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Background: Pneumonia is part of respiratory tract infections in children and is one of the diseases that causes the most deaths in toddlers. According to data from the Ministry of Health of the Republic of Indonesia for 2021, based on 34 provinces of pneumonia in toddlers, Bali ranks ninth with the largest coverage of pneumonia in toddlers, namely 28.6% of cases with 23 cases of deaths in toddlers. The purpose of this research is to describe the mapping and patterns the spread of pneumonia in toddlers in Denpasar City in 2022 based on Geographic Information Systems (GIS Methods The design in this study uses descriptive quantitative with the research design used is cross sectional. Sampling of 260 samples was carried out using a purposive sampling technique. Data analysis using spatial classification analysis. Results: From the results of the study it was found that the spread of pneumonia in toddlers in Denpasar City in 2022 was classified into three categories namely high, medium and low. The pattern of distribution of pneumonia cases in Denpasar City in 2022 is the highest in West Denpasar District with 94 cases. Conclusion: The conclusion of this research is that the West Denpasar Subdistrict region has the highest cases and the lowest cases are found in the East Denpasar Subdistrict region. Age, gender and population density are risk factors that influence the high incidence of pneumonia in children under five in Denpasar City.

This study analyzes how the translation techniques is applied in the bilingual textbook Science Biology for Junior High School.The study was conducted qualitatively. Data was collected by selecting complex sentences from chapter six and seven.Then,I analyzed and categorized the translation techniques used according to the classification of Molina and Albir. The data is then calculated to determine the main translation techniques.The findings indicated that in this textbook,there are many translation techniques that contained in a complex sentences. As a result of the study 40 complex sentences were found in the sixth and seventh chapter.This textbook has nine translation techniques there were: literal translation, borrowing, adaptation, reduction, particularization, amplification, generalization, transposition and description. From 40 complex sentences it can be concluded that there are 15 complex sentences of literal translation,4 complex sentences of borrowing,1 complex sentence of adaptation,2 complex sentences of reduction,3 complex sentences of particularization, 7 complex sentences of amplification,2 complex sentences of generalization,1 complex sentence of transposition,5 complex sentences of description. Literal translation is the most numerous technique in the text book. So , over all the concept of a sentence can be easily understood and the knowledge can be developed from daily experiences.

  This research aims to conduct a literary psychological study of the novel entitled Hai, Luka by Mezty Mez. This novel was written by a famous author who describes the complexity of the emotions and psychological conditions of the main character. This research explores the psychological elements contained in the novel and analyzes their influence on the character development of the main character. The method used in this research is qualitative method. The results of the research show that the classification of emotions in Dante's character is in the form of guilt, buried guilt, self-punishment, shame, sadness, hatred and love. In this case, the novel Hai, Luka provides a deeper understanding of the complexity of the characters and psychological conditions depicted through literary works. This research contributes to the field of literary psychology studies by revealing how authors use psychological elements to shape characters and stimulate emotional responses in readers    

The role of cooperatives in supporting the economy is reflected in their contribution to GDP, which experiences a positive trend every year. The potential of each region is different, resulting in a classification of the types of cooperative businesses that exist in order to realize regional growth in accordance with the resources it has. This research uses descriptive research with a quantitative approach using the Location Quotient (LQ) method. The data used is secondary data obtained from the Ministry of Cooperatives and BPS West Java. The results of the Location Qoutient (LQ) method analysis show that two types of business are categorized as potential bases, namely the consumer cooperative and producer cooperative sectors, because they have an LQ value> 1. Meanwhile, the cooperative, service, marketing cooperative and savings and loan cooperative sectors are in a non-base position, because they have an LQ value <1.

The global economic recession is a global economic downturn that affects the domestic economies of countries in the world. The stronger the economic dependence of one country on the global economy, the faster a recession will occur in that country. In 2020 the country of Indonesia and even the world are exposed to the COVID-19 virus which has an impact on the country's economic growth, even the world economy. This is the trigger for an economic recession. This has led to many different public perspectives on the occurrence of a global economic recession whose opinions or reactions are expressed on social media Youtube. The data was obtained by crawling techniques from social media Youtube with a total of 500 comments used. The data is then labeled (class) with a lexicon-based method with an Indonesian language dictionary. From the labeling results, it was obtained 185 positive labeled data (37%) and 315 negative opinions (63%). The data preprocessing stage is carried out in preparation for the data to be processed for sentiment analysis. Of the many opinions obtained, an analysis of public sentiment regarding the 2023 global economic recession will be carried out using the Naïve Bayes classification algorithm. This study also applied the TF-IDF word weighting method with the n-gram feature used, namely bigram (n=1). The system will be evaluated using a confusion matrix. The implementation results show a prediction model with a total of 500 opinion data with a comparison of training data and test data of 9:1, producing an accuracy value of 84.00%, a precision value of 75.00%, a recall of 30.00%, and an f1-score of 42.86%. The performance of the system model built in this study can be said to be good.

