Cervical cancer is a form of cancer that grows within the cervix that is caused by a Human Papillomavirus (HPV) infection that results in the formation of a malignant tumor. Out of all women cancer patients in Indonesia as per year 2021, 17.2% suffer from cervical cancer. One of the key factors contributing to the high incidence of cervical cancer in Indonesia is the low coverage of early screening. As of 2021, only 6.82% of women aged 30–50 had undergone Visual Inspection with Acetic Acid (VIA) screening, far below the 70% national target. Early detection with Visual Inspection with Acetic Acid (VIA) is an acceptable, affordable, and safe alternative method in developing countries. This process is relatively cheap and quick since it doesn't need any expensive tools and the results are able to be seen with the naked eye. The results are still determined manually by colposcopy which means that there's still a possibility of a misdiagnosis. Integrating an artificial intelligence (AI) that specializes in image classification using Convolutional Neural Network (CNN) into screening processes could offer faster and more accurate results to improve early detection and outcomes. The built model successfully identifies relevant visual patterns in cervical images, providing reliable predictions in classifying positive VIA and negative VIA cervicals. The proposed image classification model is proven to be effective in automatically detecting cervical cancer. Which shows the great potential of applying artificial intelligence technology in assisting the medical screening process.