BIOS : Jurnal Teknologi Informasi dan Rekayasa Komputer

Pengembangan Media Pembelajaran Berbasis Smart Apps Creator pada Mata Pelajaran Informatika Kelas X SMK Negeri 2 Tulungagung

2024-11-06T07:31:39+07:00

This research focuses on improving the quality of teaching through the use of varied learning media at SMK Negeri 2 Tulungagung, which implements the Independent Curriculum. Even though technology such as projectors are available, the use of learning media is still dominated by printed books, which has an impact on the decline in students' interest in learning. The problem in learning Informatics at SMKN 2 Tulungagung is the lack of interactive learning media that is technology-based, especially in Computer Network and Internet materials. This research develops technology-based learning media using the Smart Apps Creator Application to increase interactivity and visualization. This study uses the Research & Development (R&D) method with the ADDIE (Analysis, Design, Development, Implementation, and Evaluation) model with the test subjects being students, lecturers as validators of media experts, and teachers as validators of material experts. Data collection instruments include interviews, observations, and questionnaires. The results of media validity obtained a score of 89.5% with the "Very Feasible" criterion and the validity of the material obtained a score of 89.2% with the "Very Feasible" criterion. The small group trial received a score of 76% with the "Feasible" criterion, while the large group trial obtained a result of 84.17% with the "Very Feasible" category. This AR media has proven to be effective in increasing students' understanding and motivation despite several technical obstacles.

Analisis Kualitas Website e-RKAM Menggunakan Metode WebQual 4.0

2024-11-06T07:44:06+07:00

Technological developments in the field of education have encouraged the implementation of the e-RKAM application to facilitate the preparation and reporting of School Operational Assistance funds digitally in madrasas. However, there are still some technical obstacles such as servers that often go down, errors in some menus, and delays in producing the latest report output (update), which has a significant impact on the quality of application services. This study aims to analyze the quality of the e-RKAM website using the WebQual 4.0 method, which includes three variables: usability quality, information quality, and service interaction quality, as well as its influence on user satisfaction. The results of the analysis showed that these variables together contributed 44.7% to user satisfaction, while the remaining 55.3% was influenced by other factors outside this study. The T-test showed that only the quality of information had a significant influence on user satisfaction (sig. value 0.000), while the quality of usability and the quality-of-service interaction had no significant effect (sig. values of 0.066 and 0.844, respectively). These findings highlight that the model used has not been fully comprehensive in explaining the variation in user satisfaction, so more research is needed to explore additional factors that may have an effect.

Analisis Sentimen Program Jaminan Kesehatan Nasional Menggunakan Multiclass Support Vector Machine

2024-11-17T10:15:49+07:00

Optimizing the implementation on National Helath Insurance which requires the use of BPJS participant cards in various public services is one of the government policies that is widely discussed and has garnered many opinions in the community. Public opinion is expressed through social media, one of which is through Twitter. The aim of this research is to classify public opinion regarding the new regulations of the National Health Insurance Program as a form of government policy to implement Presidential Instruction Number 1 of 2022 using Twitter data. Public opinion as many as 1.179 tweets were labeled positive, negative and neutral sentiments, then TD-IDF wighting was carried out and analyzed using the multiclass SVM algorithm with the One Against All approach. The results of the analysis showed that Multiclass SVM with a linear kernel was able to classify with an accuracy level of 81% where the classification pf positive sentiment was17 (7.6%), negative sentiment was 115 (48.7%) and neutral sentiment are 104 (44.1%). This shows that public sentiment is dominated by negative sentiment or disagreement with the new regulations of the National Health Insurance Program.