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All Journal Jurnal Pendidikan dan Pembelajaran Khatulistiwa (JPPK) Journal of Applied Business and Technology
Leo, Leo
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Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Languange, Linguistic, Communication & Media Mathematics Other

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KELAYAKAN FLIPBOOK MATERI KEANEKARAGAMAN HAYATI TUMBUHAN OBAT DESA SEBURING KABUPATEN SAMBAS KALIMANTAN BARAT Leo, Leo; Syamswisna, Syamswisna; Ariyati, Eka
Jurnal Pendidikan dan Pembelajaran Khatulistiwa Vol 7, No 11 (2018): Nopember 2018
Publisher : Jurnal Pendidikan dan Pembelajaran Khatulistiwa

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (311.946 KB)

Abstract

AbstractThis study aims to determine the feasibility of flipbook media on biodiversity material based on the results of studies of ethnobotany of medicinal plants in the village of Seburing, Sambas regency, West Kalimantan and find out the types of plants in the village of Seburing that are used as medicine by the people of Seburing Village, Sambas Regency, Kalimantan West. This type of qualitative research, the method used is descriptive with the sampling technique using purposive sampling. Data collection techniques using interviews, observation, and documentation. From the results of the study, there were 50 types of medicinal plants consisting of 30 families. The results of the study were then implemented in the form of flipbook media. The flipbook media was tested for feasibility by two lecturers of the Biology FKIP Untan education study program, two Biology high school class teachers, namely SMA 1 Semparuk and SMAN 1 Selatiga in Sambas Regency and one Biology teacher in grade X Senior High School in Pontianak City. Based on the validator's assessment, flipbook is included in the valid category with a total average value of 0.99 validation and is suitable for use as a learning medium on biodiversity material. This research is expected to be able to make the general public, especially the Seburing village community, to always preserve the environment, especially the preservation of plants. Keywords: flipbook, medicinal plants, Seburing Village 
Optimization of Body Mass Index Classification Using Machine Learning Approach for Early Detection of Obesity Risk Nasien, Dewi; Owen, Steven; Fenly, Fenly; Johanes, Johanes; Lombu, Frendly; Leo, Leo; Baharum, Zirawani
Journal of Applied Business and Technology Vol. 6 No. 3 (2025): Journal of Applied Business and Technology
Publisher : Institut Bisnis dan Teknologi Pelita Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35145/jabt.v6i3.201

Abstract

This study aims to optimize the classification of obesity risk at an early stage using Principal Component Analysis (PCA), which is an important technique in machine learning. PCA is used to reduce the dimensionality of data, maintain important information without losing data, and has the advantage of reducing complexity which usually increases the risk of overfitting. The obesity dataset will be classified using algorithms such as K-Nearest Neighbor (KNN), Support Vector Machine (SVM), Decision Tree, Random Forest, Gradient Boosting Linear, and XGBoost. Specifically, each algorithm is chosen because of its respective advantages: KNN for nonlinear data, SVM for high-dimensional data, and Random Forest and XGBoost for complex data patterns. Evaluation is carried out using metrics such as accuracy, precision, recall, and F1-score to assess the performance of the algorithm. The results show that the Random Forest and XGBoost algorithms provide the best performance in terms of accuracy, especially when all dataset features are used without PCA reduction. This study is expected to be a consideration in determining the best algorithm for obesity classification, supporting early detection, and facilitating decision making in health analysis.
Co-Authors Baharum, Zirawani Dewi Nasien Eka Ariyati Fenly, Fenly Johanes Johanes, Johanes Lombu, Frendly Owen, Steven Syamswisna ,