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All Journal Journal International Journal of Teaching and Learning (INJOTEL) INTERNATIONAL JOURNAL OF ECONOMIC LITERATURE INTERNATIONAL JOURNAL OF SOCIETY REVIEWS (INJOSER)
Mohammad Aldinugroho Abdullah
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Economics, Econometrics & Finance Education Mathematics Social Sciences Other

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GROUPING PRODUCTS IN SUPERMARKETS USING THE K-MEANS ALGORITHM Mohammad Aldinugroho Abdullah; Rima Tamara Aldisa
INTERNATIONAL JOURNAL OF SOCIETY REVIEWS Vol. 2 No. 4 (2024): APRIL
Publisher : Adisam Publisher

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Abstract

Supermarket, a shop that provides various products for use, especially for daily life, including food products, drinks, kitchen utensils, clothing, electronic equipment and others. It is not surprising that many mothers now choose to shop for daily necessities at supermarkets rather than the nearest stall. With self-service, it can make it easier for us consumers to buy different products in one place. So there is no need to change shops to buy other items. Of course, products have different levels of popularity, not only because of taste but also because of price. The number of products provided by supermarkets is relatively large and if you look at the level of popularity, it is difficult to determine, so data mining is needed. The data mining used is clustering. After implementing and using the K-Means algorithm in clustering (grouping) supermarket products, there are two centroids used (C1 for Not Selling Products and C2 for Best Selling Products). The initial centroid value is determined randomly, while the subsequent centroids are adjusted according to the results of calculating the closest distance (maximum distance). The final result obtained is that the best-selling group consists of 12 products, namely products with serial numbers 1, 4, 5, 6, 7, 8, 9, 11, 14, 15, 16 and 17. Meanwhile, the product group does not There are 6 best-selling products, namely products with serial numbers 2, 3, 10, 12, 13 and 18.
SELECTION OF SUPERIOR EMPLOYEES USING THE PROFILE MATCHING APPROACH IN THE SALES DECISION SUPPORT SYSTEM AT AKUL CATERING Rima Tamara Aldisa; Mohammad Aldinugroho Abdullah; Puspa Ayu Sholeha
INTERNATIONAL JOURNAL OF ECONOMIC LITERATURE Vol. 2 No. 3 (2024): March
Publisher : Adisam Publisher

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Identifying and recruiting superior employees is a good challenge for every organization, including catering businesses where service quality directly influences customer satisfaction and business success. This research aims to develop a Decision Support System (DSS) using the Profile Matching approach to facilitate the selection of superior employees at Akul Catering. The Profile Matching method is used to assess the suitability between the candidate's competency profile and the competency profile required by the position to be filled. This research designs and implements an algorithm to measure the level of such matches, enabling more objective and efficient decision making. Data was collected through observation, interviews and questionnaires to determine the criteria and sub-criteria that are relevant to the positions available at Akul catering. The results of this research show that the developed system can effectively speed up the selection process by filtering out candidates who do not meet the minimum criteria and identifying candidates with the best profile match. It is hoped that this system can be integrated into the recruitment process at Catering Akul well to improve employee quality and overall improve catering performance.
THE EFFECTIVENESS OF GOOGLE CLASSROOM IN INCREASING STUDENT UNDERSTANDING AND INTERACTIVITY IN ONLINE LEARNING Rima Tamara Aldisa; Frenda Farahdinna; Mohammad Aldinugroho Abdullah
International Journal of Teaching and Learning Vol. 2 No. 4 (2024): APRIL
Publisher : Adisam Publisher

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In the current digital era, the use of online learning platforms such as Google Classroom is becoming increasingly relevant in supporting an effective learning process. This research aims to investigate the effectiveness of Google Classroom in increasing learning interactions and student involvement in learning. The research method used was an experiment with a pretest and posttest design as a group. Data was collected through the results of student engagement questionnaires, observations of learning interactions, and in-depth interviews with students. The results of the research show that the use of Google Classroom significantly increases learning interactions, student understanding in using technology and student engagement compared to conventional learning methods. Students in the experimental group showed increased motivation to learn, participation in class discussions, and collaboration between students. These findings confirm the potential of Google Classroom as an effective supporting tool in improving the quality of learning interactions and student involvement in the learning process. This research provides insight for educators and helps students to better utilize online learning technology in designing and delivering interactive and interesting learning materials.
Co-Authors Frenda Farahdinna Puspa Ayu Sholeha Rima Tamara Aldisa