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Technological developments today make it easy for people to use social media as a means of expressing opinions, including Twitter. The case study taken by the researcher is the sentiment towards the performance of the mayor of Medan. The case was taken because it was widely discussed by Indonesian people, especially the city of Medan on Twitter social media. One of the uses of this research is to find out the trend of Twitter user comments on the performance of the mayor of Medan by conducting a sentiment analysis. Sentiment will be classified as positive, negative and neutral. The algorithm used in sentiment analysis is Naïve Bayes. The stages in conducting sentiment analysis in this study are data preprocessing, data processing, classification, and evaluation. The results of this study are using the SMOTE method, the training and testing ratio is 80:20 because it has the highest accuracy, which is 78% compared to other ratios. The prediction results resulting from the classification turned out to be more dominant towards neutral labels. In addition to classifying for sentiment analysis, this study also measures the performance of the model created. The results showed that the Naïve Bayes algorithm has a precision value of 78%, a recall of 78%, and an f1-score of 77%.

The aim of this research is (1) to describe the factors causing code switching in the Drama Series Scandal 2: Sex, Love, and Revenge. (2) describe the function of using code switching in the Drama Series Scandal 2: Sex, Love, and Revenge. This research is qualitative descriptive research. The subject of this research is speech events that occurred in the Drama Series Scandal 2: Sex, Love, and Revenge. The object of this research is data containing code switching in speech events in the Drama Series Scandal 2: Sex, Love, and Revenge. The technique used in collecting data uses non-participating listening and note-taking techniques. Data were analyzed using qualitative descriptive methods with data transcription and data classification steps. The validity of the data is obtained through continuous data searching according to the facts, persistent observation techniques, and triangulation. The results of this study show two conclusions. First, there are five factors that cause code switching in Drama Series Scandal 2: Sex, Love, and Revenge, namely the speaker, the interlocutor, the presence of a third speaker, the subject of discussion, and to evoke a sense of humor, and simply to have agency. Second, there are five functions of code switching in Drama Series Scandal 2: Sex, Love, and Revenge, namely explaining, asking, reprimanding. Affirm and remind

The rapid growth of e-commerce in Indonesia has generated a massive and continuous volume of product reviews. This user-generated content is vital for business intelligence, yet its sheer scale makes manual analysis inefficient, subjective, and practically impossible. Automated sentiment analysis is therefore crucial for businesses to efficiently understand customer feedback and market perception. This research addresses this gap by implementing the Naïve Bayes Classifier (NBC) algorithm to automatically classify the sentiment of Indonesian-language e-commerce product reviews. This study utilized a dataset of 2,000 reviews collected from a major e-commerce platform's "Electronics" category. The data underwent critical text preprocessing stages (case folding, tokenizing, stopword removal, and stemming using the Sastrawi library) to handle the complexities of informal Indonesian text. The dataset was split using an 80/20 ratio, resulting in 1,600 training reviews and 400 testing reviews. Model performance was then evaluated using a Confusion Matrix, focusing on the key metrics of Accuracy, Precision, and Recall. The test results showed excellent performance, achieving an Accuracy of 90.00%, Precision of 91.93%, and Recall of 95.00%. These results demonstrate that the Naïve Bayes algorithm, when supported by robust preprocessing, is a highly effective, reliable, and computationally efficient method for this task, providing a valuable tool for e-commerce stakeholders.

The garment industry faces challenges in grouping diverse goods based on their characteristics, which can affect the efficiency of the production process and inventory management. This study aims to apply the K-Means Clustering algorithm in garment goods classification to improve business process management and optimization. The K-Means algorithm, as one of the popular clustering methods, is used to group garment goods data based on features such as size, color, fabric type, and product model. This method begins with the selection of relevant features from the dataset obtained from the garment industry. Furthermore, the K-Means algorithm is implemented to determine the optimal number of clusters using the elbow score and silhouette methods. The clustering results are analyzed to evaluate the extent to which the algorithm can form homogeneous and business-relevant groups of goods. The results of this study indicate that the K-Means Clustering algorithm is effective in grouping garment goods into several categories that are consistent with business patterns and needs. The application of this method results in a better understanding of goods grouping that can improve production efficiency and facilitate inventory management. This study contributes to the best practices in the use of the K-Means algorithm in the convection sector and shows the potential of this method in supporting data-driven decision making.   Keywords:,

Sentiment analysis of comments from visitors to tourist attractions and the public on tourist attractions in Sukabumi Regency which is one of the areas with various categories of tourist objects and is a sector of economic income for the surrounding community or for related parties such as the government and managers, in sentiment analysis research This includes using the Nave Bayes classification algorithm to examine the sentiment of tourist visitors and the performance of the classification model used. The data used in this research was taken from the website from Tripadvisor and Google Maps using a crawling technique, which then processed the data by a pre-processing process and then applied a classification to the data and got a sentiment visualization by processing word frequency on tourist visitor sentiment data. The results of the accuracy of the model used were re-tested with the k-fold cross validation method and the results of sentiment visualization got the frequency of words that most often appear on negative sentiment labels are garbage, beaches, lacking, places, roads, parking, dirty, entering, caring, clean , expensive, pay, manage, good and water.

