Analisis Trend dan Pemetaan Penelitian Mahasiswa Teknik Informatika Menggunakan Graph Convolutional Network - Tifani Intan Solihati; Rudianto Rudianto; Raden Kania (JATISI (Jurnal Teknik Informatika dan Sistem Informasi), 2023)
So far, the thesis has been compiled (during the guidance process), defended (tested in the thesis session) and revised and validated by the Advisor, Examiner, Head of Study Program, and the Dean, then collected in the library and afterwards can be used again by other students who need information the. The purpose of carrying out this research is to find student research trends and discover lecturer expertise based on the results of the work. After finding trends and expertise, the Faculty will be able to make the right decisions in determining the topic/field/study to be determined and selecting supervisors and examiners according to the scientific field and experience of the lecturer. As for the stages of the research that we will carry out, the first pre-processing stage is we conduct data providers to collect student thesis data collected in Informatics Engineering. Both learning algorithms The next stage is structured data in training data ready to be used in learning algorithms with GCN to produce candidate models and deploy selected models. Applications are the stages of applying the golden model to the testing data we have at the beginning and measuring the accuracy of the golden model. that the research trend of Informatics Engineering students is more in the field of science/the topic domain of mathematics and statistics and computer architecture. The mapping of the topic domain is 182 and 101 So far, the thesis has been compiled (during the guidance process), defended (tested in the thesis session) and revised and validated by the Advisor, Examiner, Head of Study Program, and the Dean, then collected in the library and afterwards can be used again by other students who need information the. The purpose of carrying out this research is to find student research trends and discover lecturer expertise based on the results of the work. After finding trends and expertise, the Faculty will be able to make the right decisions in determining the topic/field/study to be determined and selecting supervisors and examiners according to the scientific field and experience of the lecturer. As for the stages of the research that we will carry out, the first pre-processing stage is we conduct data providers to collect student thesis data collected in Informatics Engineering. Both learning algorithms The next stage is structured data in training data ready to be used in learning algorithms with GCN to produce candidate models and deploy selected models. Applications are the stages of applying the golden model to the testing data we have at the beginning and measuring the accuracy of the golden model. that the research trend of Informatics Engineering students is more in the field of science/the topic domain of mathematics and statistics and computer architecture. The mapping of the topic domain is 182 and 101 titles respectively. The accuracy of the GCN model determines the target class of 68.25%.