alfitanaya, alfitanaya (2026) SISTEM CERDAS REKOMENDASI TANAMAN OBAT UNTUK TREATMENT KONDISI KLINIS RINGAN MENGGUNAKAN PENDEKATAN CASE-BASED REASONING (CBR) DENGAN METODE WEIGHTED SIMILARITY. S1 thesis, Universitas Malikussaleh.

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Abstract

The use of medicinal plants as an alternative treatment for mild clinical conditions remains widespread among the Indonesian population. However, information regarding the selection of medicinal plants appropriate for a user’s condition is scattered across various sources, making it difficult to access and potentially leading to errors in their use. This study aims to design and develop a web-based intelligent system capable of providing recommendations for medicinal plants to treat mild clinical conditions using the Case-Based Reasoning (CBR) approach with the Weighted Similarity method. The CBR method operates through the stages of retrieve, reuse, revise, and retain to derive solutions based on previous case experiences. Meanwhile, the Weighted Similarity method is used to calculate the similarity level between new and old cases by assigning weights to each attribute according to its level of importance. The attributes used in the similarity search process include disease, age, medical history, and the user’s condition. The system was developed using the Python programming language based on the Flask framework, with SQLite as the database. System testing was conducted using the Black Box Testing method to ensure that all functions operate in accordance with user needs. The test results show that all system features—from the consultation process, similarity calculation, herbal plant recommendations, consultation history storage, to data management by the administrator—function properly as expected. The developed system is expected to help the public obtain recommendations for medicinal plants that are faster, more accurate, and tailored to user characteristics, as well as serve as a supporting information medium for the safer and more targeted use of Family Medicinal Plants (TOGA). Keywords: Intelligent System, Case-Based Reasoning, Weighted Similarity, Medicinal Plants, Mild Clinical Conditions, Website.

Item Type:	Thesis (S1)
Subjects:	Q Science > QA Mathematics > QA75 Electronic computers. Computer science T Technology > T Technology (General)
Divisions:	Fakultas Teknik > 57201 - Jurusan Sistem Informasi
Depositing User:	alfita naya
Date Deposited:	17 Sep 2026 07:01
Last Modified:	17 Sep 2026 07:01
URI:	https://rama.unimal.ac.id/id/eprint/22964

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