The most important part in software engineering is a software defect prediction. Software defect prediction is defined as a software prediction process from errors, failures, and system errors. Machine learning methods are used by researchers to predict software defects including estimation, association, classification, clustering, and datasets analysis. Datasets of NASA Metrics Data Program (NASA MDP) is one of the metric software that researchers use to predict software defects. NASA MDP datasets contain unbalanced classes and high dimensional data, so they will affect the classification evaluation results to be low. In this research, data with unbalanced classes will be solved by the AdaCost method and high dimensional data will be handled with the Average Weight Information Gain (AWEIG) method, while the classification method that will be used is the Naïve Bayes algorithm. The proposed method is named AWEIG + AdaCost Bayesian. In this experiment, the AWEIG + AdaCost Bayesian algorithm is compared to the Naïve Bayesian algorithm. The results showed the mean of Area Under the Curve (AUC) algorithm AWEIG + AdaCost Bayesian yields better than just a Naïve Bayes algorithm with respectively mean of AUC values are 0.752 and 0.696.

Destination from study this is for describe style language and meaning  which contained on Andmesh . album Love Extraordinary lyrics Kamaleng. Study this is study qualitative with approach descriptive qualitative. Technique collection data in study this is analysis data is identification data, classification data, analysis data, description data, and interpretation data. Results this research find that style language or figure of speech on lyrics song Amazing Love Andmesh album Kamaleng there is 3 language styles. That is, (1) style comparative language which includes hyperbole, and litotes , (2) affirmative language style which includes repetition, and climax, (3) contradictory language style which includes antithesis.

The process of finding employees, or what is often called employee recruitment, is an important concern for employers. Recruitment is carried out with the hope of getting employees with the required classification. After the recruitment process is carried out, it is necessary to conduct training for new employees according to their job title. The training was conducted to equip employees to be more creative and able to provide excellent service to visitors. Training is one of the efforts to achieve the service standards that have been set in the business. The population and sample of this study were all 37 employees at RIC, with the data collection method in this study being a questionnaire that will be distributed to employees. The list of questions on the research questionnaire uses a Likert scale. The data analysis method uses descriptive qualitative analysis, namely by distributing questionnaires to respondents to solve the problems to be studied, and quantitative analysis is carried out by processing the data using the SPSS version 23 software tool. From the results of the study, it can be concluded that there is a significant influence between recruitment and training on employee performance at Coffee Idea House. This means that business people must pay attention to a good recruitment process and intense training to improve employee performance.

The purpose of this research is that researchers want to see language acquisition in the field of syntax for a 6-year-old child named Rizky Ramadhan. The source of the data that is the object of this research is the speech or oral utterance of a 6-year-old child named Rizky Ramadhan in the field of syntax. The method used in this research is descriptive research with qualitative data analysis. Data collection techniques carried out by researchers in this study used listening, interviewing and recording techniques. The results of this study indicate that a 6-year-old child named Rizky is able to produce words and sentences in every activity. This can be proven from his daily speech with his interlocutor, namely the researcher, biological mother, and also the child's brother. The theory used in analyzing Rizky's speech refers to Abdul Chaer about sentence classification which includes news sentences (declarative), interrogative sentences (interrogative), imperative sentences, and exclamation sentences (interjective). The results of this study are that Rizky has been able to utter 22 declarative sentences, 15 interrogative sentences, 9 imperative sentences, and 8 interrogative sentences. sentence form as shown in the results.

