Pm4py: analisa performance dari xes - Revision history

Unknown user at 01:02, 30 March 2025

2025-03-30T01:02:52Z

← Older revision		Revision as of 01:02, 30 March 2025
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	from pm4py.objects.log.importer.xes import importer as xes_importer		from pm4py.objects.log.importer.xes import importer as xes_importer
	from pm4py.algo.discovery.performance_spectrum import algorithm as performance_spectrum		from pm4py.algo.discovery.performance_spectrum import algorithm as performance_spectrum
	from pm4py.~~algo.discovery~~.performance_spectrum import visualizer as performance_spectrum_visualizer		from pm4py.visualization.performance_spectrum import visualizer as performance_spectrum_visualizer
	from pm4py.algo.filtering.log.attributes import attributes_filter		from pm4py.algo.filtering.log.attributes import attributes_filter

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	# 3. Menerapkan algoritma performance spectrum		# 3. Menerapkan algoritma performance spectrum
	ps = performance_spectrum.apply(log, list_activities)		parameters = {performance_spectrum.Parameters.TIMESTAMP_KEY: 'Complete Timestamp'}
			ps = performance_spectrum.apply(log, list_activities, parameters=parameters)
			# ps = performance_spectrum.apply(log, list_activities)

	# 4. Memvisualisasikan hasil performance spectrum		# 4. Memvisualisasikan hasil performance spectrum
	gviz = performance_spectrum_visualizer.apply(ps)		gviz = performance_spectrum_visualizer.apply(ps)
	performance_spectrum_visualizer.view(gviz)		performance_spectrum_visualizer.view(gviz)



	==Penjelasan:==		==Penjelasan:==

Unknown user at 00:51, 30 March 2025

2025-03-30T00:51:58Z

← Older revision		Revision as of 00:51, 30 March 2025
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	import pm4py		import pm4py
	from pm4py.objects.log.importer.xes import ~~factory~~ as xes_importer		from pm4py.objects.log.importer.xes import importer as xes_importer
	from pm4py.algo.~~performance~~.~~spectrum~~ import algorithm as performance_spectrum		from pm4py.algo.discovery.performance_spectrum import algorithm as performance_spectrum
			from pm4py.algo.discovery.performance_spectrum import visualizer as performance_spectrum_visualizer
			from pm4py.algo.filtering.log.attributes import attributes_filter

	# 1. ~~Load~~ XES ~~event log~~		# 1. Memuat log peristiwa dari file XES
	log = xes_importer.apply("Production.xes")		log = xes_importer.apply("Production.xes")

	# 2. ~~Apply performance spectrum algorithm~~		# 2. Mengidentifikasi aktivitas unik dalam log
	~~spectrum~~ = ~~performance_spectrum~~.~~apply~~(log)		activities = attributes_filter.get_attribute_values(log, "concept:name")
			list_activities = list(activities.keys())

	# 3. ~~Tampilkan hasil awal~~		# 3. Menerapkan algoritma performance spectrum
	~~print~~(spectrum.~~head~~())		ps = performance_spectrum.apply(log, list_activities)

			# 4. Memvisualisasikan hasil performance spectrum
			gviz = performance_spectrum_visualizer.apply(ps)
			performance_spectrum_visualizer.view(gviz)

Unknown user at 00:25, 30 March 2025

2025-03-30T00:25:21Z

← Older revision		Revision as of 00:25, 30 March 2025
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	Berikut contoh '''source code Python''' untuk melakukan '''analisis performa (performance analysis)''' atau deteksi '''congestion''' (kemacetan/bottleneck) menggunakan library `pm4py` pada file `.xes` yang telah kamu lampirkan (`Production.xes`):		Berikut contoh '''source code Python''' untuk melakukan '''analisis performa (performance analysis)''' atau deteksi '''congestion''' (kemacetan/bottleneck) menggunakan library `pm4py` pada file `.xes` yang telah kamu lampirkan (`Production.xes`):

			# Pertama, pastikan pm4py terinstal:
			# !pip install pm4py

	import pm4py		import pm4py
	from pm4py.objects.log.importer.xes import ~~importer~~ as xes_importer		from pm4py.objects.log.importer.xes import factory as xes_importer
	from pm4py.algo.performance.spectrum import algorithm as performance_spectrum		from pm4py.algo.performance.spectrum import algorithm as performance_spectrum
	~~from pm4py.visualization.performance_spectrum import visualizer as spectrum_visualizer~~

	# 1. ~~Import~~ log ~~dari file XES~~		# 1. Load XES event log
	log = xes_importer.apply("Production.xes")		log = xes_importer.apply("Production.xes")

	# 2. ~~Analisis~~ performance spectrum ~~(melihat delay antar aktivitas)~~		# 2. Apply performance spectrum algorithm
	spectrum = performance_spectrum.apply(log)		spectrum = performance_spectrum.apply(log)

	# 3. ~~Visualisasi spectrum dalam bentuk chart~~		# 3. Tampilkan hasil awal
	~~gviz = spectrum_visualizer.apply~~(spectrum)		print(spectrum.head())
	~~spectrum_visualizer~~.~~view~~(~~gviz~~)

	==Penjelasan:==		==Penjelasan:==

Unknown user: Created page with "Berikut contoh '''source code Python''' untuk melakukan '''analisis performa (performance analysis)''' atau deteksi '''congestion''' (kemacetan/bottleneck) menggunakan library..."

2025-03-30T00:22:08Z

Created page with "Berikut contoh '''source code Python''' untuk melakukan '''analisis performa (performance analysis)''' atau deteksi '''congestion''' (kemacetan/bottleneck) menggunakan library..."

New page

Berikut contoh '''source code Python''' untuk melakukan '''analisis performa (performance analysis)''' atau deteksi '''congestion''' (kemacetan/bottleneck) menggunakan library `pm4py` pada file `.xes` yang telah kamu lampirkan (`Production.xes`):

import pm4py
from pm4py.objects.log.importer.xes import importer as xes_importer
from pm4py.algo.performance.spectrum import algorithm as performance_spectrum
from pm4py.visualization.performance_spectrum import visualizer as spectrum_visualizer

# 1. Import log dari file XES
log = xes_importer.apply("Production.xes")

# 2. Analisis performance spectrum (melihat delay antar aktivitas)
spectrum = performance_spectrum.apply(log)

# 3. Visualisasi spectrum dalam bentuk chart
gviz = spectrum_visualizer.apply(spectrum)
spectrum_visualizer.view(gviz)

==Penjelasan:==
* '''`performance_spectrum.apply(log)`''': Menghitung waktu antar aktivitas, mendeteksi bottleneck atau kemacetan proses.
* '''`spectrum_visualizer.view()`''': Menampilkan visualisasi interaktif (biasanya dalam bentuk histogram atau heatmap) yang menunjukkan waktu yang dihabiskan antara transisi aktivitas.

Kalau kamu ingin menganalisis '''performance berdasarkan start time, end time, atau throughput''', kamu juga bisa gunakan ini:

from pm4py.algo.performance.summarization.pandas import algorithm as performance_summarizer

df = pm4py.convert_to_dataframe(log)
summary = performance_summarizer.apply(df, parameters={"timestamp_key": "time:timestamp"})
print(summary)