One form of text that can express emotions is lyrics. Lyrics are a type of literary work expressed in the form of words, the contents of which can express the songwriter's personal feelings, thoughts, and emotions. Therefore, the lyrics can be used as an object of research on the classification of emotions. The classification of song lyrics really requires bi-LSTM to be the input value when classifying data in the form of song lyrics in order to get high accuracy results. This research was carried out systematically and the results were measurable. Descriptive qualitative research was used in this research. The results of identification based on case studies and statistics show that the reviews of popular topics are identical. The classification of song lyrics really requires bi-LSTM to be the input value when classifying data in the form of song lyrics in order to get high accuracy results.

This research was motivated by the low level of encouragement and results of practicing the Quran Hadith for category VII students at SMPIT Kawan Quran. The aim of this research is to identify the impact of the card sort procedure in the main review of strengthening my faith by worshiping the encouragement and results of practicing the Qur'an Hadith at SMPIT Kawan Qur'an, Sawahlunto City. This type of research is imaginary research, with the concept of randomized control group only design research. Based on research results, it was found that in general the encouragement of students for each marker was in the range of 80% - 84% with a large classification and in general the percentage of encouragement for students to practice Al-Quran Hadith after applying the Card sort procedure was 82% with a large classification also. On the other hand, students' results for practicing the Qur'an, the Words of the Prophet in the research category were 82.08 with a completion percentage of 72%. On the other hand, in general what was obtained in the supervision category was 73.72 with a completion percentage of 56%. From the calculations we get tcount= 2.67 and ttable= 2.02. Because tcount ttable until H1 is obtained. So, it can be said that the results of students' training with the application of card sort procedures are better than conventional training in the subject of the Qur'an, Words of the Prophet, category VII SMPIT Kawan Quran, Sawahlunto City.

The purpose of writing this article is to determine the application of the nearest neighbor classification algorithm in diabetes detection. This nearest neighbor classification algorithm is a classification method often used to classify objects based on available data. This method works by searching for the closest objects in the dataset and classifying the new objects based on the closest object category. The application of the KNN algorithm can be carried out in various fields, such as analyzing the feasibility of credit granting, classifying online news materials or diagnosing diabetes. In this article, the researcher uses a literature review research method assisted by a descriptive analysis approach, to analyze the data and by describing the data that has been previously collected where the author describes data that has been obtained from various literary sources such as journals, data and others. The data obtained will be analyzed and interpreted in accordance with the objective of this research, which is to determine the application of nearest neighbor classification to detect diabetes.

The aim of this research is to describe and analyze the form of directive speech acts and the background of the speech in the short story collection Rokat Tase by Muna Masyari. This research is a type of qualitative research. The approach used is a sociopragmatic approach. The data collection techniques used are listening techniques and note-taking techniques. The instrument used is a data card for the classification of forms of directive speech acts. The analysis technique used is descriptive analysis technique. Presentation of the results of data analysis is carried out informally. The forms of directive speech acts found were (9) directive speech acts of giving advice, (31) directive speech acts of commands, (8) directive speech acts of requests, (3) directive speech acts of ordering, and () directive speech acts of criticism. Meanwhile, the background causes of speech are influenced by physical environmental factors, social influences, culture, social status, social relationships and work. This research can have implications for literature learning at junior high school level.

Japanese papaya leaves (Cnidoscolus aconitifolius) contain active compounds such as flavonoids, tannins, saponins, alkaloids and terpenoids which have the potential to have antibacterial activity. The aim of this research is to determine the antibacterial activity of Japanese papaya leaves against Staphylococcus aureus bacteria. Extraction of Japanese papaya leaves has been carried out using the maceration method and 96% ethanol solvent. The antibacterial activity test used the agar diffusion method using a cylindrical plate. Sterile distilled water was used as a negative control while as a positive control the antibiotic ciprofloxacin was used. The concentrations of Japanese papaya leaf ethanol extract used in testing were 10%, 20%, and 30%. The research results showed that Japanese papaya leaf ethanol extract with a concentration of 30% had the widest inhibition zone diameter, namely 17.296 mm. Meanwhile, at a concentration of 20%, the average inhibitory zone diameter was 15,222 mm, and at a concentration of 10%, the average inhibitory zone diameter was 13,018 mm. These three concentrations were included in the strong category based on Greenwood classification.  

