PARALLEL PROCESS DISCOVERY USING A NEW TIME-BASED ALPHA++ MINER

PARALLEL PROCESS DISCOVERY USING A NEW TIME-BASED ALPHA++ MINER

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A lot of services in business processes lead information systems to build huge amounts of event logs that are difficult to observe.The event log will be analysed using a process discovery technique to mine the process model by Dryer Filter Spigot implementing some well-known algorithms such as deterministic algorithms and heuristic algorithms.All of the algorithms have their own benefits and limitations in analysing and discovering the event log into process models.This research proposed a new Time-based Alpha++ Miner with an improvement of the Alpha++ Miner and Modified Time-based Alpha Miner algorithm.

The proposed miner is able to consider noise traces, loop, and non-free choice when modelling a process model where both of original algorithms cannot override those issues.A new Time-based Alpha++ Miner utilizing Time Interval Pattern can mine the process model using new rules defined by the time interval pattern using a double-time stamp event log and define sequence and parallel (AND, OR, and XOR) relation.The original miners are only able to discover sequence and parallel (AND and XOR) relation.To know the differences between the original Alpha++ Miner and the new one including the process model and its relations, the evaluation using fitness and precision was done in this research.

The results presented that the process model obtained by a new Time-based Alpha++ Miner was better than that of the original Alpha++ Miner algorithm in terms of parallel OR, handling noise, fitness value, and precision value.ABSTRAK: Banyak sistem perniagaan perkhidmatan menghasilkan sejumlah besar log data maklumat yang payah dipantau.Log data ini akan dianalisis menggunakan teknik proses penemuan bagi memperoleh model proses dengan menerapkan beberapa algoritma terkenal, seperti algoritma deterministik dan algoritma heuristik.Semua algoritma ini memiliki kehebatan dan kekurangannya dalam menganalisis dan mencari log data ke dalam model proses.

Kajian ini mencadangkan Time-based Alpha++ Miner baru yang merupakan pembaharuan dari algoritma Alpha++ Miner dan Modified Time-based Alpha Miner.Algoritma baru ini dapat mempertimbangkan kesan bunyi, pusingan, dan pilihan tidak bebas ketika memodelkan model proses di mana kedua algoritma asal tidak dapat menggantikan isu tersebut.Time-based Alpha++ Miner baru mengguna pakai Pola Interval Waktu berjaya memperoleh model proses menggunakan peraturan baru berdasarkan Pola Interval Waktu menggunakan log peristiwa waktu-ganda dan menentukan jujukan dan hubungan selari (AND, OR, dan XOR).Dibandingkan algoritma asal, ia hanya dapat menemukan jujukan dan hubungan selari Handbags (AND dan XOR).

Bagi membezakan Alpha++ Miner asal dan yang baru termasuk model proses dan kaitannya, penilaian menggunakan nilai padanan dan penelitian telah dijalankan dalam kajian ini.Hasil kajian model proses yang diperoleh oleh Time-based Alpha++ Miner baru, adalah lebih baik keputusannya berbanding menggunakan algoritma Alpha++ Miner asal, berdasarkan hubungan selari OR, bunyi kawalan, nilai padanan, dan nilai penelitian.