COMPARISON OF THE COMPLEXITY OF SEARCH ALGORITHMS IN DIGITAL PAPUAN LANGUAGE DICTIONARIES
DOI:
https://doi.org/10.33480/jitk.v11i4.5948Keywords:
Algorithm Complexity, Digital Dictionary, Low-Resource Languages, Tourism 4.0, Tree-Based SearchAbstract
Regional-language digital dictionaries play a strategic role in supporting Tourism 4.0 by enabling communication between local communities and tourists. However, inefficient search mechanisms can substantially degrade their usability, while research on the computational complexity of search algorithms for low-resource languages such as those of Papua remains scarce. This study presents a comparative analysis of three search algorithms binary search, tree-based search, and n-gram search benchmarked against an unoptimized linear search baseline in a Papuan regional-language digital dictionary containing 5,597 lemmas. Each algorithm was evaluated on both time and space complexity through controlled experiments executed on five heterogeneous computing devices. The experimental results show that the tree-based search algorithm achieves the best overall performance, with the lowest average search time of 1.28 seconds and the smallest average memory usage of 3.73 kB. These findings provide an empirical basis for selecting efficient search algorithms in regional-language digital dictionaries and contribute to the Tourism 4.0 digital infrastructure by enabling fast, scalable access to local-language information.
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[1] N. F. Hasan, A. Aisyah, R. Rahman, and H. Wonda, “Sentiment Analysis of Public Opinion Regarding Papuan Local Languages Condition Using Data Science Approach,” Digit. Zo. J. Teknol. Inf. dan Komun., vol. 13, no. 2 SE-Articles, pp. 125–139, Nov. 2022, doi: 10.31849/digitalzone.v13i2.11545.
[2] J. Kusuma, “Revolusi industri 4.0 memperkuat keberagaman bahasa daerah,” no. 1, pp. 103–106, 2022, [Online]. Available: http://sinarbahtera.kemdikbud.go.id/index.php/SB/article/view/88
[3] A. F. Aji et al., “One Country, 700+ Languages: NLP Challenges for Underrepresented Languages and Dialects in Indonesia,” in Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (ACL 2022), Dublin, Ireland: Association for Computational Linguistics, pp. 7226–7249. doi: 10.18653/v1/2022.acl-long.500.
[4] J. Mothe, “Shaping the Future of Endangered and Low-Resource Languages—Our Role in the Age of LLMs: A Keynote at ECIR 2024,” arXiv Prepr., vol. 58, no. 1, pp. 1–13, 2024.
[5] G. B. Dalkiran, “The Effects of Industry 4.0 Components on the Tourism Sector,” 2022, pp. 235–250. doi: 10.1007/978-981-16-5644-6_14.
[6] A. Jariah, “Implementasi Literasi Digital Dalam Peningkatan Daya Tarik Wisata Di Era New Normal Kota Palangka Raya,” J. Hadratul Madaniyah, vol. 8, no. 1, pp. 74–87, 2021, doi: 10.33084/jhm.v8i1.2441.
[7] V. Rodrigues, Z. Breda, and C. Rodrigues, “The Implications of Industry 4.0 for The Tourism Sector: A systematic literature review,” Heliyon, vol. 10, no. 1, 2024, doi: 10.1016/j.heliyon.2024.e31590.
[8] W. Wu, C. Xu, M. Zhao, X. Li, and R. Law, “Digital Tourism and Smart Development: State-of-the-Art Review,” Sustainability, vol. 16, no. 23, pp. 1–19, 2024, doi: 10.3390/su162310382.
[9] A. K. Sharma and R. Sharma, “Smart tourism in the digital age: overcoming barriers and unlocking,” Rev. Gestão, vol. 32, no. 3, pp. 224–237, 2025, doi: 10.1108/REGE-02-2025-0030.
[10] K. Kasmawati, B. Kadir, A. Agussalim, R. Renold, F. Firmansyah, and M. Antasari, “The Use of Digital Library for Tourism Promotion Through Tourism Object Transliteration into Katakana and Lontara Letter,” Pusaka J. Tour. Hosp. Travel Bus. Event, vol. 5, no. 1, pp. 11–19, 2023, doi: 10.33649/pusaka.v5i1.190.
[11] N. F. Hasan and M. S. A. Iribaram, “Digitizing the Papuan Regional Language Dictionary using the Rapid Application Development Method,” MATRIK J. Manajemen, Tek. Inform. dan Rekayasa Komput., vol. 21, no. 3, pp. 710–720, 2022, doi: 10.30812/matrik.v21i3.1688.
[12] Y. M. Mantri, “Digitalisasi Bahasa Daerah Sebagai Upaya Meningkatkan Ketahanan Budaya Daerah,” Textura J., vol. 2, no. 2, pp. 67–83, 2021, [Online]. Available: http://journal.piksi.ac.id/index.php/TEXTURA
[13] S. Phalke, Y. Vaidya, and S. Metkar, “Big-O Time Complexity Analysis Of Algorithm,” in 2022 International Conference on Signal and Information Processing (IConSIP), 2022, pp. 1–5. doi: 10.1109/ICoNSIP49665.2022.10007469.
[14] F. A. Mala and R. Ali, “The Big-O of Mathematics and Computer Science,” J. Appl. Math. Comput., vol. 6, no. 1, pp. 1–3, 2022, doi: 10.26855/jamc.2022.03.001.
