Glucofit: Evaluating Daily Sugar Consumption in Preventing Diabetes using SUS Method

Abstract

Diabetes Mellitus (DM) is a growing global health issue, particularly in Indonesia, with excessive sugar consumption identified as a major contributing factor. However, public awareness regarding daily sugar intake remains low, partly due to the complexity of interpreting nutritional information. To address this problem, this study proposes the development of an Android-based application aimed at monitoring daily sugar consumption and supporting diabetes prevention efforts. The application integrates both manual input and automated food detection to estimate sugar intake, along with a barcode scanner for retrieving product nutritional data. A calorie-based calculation method is applied to adjust individual sugar intake recommendations based on personal energy needs. The development follows the AGILE methodology. System functionality was evaluated through black-box testing, while usability was assessed using the System Usability Scale (SUS). The results demonstrated that the application functions reliably, with an average SUS score of 81.43, classified as “Excellent” and within the “Acceptable” range. These findings suggest that the application has a high level of usability and user acceptance, offering a promising tool for promoting healthy sugar consumption behavior and supporting preventive healthcare through digital monitoring.