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Digital Population Identity (IKD) is a digital-based location data innovation through a mobile application with a photo or QR Code. The government's objective is to reduce the physical prints of KTP as well as the use of blank KTP-el in the hope of administrative efficiency. ICT is integrated with health services, education, banking, and taxation, facilitating public access in the era of technological development. However, in remote areas, limited internet access and minimal socialization raise concerns about the security of digital identity data being considered. Social media, especially YouTube, is a channel platform used by the public to convey opinions, opinions and comments about ICTs. So that's why sentimental analysis is needed using the Naive Bayes algorithm to help understand public opinion. The tests were conducted using Orange on 1,561 data showing accuracy, precision, recall, and F1 above 90%. The results of this analysis can serve as a guide for staff in interacting with the community for the implementation of Digital KTP through IKD, as well as improving services regarding the applications provided.

Early childhood plays an important role in forming the basis of development, which involves stimulation of various aspects such as moral religious values, social emotional, language, cognitive, and physical motor skills. The concept of early childhood learning is focused on play, where every activity is designed to be play, so that learning becomes more effective. Parents also need to understand today's children's education to interact with children positively. This research focuses on sentiment analysis of children's education-based app reviews on the Google Play Store, using Random Forest and Logistic Regression methods. The review data is taken from three apps with the theme of child development, namely "About Kids", "PrimaKu", and "Teman Bumil", with a range of review years between 2018 and 2023. The test results show that Logistic Regression has higher accuracy compared to Random Forest, especially in the "About Kids" and "PrimaKu" applications with accuracy above 90%. The conclusion of this research highlights the importance of sentiment analysis in improving understanding of user responses to children's education applications, with suggestions for future research to increase the number of datasets and variations in testing schemes by tuning hyperparameters to improve prediction accuracy and more optimal results.

The aim of this study is to find out how to implement the use of Artificial Intelligence (AI) in the formation of laws and regulations in Indonesia. This study uses a normative juridical method with a statutory and regulatory approach as well as secondary legal materials, namely books on Legislation, other books related to this case and scientific journals from previous research. The study results show that Al can still be utilized in the process of forming regional regulations without eliminating or even replacing the role and function of the regional regulation forming organs. The use of AI in the process of forming regional regulations is only limited to tools that can be used during the harmonization process in the stages of drafting regional regulations. The use of AI is said to have better accuracy and speed in predicting potential disharmony between regional regulations and various other laws and regulations.

The use of standard language is used in writing news. This research aims to identify and analyze writing errors made by journalists in writing news on internet media, especially on CNBC Indonesia. The research method used is descriptive qualitative, focusing on Indonesian writing errors from the aspects of spelling and diction. The research results show that there are several errors that often occur in news writing on CNBC Indonesia, such as inappropriate use of punctuation, letter writing errors, and word writing errors. These errors can confuse readers and create ambiguity in understanding. Recommendations that can be given are to increase accuracy in the use of punctuation marks, letters and words. Journalists need to pay attention to correct writing rules and double-check before publishing news. Apart from that, the editorial team also needs to provide training and guidance to journalists to improve the quality of news writing. It is hoped that the results of this research can contribute to improving the quality of CNBC Indonesia's online news writing and reducing ambiguity in reader understanding. This is important to maintain media professionalism and provide clear and accurate information to readers. In this way, it is hoped that CNBC Indonesia's online news can become a reliable source of information that is easy for readers to understand.

This community service was conducted on Jalan Jembatan Merah I and Jalan Wisata Babarsari. The purpose of this community service is to improve the quality of financial record-keeping, ensuring accuracy and correctness, to provide an accurate overview of the financial condition of UMKM Siomay Indul and Gudeg Jogya Mak Karti. This community service is focused on enhancing the quality of the financial reports of these UMKMs through understanding and implementing proper accounting practices in financial record-keeping. With the provision of training and mentoring, it is expected that the stakeholders of traditional culinary UMKMs can optimize their business potential. The results of the community service indicate that improvements in transaction recording systems and a better understanding of accounting standards can significantly enhance the quality of financial reports, providing the clarity needed for better decision-making in business management.

