Abstract:This study were aimed to (1) To study the effectiveness of white turmeric extract Curcuma domestica .Vall in treating a mouse Cromileptes altivelis from the attack of Vibrio alginolyticus., (2) To study the dose of the best…
est white turmeric extract in treating a Cromileptes altivelis from attacks by bacteria Vibrio alginolyticus. (3) To study the effect of white turmeric extract against the survival rate Mouse grouper (Cromileptes altivelis), which in the infection of Vibrio alginolyticus. The experiment was arranged with a Completely Randomized Design (CRD). Preliminary research conducted LD50 test to determine the pathogenic bacterium V. alginolyticus which caused the death of test fish as much as 50%. In vitro test was done to see anti-bacterial activity of white turmeric extract against V. alginolyticus. From this test, the optimum concentration of white turmeric extract the effective tackling of V. Alginolyticus was obtained was obtained Test in vivo was carried out to determine the effect of the bacteria V. alginolyticus against Cromileptes altivelis healing response in Cromileptes altivelis after giving white turmeric extract. Results showed that (1) MIC and MBC values obtained by concentration of 0.25% and 0.75%, where the concentration of 0.75% was the effective dose of white turmeric extract in tackling the V. alginolyticus (2) The best treatment dose of the best survival rate of Cromileptes altivelis was 1% of white turmeric extract (3) the Survival Rate of mouse grouper wasn’t effected by white turmeric extract treatment significantly
Abstract:The rapid growth of the hotel industry requires hotels to improve operational planning, one of which is by forecasting room reservations. Inaccurate forecasting may cause an imbalance between room availability and customer…
er demand. This study aims to compare the Weighted Moving Average and Single Exponential Smoothing algorithms in forecasting room reservations at Raz Hotel and Convention Medan using historical data from January 2025 to May 2026. The research method consisted of data collection, forecasting using both algorithms, and accuracy evaluation through Mean Absolute Deviation, Mean Squared Error, and Mean Absolute Percentage Error. The results indicate that the Single Exponential Smoothing algorithm achieved a Mean Absolute Percentage Error of 15.24%, which is lower than the 15.63% obtained by the Weighted Moving Average algorithm. Furthermore, the Single Exponential Smoothing algorithm predicted 835.90 room reservations for June 2026. Therefore, it can be concluded that the Single Exponential Smoothing algorithm provides better forecasting accuracy and is more suitable for predicting room reservations at Raz Hotel and Convention Medan.
Abstract:Alumni data management is an important aspect for educational institutions, especially vocational high schools that focus on graduates’ readiness for the workforce. SMK Negeri 1 Kisaran still faces problems in managing alumni…
alumni data and tracking career paths due to manual and unintegrated processes. This study aims to implement a web-based alumni and career tracking information system to improve the effectiveness of alumni data management, facilitate communication between the school and alumni, and support graduate career tracking. The research methods used include observation and interviews with school staff and alumni. The system was developed using PHP programming language and MySQL database, with system design based on Unified Modeling Language (UML). The results show that the developed system is able to manage alumni data centrally, provide career path information, and generate accurate and accessible alumni reports. Therefore, this system can serve as an effective solution to improve alumni information services at SMK Negeri 1 Kisaran
Abstract:This study aims to develop a web-based information system to improve the management of inventory and equipment borrowing at the Network Laboratory of Universitas Royal Asahan. The system is designed to replace manual procedures…
cedures that are prone to data errors, duplication, and time inefficiency. The system development adopts the Waterfall methodology, which includes requirement analysis, UML-based system design (Use Case, Class, Activity, and Sequence Diagrams), implementation using PHP, MySQL, and the CodeIgniter framework, as well as functional testing through the black-box method. The results show that the system provides core features such as inventory management, borrowing transactions, and automated reporting. System testing indicates improved data accuracy, a 70% increase in search efficiency, and enhanced transparency in laboratory asset management. Overall, the system enables a more organized, accountable administrative process and supports the campus digitalization program.
Abstract:Technological advances support digital transformation in sales data management. Wan Toys & Sport stores face difficulty understanding sales patterns, such as the highest sales months and most popular products. This research…
rch uses the K-Means clustering method with the CRISP-DM approach to group sports products based on their sales level. The analysis results show that this method is able to divide products into three categories: high, medium and low, thus providing strategic insight for stock management and marketing. Products with high sales are prioritized for stock, while products with low sales are targeted for promotion. This method effectively supports operational efficiency and data-based decision making at Wan Toys & Sport stores.
