Journal• ISSN: 2581-1916
Tech-e
Universitas Buddhi Dharma
About: Tech-e is an academic journal published by Universitas Buddhi Dharma. The journal publishes majorly in the area(s): Computer science & Engineering. It has an ISSN identifier of 2581-1916. Over the lifetime, 12 publications have been published receiving 1 citations.
Topics: Computer science, Engineering, Linguistics, The Internet, World Wide Web
Papers
TL;DR: In this article , the authors classify the types of mint leaves using the Euclidean distance algorithm and K-means clustering with shape and texture feature extraction, and the results of the evaluation using a confusion matrix by calculating precision, recall and accuracy.
Abstract: Mint is a plant that has many benefits and uses. However, some people are not familiar with the types of mint leaves because they cannot tell the difference. Actually, if you look closely, mint leaves have their own characteristic shape and texture. However, most people judge mint leaves to have a shape similar to other leaves so it is difficult to tell them apart. This paper aims to classify the types of mint leaves using the Euclidean distance algorithm and K-Means clustering with shape and texture feature extraction. The K-Means Clustering Algorithm functions as a segmentation so that the image to be classified can be separated from other objects. In the feature extraction process, metric and eccentricity parameters are used. Meanwhile, for texture feature extraction, use the parameters in the Gray Level Co-occurence Matrix (GLCM). Furthermore, the classification process uses the Euclidean Distance algorithm which has a function to represent the level of similarity between two images by taking into account the distance value from the identified image. Based on the results of the evaluation using a confusion matrix by calculating precision, recall and accuracy, the precision value is 82%, recal is 84% ​​and accuracy is 83%.
3 citations
TL;DR: In this article , the profile matching method with interpolation at the Indonesian Christian Church Pos Cikoleang, it will require decision makers to determine the weight value for each criterion and the results issued by the system are the congregations that are accepted and rejected in the scholarship application.
Abstract: Education is very necessary in social life. Education has a role that will improve the quality of resources to be able to have the competencies needed in an increasingly advanced and developing era. Giving this scholarship will also greatly help someone in pursuing and even getting an education. Scholarships must also be done objectively, not just subjectively. Because the problems that occur when objectively granting scholarships may not be in accordance with the target of the scholarship award. Scholarships must also be given according to the right criteria so that the scholarship grants get maximum results for the administrators and scholarship recipients. The research was conducted using the Profile Matching method with Interpolation at the Indonesian Christian Church Pos Cikoleang, it will require decision makers to determine the weight value for each criterion. The results issued by the system are the congregations that are accepted and rejected in the scholarship application. and the system can provide scholarships with an accuracy rate of 78%.
2 citations
TL;DR: The clustering method approach can be applied in analyzing the potential level of PMB quality produced by utilizing the PMB recording dataset for the 2023 period using stages in data mining.
Abstract: Acceptance of new students is a very important activity for a high school or university. The admissions data has not been utilized by the campus in making strategic decisions, marketing potential, and considering invitations through academic admissions. So, to assist in processing the new student admissions data, in this study the design and analysis of new student admissions data was carried out using stages in data mining. The clustering method approach can be applied in analyzing the potential level of PMB quality produced by utilizing the PMB recording dataset for the 2023 period. 86 data records. The K-Means and K-Medoids algorithm models that are applied have results that show a new insight, namely grouping based on 2 clusters, cluster 1 (C0) is a pass category while cluster 2 (C1) has not been determined. The results of the K-Medoids algorithm which has cluster 1 (C0) 60 results, cluster 2 (C1) has 26 results is a potential pass of 60 and has not yet been determined 26 of the data tested 86 while the results of the K-Means cluster 1 algorithm (C0) 40 , cluster 2 ( C1 ) 46 is a potential pass consisting of 40 and 46 undetermined data from the 86 datasets tested. Testing using the RapidMiner Studio application can also produce similar insights, namely each cluster has Davies Bouldin Index or DBI results from each K-Means and K-Medoids algorithm. K-Means has a Davies Bouldin Index result of -0.533 while K-Medoids has a Davies Bouldin Index result of -0.877
1 citations
TL;DR: In this paper , the authors compared several algorithms in machine learning to see the best ability in sentiment classification and showed that the selection of the right machine learning algorithm will have a very good impact on the classification of public opinion through social media.
Abstract: Sentiment analysis is one way that is widely used to identify the beginning of public opinion in various fields of life which are associated with very massive and a lot of information through social media. This study aims to compare several algorithms in machine learning to see the best ability in sentiment classification. The research dataset uses a dataset of public opinion related to tourism in Indonesia. The number of datasets used is 10,228 twitter data that have been cleaned and labelled. The machine learning algorithm used is Logistic Regression, KNN, AdaBoost, Decision Tree, SVM, Random Forest and Gaussian. The seven algorithms for sentiment classification from the Twitter public opinion each produce a Gaussian accuracy of 0.52; SVM 0.78; KNN 0.98; Logistic Regression, Random Forest, Decision Tree, AdaBoost of 0.99. This study shows that the selection of the right machine learning algorithm will have a very good impact on the classification of public opinion through social media
1 citations
TL;DR: In this paper , the authors used the Laravel framework to create an admin dashboard and provide a Restful API for android applications to handle database management on the server and used Laravel's features to build a fullstack application that handles requests, routing, controllers, services, models, and views.
Abstract: Online learning is a concept of learning that is carried out online or through the internet network. Very advanced technology in the modern era and globalization makes various activities carried out efficiently and can be done using only gadgets. Technological developments in the field of education with the use of e-learning in learning activities in schools, colleges, courses and even online communities have started to use concepts like this.
This study uses Flutter to create applications for users and consultants in conducting online consultations on android devices. The author uses a collection of widgets that have been provided by flutter to create components in the user interface such as buttons, input text, text, icons, and others.
In this study, we use the Laravel framework to create an admin dashboard and provide a Restful API for android applications to handle database management on the server. The author uses Laravel's features to build a fullstack application that handles requests, routing, controllers, services, models, and views.
Performance Metrics
| Year | Papers |
|---|---|
| 2023 | 5 |
| 2022 | 12 |