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Gangrenous wounds are wounds that occur due to diabetes complications caused by nerve damage and poor blood circulation which makes diabetic wounds unable to prevent infection. Infection is caused by the growth of microbes. High levels of sugar in the blood of DM sufferers provide food for microbes to reproduce. One of the bacteria that causes gangrene is Staphylococcus aureus. Plants that can be used as antibacterials are cherry leaves, also known as seri (Muntingia calabura L.), which contain tannins, terpenoids, saponins, flavonoids and polyphenols. This research aims to identify the antibacterial activity of cherry leaf extract against Staphylococcus aureus bacteria from DM wound wipes. This research was carried out in an experimental laboratory by applying the disc diffusion research method. The resistance is measured through the clear zone that extends around the paper disc. Kersen leaf extract was obtained through a maceration process with 96% ethanol solvent to obtain a thick extract of 0.074%. The test concentrations used were 12.5%, 25%, 50% and 75%. Positive control tetracycline 500 mg and negative control DMSO (dimethyl sulfoxide). The results of this research show that Kersen leaf extract inhibits the growth of Staphylococcus aureus bacteria in diabetic wounds. In concentrations of 12.5%, 25%, 50%, and 75%, the average diameter obtained was 2.70 mm, 4.67 mm, 6.30 mm, 7.89 mm. Conclusion: the effect of ethanol extract of cherry leaves on the growth of Staphylococcus aureus bacteria in diabetic wounds is antibacterial.

Data mining is a technique for extracting new information from data warehouses, information is seen as very important and valuable because by mastering information it is easy to achieve a goal, this makes everyone compete to obtain information, as is the case with the Dimsum business at Dimsum Madani.toko. This is located on Jalan Lampu gg. Pelita 4, Brayan Bengkel, East Medan, the location is close to many Brayan Resident's Houses. This of course affects sales levels. Increasing daily sales activity results in an accumulation of sales transaction data that continues to increase, thereby burdening data storage. Unfortunately, this data is only stored without further processing. In fact, this data collection holds valuable information.This research uses Market Basket Analysis with the Apriori Algorithm to find association patterns based on consumer shopping behavior. The goal is to identify items that are often purchased together. The research results showed that the combination of Seaweed Dimsum with Tofu Skin Spring Rolls had the highest support value (50%) and the highest confidence (75%).

Background: Petai seed extract (Parkia speciosa Hassk.) contains flavonoids and polyphenols. These compounds have good antioxidant activity to lower oxidative stress. The product of oxidative stress is called MDA (Malondialdehyde) which can be used as an indicator of oxidative stress. The study aimed to determine the effect of petai seeds on MDA serum levels in rats (Rattus novergicus) on a high-fat diet. Objective: To determine the effect of the administration of        Methods: This research was a true experimental study with post test only control group design. A total of 25 rats were divided into five groups : negative control (K-), positive control (K+), treatment 1 (P1), treatment 2 (P2), and treatment 3 (P3). The K+, P1, P2, and P3 groups were given a high-fat diet for 30 days and continued to administer extract of petai seeds doses of 100 mg/kgBW, 200 mg/kgBW, and 400 mg/kgBW consecutively for P1, P2, P3 for 10 days. The levels of MDA serum were measured by the P. P. Nair method. Data were analyzed using the nonparametric Kruskal-Wallis test and Post-Hoc Mann-Whitney test.Results: The results of this study indicate the effect of the administration of petai seeds (Parkia speciosa Hassk.) on the MDA serum levels. Conclusion: The study concludes that extract of petai seeds with 100 mg/kgBW has no effect on MDA serum levels, while in rats with a dose of 200 mg/kgBW and 400 mg/kgBW can decrease MDA serum levels.