[15] J. Singh, “Computational Complexity and Analysis of Supervised Machine Learning Algorithms BT - Next Generation of Internet of Things,” R. Kumar, P. K. Pattnaik, and J. M. R. S. Tavares, Eds., Singapore: Springer Nature Singapore, 2023, pp. 195–206.
[16] R. D. A. Aviantika, K. Kustanto, and M. Hasbi, “Pencarian Data Barang Produk Atribut Sekolah Menggunakan Algoritma Binary Search,” J. Teknol. Inf. dan Komun., vol. 9, no. 1, pp. 75–80, 2021, doi: 10.30646/tikomsin.v9i1.546.
[17] N. Arifin, F. Fauziah, and N. Nurhayati, “Kombinasi Algoritma Sequential Searching dan Bubble Sort Pada Manajemen Laboratorium,” J. Sains Komput. Inform., vol. 6, no. 1, pp. 294–306, 2022, [Online]. Available: http://www.tunasbangsa.ac.id/ejurnal/index.php/jsakti/article/view/445
[18] W. S. Wahyuni, S. Andryana, and B. Rahman, “Penggunaan Algoritma Sequential Searching Pada Aplikasi Perpustakaan Berbasis Web,” J. Ilm. Penelit. dan Pembelajaran Inform., vol. 07, no. 02, pp. 294–302, 2022, [Online]. Available: https://www.jurnal.stkippgritulungagung.ac.id/index.php/jipi/article/view/2646
[19] Z. Zhang, “Computational Technologies for Construction of Business Korean Translation Corpus Based on Association Rules Mining,” ACM Trans. Asian Low-Resource Lang. Inf. Process., 2023, doi: 10.1145/3603500.
[20] I. Arapakis, S. Park, and M. Pielot, “Impact of Response Latency on User Behaviour in Mobile Web Search,” in Proceedings of the 2021 Conference on Human Information Interaction and Retrieval (CHIIR ’21), Canberra, Australia: ACM, pp. 279–283. doi: 10.1145/3406522.3446038.
[21] V. J. Reddi et al., “MLPerf Mobile Inference Benchmark,” in Proceedings ofthe 5th Machine Learning and Systems (MLSys) Conference, Santa Clara, CA, USA: Cornell University, 2022, pp. 1–18. doi: https://doi.org/10.48550/arXiv.2012.02328.
[22] N. Q. Dhaneswara, K. Nasution, and T. Haramaini, “Perancangan Aplikasi Kamus Digital Bahasa Minang dengan Menggunakan Metode String Matching Knuth Morris Praat,” J. Minfo Polgan, vol. 10, no. 1, pp. 1–7, 2021, doi: 10.33395/jmp.v10i1.11018.
[23] R. Rismayani, N. Sambo Layuk, S. Wahyuni, H. Wali, and N. K. Marselina, “Pencarian Kata Pada Aplikasi Kamus Istilah Komputer dan Informatika Menggunakan Algoritma Brute Force Berbasis Android,” Komputika J. Sist. Komput., vol. 10, no. 1, pp. 43–52, 2021, doi: 10.34010/komputika.v10i1.3644.
[24] Y. Rahmanto, J. Alfian, D. Damayanti, and R. I. Borman, “Penerapan Algoritma Sequential Search pada Aplikasi Kamus Bahasa Ilmiah Tumbuhan,” J. Buana Inform., vol. 12, no. 1, pp. 21–30, 2021, [Online]. Available: https://ojs.uajy.ac.id/index.php/jbi/article/view/4367
[25] D. J. Zalukhu, P. Karo-karo, and N. M. Faizah, “Perancangan Aplikasi Kamus Bahasa Daerah Nias Berbasis Android dengan Metode Rapid Application Development (RAD) Menggunakan Android Studio,” Comput. J., vol. 1, no. 1, pp. 9–14, 2023, doi: 10.58477/cj.v1i1.30.
[26] R. Y. Darmawantoro, Y. R. W. Utami, and K. Kustanto, “Implementasi Binary Search Untuk Data Obat di Apotek,” J. Teknol. Inf. dan Komun., vol. 10, no. 1, 2022, doi: 10.30646/tikomsin.v10i1.607.
[27] R. Rismayani, N. Sambo Layuk, S. Wahyuni, H. Wali, and N. K. Marselina, “Pencarian Kata Pada Aplikasi Kamus Istilah Komputer dan Informatika Menggunakan Algoritma Brute Force Berbasis Android,” Komputika J. Sist. Komput., vol. 10, no. 1, pp. 43–52, 2021, doi: 10.34010/komputika.v10i1.3644.
[28] N. Purnama, “Comparative Performance Study of Search Algorithms on Large-Scale Data Structures,” J. Ilmu Pengetah. dan Teknol. Komput., vol. 11, no. 1, pp. 99–109, 2025, doi: 10.33480/jitk.v11i1.
[29] N. R. Feta and F. Fitria, “Implementation of Concolic Unit Testing in Testing Binary Search Algorithm Using Jcute,” JITK (Jurnal Ilmu Pengetah. dan Teknol. Komputer), vol. 7, no. 2, pp. 37–44, 2022, doi: 10.33480/jitk.v7i2.2758.
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