Residential is a place to live or everything related to a place to live and in a narrow sense can be interpreted as a residential area or residential building. In connection with the quality of residential facilities, employee satisfaction is an important aspect in improving the quality of the provided residential facilities. If the satisfaction of the residential facilities provided to employees is not met, the employees will feel uncomfortable and will sue the plantation of PTPN IV Marjandi Unit. Analyze the level of employee satisfaction with the quality of the residential provided by the plantation to its employees is The purpose of this study. One of the efforts to find out the satisfaction of employees of residential facilities is to use the C4.5 algorithm classification, where Dataset is obtained through the Questionnaire technique that will be given to employees at PTPN IV Marjandi Unit. As for the satisfaction of employees of residential facilities in terms of aspects (1) water facilities, (2) electricity facilities, (3) kitchen conditions, (4) bedroom conditions, (5) toilet conditions in dwellings inhabited by PTPN IV Unit plantation employees Marjandi. Data processing is assisted using Microsoft Excel software and to validate study data using a rapidminer tool. It is hoped that this research can provide solutions or become a reference for plantations to improve the quality of residential facilities provided to PTPN IV Marjandi Unit employees..

The conflict between Israel and Palestine has been a prominent topic of international discourse for several decades. This dispute spans a century, commencing in 1917 and persisting to the present day. This research delves into sentiment analysis of the Indonesian community concerning the Israel-Palestine conflict through the Twitter social media platform, with a specific focus on boycotting Israeli products. Utilizing Orange and Naive Bayes classification, the study analyzes over 300 datasets of tweets acquired through the scraping process. The objective is to comprehend the nuances, trends, and variations in sentiment among Twitter users regarding the issue of boycotting Israeli products. The results reveal that the majority of the population tends to support the boycott, with a Naive Bayes classification accuracy of 95%, Precission of 96%, Recall of 95%, and F1 Score of 95%. The data preprocessing process, encompassing transformation, tokenization, and filtering, effectively eliminates noise and prepares the data for a more in-depth sentiment analysis.

Batik culture is very strong in Indonesia, this is the reason that batik can be found throughout the archipelago, with unique characteristics that distinguish it in each region. However, people are often confused and find it difficult to recognize one type of batik from another. One of the famous types of batik motif is Batik Parang. This research aims to establish a Convolutional Neural Network (CNN) model to classify Batik Parang and help people distinguish it from other batik motifs. Deep learning, particularly CNN, was chosen because it has a high accuracy rate in image classification. A quantitative Experimental design is used, using a dataset of 100 batik images evenly divided into two classes, namely Batik Parang and not Batik Parang. The dataset is divided into two categories, namely training data and testing data, with a data ratio of 80:20. Thus, by using Convolutional Neural Network (CNN), the classification between Batik Parang and not Batik Parang produces an accuracy of 95%, with the use of epoch = 118 and batch_size = 100.

This research allows an automated system for detecting classified means of transportation in Medan City traffic using the YOLOv8 algorithm. The YOLOv8 algorithm is used to detect transportation objects with accuracy that is many times better than other object detection algorithms and with good accuracy after training with various data sets. The use of this algorithm provides an effective solution for handling congestion in the form of increasing the number of vehicles and less orderly traffic users in the city of Medan. The placement of each transportation object in the image to be tested by the system has an influence on the shape accuracy of the object detection results by the algorithm.

The Nutrition Care Center (NCC) is a teaching factory (TEFA) at the Jember State Polytechnic (Polije) which provides assessment and diagnostic services for nutritional problems, comprehensive nutritional assessments, diagnostic services, nutritional counseling, and customized diet plans for clients. Health services, including nutrition, require accurate medical records that include patient identification, examination, treatment, interventions, and other relevant information. However, NCC faces challenges, namely that the medical recording system is still manual paper-based. Medical record numbers do not comply with numbering regulations, age is still used instead of date of birth, the nutritional assessment section is not yet standardized and disease code classification does not yet exist. This manual system is susceptible to damage, loss, and requires dedicated storage time and space. Since it was inaugurated in November 2021, the number of NCC visits has continued to increase both from internal clients and external clients of Polije with initiations with several educational institutions, offices and elderly groups. The use of EMR which is made easier with QR Codes and the application of Whatsapp Bot is the main alternative to build or improve the management of assessment and diagnostic services for nutritional problems according to client needs. Socialization of assistance in implementing Electronic Medical Records (EMR) with QR Code and WhatsApp Bot at NCC aims to make things easier for experts. nutrition to access the client's examination history, allergy history and previous therapy in one view and make it easier for clients to access medical record numbers without a card. This initiative is in line with the Department of Health Research Masterplan 2022 and the development of TEFA services. NCC recognized the need for a more efficient system and proposed implementing EMR with QR Codes and WhatsApp Bots to optimize patient care. This socialization was carried out at the Jember State Polytechnic NCC with the presence of participants from nutritionists, students, the community and administrators from NCC. This socialization obtained results in the form of increasing public understanding of nutritional care, especially in relation to the existence of NCC as a teaching factory at the Jember State Polytechnic, the use of EMR via QR codes and WhatsApp Bot as a solution implemented by NCC in optimizing patient care and increasing the empowerment of partners in using it. and implementation of EMR with QR codes and WhatsApp Bot in patient nutrition care at NCC.

