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All Journal Journal of Computer Science, Information Technology and Telecommunication Engineering (JCoSITTE) Intellektika: Jurnal Ilmiah Mahasiswa
Ira Safira
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Arts Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Social Sciences

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Performance Comparison of Boosting Algorithms in Spices Classification Using Histogram of Oriented Gradient Feature Extraction Muhathir Muhathir; Reydo Trisno Pangestu; Ira Safira; Melisah Melisah
Journal of Computer Science, Information Technology and Telecommunication Engineering Vol 4, No 1 (2023)
Publisher : Universitas Muhammadiyah Sumatera Utara, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30596/jcositte.v4i1.13710

Abstract

Spice classification is an important task in the food industry to ensure food safety and quality. This study focuses on the classification of spices using the HoG feature extraction method and boosting algorithms. The objective of this research is to compare the performance of four different models of boosting algorithms, namely Adaboost Classifier, Gradient Boosting Classifier, XGB Classifier, and Light GBM Classifier, in classifying spices. The evaluation metrics used in this research are Precision, Recall, F1-Score, F2-Score, Jaccard Score, and Accuracy. The results show that the XGB Classifier model achieved the best performance, with a precision of 0.811, recall of 0.809, and F1-score of 0.809, while the Adaboost Classifier model had the lowest performance, with a precision of 0.709, recall of 0.689, and F1-score of 0.682. Overall, the results indicate a fairly good success rate in classifying spices using the HoG feature extraction method and boosting algorithms. However, further evaluation is needed to improve the accuracy of the classification results, such as increasing the number of training data or considering the use of other feature extraction methods
Sinergi Pendidikan dan Kesehatan untuk Masyarakat Melalui Jalan Sehat di Nagari Kampung Tengah Fahmarita Fahmarita; Fitri Handayani; Ghina Alya Dzakwan; Ira Safira; Nasya Aulia Ramadhani; Yasypi’i Pakhiri Caniago; Sandra Dewi
Intellektika : Jurnal Ilmiah Mahasiswa Vol. 2 No. 5 (2024): September : Jurnal Ilmiah Mahasiswa
Publisher : STIKes Ibnu Sina Ajibarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59841/intellektika.v2i5.1685

Abstract

This article aims to analyze the impact of the "Jalan Sehat" program as an effort to synergize education and health for the community in Nagari Kampung Tengah. This program is a collaborative initiative between educational institutions and communities designed to raise awareness of the importance of a healthy lifestyle and basic health education. The results showed that "Jalan Sehat" succeeded in increasing community participation in physical activity, reducing levels of physical inactivity, and strengthening knowledge and awareness of the importance of health. In addition, the program has strengthened the relationship between education and health institutions, creating an environment that supports continuous learning about health. Other positive impacts include increased social interaction and sense of community among community members. Overall, it can be concluded that health walk activities have great potential to effectively integrate aspects of education and health in the community, which in turn can improve the quality of life and well-being of the community.
Co-Authors Fahmarita Fahmarita Fitri Handayani Ghina Alya Dzakwan Melisah Melisah Muhathir Muhathir Nasya Aulia Ramadhani Reydo Trisno Pangestu sandra dewi Yasypi’i Pakhiri Caniago