International Journal on Information and Communication Technology (IJoICT) 2021-06-25T15:23:10+07:00 SOCPress Noreply Open Journal Systems <p align="justify">International Journal on Information and Communication Technology (IJoICT) is a peer-reviewed journal in the field of computing that published twice a year; scheduled in December and June.</p> <p align="justify">IJoICT includes novel ideas on ICT, state of the art technique implementations, and study cases on developing countries. Each article is featured with details of the proposed method including dataset and external link for program or codes. The journal is published for those who wish to share information about their research and innovations and for those who want to know the latest results in the field of Information and Communication Technology (ICT).&nbsp;&nbsp;The Journal is published by the <a href="" target="_blank" rel="noopener">School of Computing</a>, Telkom University, Bandung, Indonesia. Accepted paper will be immediately available online (open access) without any publication fee.</p> Safety Requirements Analysis using Misuse Cases Method 2021-06-18T10:42:20+07:00 Ryo Alif Ramadhan Dana Sulistyo Kusumo Jati Hiliamsyah Husen <p>Safety requirements analysis is an activity inside software requirements engineering that focuses on finding and solving safety gaps inside a software product. One method to do safety requirements analysis is misuse cases, a technique adopted from the security analysis method. Misuse cases provide a safety analysis approach which allows detailed steps from different stakeholders' perspective. In this research, we evaluate the misuse cases method's understandability by implementing it to analyze safety requirements for an electric car's autopilot system. We assessed the developed models using the walkthrough method. We found differences between how the model understood from someone with experience in software development and those who don't.</p> 2021-06-17T16:33:32+07:00 Copyright (c) 2021 Ryo Alif Ramadhan, Dana Sulistyo Kusumo, Jati Hiliamsyah Husen Classification of Dengue Hemorrhagic Fever (DHF) Spread in Bandung Regency using Hybrid Naïve Bayes, K-Nearest Neighbor, and Artificial Neural Network Methods 2021-06-25T15:23:10+07:00 Fatri Nurul Inayah <p>Dengue fever is a dangerous disease caused by the dengue virus. One of the factors causing dengue fever is due to the place where you live in the tropics, so that cases of dengue fever in Indonesia, especially in the Bandung Regency area, will continue to show high numbers. Therefore, information is needed on the spread of this disease by requiring the accuracy and speed of diagnosis as early prevention. In terms of compiling this information, classification techniques can be done using a combination of methods Naïve Bayes, K-Nearest Neighbor(KNN), and Artificial Neural Network(ANN) to build predictions of the classification of dengue fever, and the data used in this Final Project are dataset affected by the spread of dengue fever in Bandung regency in the 2012-2018 period. The hybrid classifier results can improve accuracy with the voting method with an accuracy level of 90% in the classification of dengue fever.</p> 2021-06-25T15:08:58+07:00 Copyright (c) 2021 Fatri Nurul Inayah