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Heuristic Evaluation on Interface of Thesis Management Information System in Vocational Environment Thamrin, Thamrin; Ambiyar, Ambiyar; Simatupang, Wakhinuddin; Wahyudi, Rido
Jurnal Teknologi Informasi dan Pendidikan Vol. 16 No. 2 (2023): Jurnal Teknologi Informasi dan Pendidikan
Publisher : Universitas Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/jtip.v16i2.727

Abstract

In this study, we used Nielsen's heuristics to analyze the user interface of a thesis management information system in the vocational education environment. This system environment is designed to assist students in managing and organizing all processes related to thesis writing. The main framework in this study is Nielsen's heuristics, supplemented with experiments to evaluate the extent to which the user interface of the system meets user preferences (user-friendly). The population involved in this research consists of faculty members and students, with a sample size of 50 individuals. Analysis and discussion were conducted through the distribution of questionnaires to the participants. Based on the research findings, it was discovered that the Visibility of system status achieved a score of 163.5. Overall, this study concludes that the thesis management information system in the vocational education environment that we developed successfully achieves its main objective by having a user-friendly interface.
Analysis of Job Recommendations in Vocational Education Using the Intelligent Job Matching Model Farell, Geovanne; Zin Latt, Cho Nwe; Jalinus, Nizwardi; Yulastri, Asmar; Wahyudi, Rido
JOIV : International Journal on Informatics Visualization Vol 8, No 1 (2024)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/joiv.8.1.2201

Abstract

Vocational high schools are one of the educational stages impacted by Indonesia's low quality of education. Vocational High Schools play a crucial role in improving human resources. Graduates of Vocational High Schools can continue their education at universities or enter the workforce directly. Many students are found to have not yet considered their career path after graduation. At the same time, graduates are still expected to find mismatched employment with their expertise and skills. This research uses CRISP-DM, or Cross Industry Standard Process for Data Mining, to build machine learning models. The approach used is content-based filtering. This model recommends items similar to previously liked or selected items by the user. Item similarity can be calculated based on the features of the items being compared. After students receive job recommendations through intelligent job matching, they can use these recommendations as references when applying for jobs that align with their results. This process helps students direct their steps toward finding jobs that match their profiles, ultimately increasing their chances of success in the job market. These recommendations are crucial in guiding students toward career paths that align with their abilities and interests. The Intelligent Job Matching Model developed in this research provides recommendations for the job-matching process. This model benefits graduates by providing job recommendations aligned with their profiles and offers advantages to the job market. By implementing the Model of Intelligent Job Matching in the recruitment process, applicants with job qualifications can be matched effectively.