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All Journal Jusikom: Jurnal Sistem Informasi Ilmu Komputer Jurnal Komtekinfo
Wirahmadayanti, Isna
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Computer Science & IT Decision Sciences, Operations Research & Management

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IMPLEMENTATION OF DATA MINING ROUGHT SET IN ANALYZING LECTURER PERFORMANCE Hadiyanto, Tegas; Sari, Fitri Permata; Budiarti, Lela; Syahputra, Afriadi; Wirahmadayanti, Isna
Jurnal Sistem Informasi dan Ilmu Komputer Vol. 7 No. 2 (2024): JUSIKOM: JURNAL SISTEM INFROMASI ILMU KOMPUTER
Publisher : Fakultas Teknologi dan Ilmu Komputer Universitas Prima Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34012/jurnalsisteminformasidanilmukomputer.v7i2.4842

Abstract

Lecturers are professional educators or scientists with the main task of transforming, developing, and disseminating science, technology, and art through education, research, and community service by the Tridharma of Higher Education. The main task of lecturers is to implement the tri dharma of higher education with the scope of activities in the form of teaching, research, and community service. Based on this, the Payakumbuh College of Technology assesses lecturers' performance to maintain the educational institution's quality. A method is needed to identify the quality of lecturers' performance. Lecturer performance can be determined using a rough set approach with several stages. Rough set is a data mining technique applied in several fields, including selecting study programs and predicting mobile phone sales income. Based on the results of using the rough set method, lecturer performance information is produced in a certain period, which aims to help leaders understand the possible performance of lecturers in a certain period. The benefit that can be obtained is that the knowledge obtained through the rough set method can determine the possibility of achieving lecturer performance.
Technology Readiness Index untuk Menganalisis Kesiapan Adopsi Teknologi Kecerdasan Buatan Mahasiswa Komputer Wirahmadayanti, Isna; Yuhandri, Y; Sumijan, S
Jurnal KomtekInfo Vol. 12 No. 1 (2025): Komtekinfo
Publisher : Universitas Putra Indonesia YPTK Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35134/komtekinfo.v12i1.584

Abstract

The education sector combined with the branch of artificial intelligence has great potential to change the way information is accessed and managed to improve the learning experience and support decision making in the educational process. It is important to understand the level of readiness for the adoption of artificial intelligence among students as the main stakeholders in the educational environment. The purpose of this study was to determine the readiness for adoption of technology, and what factors influence the readiness for adoption of artificial intelligence in Computer Science Students at Universitas Putra Indonesia "YPTK" Padang. This study uses the Technology Readiness Index (TRI) method which consists of four variables, including the variables of optimism, innovativeness, discomfort, and insecurity. The Technology Readiness Index (TRI) measures a person's tendency to accept and use technology to complete goals in their home life or at work. This study was conducted by distributing questionnaires to 348 students consisting of students of information systems and informatics engineering study programs. Data were obtained from a total population of 2689 students, 348 samples were obtained based on the Slovin formula with an error margin of 5%. Determination of the sample to determine the number of samples of each stratum in the population with proportionate stratified random sampling in the Information Systems study program of as many as 250 students and the Informatics Engineering study program of 98 students. Manual calculations and using applications show that computer students at Universitas Putra Indonesia “YPTK” Padang are very ready to adopt artificial intelligence technology with variable values ​​of optimism 93.27%, innovative 92.64%, discomfort 91.66%, and insecurity 88.73%. These results can be stated that the factors that influence the readiness to adopt artificial intelligence technology include optimism, innovative, discomfort, and insecurity with a median index value of all variables of 92.15%
Co-Authors Budiarti, Lela Fitri Permata Sari, Fitri Permata Hadiyanto, Tegas Sumijan, S Syahputra, Afriadi Yuhandri, Y