PENERAPAN TEKNIK DATA MINING DALAM PREDIKSI MASA TUNGGU MAHASISWA MENGGUNAKAN METODE KLASIFIKASI

ALFARUQ, IQBAL MALIK and Tania, Ken Ditha (2022) PENERAPAN TEKNIK DATA MINING DALAM PREDIKSI MASA TUNGGU MAHASISWA MENGGUNAKAN METODE KLASIFIKASI. Undergraduate thesis, Sriwijaya University.

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Abstract

Unemployment is one of the crucial problems faced by Indonesia. Moreover, unemployment for Bachelor and Diploma graduates, which has a large number every year. Based on official data published by the Indonesian Central Bureau of Statistics (CBS), it is recorded that open unemployment for Bachelor and Diploma graduates from 2019 to 2021 has not reached less than 9 hundred thousand people. From this data, the waiting period dataset after graduating from 2019 to 2021 was used which was obtained by the Sriwijaya University Career Development Center (CDC Unsri) with a Tracer Study activity that conducted questionnaires on alumni of Sriwijaya University. This study uses the Cross Industry Standard Process for Data Mining (CRISP-DM) method because it has stages used for data mining, each stage has its own function but is related to the others. The stages are in the form of business understanding phase, data understanding phase, data preparation phase, modeling phase, evaluation phase, and deployment phase. Based on this study, it was found that the variables that had a relationship with the waiting period were years of study, English language skills, analytical skills, leadership, and writing documents. Then the algorithm used is Random Forest because it has advantages in producing good classification results, can process large data and provides results that are less scattered but more innovative. And producing combined training data for 2021, 2020 & 2019 has an accuracy of 78.17% and a standard deviation of 1.85% which of course meets the criteria of no more than 2%.

Item Type:	Thesis (Undergraduate)
Uncontrolled Keywords:	Data Mining, Klasifikasi, Masa Tunggu, CRISP-DM
Subjects:	Q Science > QA Mathematics > QA75-76.95 Calculating machines > QA76.9.D343 Data mining. Database searching. Big data.
Divisions:	09-Faculty of Computer Science > 57201-Information Systems (S1)
Depositing User:	Iqbal Malik Alfaruq
Date Deposited:	24 Jan 2023 07:08
Last Modified:	24 Jan 2023 07:08
URI:	http://repository.unsri.ac.id/id/eprint/87374

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