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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

Diabetes is a serious chronic disease that occurs because the pancreas does not produce enough insulin (a hormone that regulates blood sugar or glucose), or when the body cannot effectively use the insulin it produces. WHO data shows that the incidence of non-communicable diseases in 2004 reached 48 , 30% is slightly higher than the incidence rate of infectious diseases, namely 47.50% [1]. According to the Ministry of Health in 2012 diabetes caused 1.5 million deaths. Some Indonesian people, this disease is better known as diabetes or blood sugar. This research was developed through secondary data processing from the Pima Indians Diabetes Dataset health database which was taken from the Kaggle dataset and can be accessed through https://www.kaggle.com/uciml/pima-indians-diabetes-database. Where the data itself consists of 768 records with several medical predictor variables (Pregnancies, Glucose, Blood Pressure, Skin Thickness, Insulin, BMI, Diabetes Pedigree Function, Age and Outcome). Then the data will be processed using the Particle Swarm Optimization (PSO) feature selection to increase the accuracy value and the Naive Bayes algorithm to determine the accuracy results of the diagnosis of diabetes. From the results of research that has been done for the accuracy of the classification algorithm Naive Bayes is 74.61%, while the accuracy of the classification algorithm with Particle Swarm Optimization is 77.34% with an accuracy difference of 2.73%. So it can be concluded that the application of the Particle Swarm Optimization technique is able to select attributes in the Naive Bayes Algorithm, and can produce a better level of diabetes diagnosis accuracy than using only the individual method, namely the Naive Bayes algorithm. Keywords: Diabetes, Particle Swarm Optimization, Naive Bayes Algorithm

A house for every human being is the main and most important need compared to others needs in general. A financial institution is an institution engaged in the financial sector where its customers are people from various walks of life with various behaviors. Lending is a business activity that carries a high risk and affects the business continuity of a banking company. The problem that is often faced in providing home loans is determining the decision to extend credit to prospective customers, while another problem is that not all home loan payments by customers can run well or commonly known as bad credit. One of the causes of bad credit is an assessment error in making credit decisions. Data mining is a process used to analyze cases in order to find the best performance of an algorithm being tested. One way to get information or patterns from a large data set is to use techniques in data mining. There are many classification methods that can be used to produce precise accuracy values. In this study, two classification algotihm methods are used in classifying the home crediting dataset, namely the C4.5 decision tree algorithm and the Naïve Bayes algorithm. The comparison of the two algorithms produces an accuracy value fo the Naïve Bayes algorithm of 36.36% and the Decision Tree C4.5 algorithm has an accuracy rate of 59.54%.

With the increasing development of technology the more variety of books circulating on the internet. As is the recommendation system on online book sites that provide books relevantly and as needed with one's preferences. One alternative is GoodReads, a social networking site that specializes in cataloging books and users can share reading book recommendations with each other by rating, reviewing, and commenting. As a large book recommendation site, it has a lot of data that can be processed by applying machine learning methods, but still not known as the most accurate model. By using the right model, we can provide more accurate recommendations. Therefore, this study will analyze the data obtained from the www.kaggle.com namely the goodreads-books dataset. This study proposed a data mining classification model to get the best model in recommending books on GoodReads. The algorithms used are Decision Tree, K-Nearest Neighbor, Naïve Bayes, Random Forest, and Support Vector Classifier, then for model evaluation using accuracy, precision, recall, f1-score, confusion matrix, AUC, and Mean Error Absolute. The test results of several classification algorithms found that Decision Tree has the highest accuracy among the methods presented by 99.95%, precision by 100%, recall by 96%, f1-score of 98% with MAE of 0.05 and AUC of 99.96%. This is proof that decision tree algorithms can be used as book recommendations based on book categories on GoodReads.

Classification is one of the most widely used techniques in machine learning. Text classification is the process of classifying data according to pre-determined groups or classes. Where in most cases, text classification uses labeled training data to obtain the rules used to classify test data into predefined groups. In this study, it is proposed to use CountVectorizer for Indonesian text classification which will be compared with TF-IDF Term Weighting and its three feature levels, namely Character Level, Word Level and N-gram Level as feature extraction which is implemented together with Naive Bayes classification and the BPPPTIndToEngCorpusHalfM dataset. To compare the classification performance, this study uses 10-Fold Cross Validation and Split Data using a ratio of 90:10, while to evaluate the accuracy of the authors using the F1-Score and AUC with the hope that this study will get good accuracy results so that it can be used as a reference to be developed using another method. The F1-Score accuracy obtained in this study was 0.93 and the AUC score was 0.95.

Chronic kidney failure is the failure of kidney function in maintaining metabolism and fluid and electrolyte balance in the body. Chronic kidney disease initially does not show significant symptoms and signs but can develop rapidly into kidney failure. Kidney disease can be prevented and treated if known earlier. One way to find out chronic kidney failure is to detect using data mining. Iterative Dichotomiser 3 (ID3) algorithm is one of the classification methods and is a type of method that can map or separate two or more different classes. Based on the measurement of performance classification of 80% of training data from 400 data used, it shows that the accuracy value reached 96.25%. It can be concluded that the ID3 Algorithm method is feasible to be used in research predictions for chronic kidney failure.

Infant health can be known one of them through the assessment of nutritional status. In general, Body Mass Index (BMI) has been used as a method for measuring the nutritional status of children. If there are two children who have same body weight and height, they may have different nutritional status. Whenever this occurs, the use of BMI for measuring the nutritional status shall be deemed less accurate. The anthropometry will be vital in measuring the nutritional statuss. The guidelines for determining the nutritional status Anthropometry parameters are selected and recommended which includes an assessment of the age, weight, body length or height. This research aims to build a model of C4.5 adaboost so it can recognize patterns and be able to classify the nutritional status of children into five classes: normal, fat, very fat, thin and very thin. The variables used in this classification is Gender, Age (Months), Weight (kg) Height (cm). C4.5 (decision tree) Method has a good performance in dealing with the classification of nutritional status but the C4.5 has a weakness in the class imbalance. Adaboost isone ofboosting methods that could reduce imbalances class by giving weight to the level of classification error which may alter the distribution of data. Experiments carried out by applying the adaboost method C4.5 to obtain optimal results and a good degree of accuracy. The experimental results obtained from C4.5 method show that accuracy is 89.53%, the error rate is 10.47%, while the results of C4.5 with adaboost show 90.23% accuracy and 9.77% error rate. It can be concluded in the classification of nutritional status of children with C4.5 and adaboost proven method to solve problems of class imbalance and improve the high accuracy and can reduce the level of classification error.

Heart failure has an impact not only on one's physical condition but also on the psychological impact of anxiety. Patients with heart disease who experience psychosocial problems, especially anxiety, will have a slower recovery process and more severe physical symptoms they experience. Thus, an intervention is needed to provide back massage to overcome anxiety. The purpose of this study was to describe the application of back massage towards anxiety scores in heart failure patients.This study belongs to descriptive research using the case study approach method. The sample in this study were 2 subjects who suffered classification II and III heart failure according to NYHA who experienced low to moderate anxiety. Both subjects were given back massage therapy. Hamilton Anxiety Rating Scale (HARS) was used as the instrument to measure the level of anxiety. The results showed that there was a significant decrease in the two subjects who initially fell into the anxiety category into the category of low anxiety after being given back massage therapy for 15 minutes at 24-hour intervals for 3 days. In conclusion, back massage is recommended to be applied in the hospital as a nursing intervention to overcome anxiety in heart failure patients.