Angkot drivers can compete with online transportation in getting passengers via smartphones. This application is based on a geographic information system, which is a system that can show the location of a person or place online, using this system to be integrated with public transportation makes it possible to add or pick up passengers more efficiently not only by waiting in one place but can pick up passengers according to the location of the passenger and the transportation route. To overcome the above problems, making applications with a technology theme is one of the right solutions for innovative methods that will be applied to public transportation drivers so they can get passengers efficiently. The purpose of this study is to determine the user's response to the application that has been developed. The research method used is research and development with a 4D development model with “define, design, development, and dissemination stages”. Data collection was carried out by distributing questionnaires to several respondents, while the trial stages carried out included alpha version trials, beta versions trials, Version Release, and Implementation. The results of the study show that the indicators of language, appearance, and accessibility of applications that have been developed are classified as "very feasible". The developed online angkot application is expected to be a solution in dealing with technological developments that can be applied to public transportation

Introduction: The student points system is an application for recording students' achievement and offense points. The lack of recording and dissemination of information on achievement results makes students less motivated to improve achievement, and the distribution of scholarships for outstanding students is inappropriate. To improve student achievement, an application program is needed that can record and disseminate student achievement data in real-time, accurate, and effective. So, the purpose in this study is to know and analyze the design of the student point system to improve student achievement using the clustering method. Method: Researchers use the Clustering Method in calculating data to determine the accuracy of scholarship distribution for outstanding students. Result: Clustering with the most achievement points is clustering 2 with 25,254 Achievement Points. The total number in the level 2 cluster is 1,797 which indicates the number is close to 2,000 or 2 which is the result of data transformation from the junior high level. Conclusion: The implication of clustering research on student point data is to provide useful information for the Foundation as an institution that houses schools in allocating scholarships for outstanding students. In this case, clustering 2 with the highest number of Achievement Points indicates that there is a group of students with high achievement points. By using the clustering results, the Foundation can allocate scholarships more effectively and efficiently, because it can identify outstanding students from various school levels more easily.