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All Journal IJCCS (Indonesian Journal of Computing and Cybernetics Systems) International Journal of Artificial Intelligence in Medical Issues
Fadhila Tangguh Admojo
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Computer Science & IT Control & Systems Engineering Dentistry Health Professions Medicine & Pharmacology Public Health

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Sistem Pencarian Informasi Berbasis Ontologi untuk Jalur Pendakian Gunung Menggunakan Query Bahasa Alami dengan Penyajian Peta Interaktif Fadhila Tangguh Admojo; Edi Winarko
IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Vol 10, No 1 (2016): January
Publisher : IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/ijccs.11186

Abstract

Mountain climbing path information has been widely available on the internet. However, to get information that suits the needs of climbers take time to browse and compare all the available information. The diversity of the search results content actually confuse the climbers.            This research aims to provide a solution to the problems faced by climbers, by developing an information retrieval system for mountain climbing path using semantic technology (ontology) based approach .   The system is developed by using two knowledge base (ontology), ontology Bahasa represents linguistic knowledge and ontology Mountaineering represents mountaineering knowledge. The system is designed to process and understand natural language input form. The process of understanding the natural language based on syntactic and semantic analysis using the rules of Indonesian grammar.            The results of the research that has been conducted shows that the system is able to understand natural language input and is capable of detecting input that is not in accordance with the rules of Indonesian grammar both syntactically and semantically. The system is also able to use a thesaurus of words in the search process. Quantitative test results show that the system is able to understand 69% of inputs are taken at random from the respondents.
Comparative Study on the Performance of the Bagging Algorithm in the Breast Cancer Dataset Fadhila Tangguh Admojo; Waluyo Poetro, Bagus Satrio
International Journal of Artificial Intelligence in Medical Issues Vol. 1 No. 1 (2023): International Journal of Artificial Intelligence in Medical Issues
Publisher : Yocto Brain

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56705/ijaimi.v1i1.87

Abstract

Breast cancer remains a predominant health concern globally. Early detection, powered by advancements in medical imaging and computational methods, plays a vital role in enhancing survival rates. This research delved into the application and performance of the Bagging algorithm on a Breast Cancer dataset that underwent image segmentation using the Canny method and feature extraction through Hu-Moments. The Bagging algorithm demonstrated moderately consistent performance across a 5-fold cross-validation, with average metrics of 56.9% accuracy, 58.3% precision, 57.7% recall, and 56.6% F-measure. While the results showcased the potential of the Bagging algorithm in classifying breast cancer data, there remains an avenue for further optimization and exploration of other ensemble or deep learning techniques. The findings contribute to the broader domain of machine learning in medical imaging and offer insights for future research directions and clinical diagnostic tool development.
Co-Authors Edi Winarko Poetro, Bagus Satrio Waluyo