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All Journal JURNAL TEKNIK INFORMATIKA DAN SISTEM INFORMASI JISA (Jurnal Informatika dan Sains)
Wibowo, Firmansyah Rekso
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Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering

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Comparative Analysis of Sorting Algorithms: TimSort Python and Classical Sorting Methods Wibowo, Firmansyah Rekso; Faisal, Muhammad
JISA(Jurnal Informatika dan Sains) Vol 7, No 1 (2024): JISA(Jurnal Informatika dan Sains)
Publisher : Universitas Trilogi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31326/jisa.v7i1.1785

Abstract

The sorted() function within the Python programming language has emerged as the primary choice among developers for sorting operations. Consequently, this study offers a comparative analysis of various classical sorting algorithms and Python's built-in sorting mechanisms, with the objective of identifying the most time-efficient sorting algorithm. The analysis involves assessing the time complexity of each algorithm while handling data arrays ranging from 10 to 1,000,000 elements using Python. These arrays are populated with randomly generated numeric values falling within the range of 1 to 1000. The benchmark algorithms utilized encompass Heap Sort, Shell Sort, Quick Sort, and Merge Sort. A looping mechanism is applied to each algorithm, and their execution speeds are gauged utilizing the Python 'time.perf_counter()' library. The findings of this study collectively indicate that Python's standard algorithm, surpasses classic sorting algorithms, including Heapsort, Shellsort, Quicksort, and Mergesort, in terms of execution.
Evaluasi dan Analisis Domain Shift Model NER pada Industri Game Berbahasa Indonesia Wibowo, Firmansyah Rekso; Abidin, Zainal; Kusumawati, Ririen
JATISI Vol 12 No 4 (2025): JATISI (Jurnal Teknik Informatika dan Sistem Informasi)
Publisher : Universitas Multi Data Palembang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35957/jatisi.v12i4.13591

Abstract

Indonesia’s gaming industry is rapidly expanding and produces extensive textual data from diverse sources such as news articles and social media. Named Entity Recognition (NER) models can extract valuable information from this data; however, general-purpose models remain suboptimal for the gaming domain due to its unique terminology. This study evaluates the impact of domain shift on the NERGrit model, a standard NER model from the IndoNLU benchmark, when applied to an Indonesian gaming text corpus. The model was tested on the gaming-domain corpus and compared with a domain-specific lexicon to identify error patterns through qualitative and quantitative analyses. Results show that although NERGrit can detect numerous entities, it often fails to classify them correctly. The dominance of the MISC category (61.8%) and recurring issues such as misclassification, entity boundary errors, and ambiguity between fictional and real entities indicate the model’s limitations. This study confirms the existence of domain adaptation challenges and introduces a new entity schema covering the categories GAME, PLATFORM, TECH, EVENT, CHAR,and COMPANY. The proposed schema provides a foundation for developing a more relevant NER dataset and model tailored to Indonesia’s gaming industry ecosystem.
Co-Authors Muhammad Faisal Ririen Kusumawati Zainal Abidin