactic acid bacteria (LAB), to produce unique organoleptic, chemical, and microbiological characteristics. The fermentation process of bekasam plays a significant role not only in extending the shelf life of fish but also in creating a distinctive sour taste and texture that differs from other fish products. This study aims to analyze the microbiological community involved in the fish bekasam fermentation process through observation and identification of bacteria using Safranin Violet and Iodine staining techniques. This study employs a literature review approach, examining various references related to the fermentation process, the dominant bacteria species, and the environmental factors that affect the quality of bekasam. The analysis revealed that lactic acid bacteria such as Lactobacillus plantarum, Lactobacillus casei, and Pediococcus spp. play an important role in the fermentation of bekasam fish. These bacteria produce lactic acid, which contributes to the sour taste and plays a role in forming the product's texture. The Safranin Violet and Iodine staining techniques were effective for identifying bacteria based on their cell wall characteristics, with Gram-positive bacteria dominating the fermentation process. Environmental factors such as the fermentation time, salt concentration, and the addition of ingredients like carbohydrates or turmeric extract influence the dynamics of bacterial populations in the fermentation of bekasam. This study also emphasizes the importance of controlling pathogenic bacterial contamination, such as Salmonella spp. and Escherichia coli, to ensure food safety in bekasam products. The findings provide a deeper understanding of the microbiological dynamics in fish bekasam fermentation and the relevance of staining techniques in microbiological analysis, which can be used to improve the quality and safety of traditional fermented products. This study also opens opportunities for developing safer and higher-quality bekasam products.

Wireless Medical Sensor Networks (WMSNs) are a key component of modern Healthcare Internet of Things (IoT) systems, enabling continuous and real-time monitoring of patients’ physiological parameters. These networks support timely medical intervention, improve patient outcomes, and facilitate remote healthcare delivery. However, due to the open and resource-constrained nature of WMSNs, they are highly susceptible to various security threats, particularly during the authentication phase. Existing authentication protocols have been found vulnerable to a range of attacks, including impersonation, session key disclosure, and gateway database compromise, which can lead to severe privacy breaches and potentially life-threatening situations. To address these issues, this paper proposes a secure and lightweight three-factor authentication protocol tailored for WMSNs in healthcare IoT environments. The proposed protocol integrates Elliptic Curve Cryptography (ECC) for strong public key-based security with minimal computational overhead, fuzzy extractors to securely handle biometric information and ensure resistance against biometric template compromise, and session-based randomness to achieve forward secrecy and prevent replay or key-compromise impersonation attacks. Security analysis demonstrates that the proposed protocol successfully mitigates prominent threats such as impersonation attacks, man-in-the-middle attacks, session key leakage, and database compromise. In addition, the protocol ensures mutual authentication between the user, the gateway, and the sensor nodes, while maintaining data confidentiality and integrity. Performance evaluation indicates that the protocol offers significantly reduced computational cost and communication delay compared to existing schemes. Its low energy consumption and minimal storage requirements make it suitable for deployment in resource-constrained medical devices and large-scale IoT healthcare networks. The results highlight the protocol’s scalability, energy efficiency, and robustness, making it a practical and secure solution for safeguarding patient data and ensuring trustworthy communication in WMSNs-based healthcare IoT systems.

This study aims to analyze the factors that influence students' learning motivation in the Lathe Engineering subject in class XI of the Department of Machining Engineering at SMK Negeri 1 Padang. Several variables studied include learning interest, ideals, friendship environment, and family environment, each of which acts as an independent variable, while learning motivation functions as a dependent variable. The method used in this study is quantitative with a correlational approach, where the research sample consisted of 51 students selected using a saturated sampling technique, namely sampling that covers the entire population in the class. The instrument used in this study was a questionnaire with a Likert scale that has been tested for validity and reliability to ensure that the measuring instrument used is able to extract accurate and consistent data. The data obtained were then analyzed using multiple linear regression techniques with the help of SPSS version 26 to determine the effect of each variable on student learning motivation. The results of the study indicate that partially, learning interest and friendship environment have a significant influence on student learning motivation. Students who have a high interest in the Lathe Engineering subject tend to have better learning motivation, and positive relationships with their friends also increase their enthusiasm for learning. In contrast, the variables of ideals and family environment did not show a significant influence on students' learning motivation in the context of this study. Although ideals and family support are often considered important factors in education, the results of this study indicate that external factors such as friendships are more dominant in influencing students' learning motivation. Simultaneously, all four variables significantly influenced students' learning motivation, with the friendship environment being the most dominant factor.

