Mapping log data activity using heuristic miner algorithm in manufacture and logistics company

Abstract

Strategies for the procurement of goods and services are essential for companies in Indonesia's manufacturing and logistics sectors. The solution to reducing the existing problem is to make a mapping plan, such as verifying documents from each department, so that it takes a long time, resulting in many issues, such as procedural misuse findings. Heuristics miner algorithms get data to form logs that consist of goods and services procurement activities. Processing log data into XML data (data extraction), which produces a dependency model and business and casual matrix (discovery process), then determines the value of fitness and precision (suitability) called the conformity checking phase process. This phase aims to produce a new business (process enhancement phase), which will create a solution to the risk of delay and procedural abuse. The results of each of these processes rank each stage of the procurement of goods and services sequentially and together to provide time-efficient and accurate decisions, resulting in project implementation comparable to the company's business strategy. Implement the heuristics miner algorithm using the Python programming language.