This research explores the use of Text Mining Methods as an innovative approach to extract important information from research report text. With a strong conceptual foundation from the literature review, this research details the key concepts of Text Mining, such as tokenization techniques, sentiment analysis, and entity extraction. The steps of applying Text Mining Methods to research reports are explained in depth, with a focus on using such techniques to improve the efficiency and accuracy of information extraction. Through the evaluation of the method's performance, the research demonstrates a significant improvement in analysis speed and information extraction accuracy compared to conventional methods. The research conclusions provide a holistic picture of the potential of Text Mining Methods in improving the effectiveness of the research report text analysis process. The implications of this research stimulate thoughts on the applicability of this technology in various disciplines that rely on research reports as a primary source of information. Thus, this research makes a positive contribution to the understanding and development of text analysis techniques to support more efficient decision making.

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.

Accounting pays close attention to aspects of foreign currency transactions and adjustments to the functional currency that impact financial statements. PSAK 10 is the main guideline in regulating changes in foreign exchange rates and affecting businesses. A good understanding of PSAK 10, functional currency, and foreign currency transactions is crucial for business entities, especially those operating in a foreign currency economic environment. The case study used in this research is descriptive qualitative with literature review method. Research that characterizes research subjects based on emerging facts is known as descriptive qualitative research. The results of the research on the case study of PT Dianta Mitrafairindo Internasional highlighted the significant role of foreign exchange transactions in the company's operations, with management seriously implementing proper accounting processes, dealing with foreign exchange differences, and recording them thoroughly. Despite a loss in 2018, the company managed to record a profit in 2019, demonstrating its seriousness and commitment in managing foreign exchange risks. Overall, PT Dianta Mitrafairindo Internasional demonstrated accuracy, vigilance, and a strong commitment to foreign exchange-related accounting aspects in the context of its global business.    

An audit is a systematic, independent examination of financial statements, accounting records, and supporting documents prepared by management, the purpose of which is to form an opinion on the accuracy of financial statements. Financial statements must have relevant characteristics (reliability) and reliability (reliability). Without the services of auditors, management cannot convince outsiders that the financial statements presented by management contain reliable and reliable information. Independence is the auditor's attitude to impartiality. The experience of the examiner contributes to high-quality inspection. The purpose of this study is to analyze the influence of auditor behavior, time pressure, audit experience, and independence on audit quality.   The research was conducted at a Public Accounting Firm (KAP) in Medan City. The number of research samples of 80 people was selected by the nonprobability sampling method. Data collection was carried out by questionnaire through Google form and literature studies that supported this study. The method used in this study is to use the Structural Equation Model (SEM) equation using the Partial Least Square (PLS) tool version 3.0. PLS consists of external relationships (outer model) and internal relationships (inner model), cross-loading> 0.7, Composite Reliability, Convergent Validity, Exploratory Factor Analysis (EFA), and Confirmatory Factor Analysis (CFA). Based on the results of the analysis, it was found that the first, second, fourth, and seventh hypotheses were rejected where each variable such as auditor behavior, and time pressure,  did not affect audit quality and independence could not moderate the influence between auditor behavior on audit quality,  independence could not moderate audit quality. The third, fifth, and sixth hypotheses are accepted where each variable such as audit experience, independence moderates the effect of time pressure on audit quality, and independence moderates the effect of audit experience on audit quality.

