Implementasi Model Poisson Laplace untuk IR pada E-Skripsi Universitas Udayana

Abstract

At Udayana University, a digital repository system is available to store books and student theses. However, the current repository system only categorizes documents based on the year of publication, without any grouping based on topics, fields of science, or other data. Although a search feature is available, the function has not been optimized. To overcome this problem, research was conducted on the Probabilistic Information Retrieval Model, namely the Poisson Model with Laplace Smoothing and Normalization 2. Research was conducted on student thesis title data in 2024 as many as 4,671 titles and evaluation using 10 queries. The research resulted in a Mean Average Precision value, normalized Discounted Cumulative Gain, and recall of 0.715 and a precision value of 0.1421. From this value, further experiments need to be held because the precision value is far different from the recall, indicating the number of False Positive values.