The incidence of diabetes continues to increase worldwide. The state of hyperglycemia during pregnancy can trigger oxidative stress which can result in hypoxic conditions in the tissues characterized by an increase in HIF-1α. Basil which contains antioxidants is expected to reduce the expression of HIF-1α. This study aims to determine the effect of the administration of basil on the expression of HIF-1α in gestational diabetes mellitus model rats. To determine the effect of the administration of basil extract (Ocimum basilicum) on the expression of HIF-1α in gestational diabetes mellitus model rats. This research is experimental research conducted using the post test only control group design method. The research sample used biological material stored from rat RNA that had been induced by streptozotocin 40 mg/kgBB as an animal model of DMG in humans stored in the Biomedical Lab, FK Unand. The results of this study indicate the effect of the administration of basil extract (Ocimum basilicum) on the expression of HIF-1α in gestational diabetes mellitus model rats. Researchers used conventional PCR tools and still manually used ImageJ to look for HIF-1α expression values from electrophoresis results, so the possibility of bias still exists.

This research designs a system to classify apple leaf diseases using RGB (red, green and blue) color feature extraction. The essence of this research is to design a system to recognize and determine disease on apple leaves based on RGB color features using the Matlab 2024 application. The data in this research uses apple leaf images from kaggle.com, which are then cropped and adjusted to the image shape and precision in the leaf image. , Increasing the contrast of the cropped image and converting it to a grayscale image, Determining the threshold for binarization and converting the grayscale image to a binary image, Detection of green, yellow, and black/gray pixels based on RGB values ​​and calculating the proportion of each color, Detection of pixels scab by filtering out black/grey pixels that do not include green or yellow pixels Classification of leaves based on the proportion of detected colors. With the method that has been passed and uses apple leaf data, namely Healthy, Rust and Scab, each data contains 20 images with a total of 60 images and the level of accuracy is determined using the labeling method for each data and reaches the final result with an accuracy level of 86, 6667% which has a fairly accurate meaning  

Background: Acne vulgaris is a chronic inflammation of the pilosebaceous follicle and its causes are multifactorial. Smoking causes changes in skin microcirculation, keratinocytes, fibroblasts and blood vessels. Physical activity can cause acne vulgaris because there is an increase in sweat secretion followed by sebum hypersecretion. Objective: This study aims to determine the relationship between smoking and physical activity with the incidence of acne vulgaris. Methods: This study used a cross-sectional design conducted in December 2021 at the Faculty of Medicine, Unand and the Griya Satya Clinic. The research population was male students of the Faculty of Medicine, Unand batch 2018. The method used total sampling method, there were 61 respondents in the  age range of 19-22 years. The data obtained were primary data from a questionnaire and the diagnosis was confirmed by extraction of comedones. The analysis uses the chi-square test to determine the relationship between variables.Results: The results of statistical test  using thetest chi-square showed that, there is no significant relationship between smoking habits and the incidence of acne vulgaris (p = 0.335), there is no significant relationship between physical activity habits and the incidence of acne vulgaris (p value = 0.851), there is no relationship significant relationship between smoking habits and physical activity with the incidence of acne (p value = 0.335). Conclusion: Medical students at the Faculty of Medicine, Andalas University, most of them had light smoking habit and most of them had moderate-to-heavy physical activity. And there is no relationship between smoking and physical activity toward the incidence of acne vulgaris.  

In the execution of regional autonomy, local taxes and levies stand as crucial sources of local revenue aimed at financing various endeavors of local governance. The South Kalimantan Provincial Government has regional financial challenges in the future, in increasing the independence and optimization of its local taxes in order to increase PAD. The aim of this research was to investigate the impact of entertainment tax, restaurant tax, and hotel tax on regional original income. This study employed quantitative methods, utilizing secondary data extracted from the South Kalimantan regional government financial report (LKPD) spanning from 2019 to 2021.The sampling technique used is a saturated sample. the regression test results prove that restaurant and entertainment taxes have no effect on (PAD) while hotel taxes have a positive effect on (PAD). The limitation of this study is that the independent variables used are limited to three types of local tax variables, namely restaurant, entertainment and hotel taxes, without making demographic factors, area and income level as intervening or moderating variables. Local taxes will be able to have a positive influence if supported by adequate demographic and geographic factors. 

