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All Journal Jurnal Pengabdian Masyarakat Ilmu Terapan (JPMIT) Polygon: Jurnal Ilmu Komputer dan Ilmu Pengetahuan Alam
Aswani Aswani
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Agriculture, Biological Sciences & Forestry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering

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PENDAMPINGAN OPTIMALISASI LAYANAN KELURAHAN ABELI KOTA KENDARI Muh. Kabil Djafar; Asrul Sani; Wayan Somayasa; Andi Tenriawaru; Ruslan Ruslan; Herdi Budiman; Aswani Aswani
Jurnal Pengabdian Masyarakat Ilmu Terapan Vol 4, No 2 (2022)
Publisher : Vokasi Universitas Halu Oleo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33772/jpmit.v4i2.28482

Abstract

Pelaksanaan program kegiatan Pengabdian kepada Masyarakat Terintegrasi Kuliah Kerja Nyata–Tematik bertujuan untuk meningkatkan optimalisasi layanan masyarakat, dengan memanfaatkan  sumberdaya yang tersedia pada Kelurahan Abeli. Metode pelaksanaan kegiatan ini dengan cara   memberikan pendampingan pembuatan Sistem Informasi Kelurahan, pendampingan  penguatan literasi dan numerasi di sekolah, pendampingan sosialisasi Pola Hidup Bersih dan Sehat, dan pendataan kasus stunting. Hasil dari kegiatan PkM terintegrasi KKN-Tematik adalah mitra dalam hal ini Kelurahan Abeli telah memiliki Sistem Informasi Kelurahan berbasis web, terjadi peningkatan motivasi siswa dalam literasi dan numerasi melalui belajar bersama dan berbagai permainan, dan diperolehnya data awal kasus stunting di sekolah.  
Implementasi Algoritma Miller-Rabin untuk Pengujian Bilangan Prima Menggunakan Python Sufri Adiyatno; Muhammad Sadno; Aswani Aswani; Arga Wiradarma; Rifa’atus Shalihah
Polygon : Jurnal Ilmu Komputer dan Ilmu Pengetahuan Alam Vol. 4 No. 4 (2026): Juli : Polygon : Jurnal Ilmu Komputer dan Ilmu Pengetahuan Alam
Publisher : Asosiasi Riset Ilmu Matematika dan Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62383/polygon.v4i4.1050

Abstract

Prime numbers play a crucial role in modern cryptography, necessitating fast and accurate primality-testing methods. The Miller-Rabin algorithm is an efficient probabilistic method; however, the literature discussing its practical implementation and empirical evaluation remains limited. This study aimed to implement the Miller-Rabin algorithm using Python and evaluate its classification accuracy and execution time. This implementative research tested prime and composite numbers of sizes 32, 64, 128, 256, and 512 bits. The algorithm was implemented using Python's built-in pow() function for efficient modular exponentiation. The experimental results demonstrated that the implemented Miller–Rabin algorithm correctly identified all prime numbers as probably prime and all composite numbers as composite in all test cases. Furthermore, the computational time evaluation revealed that the execution time was directly proportional to the bit length of the numbers and the number of testing iterations. This execution time remains highly efficient for numbers of up to 512 bits. The implications of this research highlight that the Python implementation of Miller-Rabin is highly effective, serving as an excellent educational medium and a foundational tool for developing systems requiring large prime number testing.
Co-Authors Arga Wiradarma Asrul Sani Budiman, Herdi Muhammad Kabil Djafar Muhammad Sadno Nurwijayanti Rifa’atus Shalihah Ruslan Ruslan Sufri Adiyatno Wayan Somayasa