IMPLEMENTASI BUSINESS INTELLIGENCE UNTUK EVALUASI KINERJA EXCAVATOR OVERBURDEN PADA KUARTAL 3 TAHUN 2022 DI BLOK PARAPATAN UTARA PT BERAU COAL, KALIMANTAN TIMUR

SAPUTRA, BAGUS ADRIAN and Amin, Muhammad and Puspita, Mega (2024) IMPLEMENTASI BUSINESS INTELLIGENCE UNTUK EVALUASI KINERJA EXCAVATOR OVERBURDEN PADA KUARTAL 3 TAHUN 2022 DI BLOK PARAPATAN UTARA PT BERAU COAL, KALIMANTAN TIMUR. Undergraduate thesis, Sriwijaya University.

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Abstract

The industrial revolution 4.0 is guiding all industrial fields, including the mining industry. PT Berau Coal is one of the largest mining companies in Indonesia. PT Berau Coal's overburden budget plan in 2022 will increase by 347,581,617 bcm. With the increase in the overburden budget plan, it is necessary to control and evaluate the performance of the excavator. Evaluation of excavator performance is often carried out manually, that is, without using tools such as applications or software which can take longer to carry out the evaluation. Therefore, to evaluate excavator performance, implement business intelligence. Business Intelligence (BI) is a solution that meets the need to analyze existing problems and the results of this analysis can be used in the decision making process. In implementing Business Intelligence to evaluate excavator performance using the Business Intelligence Roadmap method which consists of 5 stages, namely justification, planning, business analysis, design and construction with the final result being a dashboard. Based on the dashboard results, the excavator performance evaluation results were obtained with PA, UA, MA, EU and Productivity values of 97%, 57%, 95%, 55% and 411 bcm/hour respectively. With total production of 1,668,442 bcm. With the total influence of Production Parameters (PA, UA, Productivity) on production respectively amounting to 98,713 bcm, 18,258 bcm, and 113,721 bcm. Total active working time is 4,055 hours, standby time is 3,112 hours and repair time is 225 hours. The three biggest working time constraints are No Job Plan, Wait Support, and Wait Operator with actual time of 145.32 hours, 139.45 hours, and 124.35 hours respectively. With the total effect of working time constraints on production respectively amounting to -17,075 bcm, -16,385 bcm, and -14,611 bcm.

Item Type:	Thesis (Undergraduate)
Uncontrolled Keywords:	Business Intelligence, Evaluasi Kinerja Excavator, Dashboard, Business Intelligence Roadmap
Subjects:	T Technology > TN Mining engineering. Metallurgy > TN275-325 Practical mining operations. Safety measures
Divisions:	03-Faculty of Engineering > 31201-Mining Engineering (S1)
Depositing User:	Bagus Adrian Saputra
Date Deposited:	25 Jan 2024 01:40
Last Modified:	25 Jan 2024 01:40
URI:	http://repository.unsri.ac.id/id/eprint/139606

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