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All Journal JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Transaction on Informatics and Data Science
Hariyanto, Dikky Cahyo
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Computer Science & IT Decision Sciences, Operations Research & Management Education Engineering

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K-MEANS CLUSTERING DALAM PENGELOMPOKAN RELEVANSI PEKERJAAN S1 INFORMATIKA (STUDI KASUS JURUSAN TEKNIK INFORMATKA UMM MALANG) Hariyanto, Dikky Cahyo; Harini, Sri; Chamidy, Totok
JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Vol 9, No 2 (2024)
Publisher : STKIP PGRI Tulungagung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29100/jipi.v9i2.5507

Abstract

Perguruan tinggi merupakan salah satu tingkatan dalam menuntut ilmu diharapkan untuk menciptakan lulusan yang mampu dan berkompeten sesuai dengan bidang ilmu yang diambil. Banyaknya jumlah lulusan dari perguruan tinggi dengan jumlah lapangan pekerjaan yang aa menyebabkan banyaknya lulusan bekerja tidak sesuai dengan jurunnya, sehingga perlu adanya evaluasi akan tingkat keberhasilan capaian pembelajaran lulusan yang ada di perguruan tinggi. Tujuan dari penelitian ini adalah untuk menganalisa data relevansi pekerjaan para lulusan S1 Teknik Informatika dengan apa yang mereka pelajari sesuai dengan capaian pembelajaran yang ada di program studi Teknik Informatika Universitas Muhammadiyah Malang menggunakan K-Means clustering. Menggunakan data hasil kuisioner pengukuran capaian pembelajaran para lulusan dan pengukuran kesesuaian perkerjaan sebanyak 137 responden yang telah diuji validitas, reabilitas dan multikolinieritas, hasil penelitian ini menunjukkan dta dibentuk menjadi tiga cluster dengan analisa bahwa 29.92% lulusan Teknik Informatika UMM mampu memenuhi capaian pembelajaran lulusan dan mendapatkan pekerjaan yang relevan denga apa yang mereka pelajari, 49.63% lulusan lainnya juga mendapat pekerjaan yang relevan dengan jurusannya walaupun kurang menguasai keterampilan khusus yang diukur pada capaian pembelajara lulusan, dan 20.45% lulusan lainnya mendapatkan pekerjaan yang kurang relevan dengan bidang teknik Informatika.
K-Means Clustering in Relevance Grouping of Undergraduate Informatics Jobs: Case Study at the Informatics Engineering Department, Universitas Muhammadiyah Malang, Malang, Indonesia Hariyanto, Dikky Cahyo; Harini, Sri; Chamidy, Totok
Transactions on Informatics and Data Science Vol. 1 No. 1 (2024)
Publisher : Department of Informatics, Faculty of Da'wah, UIN Saizu Purwokerto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24090/tids.v1i1.12231

Abstract

Higher education is one of the levels of study expected to produce graduates competent in the field of knowledge taken. The large number of graduates from tertiary institutions with many job opportunities causes many graduates to work in ways that do not match their majors, so there is a need to evaluate the level of success of graduates learning achievements in tertiary institutions. This research aims to analyze data on the relevance of the work of undergraduate graduates in Informatics Engineering to what they have learned by the learning outcomes in the Informatics Engineering study program at the University of Muhammadiyah Malang using K-Means clustering. Using data from questionnaires measuring graduate learning outcomes and measuring job suitability for 137 respondents who had been tested for validity, reliability, and multicollinearity, the results of this research showed that the data was formed into three clusters with the analysis that 29.92% of UMM Informatics Engineering graduates were able to meet graduate learning outcomes and obtain jobs that are relevant to what they studied, 49.63% of other graduates also got jobs that were relevant to their major even though they lacked mastery of specific skills as measured by graduate learning outcomes, and 20.45% of other graduates got jobs that were less relevant to the field of Informatics engineering.
Co-Authors Sri Harini Totok Chamidy