IMPLEMENT MARKOV CHAIN ANALYSIS AND CONFUSION MATRIX FOR ASSESSING KEY PERFORMANCE INDICATORS IN HEAVY EQUIPMENT MAINTENANCE

dc.contributor.authorNugroho, Aloysius Adi
dc.contributor.author.Baskoro, Gembong
dc.contributor.authorBudiarto, Eka
dc.date.accessioned2026-05-21T03:02:24Z
dc.date.issued2025-08-29
dc.description.abstractCurrently, the coal business is still vibrant, making the role of heavy equipment in coal mining operations crucial. Effective maintenance of heavy equipment is essential to maintain its performance. Equipment breakdowns and component failures can lead to significant losses and impact mining operations. To address this issue, this study focuseds on implement markov chain analysis and confusion matrix for assesing key performance indication in heavy eauipment maintenance Every year target of production of coal increase . This increasing production will challange for performance of Plant’s KPI to support this conditions . Plant using Balance Scorecard to manage all KPI Plant under one sheet monthly report performance . This Balance Scorecard compare monthly KPI performance to yearly target performance . This calculation method make two state condition . An achieve target of Plant KPI and An unachieve target of Plant KPI .Using Markov chain can be modeling history of KPI performance visualy probability of change between any state of conditions . This model can be develop four state condition to increase sensitivity of change of state . The four state conditions of markov chain can make plant more spesific and more accurate to take action base on this state condition. To measure effektiveness of action on every state condition in this thesis use confution matrix . This confution matrix also can measured capability of history KPI to get the target . This confusion matrix can revisi yearly KPI target for drive any improvement in KPI performance . if the KPI target not challange plant will not aware to improve more effektive and more efficient than before . This confusion matrix can help Plant Div to measure accuracy and precision of planning phase in the future . Base on Markov chain situation model . Plant can make Task recommendation and Action recommendation of in four state of condition . This Task and Action can be measured They’s effectiveness with confution matrix result .This new process of problem solving method are Situation Task Action Result ( STAR ) . STAR method was not develop to change current Problem Identification Correction Action ( PICA ) Method . STAR will substite the PICA to more completed and spesific . Because STAR method can integrated to current Balance Scorecard of KPI.
dc.identifier.urihttps://dspace-repository.sgu.ac.id/handle/123456789/163
dc.language.isoen
dc.publisherSwiss German University
dc.subjectCoal Mining
dc.subjectHeavy Equipment
dc.subjectKey Performance Indicator
dc.subjectBalance Scorecard
dc.subjectMarkov chain
dc.subjectConfusion matrix Four state condition of Markov
dc.subjectSetting New Target of KPI
dc.subjectCondition Monitoring of KPI
dc.subjectTASK recommendation . ACTION Recommendation
dc.subjectSituation Task Action Result method
dc.titleIMPLEMENT MARKOV CHAIN ANALYSIS AND CONFUSION MATRIX FOR ASSESSING KEY PERFORMANCE INDICATORS IN HEAVY EQUIPMENT MAINTENANCE
dc.typeThesis

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