PROCESS MINING DWELLING TIME PADA PELABUHAN PETI KEMAS MENGGUNAKAN METODE ALPHA MINER

FIRMANSYAH, RIVALNO (2022) PROCESS MINING DWELLING TIME PADA PELABUHAN PETI KEMAS MENGGUNAKAN METODE ALPHA MINER. S1 thesis, Universitas Mercu Buana Jakarta.

Preview	Text (HAL COVER) 01 Cover .pdf Download (555kB) | Preview
Preview	Text (ABSTRAK) Abstrak.pdf Download (201kB) | Preview
	Text (BAB I) 02 Bab 1.pdf Restricted to Registered users only Download (29kB)
	Text (BAB II) 03 Bab 2.pdf Restricted to Registered users only Download (362kB)
	Text (BAB III) 04 Bab 3.pdf Restricted to Registered users only Download (82kB)
	Text (BAB IV) 05 Bab 4.pdf Restricted to Registered users only Download (882kB)
	Text (BAB V) 06 Bab 5.pdf Restricted to Registered users only Download (16kB)
	Text (DAFTAR PUSTAKA) 07 Daftar Pustaka.pdf Restricted to Registered users only Download (84kB)
	Text (LAMPIRAN) 08 Lampiran.pdf Restricted to Registered users only Download (125kB)

Abstract

In recent years, the problem of measuring the dwelling time of container logistics processes at ports in developing countries is often a major problem. Therefore, process mining which is a sub-field of data science focuses on analyzing event log data generated during the execution of business processes. In process mining, a process is a sequence of events that are executed to achieve a specific goal or result. Event logs help an organization to find gaps between the designed business processes and the reality of the processes that occur. PM4PY is a tool that is built using the python programming language and is used in process mining. In this study, we will compare the container logistics business process based on existing parameters to find the fitness and structure values in the event log. Key words: Process Mining, Event log, PM4PY. Dalam beberapa tahun terakhir, masalah pengukuran dwelling time proses logistik peti kemas di pelabuhan pada negara berkembang seringkali menjadi masalah utama. Oleh karena itu, process mining yang merupakan sub bidang ilmu data berfokus pada analisis data event log yang dihasilkan selama pelaksanaan proses bisnis. Dalam process mining, proses merupakan urutan kejadian yang dijalankan untuk mencapai tujuan atau hasil tertentu. Event log membantu sebuah organisasi untuk menemukan kesenjangan antara proses bisnis yang dirancang dengan realita proses bisnis yang terjadi. PM4PY merupakan sebuah tools yang dibangun menggunakan bahasa pemrograman python dan digunakan dalam melakukan process mining. Dalam penelitian ini akan membandingkan proses bisnis logistik peti kemas berdasarkan parameter yang ada untuk mencari nilai fitness dan structure pada event log. Kata kunci: Event log, Process Mining, PM4PY.

Item Type:	Thesis (S1)
Call Number CD:	FIK/SI. 22 082
NIM/NIDN Creators:	41817010139
Uncontrolled Keywords:	Event log, Process Mining, PM4PY.
Subjects:	000 Computer Science, Information and General Works/Ilmu Komputer, Informasi, dan Karya Umum > 000. Computer Science, Information and General Works/Ilmu Komputer, Informasi, dan Karya Umum 000 Computer Science, Information and General Works/Ilmu Komputer, Informasi, dan Karya Umum > 000. Computer Science, Information and General Works/Ilmu Komputer, Informasi, dan Karya Umum > 000.01-000.09 Standard Subdivisions of Computer Science, Information and General Works/Subdivisi Standar Dari Ilmu Komputer, Informasi, dan Karya Umum 000 Computer Science, Information and General Works/Ilmu Komputer, Informasi, dan Karya Umum > 000. Computer Science, Information and General Works/Ilmu Komputer, Informasi, dan Karya Umum > 003 Systems/Sistem-sistem
Divisions:	Fakultas Ilmu Komputer > Sistem Informasi
Depositing User:	WADINDA ROSADI
Date Deposited:	03 Oct 2022 03:32
Last Modified:	03 Oct 2022 08:21
URI:	http://repository.mercubuana.ac.id/id/eprint/69816

Actions (login required)

View Item