Article Per Year (5 Year)
p-Index From 2020 - 2025
0.444
P-Index
This Author published in this journals
All Journal Jurnal Ilmiah Sinus Jurnal Kridatama Sains dan Teknologi
Kumarahadi, Yovita Kinanti
Unknown Affiliation
Agriculture, Biological Sciences & Forestry Civil Engineering, Building, Construction & Architecture Computer Science & IT Education Social Sciences

Published : 2 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search

 1 
Content-Based Filtering pada Sistem Rekomendasi Buku Informatika Ridhwanullah, Dziky; Kumarahadi, Yovita Kinanti; Raharja, Bayu Dwi
Jurnal Ilmiah SINUS Vol 22, No 2 (2024): Vol. 22 No. 2, Juli 2024
Publisher : STMIK Sinar Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30646/sinus.v22i2.840

Abstract

There are changes taking place in Indonesia's educational system, particularly in universities. The learning approach used in the transformation program is student-centered. A firm foundation in literacy is required for the application of this learning. A library is one of the amenities that students require. The library is an ideal resource for pupils to enhance their critical thinking skills. It's not always simple to find books in the library, though. Students could find it challenging to locate the books they seek because there are so many collections already in existence. One method for doing book searches is through the use of a recommendation system. Using content based filtering is one recommendation system algorithm. This study suggests a content based filtering algorithm-based book recommendation system to facilitate students' search for informatics book titles. TF-IDF and Cosine Similarity are used in a similarity search to find phrases and assign weights to them. The content-based filtering algorithm's research findings might suggest books depending on user-specified parameters. 90% accuracy is the average for this method.Keywords: recommendation system, content based filtering, TF-IDF, Cosime Similarity
Sistem Rekomendasi Makanan Kucing Menggunakan Metode Content-Based Filtering Kumarahadi, Brigitta Melati; Kumarahadi, Yovita Kinanti; Ridhwanullah, Dziky
Jurnal Kridatama Sains dan Teknologi Vol 7 No 01 (2025): Jurnal Kridatama Sains dan Teknologi
Publisher : Universitas Ma'arif Nahdlatul Ulama Kebumen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53863/kst.v7i01.1471

Abstract

Cats are popular pets because they have cute behavior and adorable physical appearance. Caring for cats does require extra attention, especially when feeding them. Providing food that suits their needs is very important for optimal growth and preventing various health problems. The cat food recommendation system is the right solution for cat owners to choose food that suits their cat's needs. A recommendation system is a system designed to help users get recommendations for items that are relevant and useful. Content based filtering is a recommendation system that provides suggestions based on user preferences for several items, including age, variant, brand, taste, size and price. The data used is cat food products with the brands Whiskas, Cat Choize, Me-O, and Royal Canin at the Pet Shop Colomadu. The recommendation value is calculated based on the cosine similarity value between two items. System testing is carried out using functionality testing (blackbox) and validity testing. The results of functionality testing show that the system can function well. The results of validity testing show that the system is valid and can be used appropriately. It can be concluded that the cat food recommendation system using the content-based filtering method can be used to recommend the right cat food
Co-Authors Kumarahadi, Brigitta Melati Raharja, Bayu Dwi Ridhwanullah, Dziky