This study discusses the use of diction, imagery, and figure of speech in the poem Aku Waiting for the Flower. The poem I Wait for Flowers is a poem that talks about someone who is waiting for someone they love very much. With beautiful poetry lines and contains very strong meanings and meanings. This study aims to: 1) Describe Diction 2) Explain imagery 3) Describe the figure of speech in the poem Aku Waiting Bunga. This research uses qualitative descriptive research. The data collection technique used is reading and note-taking technique and data analysis technique using descriptive analysis technique which includes description, classification, and analysis. The results of the research on the poem ''I am waiting for the flower'' have denotative and connotative diction, visual imagery, feeling imagery, and imagery. intellectual, as well as figure of speech personification and hyperbole  

This study aims to determine and analyze the influence of tourism promotion, tourist attractions, tourist facilities, accessibility, service quality, accommodation, tourist age, and tourist income in Batu Katak Tourism Object, Batujonjong Village, Bahorok District, Langkat Regency. This study used primary data collected to see the classification of tourist visit levels using a sample of 90 visitors to tourist attractions, using the Confirmatory Factor Analysis (CFA) analysis method and then using Multiple Linear Regression. The results of the study showed that of the 8 variables analyzed using a factor analysis model that affects the level of tourist visits to Batu Katak, only 3 factors affect the level of tourist visits, namely tourism promotion, service quality, and tourist income. Based on the results of multiple linear regression analysis, it shows that tourism promotion and service quality have an effect and are signed on the factors of Batu Katak tourism visitation rates, while tourist income has an effect and is not significant on the level of tourist visits to Batu Katak Batujongjong Village, Bahorok District, Langkat Regency.    

Inequality of access to social assistance services is still a sectoral problem faced in various regions including Baubau. Although the local government has carried out policy masculinization, in reality it still faces a variety of obstacles oriented towards biased access to social assistance services in the community. This study aims to further explore the alleged inequality and or inequality of access to social assistance services in Baubau. There are at least three important questions raised in this research. First, what is the reality of the implementation of social assistance services in Baubau? Second, what are the factors behind the inequality of access to social assistance services? Third, how is the mapping and counseling of bias in access to social assistance services in Baubau. In dissecting these questions, this research uses a descriptive-qualitative method with a critical paradigm. The data analysis process in this case uses the offer of Matthew B. Miles and Michael Haberman. The findings in this article show that the implementation of social assistance services in Baubau still faces many challenges oriented towards two main aspects, namely the issue of beneficiary data (data fresness and Ineligible data) and community accessibility issues These two points are the main starting point for inequality in access to social assistance services in Baubau, which can technically be categorized into two major classifications, namely bias (Inequality) between urban (urban) and rural (rural) areas. With the extension activities, this problem is expected to be minimized for the sake of more solitive and adaptive social assistance governance.

This study aims to find out the feasibility of flash flipbook media based on the results of macroscopic fungi inventory found in the Mount Pemangkat Protected Forest, Sambas Regency. The form of research used is quantitative descriptive methods. The creation of flash flipbook media is enriched with the richness of local fungi found in the Protected Forest of Mount Pemangkat, Sambas Regency. Flash flipbook media is validated by five validators, including two lecturers of Biology Education Tanjungpura University and three high school teachers who were determined using purposive sampling techniques. Flipbook flash media validation sheets are assessed using the Likert scale and data analysis based on the Lawshe Formula (1975). Validation of flash flipbook media obtained a CVI (Content Validity Index) value of 0.94, so it is declared feasible and can then be used as a learning medium in the fungi classification sub-material and provide additional information about the diversity of mushrooms in the surrounding environment for students of class X high school.

Field Work Practice is a training facility for informatics engineering students to develop, implement and answer problems faced by their environment. The problem that occurs is where the management and data collection of student data is still carried out semi-systemically because it is recorded in a spreadsheet application so that the data is not structured properly, as a result, information from the placement/assignment process, reporting, and classification of PKL student data is less relevant, accurate and timely. and sometimes human error occurs. Therefore we need a system that is able to make it easier to manage student data from street vendors participants into relevant, accurate and timely information when needed entitled "Web-Based Field Work Practice Information System (PKL). This system is built using the CodeIgniter framework and CSS Layout Bootstrap, then this system will be tested through the blackbox method and compatibility testing. So that we get a system that is able to make it easier to manage student data from street vendors participants into relevant, accurate and timely information when needed.

Electrical equipment plays an important role in everyday life, from households, schools, hotels, offices, to industrial environments. Because it really helps humans in making work easier. The need for automated tools to facilitate human activities, makes the need for smart chips or microcontrollers increasing. A new breakthrough in the world of microcontrollers with the application of Arduino.Especially at SMPN 10 Salatiga, there are fish ponds and garden lights, which you forget to feed or not, while the officers forget to turn off the lights, causing the fish to die and the lights stay on even though it is noon. This study tries to implement Fish Feed Control and  automatic garden lights on and off using Arduino and scheduling, this is so that the fish stay healthy   and the garden lights can turn on or off according to the schedule desired by management. The author designed a garden lamp and automatic fish feed based on a case study at the school. The tool is designed with three sources of tool control. The first manual is pressing the fish feed manual button, the light switch and the reset button. Both semi-automatic, as a fish feeder, light ON/OFF and reset remote control with the Android application. The third auto is scheduled feeds and lights. This tool is designed to manage fish feed and garden area lighting. This tool is practical to use, inexpensive, useful, flexible and easy to build. The classification of this tool is sufficient for the needs of the school garden. Among the advantages of this tool is that it can be controlled remotely effectively 25 m without a hitch using the android application. The author hopes, this tool provides benefits and solves problems in schools.

