Fakultas Teknologi Informasi

Breast cancer identification using a hybrid machine learning system

Breast cancer remains one of the most prevalent malignancies among women and is frequently diagnosed at an advanced stage. Early detection is critical to improving patient prognosis and survival rates. Messenger ribonucleic acid (mRNA) gene expression data, which captures the molecular alterations... Selengkapnya


Stock’s selection and trend prediction using technical analysis and artificial neural network

Stock trading offers potential profits when traders buy low and sell high. To maximize profits, accurate analysis is essential for selecting the right stocks, timing purchases, and selling at peak prices. The authors propose a new method for selecting potential stocks that are highly likely to rise... Selengkapnya


Balancing Cybersecurity Policies and Institutional Ethics: A Legal and Cultural Perspective on Higher Education Frameworks

Objective: The objective of this study is to investigate the intersection of cybersecurity policies with legal and<br /> cultural considerations within higher education institutions (HEIs), with the aim of addressing key challenges and<br /> proposing a balanced framework that ensures... Selengkapnya


Searching Sahih Hadiths Based on Queries using Neural Models and FastText

Hadith is the second source of Islamic law after the Qur’an, and the availability of accurate and easily accessible information about hadith is crucial, as it directly affects a person’s belief (aqidah). This highlights the importance of having hadith collections as essential guidance in... Selengkapnya


Breast cancer identification using machine learning and hyperparameter optimization

Breast cancer identification can be analyzed through genomic analysis using gene expression data, one type of which is mRNA. This involves analyzing gene expression patterns of breast tissue samples to distinguish breast cancer from healthy tissue or to differentiate subtypes of different breast... Selengkapnya


Artificial intelligence detection of refractive eye diseases using certainty factor and image processing

Refractive errors are defined as an impairment in the eye’s capacity to focus<br /> light, resulting in the formation of blurred or unfocused images. These issues<br /> arise from alterations in the shape of the cornea, the length of the eyeball, or<br /> the aging of the crystalline lens. It... Selengkapnya


Feature Selection of Diabetic Retinopathy Disease Using Particle Swarm Optimization and Neural Network

Currently, there are many medical experts who face difficulty in conducting early detection for diabetic retinopathy. This occurs because it is difficult to recognize the early symptoms of this disease. In order for this disease to be detected early, an accurate classification method is required.... Selengkapnya