The utilization of natural materials in household products is increasingly in demand along with the increasing awareness of the importance of maintaining environmental sustainability.One innovative way to utilize natural materials is by utilizing pandanus leaves into natural dyes. Pandanus extract was chosen because of its active compounds that have antibacterial properties and a refreshing aroma.This activity was carried out with the women of the Forum Kesehatan Keluarga (FKK) in Jogoprono RW VI Sadeng Village, Gunungpati District, Semarang City. The purpose of this activity is to increase community awareness and skills in using environmentally friendly soaps that are not only beneficial for health but also contribute positively to the environment.The methodology used in this paper uses a qualitative method with an experimental approach.The results of the activity show that the utilization of pandanus extract in liquid soap not only provides an alternative cleaning product that is safer for the environment but also empowers the local community through active involvement in the production process. In addition, this activity is expected to serve as a model for similar initiatives in creating eco-friendly products that empower communities and support environmental conservation.

This study aims to provide a bibliometric analysis of course-based undergraduate research experience from 2010-2023. Data were extracted from the Scopus database and analyzed using VOSviewer. A total of 67 related publications were analyzed and mapped. According to bibliometric analysis, course-based undergraduate research experience, inquiry-based learning, and upper-division undergraduate become the center of the topic in the study of course-based undergraduate research experience in chemistry. It also shows that collaborative/cooperative learning, discovery learning, problem-solving/decision-making, first-year undergraduate, organic chemistry, and chemical education research. are among the novel and emerging topics in course-based undergraduate research in chemistry. This research is expected to provide a better understanding of the challenges and opportunities of studying course-based undergraduate research experience in chemistry.

Nausea and vomiting or emesis gravidarum are symptoms that commonly occur in pregnant women in the firs trimester and are physiological, caused by hormonal changes in pregnant women. The purpose of this study was to determine the effectiveness of giving red ginger water to reduce the frequency of emesis gravidarum in first trimester pregnant women. One Group Pre-Post Test Design research design. The research was conducted in Februari - July 2024 in the working area of the Jabon Public Health Center Jombang. The sample was 60 respondents selected with purposive sampling technique. The instrument used to measure emesis gravidarum is The Rhodes Index Nausea, Vomiting and Retching. Bivariate analysis using the Mann-Whitney test. The average difference in the frequency of emesis gravidarum before and after the intervention of red ginger extract was 3.01 and cardamom water was 2.91. The results of the Mann-Whitney test in which the intervention pretest and posttest intervention pairs of giving red ginger were a p value of 0.000 <0.05. Giving red ginger  intervention is effective in reducing the nausea of emesis gravidarum significantly in reducing the frequency of emesis gravidarum.

Land classification for oil palm plantations is an important topic in agricultural and plantation development. In this research, the local binary pattern (LBP) method and support vector machine (SVM) classification were used to identify oil palm plantations from aerial photography images. The main challenge in this process is accurately distinguishing oil palm fields and forests that have similar patterns and colors in satellite images. The LBP method is used to extract important texture features from images, while SVM is used to build a classification model based on these features. The test results show that using this method provides an accuracy value of 83.33% in the classification of oil palm land images. The development of oil palm plantations in Indonesia is becoming increasingly important as investment prospects strengthen. This research helps develop image classification technology to support the agricultural industry.