The inner conflict of the main character in the novel entitled Sebening Syahadat by Diva Sinar Rembulan is interesting to research through the study of literary psychology. The inner conflict experienced by the main character in the novel begins when the main character finds the woman of his dreams and searches for an identity that he has not yet believed in. The aim of this research is to describe the inner conflict experienced by the main character of the novel Sebening Syahadat by Diva Sinar Rembulan. This type of research is a literature study. The approach used is a literary psychology approach. The method used is a qualitative method. The data collection technique used is a documentation technique in three ways, namely, literature study, reading technique, and note-taking technique. The instrument used is a data card for the classification of intrinsic elements and forms of inner conflict. The analysis technique used is content analysis technique. The presentation of the results of data analysis is carried out descriptively. The results of this research found intrinsic elements in the form of characters and characterization, plot and setting. The second thing was found to be 47 data on the form of inner conflict in the form of (6) anxiety, (1) obsession, (3) frustration, (12) guilt, (7) hurt, (1) fear, (5) inability, (12) angry. This research can be used as an alternative teaching material at the high school/vocational school level.

This study is to find out about Parotid Gland Tumors, Salivary Gland Physiology, Definition of Parotid Tumors, Epidemiology, Etiology, Classification, Benign Parotid Tumors, Malignant Parotid Tumors, Clinical Manifestations, Diagnosis, Supporting Examinations, Therapy, Complications and Prognosis. Parotid tumors are tumors that attack the parotid salivary glands. The etiology of salivary gland tumors remains unknown but a multifactorial role is thought to be involved. The most common benign salivary gland tumor in children is parotid gland hemangioma. In adults, benign salivary gland tumors that often occur include pleiomorphic adenomas. Parotid malignant tumors in children are rare and the most common in children is mucoepidermoid carcinoma. The diagnosis of a parotid gland tumor will depend on the history, clinical examination, imaging, and fine needle aspiration biopsy (FNAB). Treatment of parotid tumors is based on appropriate staging and preoperative diagnosis. Facial nerve injuries and Frey's Syndrome are complications that often arise. Most salivary gland tumors are non-malignant and grow slowly. Surgical removal of the tumor usually cures the patient.

As many as 7.3 million people worldwide die from heart disease. This indicates that heart disease is one of the diseases that cause the most deaths. As a preventive effort in handling heart disease, it is necessary to predict heart disease in patients. The classification process to predict heart disease is done using a decision tree. This decision tree is interesting because it is more flexible in providing the advantage of visualizing the advice so that the prediction can be observed. This study uses Heart Disease Prediction Dataset data with a total of 303 data. Then predictions are made using Decision tree so that the accuracy results are 83.60%, precision 89.28%, recall 78.12% and F1 score of 83.33%.

Scholarships are a form of assistance in the form of educational expenses provided by the government or foundations to students or students who are categorized as from underprivileged families. However, in datermining scholarship recipients, there are still many scholarship recipients who come from wealthy families, while those from less fortunate families do not receive this assistance. This may be due to calculations and data processing that still use manual methods, causing scholarship recipients to not be on target. The purpose of this research is to simplify and minimize calculation errors in determining scholarship recipients for the Smart Indonesia Program (PIP) at SMK Karya Medika. Therefore, for calculating and processing PIP scholarship recipients data, data mining techniques can use the calssification method using the K-NN algprithm. K-Nearest Neighbor is a data classification method that will be used for data objects based on learning data that is closer to the object. In this study using the Confusion Matrix test so as to obtain an accuracy value of 80.00%.     

The use of the Decision Tree method in smartphone price classification is the focus of this study. By using the 10 most relevant features and data normalization to achieve scale consistency, the Decision Tree algorithm delivers an average accuracy of 81%. Although some false positives and false negatives occur, the model is able to classify smartphone prices well, especially in identifying low and high prices. These results provide important insights into the features that affect smartphone prices. While there is still room for improvement, this model provides a solid foundation for the smartphone industry to determine prices based on certain specifications. The importance of relevant feature selection and data normalization was revealed in this study. Despite the accuracy reaching 81%, improvements in the classification of medium and high price classes are still possible to reduce prediction errors. This method provides an important basis for the smartphone industry to set prices based on specifications, and data mining techniques such as Decision Tree can be improved to improve the accuracy of future price predictions.