Article Per Year (5 Year)
p-Index From 2021 - 2026
3.249
P-Index
This Author published in this journals
All Journal Religious: Jurnal Studi Agama-Agama dan Lintas Budaya Islamika Inside: Jurnal Keislaman dan Humaniora Tasfiyah 'Anil Islam: Jurnal Kebudayaan dan Ilmu Keislaman Nizham Journal of Islamic Studies Open Access Indonesia Journal of Social Sciences Jurnal Ilmiah Ar-Risalah: Media Ke-Islaman, Pendidikan, dan Hukum Islam Khalifa: Journal of Islamic Education Open Access Indonesia Journal of Social Sciences Nabawi: Journal of Hadith Studies JURNAL ELEKTRO DAN INFORMATIKA SWADHARMA (JEIS) Rausyan Fikr: Jurnal Ilmu Studi Ushuluddin dan Filsafat Akademika : Jurnal Pemikiran Islam Millah: Journal of Religious Studies Islamika Inside: Jurnal Keislaman dan Humaniora International Journal of Islamic Studies Higher Education Jurnal Sejarah Peradaban Islam Sriwijaya Journal of Forensic and Medicolegal Journal of Health Innovation and Environmental Education Tapis : Jurnal Penelitian Ilmiah
Faiz, Muhammad
UIN Kiai Haji Achmad Siddiq
Religion Arts Humanities Biochemistry, Genetics & Molecular Biology Computer Science & IT Economics, Econometrics & Finance Education Environmental Science Health Professions Immunology & microbiology Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Medicine & Pharmacology Public Health Social Sciences Other

Published : 21 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 21 Documents
Search

 1   2   3 
EFISIENSI MEMORI DAN WAKTU: ARRAY SORTING ALGORITHM VS ALGORTIMA PENGURUTAN TRADISIONAL MENGGUNAKAN PYTHON Muhammad Zaki Musyaffa; Karunia Raharjo; Muhammad Faiz; Satriaji Ammarulloh; Imam Prayogo Pujiono
JEIS: Jurnal Elektro dan Informatika Swadharma Vol 5, No 2 (2025): JEIS EDISI JULI 2025
Publisher : Institut Teknologi dan Bisnis Swadharma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56486/jeis.vol5no2.785

Abstract

The development of information technology has transformed data storage from physical to digital formats. However, digital data is difficult to access and verify without an effective sorting mechanism in place. This study compares the memory usage efficiency and execution time of the array sorting algorithm with two traditional sorting algorithms, bubble sort and quick sort, using a quantitative comparative method, all implemented in Python. Experiments were conducted on random numerical data sets of 100, 1.000, and 10.000 elements. Results show that the Array Sorting Algorithm excels in computational speed, with average times of 231.500, 352.500, and 1.214.150 nanoseconds for each data scale. However, it requires slightly larger memory (2.320 – 84.304 bytes). In contrast, Bubble Sort is the slowest but most memory-efficient, while Quick Sort is intermediate in both aspects. On the other hand, the Array Sorting Algorithm recorded relatively higher memory usage compared to the traditional sorting algorithms, Bubble Sort and Quick Sort. Based on these findings, algorithm selection should be based on the primary need. The Array Sorting Algorithm can be used when execution speed is a priority, and Bubble Sort is suitable for environments with memory constraints and small datasets. At the same time, Quick Sort offers a balance between speed and memory usage efficiency.Perkembangan teknologi informasi telah mentransformasi penyimpanan data dari format fisik ke digital. Namun, tanpa mekanisme pengurutan yang efektif, data digital sulit diakses dan diverifikasi. Penelitian ini membandingkan efisiensi penggunaan memori dan waktu eksekusi Array Sorting Algorithm dengan dua  algoritma pengurutan tradisional, Bubble Sort dan Quick Sort menggunakan metode komparatif kuantitatif., semuanya diimplementasikan dalam bahasa Phyton. Eksperimen dilakukan pada kumpulan data numerik acak berukuran 100, 1.000, dan 10.000 elemen. Hasil menunjukkan bahwa Array Sorting Algorithm unggul dalam kecepatan komputasi dengan rata-rata waktu 231.500, 352.500, dan 1.214.150 nanodetik untuk masing-masing skala data, namun memerlukan memori sedikit lebih besar (2.320 – 84.304 byte), sedangkan Bubble Sort paling lambat namun paling hemat memori, dan Quick Sort menengah di kedua aspek. Di sisi lain, Array Sorting Algorithm mencatatkan pemakaian memori yang relatif lebih tinggi dibanding algoritma pengurutan tradisional Bubble Sort dan Quick Sort. Berdasarkan hasil dari temuan ini pemilihan algoritma harus didasarkan pada kebutuhan utama, Array Sorting Algorithm bisa digunakan saat kecepatan eksekusi menjadi prioritas, Bubble Sort cocok untuk lingkungan dengan keterbatasan memori dan dataset berukuran kecil, sedangkan Quick Sort menawarkan keseimbangan antara kecepatan dan efisiensi penggunaan memori
Co-Authors Ahmad Fajar Shodik Antomi, Antomi Atalia, Laura Ayesh Mahmood Burhanuddin Burhanuddin Chairina Chairina Dalil, Fitriyeni Dzulkifli Hadi Imawan Eduardo Michael Perez Erizal, Arif Hendra Fadila Putri, Sarah Firdaus, Achmadana Syachrizal Muziburrochman Gina Romadhona Hasbi Sen Iftilah Dian Humayroh Imam Muhsin Imam Prayogo Pujiono Islahuddin, Islahuddin Iting Shofwati Jamaludin, Fitah Karunia Raharjo Luqman Al Hakim Luqman Al Hakim Luqman Al Hakim Luqmanul Hakim Mahillah Muhammad Masruri, Muhammad Muhammad Numan Muhammad Zaki Musyaffa Nelwati, Sasmi Putri Ratricia Ryzar, Iqfa Amella Sa'ad, Aslam Safri, Edi Saputra, Edriagus Satriaji Ammarulloh Syaifudin Syukri, Teddy Rahardian Taufiq, Abdul Rahman Theresia Putri Sinaga Vera Yuli Andini Zaenol Abidin