This study employed knowledge discovery in databases (KDD) to extract and discover knowledge from the Benue State Polytechnic (Benpoly) admission database and used a structural causal model (SCM) ontological framework to represent the admission process in the Nigerian polytechnic education system. The SCM ontology identified important causal relations in features needed to model the admission process and was validated using the conditional independence test (CIT) criteria. The SCM ontology was further employed to identify and constrain input features causing bias in the local interpretable model-agnostic explanations (LIME) framework applied to machine learning (ML) black-box predictions. The ablation process produced more stable LIME explanations devoid of fairness bias compared to LIME without ablation, with higher prediction accuracy (91% vs. 89%) and F1 scores (95% vs. 94%). The study also compared the performance of different ML models, including Gaussian Naïve Bayes, Decision Trees, and Logistic Regression, before and after ablation. The limitation is that the SCM ontology is qualitative and context-specific, so the fair-LIME framework can only be extrapolated to similar contexts. Future work could compare other explanation frameworks like Shapley on the same dataset. Overall, this study demonstrates a novel approach to enforcing fairness in ML explanations by integrating qualitative SCM ontologies with quantitative ML/LIME methods.

The objectives of this study were:  1) to determine the acceptance of color, aroma, texture, and taste of turmeric-tamarind jelly candy with the addition of psyllium husk; and 2) to identify the composition of the selected turmeric-tamarind jelly candy product. The research employed experimental methods, hedonic tests, and ranking tests. Three variants of psyllium husk were used: Product 1 with 1 g, Product 2 with 3 g, and Product 3 with 5 g of psyllium husk added.  Data obtained from sensory evaluations were descriptively analyzed using Microsoft Excel 2019. Results indicated that the turmeric-tamarind jelly candy with the addition of 1 g of psyllium husk was the most preferred and well-received product.   The composition of the selected jelly candy included 150 ml of turmeric-tamarind extract, 60 g of sugar, 60 g of glucose, 21 g of gelatin, and 1 g of psyllium husk.    

This research uses the Systematic Literature Review (SLR) method to explore the main challenges in child protection as well as effective strategies for overcoming these challenges. This research was carried out through a series of systematic stages, starting from formulating research questions, literature search, literature selection, data extraction, data analysis and synthesis, to presentation of results. The main challenges in child protection include violence against children and exploitation of children in various forms. Effective strategies include cross-sector collaborative approaches, community education, and strengthening local child protection systems. Implementation of this strategy requires adaptation to different local contexts, as illustrated in case studies in Indonesia. The SLR method was used to ensure a comprehensive and reliable analysis by minimizing research bias. Validity and reliability were strengthened through data triangulation and independent analysis by two researchers. It is hoped that the results of this research can provide a strong foundation for the development of child protection policies and programs, not only in Indonesia but also in other countries that face similar challenges. This research makes an important contribution to the understanding of effective child protection strategies, as well as offering practical recommendations for the implementation of child protection policies in various contexts.  

This research discusses the implementation and evaluation of the Convolutional Neural Network (CNN) convolutional neural network model for classification of fruit types, specifically to differentiate between Banana and Papaya. The CNN model used consists of several convolutional, pooling, and fully connected (dense) layers designed to extract features and perform binary classification. Data augmentation is applied to the training set to increase data variation and prevent overfitting. The image data used is normalized to speed up training convergence. The model was trained using the Adam optimizer and the binary crossentropy loss function for 20 epochs. Performance evaluation was carried out using the validation set. The results show that the model is able to effectively classify fruit images with a high level of accuracy. Predictions are made by uploading images, resizing them, and normalizing them before using the model for predictions. The classification threshold was set at 0.4, where a predicted probability greater than or equal to 0.4 was classified as Banana and a probability less than 0.4 was classified as Papaya. This research shows that the CNN model can be used effectively for binary image classification tasks and can be extended to classify more types of fruit with appropriate data adjustments and model architecture.

