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PT. Nerangi Sarana Karya often experiences several problems because of the large number of purchases purchased but there is no system that helps to recommend product purchases, for example on 9 October 2018 PT. To solve the problems that occur at PT Nerangi Sarana Karya, it is necessary to apply a decision making system using the Fuzzy MCDM method, based on the results of data testing that this method has an accuracy rate of data analysis of 87% so that this method is quite feasible to use in decision making.

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

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.

Abstract In this study that was used as the object of research in classifying red wine based on the quality influenced by each red wine or red wine based on the content of each type of wine, from each attribute containing the composition in the wine seen which attributes most affect the quality of red wine, so that it will be known ingridents that can improve the quality of the wine, in this study was carried out by the application of Machine learning by comparing three algorithms of mining data that is , Decission Tree, Random Forest and Support Vector Machine (SVM), from the results of research that has been done by comparing the three algorithms, Random Forest produced the best accuracy among other algorithms that have been tested. Random Forest with accuracy results of 0.7468 makes this algorithm best used to classify the quality of red wine. And in the second order Decission Tree with accuracy results of 0.7031, while Support Vector Machine (SVM) get an accuracy result of 0.65. So in the research that has been done to classify the quality of red wine based on its composition Random Forest becomes the best algorithm to use..

The certainty of disclosing local government financial reports to the public in a timely manner is one of the main factors of a local government's success in financial management. This is because financial reports are used by the public to evaluate the management capabilities of existing resources. The public wants to ensure that these resources are managed effectively and efficiently. Additionally, the accuracy of local government financial reports disclosure is also used as a basis for future decision making. This study will examine several indicators related to the time of local government financial reports disclosure in Central Java during 2015 - 2017. This study used a measure of the effectiveness of internal audit, local government measurement from the perspective of audit opinion in each region. The data in this study were secondary data, namely the audit report of the financial audit agency (LHP BPK) from each local government. Furthermore, it also comprised the performance report of state development audit agency (LKjIP BPKP) in Central Java. The data obtained will be processed using Eviews 9 analysis tool. The results of this study indicate that the Internal Audit has no significant negative effect on the Audit Lag Report, the Size of the Local Government has no significant negative effect on the Audit Report Lag, and the Audit Opinion has no significant negative effect on the Audit Report Lag.  Keywords: Audit Report Lag, Internal Audit, Local Government Measurement, Audit Opinion.

financial information in schools. Payment information which is the basis for schools to determine future policies. The object of research in this thesis is the Demak Development High School which is one of the agencies engaged in the field of science and education. The research objective is to design an effective and efficient school payment administration recording information system and design a school payment administration recording information system that has a system security that can maintain the accuracy of the data. The research method used is the Borg and Gall R&D Development Research model, the Prototyping System Development Method to produce a product in the form of a Prototype with 6 stages: Research and Data Collection, Planning, Initial Product Development, Product Testing, Product Revision, Final Trial. The conclusion from the results of this study is that this system can facilitate the recording of administrative payment transactions so that there are no mistakes in recording, users can easily present payment reports more quickly so that they can minimize recording time and recording errors, and make it easier for users to print payment reports with affectic and efficient results so as to support and accelerate decision making

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.

The quality of health services shows the level of perfection of health services in creating a sense of satisfaction in patients.In this study, researchers used a purposive sampling type of research, namely sampling with special criteria, namely inclusion and exclusion criteria with a cross sectional approach, namely research that explores, analyzes and explains the relationship between the quality of health services and patient satisfaction at the Ridge Health Center. The data needed comes from filling out questionnaires by patients or families of patients seeking treatment at the Ridge Health Center.The sample in this study used 44 respondents who received treatment at the Ridge Health Center. And in this research, the instrument used was a questionnaire with a total of 40 questions.The results of this study show that there is a relationship between the quality of health services, reliability (0.038<0.05), assurance (0.000<0.05), tangibility (0.002<0.05), empathy (0.000<0.05), and responsiveness (0.000 <0.05) with patient satisfaction. The conclusion of this research is that there is a relationship between the quality of health services (reliability, assurance, tangibility, empathy and responsiveness) with patient satisfaction at the Ridge Community Health Center. The advice that researchers can give is that they can evaluate and improve management to improve the quality of service so that patient satisfaction is related to research results, namely the components of speed of administration, patient comfort as well as completeness of medical equipment and accuracy of information so that it is hoped that it can increase patient satisfaction.