Aging or the process of getting old is a process of disappearing or decreasing health functions in meeting the needs of life. Aging is characterized by sagging skin, gray hair, poor hearing, and worsening vision.1 The WHO classification of elderly (elderly) includes middle age (45-59 years), elderly (60-59 years). 74 years), old (75 – 90 years), very old (above 90 years).2  

The solar water heater (SWH) testing laboratory (LPPATS-B2TKE) has been able to serve commercial product testing based on SNI 3021-1992 1st Edition. Development of test procedures needs to be improved in order to complement the ability to test all parameters contained in the SNI standard. The SWH system performance testing procedure is implicitly described in the form of tables and formulas, so that it needs to be detailed to be implemented in the test. Adopting the SNI thermosiphon procedure, by calculating the daily heat gain, this procedure can produce SWH daily efficiency parameters, which can be used to predict the annual SWH heat gain, PATS product classification, and solar fraction. The results of testing this procedure on a SWH unit with a capacity of 150 liters and a collector area of ​​1.97 m2 for 19 days, obtained daily efficiency in the range of 39.13% to 47.61% in daily radiation between 3.66 - 5.82 kwh/m2, prediction of annual heat gain of 1370, 87 kWh, 75% solar fraction, and prediction of annual heat gain classification of 2783.49 kWh, placing this tested specimen in class III based on SNI standards.

In 2018, Basic Health Research (Riskesdas) data showed that the prevalence of wasting in children under five in Indonesia was 10.2%, while in the age group under two years (baduta) it was higher, namely 11.7%. Nutrition Status Monitoring Data for 2017 also shows that the prevalence of wasting in under-fives is higher, which is 12.8% when compared to the toddler group, which is 9.5% (Ministry of Health RI, 2018). Based on the WHO classification, wasting in the underdog group in Indonesia is categorized as a serious public health problem, with a prevalence in the range of 10-14%. Malnutrition that occurs in 1,000 HPK, besides being at risk of inhibiting physical growth (failure to thrive) and being susceptible to disease (metabolic disorders: DM. Hypertension, obesity), also inhibits cognitive development (motor cognitive impairment) which will affect the level of intelligence and productivity of children in the future.    

Main Objective: This research targets AP sizing entrenched on image structure to raise denoising performance using an improved method for classifying image pixels. Background problem: Digital images may be blended by noise while the addition or communication process, affecting the authentic image signal. Image noise can cause problems at several stages of image processing equally image distribution. Accordingly, image denoising is a significant activity to recover the initial clean image signal from the detected noise signal. Novelty: The proposed WAV method has been refined and improved regarding the classification scheme, and the APS, and the classification results can be used as a mask on the noise image to fix identical patches. Research Method: This study proposes a WAV reprojection algorithm, with the PS being set dynamically entrenched on the image structure. Image structures are consistently taken with an upgraded and enhanced analysis method entrenched in the structure tensor matrix. Analysis results are also used to develop the analysis of comparable patches in images. Finding/Result: Empirical outcomes present that the noise cancellation work of the suggested method is better than the authentic WAVRA, along with several other modifications of the NLMA. Conclusion: In intensity profiles, the proposed method mostly has fewer changes to the original image values than other methods, thus, this method can be continued again to color images, and can also be applied to various types of data such as medical images.   Keywords: Weighted Average (WAV), Noise Cancellation Image, Non-Local Means (NLM), Adaptive Patch

The purpose of this study is to examine influence of financial stability, external pressure, nature of industry, and rationalization to financial statement fraud. The sample used in this study is manufacture companies listed on the Indonesia Stock Exchange (BEI)in the period 2018-2019. By using purposive sampling method, it is obtained as many as 77 mnufacture companies as the study sample. The method of analysis used in this study is logistic regression. In this research include overall fit model test, hosmed and lemeshow test, goodness of fit test, and classification matrix result of this study indicate that the financial stability is significant to financial statement fraud, while external pressure, nature of industry, and rationalization are not significant to financial statement fraud