Publication Search

This study aims to examine the effect of learning accounting character, interest, and learning motivation on learning achievement of accounting students at the University of Victory Sorong. The research was carried out on all students of the Accounting Study Program of the Faculty of Economics and Business, University of Victory Sorong. The data collection method used in this study is a survey method through distributing questionnaires. The sampling technique used was saturated sampling method. Students as the unit of analysis participated as many as 83 students. Data analysis used multiple linear regression with the help of the application of Statistical Package for The Social Science version 22. The results showed that the character of accounting learning, interest, and learning motivation had a positive and significant effect on learning achievement of accounting students.

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.