Abstract.Network anomaly detection is a situation that occurs in network traffic that causes conditions to become abnormal. This research aims to analyze the performance of various machine learning algorithms in network anomaly detection and compare the performance of single classifier algorithms with ensemble learning. This ensemble learning technique has advantages such as increased accuracy and performance, can reduce the risk of overfitting and underfitting by using different subsets and features of data, and can turn weak learning into strong learning. However, on the other hand, this ensemble learning technique also has disadvantages in its use, namely that this ensemble method may not work well with high variance models, as the ensemble method may not be optimized for anomaly detection and that this method can be computationally expensive and time consuming due to the need to train and store multiple models. Some of the techniques used are deep learning, eager learning, lazy learning, bagging, feature selection, boosting, and stacking. In addition to this, this machine learning algorithm has weaknesses, including if any of the data used is incomplete, it will result in inaccurate completion data, making the programming process quite time-consuming. This research can help develop a more effective and efficient network anomaly detection system. The results of this research show that using ensemble learning and feature selection techniques can improve anomaly detection performance by reducing the processing time of redundant data and classification, as well as increasing precision values.    

The purpose of this research is to determine the influence of learning motivation and style in learning on learning outcomes. The type of research that will be carried out is using quantitative research methods with descriptive analysis. Data collection was carried out through a questionnaire which was measured using a Likert scale from one to five for 100 respondents with the criteria being students aged 18-22 years. The data analysis technique that will be used in this research is the Outer Model with calculations of Convergent Reliability, Discriminant Validity, Composite Reliability, Cronbach's Alpha and Inner Model with T statistics, R-Square and VIF calculations using SmartPLS 4 tools. The results of the research show that learning motivation influences learning achievement because of the accuracy factor in collecting assignments, this has high motivation. Learning style has no effect on learning achievement because it is caused by the very minimal study time that students spend. Apart from that, learning motivation and learning style together influence student learning achievement.    

Music genres are becoming increasingly diverse, and many people listen to music because it has benefits such as refreshing, motivating or therapeutic. However, with the increasing number of genres, some listeners have a tendency towards the type of genre they like. In Indonesia itself, there are several popular music genres such as pop, folk, rock, indie and dangdut. Classification of music genres is an interesting topic when looking at this behaviour. Several approaches to classify popular music genres include audio and tabular data approaches. In this research, classifying music genres using an image approach by implementing SuperTML to change the form of tabular data into image form, which is then trained using a pre-trained CNN Densenet, succeeded in achieving an accuracy of 67%.

Website promotion is a process of increasing visibility, traffic, and online presence which is a way to find and attract potential visitors by listing the website on popular internet directions using Search Engine Optimization and Search Engine Submission. With a more in-depth analysis of the quality of service on the website through the End User Computing Satisfaction (EUCS) method, Banyan Tree Bintan can take more targeted corrective actions to improve interactions with guests, increase guest satisfaction levels, and optimize the communication and interaction goals to be achieved through the website. This research is a descriptive research with Content Analysis approach. This study used a sampling total technique. Data collection was carried out in July 2023. The purpose of this research is to analyze the Banyan Tree Bintan promotional website using the End User Computing Satisfaction (EUCS) method from the aspects of content, accuracy, format, ease of use, and timeliness. The results of this study indicate that the Banyan Tree Bintan website is quite good and does not experience any problems. However, in terms of timeliness, it needs improvement regarding response time and also quick responses.

The effectiveness of the food granary program implemented by the Food Security Office of the city of Pekanbaru in implementing the Regulation of the Minister of Agriculture of the Republic of Indonesia Number: 17/Permetan/Hk.140/4/2015 is seen from indicators of program target accuracy, program socialization, achievement of program objectives and program monitoring. The purpose of this study is to analyze how the effectiveness of the food granary program in an effort to realize food security in the city of Pekanbaru using Budiani's theory, as well as analyze what are the inhibiting factors of the effectiveness of the food granary program in an effort to realize food security in the city of Pekanbaru. The method used in this study is qualitative research with a descriptive analysis approach that describes the effectiveness of the food granary program in an effort to realize food security in the city of Pekanbaru. In addition, to analyze the inhibiting factors of the effectiveness of the food granary program in efforts to realize food security in the city of Pekanbaru. The results of this study show that in the implementation of the food granary program, the food granary program plan that has been determined is not effective to be implemented. Inhibiting factors for the ineffectiveness of the program are the conversion of food barns that are used as residences by farmers making the crops produced by farmer groups directly sold to agents, maintenance of livestock that is not running well due to environmental factors, the existence of a land distribution system to farmer groups and the Agency.    

