International Journal of Electrical and Computer Engineering (IJECE) Vol. 8, No. 6, December 2018, pp. 5415~5424 ISSN: 2088-8708, DOI: 10.11591/ijece.v8i6.pp5415-5424  5415 Journal homepage: http://iaescore.com/journals/index.php/IJECE Improving Hierarchical Decision Approach for Single Image Classification of Pap Smear Dwiza Riana 1 , Yudi Ramdhani 2 , Rizki Tri Prasetio 3 , Achmad Nizar Hidayanto 4 1 STMIK Nusa Mandiri, Indonesia 2,3 Universitas BSI, Indonesia 4 Universitas Indonesia, Indonesia Article Info ABSTRACT Article history: Received Mar 28, 2018 Revised Jul 27, 2018 Accepted Aug 7, 2018 The single image classification of Pap smears is an important part of the early detection of cervical cancer through Pap smear tests. Unfortunately, most classification processes still require accuracy enhancement, especially to complete the classification in seven classes and to get a qualified classification process. In addition, attempts to improve the single image classification of Pap smears were performed to be able to distinguish normal and abnormal cells. This study proposes a better approach by providing different handling of the initial data preparation process in the form of the distribution for training data and testing data so that it resulted in a new model of Hierarchial Decision Approach (HDA) which has the higher learning rate and momentum values in the proposed new model. This study evaluated 20 different features in hierarchical decision approach model based on Neural Network (NN) and genetic algorithm method for single image classification of Pap smear which resulted in classification experiment using value learning rate of 0.3 and momentum of 0.2 and value of learning rate of 0.5 and momentum of 0.5 by generating classification of 7 classes (Normal Intermediate, Normal Colummar, Mild (Light) Dyplasia, Moderate Dyplasia, Servere Dyplasia and Carcinoma In Situ) better. The accuracy value enhancemenet were also influenced by the application of Genetic Algorithm to feature selection. Thus, from the results of model testing, it can be concluded that the Hierarchical Decision Approach (HDA) method for Pap Smear image classification can be used as a reference for initial screening process to analyze Pap Smear image classification. Keyword: Cervical cancer Genetic algorithm Hierarchical Decision Approach (HAD) Neural Network (NN) Pap smear Copyright © 2018 Institute of Advanced Engineering and Science. All rights reserved. Corresponding Author: Dwiza Riana, STMIK Nusa Mandiri Jakarta, Jalan Damai no 8 Jakarta Selatan, Indonesia. Email: dwiza@nusamandiri.ac.id 1. INTRODUCTION Research on the classification of single Pap smear image has been done. This attempt was intended to digitize the introduction of early detection of cervical cancer. As known that one type of malignant cancer that attacks women according to WHO body with the massive number of patients in Indonesia is cervical cancer. It is no wonder that Indonesia became one of the countries that have a lot of cervical cancer patients. Cervical cancer is generally caused by a virus called Human Papilloma Virus (HPV). Sexual intercourse became the largest case of HPV [1]. Pap smear is a method of early detection of cervical cancer. The process applied on Pap smear continuously and consistently in a country will help prevent early cervical cancer. This method was performed by a Pathologist in a clinical pathology laboratory, in which tests were performed on a woman's squamous epithelium. The results of pathologist's examination with a Pap smear will show whether the