This study aims to utilize data mining techniques, specifically the K-Nearest Neighbors (KNN) algorithm, to classify leaf diseases in sugarcane (Saccharum officinarum). Early and accurate detection of leaf disease types is a crucial step in prevention and control strategies, thereby reducing potential crop losses caused by pathogen attacks. Leaf diseases in sugarcane, such as leaf scald, rust, and mosaic virus, are known to affect photosynthesis, inhibit growth, and reduce the quality and quantity of sugarcane produced. The classification process in this study was carried out through image analysis of infected sugarcane leaves, where features such as color, texture, and shape were extracted using digital image processing techniques. The KNN algorithm was chosen because of its non-parametric nature, ease of implementation, and its ability to provide accurate classification results even with limited data size. The working principle of KNN is to determine the class of a new sample based on the majority class of its k nearest neighbors in the feature space, making it very suitable for the case of leaf disease image classification. In addition to building a classification model, this study also examines disease prevention strategies based on the identification results. These strategies include the use of disease-resistant sugarcane varieties, the implementation of appropriate planting patterns, land moisture management, regular plantation sanitation, and the measured and environmentally friendly use of pesticides or fungicides. Model performance evaluation was conducted using accuracy, precision, recall, and F1-score metrics to assess model effectiveness across various data scenarios. The results of this study are expected to not only contribute to the development of decision support systems for farmers and related parties but also support the application of artificial intelligence-based technology in the agricultural sector.

Indonesia is recognized as one of the world’s richest countries in terms of biodiversity, including a wide variety of traditional medicinal plants. One of the lesser-known yet promising local species is matoa (Pometia pinnata J.R. Forst & G. Forst), whose leaves have been traditionally used by local communities to treat various ailments, including diarrhea and seizures. This study aims to investigate the pharmacological effects of matoa leaf extract, with a particular focus on its anticonvulsant activity, while also reviewing its potential chemical constituents as a basis for herbal medicine development. The research was conducted using a combination of literature review and experimental testing on mice (Mus musculus) induced with strychnine to trigger seizures. Key observed parameters included seizure onset time and survival duration (dead time) following the administration of either synthetic drugs or matoa leaf extract. The results demonstrated that the matoa leaf extract exhibited significant anticonvulsant effects, as indicated by prolonged seizure onset and increased survival time in test animals. These pharmacological effects are presumed to be related to the presence of active compounds such as flavonoids, tannins, and alkaloids, which may contribute to the stabilization of the central nervous system. Compared to conventional synthetic anticonvulsants, matoa leaf extract may offer a safer, plant-based alternative with potentially fewer side effects. The findings of this study provide valuable scientific evidence supporting the potential of Pometia pinnata leaves in the development of Indonesian herbal phytopharmaceuticals. Furthermore, they highlight the importance of further research, including preclinical and clinical trials, to validate efficacy, determine optimal dosages, and ensure safety for human use.

This study aims to analyze the differences in various extraction techniques and their relationship to the yield and biological activity of phytochemical compounds from natural materials. The research was conducted through a systematic literature review from various reliable scientific sources over the last decade. The results indicate that extraction methods such as maceration, soxhlet extraction, microwave-assisted extraction (MAE), and ultrasound-assisted extraction (UAE) have varying effectiveness. The effectiveness of these methods is highly dependent on the type of material, solvent used, and process parameters such as temperature, time, and solvent-to-material ratio. Modern extraction methods such as sonication, MAE, and UAE tend to produce higher yields and better biological activity. These modern methods have the advantage of being more time-efficient and requiring fewer solvents, thus allowing the extraction of active compounds more optimally. Additionally, technologies like microwave and ultrasonic waves help break down the cell walls of natural materials, enhancing the release of phytochemical compounds more effectively and rapidly. However, conventional methods such as maceration and soxhlet extraction remain relevant, especially for materials containing thermolabile compounds that may degrade at high temperatures. These methods are still preferred to maintain the stability of active compounds sensitive to thermal degradation. Choosing the appropriate extraction method is crucial in producing high-quality extracts that can potentially be used as raw materials for phytopharmaceuticals, supplements, or other natural products. This study provides a strong theoretical foundation for further experimental research and guidance in selecting extraction methods based on the required efficiency and effectiveness for industrial applications. Thus, this study contributes to the development of more efficient and high-quality natural products.

Pain is an unpleasant sensation that can interfere with an individual's quality of life and requires effective management. Synthetic analgesics such as ketorolac, codeine, etoricoxib, and celecoxib are commonly used to relieve pain, but long-term use can cause adverse side effects, including gastrointestinal disturbances, dependence, and cardiovascular risks. Therefore, it is important to find safer, natural alternatives. One promising alternative is the extract of the dragon’s tail leaf (Rhaphidophora pinnata), a plant traditionally used in Indonesian medicine as a pain reliever. This study aims to evaluate and compare the analgesic effects of Rhaphidophora pinnata leaf extract with several synthetic drugs using the writhing test on male mice (Mus musculus). The mice were induced with pain by injecting a 0.5% acetic acid solution. The treatments included ketorolac, codeine, etoricoxib, celecoxib, and Rhaphidophora pinnata leaf extract. The results showed that all treatments, including both synthetic drugs and Rhaphidophora pinnata leaf extract, produced significant analgesic effects compared to the negative control (Na CMC 0.5%). Ketorolac showed the highest effectiveness, followed by codeine, etoricoxib, and celecoxib. Although the Rhaphidophora pinnata leaf extract showed potential as a natural analgesic, its effectiveness varied among individual test animals. Some mice showed a better response to the leaf extract, but overall, the analgesic effect was still lower than that of synthetic drugs. These findings support the use of medicinal plants as a safer alternative to synthetic analgesic drugs. Moreover, this study provides a foundation for further research aimed at isolating active compounds from Rhaphidophora pinnata leaf extract to develop more effective and safer pain-relieving medications.