Abstract:Academic achievement is a measure of students' learning outcomes, encompassing aspects of knowledge and skills. Academic performance serves as a crucial indicator in evaluating students' learning progress. MAS Al-Wasliyah…
h Petatal is committed to providing quality education but still faces limitations in applying technology to evaluate student learning. The current evaluation process relies on teachers' subjective assessments, which restricts the information about students' progress. Therefore, the implementation of machine learning is proposed as a solution to enhance objectivity in student learning evaluation through more effective data processing. The method used is the K-Means Clustering algorithm, which can group or classify data based on specific patterns. This study aims to evaluate the extent to which machine learning can process student learning evaluation data through the analysis results obtained from the clustering process, which are then used as benchmarks to improve the evaluation system and provide feedback for students needing improvement in their academic performance. The data used comprises students' grades from the odd semester of the 2024/2025 academic year, with a total of 210 data points. The clustering results produced three clusters: the "good" cluster with 60 students, the "average" cluster with 99 students, and the "low" cluster with 51 students.
Abstract:Bread product sales have become an important aspect of the bakery business, influenced by fluctuations in demand that are not easily predictable. Efficient sales management requires a deep understanding of sales patterns.…
. This study aims to optimize bread product sales by using the K-Means Clustering algorithm to analyze daily sales performance at Toko Roti Amin. The data used includes sales volume and transaction frequency for bread products, consisting of 356 data points. The results show that the bread products can be grouped into three clusters: 129 data in the “Good Sales” cluster, 28 data in the “Moderate Sales” cluster, and 199 data in the “Low Sales” cluster. These findings assist bakery owners in managing stock, production planning, and more targeted marketing strategies. Although there are limitations in using K-Means Clustering, such as dependence on the initial centroid selection, this study proves that applying this technique can enhance inventory management and maximize profit in the bakery business.
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:The development of information technology provides solutions for increasing efficiency and accuracy in decision-making, such as in determining students eligible for BLT at SD Swasta IT ABI Husni. This study aims to implement…
ment the Naive Bayes algorithm to support a more objective BLT recipient selection process. The method used is CRISP-DM, starting from understanding the problem, data preparation, to model implementation. The data analyzed included type of residence, KPS recipients, parents' income, KIP recipients, number of siblings, distance from home and reasons for eligibility for BLT used were data from students of SD Swasta IT ABI Husni in the odd semester of 2024/2025, with a total of 137 data. The results of the study showed that the Naive Bayes algorithm was able to achieve an accuracy level of 98% with precision and recall of up to 100%, proving the effectiveness of the model in minimizing classification errors. In conclusion, the use of the Naive Bayes algorithm can help make decisions that are more targeted, transparent, and fair in the distribution of BLT.
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:The Self-Help Housing Stimulant Assistance (BSPS) is a government house renovation program aimed at low-income communities. This program aims to enhance self-sufficiency in construction and improve the quality of houses,…
facilities, infrastructure, and public utilities through the principle of mutual cooperation. BSPS recipients must meet several criteria, such as income, house ownership status, house size, floor type, wall type, roof type, and water source. To address issues based on these criteria, Data Mining techniques using the Naive Bayes method were employed. This study utilized a dataset of BSPS recipients in Air Genting Village, Air Batu Sub-district, comprising 88 samples. The classification results from applying Naive Bayes yielded a precision value of 84%, a recall value of 81%, an F1-score of 82%, and an accuracy of 81%. The objective of this research is to facilitate the classification of eligible and rightful recipients of government assistance in the form of BSPS. The results of this study are expected to provide an alternative solution in determining BSPS recipients in Air Genting Village, Air Batu Sub-district
Abstract:The use of smartphones in Indonesia has been steadily increasing each year. In the era of the Fourth Industrial Revolution, smartphones have become a lucrative business sector, leading to intense market competition. Consequently,…
equently, smartphone companies must pay closer attention to the market segmentation desired by consumers. Data mining is the process of discovering significant relationships and patterns by analyzing large datasets using statistical and mathematical techniques. This study aims to identify and analyze the market segments of Android smartphone users among students at STMIK Royal. The data used in this research were collected from 122 student respondents. The study employs clustering using the K-means algorithm. The resulting data modeling will categorize market segments into several clusters. This segmentation yields three clusters: Cluster 1 (features), consisting of 36 respondents who prioritize price, battery, camera, and warranty; Cluster 2 (product), with 49 respondents who value all attributes except warranty; and Cluster 3 (superiority), comprising 37 respondents who prioritize camera, brand, and RAM.
Abstract:The educational approach in Indonesia, especially at Madrasah Tsanawiyah (MTs) Daarussalam, must respond to the challenges of globalization and rapid advances in information technology. This change requires a transformation…
ion of the learning system from conventional methods that are oriented toward memorization to an educational model that is more interactive and relevant to the needs of the times. Critical, creative, and adaptable skills are a must for graduates to compete in the dynamic world of work. Integrating digital technology in learning, such as the use of AI-based learning tools and digital platforms such as ChatGPT, has the potential to increase student participation and provide a more individualized approach to teaching. In this context, MTs Darussalam is committed to carrying out transformation by increasing teachers' understanding of educational technology and implementing professional training. By implementing a collaborative and creative digital learning model, it is hoped that students can develop into critical thinkers and problem solvers ready to face future challenges. This transformation is not just a change in methods but an educational investment aimed at building competitive human resources in the global era.
Abstract:Efficient queue management is a major challenge in public services, including in Cibeunying District. Traditional manual systems often lead to unorganized queues, long waiting times, and public dissatisfaction. This study…
y aims to design and implement a more modern and structured technology-based queue numbering system. The system is designed as a web-based application that allows users to take queue numbers directly on-site or via mobile devices. Additionally, the system is equipped with an automatic call feature, where if a number is not present after two calls, the next number is automatically called. The implementation results show that this system can improve service efficiency, reduce waiting times, and provide a more convenient experience for the community. With this system, the Cibeunying District can significantly optimize the quality of its public services.
Abstract:The development of digital technology has changed the way businesses market products, including culinary businesses such as chili chips. This article examines the role of social media in increasing sales of chili chips in…
n Sibuhuan Market, North Sumatra. Social media, through platforms such as Instagram, Facebook, and TikTok, allows businesses to introduce their products to a wider audience, increase brand awareness, and reach markets outside of the local area. In addition, social media provides an opportunity to interact directly with consumers, receive feedback, and build customer loyalty. Marketing through creative content, such as eye-catching photos and videos, as well as promotions through influencers or contests, also contribute to increased buying interest. By taking advantage of the e-commerce features available on social media, the purchase process becomes easier, which also drives increased sales conversions.