Mastery of the Arabic language plays a crucial role in understanding and interpreting the nushush of fiqh munakahat, which is an integral part of Islamic family law. In the context of contemporary Islamic family law, a deep understanding of the Arabic language can affect the accuracy of interpretation and application of the law as a whole. Nushush fiqh munakahat often contain technical terms, complex grammatical structures and contextual meanings that can only be properly understood through a good command of Arabic. This study aims to explore the relevance of mastering Arabic in the interpretation of the nushush of fiqh munakahat by examining the various challenges, interpretative errors, and legal implications that can arise from weak linguistic skills. This study is conducted through a qualitative approach with a literature study of primary and secondary sources in fiqh munakahat. The results of this study are expected to contribute to strengthening the method of interpretation of Islamic law, especially in the field of munakahat, as well as encouraging the improvement of Arabic language competence for practitioners and academics of Islamic law.

Such quick change in information technology and computers have required changes in the educational paradigm, particularly in teaching and learning methods. Computer applications are software services that use computers as the medium. Programming language is the language used in computing to create programs. An algorithm, a systematic sequence of steps, is used to solve a problem, and an example of one of these is the Winnowing algorithm. The Winnowing algorithm is a document fingerprinting method that utilizes hashing to detect text similarities. In an essay exam, an instructor must carry out a manual assessment by checking and correcting each participant's answers. Currently, automatic assessment is still generally limited to multiple choice questions. The purpose of this study is to investigate the extent to which previous studies have examined the assessment of essay questions using the Winnowing algorithm. The results of the study indicate that the application of the Winnowing algorithm in automatic evaluation of essay responses on online learning platforms (e-learning) provides good and stable results, and has a high degree of accuracy.

The purpose of this study is to determine the flow of work processes in the warehouse from the inbound, inventory and outbound processes, follow mentoring held every week by doing post test and pre test mentoring, and identify opportunities for improvement in the warehouse in an effort to reduce waste. The research method used by the author in this study is continuous improvement, or kaizen. The results showed that almost about 50% of the writers' activities at PT. DSV Solution Indonesia deals with labeling products with K3L (Safety, Occupational Health &; Environment) labels. This product labeling activity requires a level of accuracy and concentration so that the goods labeled are in accordance with the established category. The products labeled are footware or footwear products such as shoes or sandals. Both shoes and sandals each have an identical number of different K3L labels, not only that each category of product type is then distinguished again according to the origin or origin of the product made. The origin of products that go through the K3L label stage usually comes from Indonesia, Vietnam, and China. So for the number of identical numbers, the K3L label amounts to 6 according to the category of origin and also the type of product.

Electronic-based nursing care in hospitals refers to the application of information technology and electronic systems in the process of providing care for patients. There are various impacts in the use of electronic nursing records that have implications for patient safety. The purpose of this study was to review the impact of using electronic-based nursing documentation on patient safety and quality of nursing care. The method used is literature review by searching articles in three electronic databases: PubMed, ProQuest, and Science Direct. The inclusion criteria used were articles that matched the research objectives, according to the specified keywords, were in English, full text and published until 2022. There were eleven research articles that met the inclusion criteria. The results of a literature review on the eleven articles illustrate that electronic-based nursing documentation has a positive impact on patient safety and the quality of nursing care. The use of electronic nursing documentation provides various benefits, such as efficiency in managing patient data, increasing accuracy and speed in processing information, and improving coordination and communication between health workers. In addition, two articles also convey the impact of using electronic nursing documentation which is considered detrimental in an effort to maintain patient safety. Thus, the information in this literature review can be useful for planning the development of strategies for implementing electronic-based nursing documentation in hospitals.