Abstract:This research aims to apply the Naïve Bayes method to determine the eligibility of receiving the Smart Indonesia Program (PIP) at the 017107 Kisaran Naga State Elementary School by analyzing 207 student data. The CRISP-DM…
DM approach was used through six stages: business understanding, data understanding, data preparation, modeling, evaluation, and implementation. The variables analyzed included means of transportation, KPS and KIP recipients, worth a pip, reasons for eligibility, number of siblings, distance from home to school, and parents' income.
The results showed that this method achieved 89% accuracy, 85% precision for the positive class, and 92% for the negative class. A total of 125 students (59.9%) were declared eligible to receive assistance, while 82 students (40.1%) did not meet the criteria. The Naïve Bayes method is effective in supporting decision-making for the provision of targeted educational assistance
Abstract:Education plays an important role in improving the quality of human life, but economic constraints often prevent many students from continuing their education. The Smart Indonesia Program (PIP) was launched to address these…
ese issues by providing educational assistance. However, in its implementation, the selection of PIP recipients at IT Al-Ikhsan Private Junior High School is still inaccurate. This research aims to classify the eligibility of PIP recipients using the Naive Bayes method. This method is applied to student data from the school's Dapodik in 2024 which consists of 265 students. The data is processed through CRISP-DM data mining stages, namely Business Understanding, Data Understanding, Data Preparation, Modeling, Evaluation, and Deployment. As a result, the Naive Bayes model showed an accuracy of 92.31% with a precision value for the “Yes” class of 89%, recall 100%, and F1-score 94%. In conclusion, variables such as means of transportation, KPS and KIP recipients, parents' income, and distance from home to school affect the eligibility of PIP recipients.
Abstract:This research is motivated by the large number of prospective students who simply choose a major when they want to enter a vocational school without considering their abilities. The Decision Tree or C45 method is used because…
cause it is able to make decision trees that are easy to describe, and has a level of efficiency in handling discrete and numeric attribute data. While the Naive Bayes method is used because it has a high accuracy of results. This research was conducted based on data from students of SMK Muhammadiyah 10 Kisaran which contained questions about feelings of wrong majors, interests, and determinants of other majors. Data is divided into 2 labels, namely free labels (y) and bound labels (x). Followed by dividing the dataset into training data and testing data with a ratio of 70:30 in both methods to get the level of accuracy. From the results given, it can be seen that the C45 algorithm has an accuracy of 85% and the Naive Bayes algorithm has an accuracy of 26%. This shows that the C45 algorithm is more effective in classifying the available datasets compared to the Naive Bayes.
Abstract:Graduation marks the completion of a certain level of schooling. This study aims to predict the graduation of students at SDN 016528 BP Mandoge based on their abilities. The goal of this research is to reduce the rate of…
student failure to graduate by making predictions based on examination scores collected by the institution. The method used in this study is Naive Bayes, a technique in Data Mining that utilizes probability and statistics to predict future outcomes based on previous data. This method was chosen due to its advantage in predicting graduation rates from concrete data, ensuring the results are reliable and applicable for future predictions. The dataset used in this study includes graduation data for SDN 016528 BP Mandoge students for the 2019/2020 academic year, comprising 171 students, with 120 students used for training data and 51 students for testing data, achieving a model accuracy of 98%.
Abstract:Everbright has become one of the distributing companies selling various products, one of which is the Dettol product. In optimizing the stock and marketing of Dettol products, the company faces difficulties in identifying…
g the best-selling products and those less favored by customers. This research data originates from the sales transaction data of Dettol soap in November, comprising 77 sales data. Through the use of data mining, particularly the K-means Clustering method, it becomes a relevant approach to solving this issue. The objective of this research is to avoid excess inventory that remains unsold while meeting the diverse needs of customers. The results of this study show the visualization of the distribution of Dettol soap product clusters and grouping based on sales levels. There were 21 best-selling item data, 31 well-selling item data, and 25 less popular item data, enabling the company to manage inventory based on the best-selling items.