No abstract

No abstract

The current public transportation system must improve the quality of its services so that they can go hand in hand with technological advancements. Transportation, as a supporter of economic progress and development of the country, is expected to be able to answer the high mobility of the community of transportation needs by utilising the expansion of existing technology. Tracking and monitoring bus locations as public transportation is now an important issue that needs attention, but there is no bus tracking system based on mobile that can provide real-time locations. The research aimed to design a wireless sensor network that automatically identified and provided accurate information about travel routes and the movement of public transport buses in real-time. By using Global Positioning Systems (GPS) as vehicle tracking systems and sensor that support, this application provided bus position information and the nearest bus route recommendations to users in real-time. Thus contributing to the time management of public transport users in their activities.

The quality of the feasibility of a mobile application can be measured by evaluating the usability using certain testing methods. The refore to improve the performance of mobile applications, it is necessary to measure the level of satisfaction and user acceptance of the application. This study aims to improve the quality of the Myelkomsel mobile application by measuring the level of satisfaction and acceptance of end-users and evaluating the relationship between the level of user satisfaction with user gender differences using the System Usability Scale (SUS) method. Data collection was carried out by distributing questionnaires to 46 Telkomsel provider users consisting of 22 male users and 24 female users. The results showed that the average SUS score was 71.96 for the whole user. According to the calculation of the level of user acceptance included in the category of Acceptable, the scale of the class level is included in category C, and the ranking is included in the good category. While the results of calculations from the SUS Percentile Rank Score show that the MyTelkomsel mobile application is in class C. There are no significant differences according to gender, the average SUS score of the male is 71.93, and female is 71.98 so that gender differences do not affect the level of satisfaction and acceptance application. It can be seen that the level of end-user satisfaction from the MyTelkomsel mobile application is good but still has possible problems with its use

Image processing technology is one of the technologies that can help facilitate and speed up human work, especially in the process of determining the grain size distribution of soil in a civil building plan. Its utilization has been widely used to study, analyze, and understand the structure and framework of the soil. Image analysis is carried out as an initial or fundamental step in image processing to discover and comprehend information. With so many image segmentation methods, it is necessary to conduct research to determine which method is best for sandy soil image segmentation based on one of the image segmentation quality criteria, namely gaussian image noise. By testing the watershed transform method and the Otsu thresholding method as two of the area-based methods that are considered suitable for segmenting sandy soil images before and after distorted Gaussian noise based on the calculation of the mean square error (MSE) value.The results showed that the watershed transform method is better for segmenting sandy soil images when compared to the Otsu thresholding method. This is indicated by the average squared error (mse) of 3.08 for the watershed transform method and 4.09 for the Otsu Thresholding method. In addition to the comparison of quality tests of sandy soil based on gaussian noise with standard deviation values of normal distribution and noise intensities of 10, 20, and 30, it proves that the watershed transform method is still better at segmenting noise-distorted sandy soil images than the Otsu thresholding method. However, in terms of processing time, the Otsu Thresholding method is faster or better than the Watershed Transform method. of the results or conclusions brief. There are no citations, tables or figures in abstract.