Research on the antibacterial test of dragon fruit peel extract carried out by Anggraini & Harris (2017) shows that white dragon fruit extract is able to inhibit the growth of epidermal Staphylococcus bacteria with the lowest concentration, namely 25%, producing an average diameter of the inhibition zone of 13.7 mm, while for the highest concentration, namely 100%, it produces an average diameter of the inhibition zone of 17.7 mm. To determine the more effective antibacterial effect of white dragon fruit peel extract, the research continued to the fractionation stage to separate compounds based on polarity level. The solvents used are water which is a polar solvent, ethyl acetate which is a semi-polar solvent, and n-hexane which is a nonpolar solvent (Yohanes, 2020). Based on the description above, researchers are interested in conducting research on testing the antibacterial activity of ethanol extract and n-hexane fraction of white dragon fruit peel (Hylocereus undatus) against Staphylococcus epidermidis bacteria.    

Health services are a critical aspect that requires coordination and cooperation from various parties, including patients, families, communities and medical personnel. Therefore, this research aims to analyze the rights and obligations of patients, families, communities and medical personnel in disaster health services. The method used is literature study. Google and Google Schoolar are used as the main sources of the database used from 2020 to 2024 to extract research via publish or perish software. From the research that has been conducted, disaster health services are a very complex and challenging aspect of the health system, which requires a multi-disciplinary and collaborative approach. A deep understanding of the rights and obligations of patients, families, communities and medical personnel is a strong basis for building a health care system that is fair, effective and sustainable. Cooperation between governments, international organizations, non-governmental organizations, local communities and individuals is essential to ensure that disaster response and recovery efforts can be carried out in a coordinated and effective manner. The development of supportive policies and regulations, as well as adequate funding, are also critical to strengthening disaster health services.

implemented and evaluated the edge detection method using the Sobel Operator, which calculates the gradient of image intensity through two convoluted kernels for horizontal (Gx) and vertical directions. (Gy). The magnitudo gradient is obtained from the combination of both such directional gradients to represent the edge force on each pixel. The main steps include image pre-processing, the application of the Sobel kernel, the calculation of magnitudo gradients, and the filtering of results to extract significant edges. The results show that the Sobel Operator is effective in highlighting intensity differences that indicate the boundary of the object, although it is sensitive to noise and less accurate for fine edges. Despite its limitations, this method is simple to implement and useful as an initial step in image processing applications such as segmentation, pattern identification, and object shape analysis.  

This article discusses the effect of variations in the concentration of mannitol-sucrose as a filler in the formulation of antioxidant lozenges from various plant extracts on the physical properties of the preparation. Lozenges are preparations that can contain active substances with additional ingredients and sweeteners that dissolve in the mouth. The use of mannitol and sucrose as additional ingredients in lozenges provides advantages such as sweet taste and ease of use. The aim of this study is to find the optimal ratio between mannitol and sucrose to obtain good physical properties of lozenges. The research method used is a literature review article (LRA) by accessing information sources from databases such as Google Scholar and PubMed. The results showed that variations in mannitol-sucrose concentration affected the physical properties of lozenges, such as weight uniformity, hardness, friability, and tablet disintegration time. Thus, choosing the right ratio between mannitol and sucrose is important to produce quality lozenges.    

As a tropical country, Indonesia has many types of biodiversity, including plants that are spread throughout Indonesia, approximately as many as 40,000 species with 7,500 species of which can be used as medicinal plants which are applied for medical needs and biological and chemical research. One of the topics discussed in this journal is the gotu kola leaf, known as the Latin name (centella asiatica). This plant contains tannins, flavonoids, vitamin A and vitamin C with various properties including accelerating the wound healing process, other benefits such as improving brain and nerve function. It should be noted that this efficacy is due to the presence of secondary metabolites in the gotu kola leaf and to find out, alkaloid, flavonoid, and saponin tests were carried out using dried gotu kola leaves and then divided into two bottles of 200 ml of methanol and N-hexane solution and then macerated for 3 days. . After the maceration process is complete, a thick extract of gotu kola leaves is produced and then continued with testing for alkaloids, flavonoids, and saponins which will later get results that aim to be the first step to determine secondary metabolite compounds and be useful as information on the utilization of the efficacy of gotu kola leaves as well as research in biology and chemistry.