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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  

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.

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.

Chronic diseases in humans are very difficult to detect visually, for example glaucoma, hypertension, diabetes, and others. So it takes a lot of time for further medical examination by visiting a health center or hospital. Therefore, this research aims to find a solution combining medical and computer science to classify quickly and precisely. Classifying eye images requires good features and characteristics so that disease images can be classified. This research uses the Deep Learning method, namely Convolutional Neural Network with MobileNet-V3 architecture which can extract features from large resolution images very well. This research resulted in accurate classification of images of chronic diseases Normal, Diabetes, Glucoma, Cataract, Age related macular degeneration, Hypertension, Pathalogical Myopia. uses the MobileNet-V3 architecture, with transfer learning reaching 81%, and loss only 0.4913.

The study aimed to investigate the alkaloid content in cinnamon (Cinnamomum burmannii) powder using the Soxhlet extraction method. Alkaloids are organic chemical compounds widely found in nature as secondary metabolites in both plants and animals. They possess a cyclic structure containing one or more basic nitrogen atoms, conferring unique basic properties. The research was conducted to provide a deeper understanding of the potential utilization of plant-derived alkaloids, particularly from cinnamon, in drug development. The study sought to determine the color of the precipitate formed in the extraction solution after the addition of Mayer's reagent and to investigate the effect of the number of Soxhlet extraction cycles on the color of the ethanol used in the research with cinnamon samples. The findings from this study contribute to the exploration of the alkaloid content in cinnamon and its potential applications in pharmaceutical development.

This research explores the classification of brass instrument sounds using Convolutional Neural Network (CNN) combined with Mel-Frequency Cepstrum Coefficient (MFCC) feature extraction. This research aims to improve the accuracy of brass instrument sound recognition by utilizing CNN's ability to process audio data. Through experiments conducted with different audio durations and variations in CNN model architecture, this study evaluates the impact of dataset separation and model design on classification performance. The results show that dataset duration and CNN model architecture significantly affect classification accuracy, with the highest accuracy achieved in the scenario using 30 seconds of audio duration with an accuracy value of 84%. In addition, experiments varying the number of convolution layers in the CNN model show that the selection of the model architecture plays an important role in classification performance. Overall, this research contributes to advancing the field of audio classification by providing insight into the optimal dataset duration and model architecture for wind instrument speech recognition using CNNs.

Introduction: Banana peel is an organic waste which is known to have various benefits, especially as an antidepressant for mental health. It inspired to conduct a research on various type of banana peels in Indonesia, particularly on Kepok banana which has been widely studied. This research aimed to prove the effect of Kepok banana peel extract (Musa paradisiaca L.) as an antidepressant in mice (Mus musculus) with acute restraint stress.Method: This research used a laboratory experimental design. The male mice were acclimatized for 3 days. Twenty-four mice were then divided evenly into 4 groups. The first group was given banana peel extract (Musa paradisiaca L.) at a dose of 200 mg / kgBW, the second group was given a dose of 400 mg / kgBB, the third group was given a dose of 800 mg / kgBW and the fourth group was given water as control. Each group was given a dose orally for 14 days and ARS depressed induction for 7 hours. Subsequently, mice were treated to assess depression behavior using the tail suspension test (TST) and forced-swim test (FST) to determine the duration of immobility.Result: The result showed that there was a significant difference (p<0.01) between the control group and the experimental group, at TST there was a significant difference (p<0.01) between two doses of 400 mg / kgBW and 800 mg / kgBW, as well as on the forced-swim test (FST). In addition, there was a significant difference (p<0.01) between two doses of 200 mg / kgBW and 800 mg / kgBW, and between two doses of 400 mg / kgBW and 800 mg / kgBW. Conclusion: These result confirmed that Kepok banana peel extract (Musa paradisiaca L.) was an effective antidepressant in reducing immobility duration with acute restraint stress.

Creativity is a human potential that does not come from outside the individual. Data collection techniques carried out in the form of documentation and extracting information about innovative methods and utilization of used goods. The results of this service activity are based on observations that have been made in Aman Damai Village Hamlet 3 Sirapit District, namely some of the results show positive because the manufacturing process does not take much time, in making bookshelves from cardboard children show enthusiasm for the directions delivered by the service team, positive reactions shown by children to interest in making bookshelves where almost all participants are able to make and decorate bookshelves well, children follow the mechanism of making products and are quite good at working with the team and children's creativity develops quite well. With used goods can increase income and can help the family economy.

Kemiri Village is one of the villages located in Sidoarjo Regency. Most of the people in Kemiri Village work in the agricultural sector and small MSMEs. One of the plants that is often found is the betel plant which grows in people's yards and has not been utilized optimally. The community service program carried out by National Defense Thematic Community Service (KKN) Group 5 Batch 2 UPN Veteran East Java students is a socialization and training program for making dishwashing soap made from betel leaves which is economically valuable. The method used in this service It goes through several stages, namely the preparation stage, implementation stage and evaluation stage. This activity was attended by PKK women from Kemiri Village who were enthusiastic and enthusiastic. The result of this activity is to provide knowledge and skills to residents to be able to utilize existing natural resources optimally so that the potential of betel leaves can be utilized more effectively. This does not rule out the possibility of producing products that have attractive sales potential, thereby creating new economic opportunities and increasing the welfare of the community in Kemiri Village, Sidoarjo.

Illegal mining itself is a mining activity or extracting agricultural products carried out by the community or a business entity or we can call it a company where this activity does not have a business permit and also does not use the principles regarding how to mine in accordance with existing regulations or not. use mining methods properly and correctly. The basic mining laws that apply in Indonesia are stated in the Mining UlUl Number 3 of 2020 concerning amendments to UlUl Number 4 of 2009 concerning Mineral and Coal Mining, mining excavation itself consists of several types. Starting from strategic minerals or group a minerals, vital minerals or group c, and finally, group c minerals. In Indonesia itself we can certainly find cases of illegal mining in various regions, that is why enforcement efforts should be carried out as best as possible in order to reduce the growth rate of existing illegal mining which of course is to guarantee or increase state income through existing mining businesses. certainly legal in the eyes of the law.