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All Journal JURTEKSI Jurnal Ilmu Komputer dan Sistem Informasi Cosmic Jurnal Teknik
Selina, Natria
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Automotive Engineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Library & Information Science

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Penggunaan Algoritma Komputasi untuk Analisis Sederhana Data DNA dalam Studi Bioinformatika Nur Rizky, Ishlahiyah; Prahasti, Rosa; Selina, Natria; Barus, Rizky
Jurnal Ilmu Komputer dan Sistem Informasi Vol. 4 No. 1 (2025): Januari 2025
Publisher : LKP Unity Academy

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70340/jirsi.v4i1.163

Abstract

Advances in computational technology and bioinformatics have enabled efficient and accurate DNA (Deoxyribo Nucleic Acid) data analysis. This study explores computational algorithm utilization for simple DNA data analysis in bioinformatics. We implemented basic algorithms (sequence sequence, pattern matching, clustering) using Python and Biopython library to analyze 500 DNA sequence samples from various model organisms. Results show computational algorithms accelerate analysis by 70% compared to manual methods, achieving 95% accuracy in identifying sequence patterns and structural similarities. Performance analysis reveals dynamic programming-based sequence sequence has O(mn) time complexity, while hierarchical clustering requires O(n²) computational time. This study highlights optimization needs for large-scale Dataset s and parameter adjustments for specific cases. Computational algorithms prove effective in supporting simple DNA data analysis, paving the way for developing complex bioinformatics tools.
Desain Cover Buku dengan Teknik Overlap Menggunakan Canva selina, Natria; Dini, Juan
Cosmic Jurnal Teknik Vol 1 No 1 (2024): Februari
Publisher : Ali Institute or Research and Publication

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This research investigates the potential of overlap techniques in book cover design using the online graphic design platform, Canva. The focus of this research lies in exploring the visual and aesthetic creativity that can be produced through the use of overlap techniques. Book covers are an important element in attracting readers' attention and reflecting the contents of the book. The overlap technique, with the use of overlapping visual elements, can be an effective strategy for creating attractive and informative cover designs. This research aims to explore the potential of overlap techniques in book cover design using the Canva platform. This research uses qualitative methods with case studies on fiction and non-fiction book cover designs. Data was collected through analysis of existing cover designs and interviews with graphic designers. The research results show that the overlap technique can produce attractive and informative cover designs. This technique allows designers to display various visual elements that are relevant to the book's content, creating dynamic and eye-catching compositions. This research also found that using the Canva platform can help designers, even without in-depth graphic design skills, to produce professional and attractive cover designs using the overlapping technique. Book cover design is also a critical aspect that can attract the attention of potential readers and reflect the essence of the book's contents. The overlapping technique in book cover designs using Canva can give an interesting and dynamic visual impression. By utilizing Canva's special features, book cover designs can be produced easily and effectively. Keywords: book cover design, overlap technique, Canva, graphic design, visual communication
STUDENT ACADEMIC ACHIEVEMENT CLUSTERING USING FUZZY C-MEANS ALGORITHM Selina, Natria; Sriani, Sriani
JURTEKSI (jurnal Teknologi dan Sistem Informasi) Vol. 12 No. 2 (2026): Maret 2026
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat (LPPM) STMIK Royal Kisaran

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33330/jurteksi.v12i2.4427

Abstract

Abstract: Academic achievement mapping is an important process in higher education to support effective academic monitoring and guidance. In practice, student grouping is often conducted manually by academic staff using simple criteria such as Grade Point Average (GPA) thresholds and subjective judgment, without systematic data analysis. This study aims to apply the Fuzzy C-Means (FCM) clustering algorithm to objectively group students based on their academic achievement levels. The dataset consists of academic records from 179 sixth-semester students of the Computer Science Study Program at Universitas Islam Negeri Sumatera Utara, where 160 eligible students are processed in the FCM calculation. Three variables are used: cumulative GPA, total completed credits, and the total number of low grades (D/E). The FCM algorithm automatically performs the mapping and groups students into three categories, namely excellent, stable, and at-risk students. Cluster quality is evaluated using the Silhouette Score and Davies–Bouldin Index, showing satisfactory clustering performance. The results indicate that the proposed approach provides a data-driven and objective basis for academic decision support. Keywords: academic achievement; clustering; fuzzy c-means; student Abstrak: Pemetaan pencapaian akademik mahasiswa merupakan proses penting dalam pendidikan tinggi untuk mendukung pemantauan dan pembinaan akademik yang tepat sasaran. Dalam praktiknya, pengelompokan mahasiswa masih sering dilakukan secara manual oleh pihak akademik berdasarkan kriteria sederhana, seperti batasan Indeks Prestasi Kumulatif (IPK) dan penilaian subjektif, tanpa analisis data yang sistematis. Penelitian ini bertujuan menerapkan algoritma Fuzzy C-Means (FCM) untuk mengelompokkan mahasiswa secara objektif berdasarkan tingkat pencapaian akademik. Data penelitian berasal dari 179 mahasiswa semester enam Program Studi Ilmu Komputer Universitas Islam Negeri Sumatera Utara, dengan 160 mahasiswa memenuhi kriteria dan diproses menggunakan algoritma FCM. Variabel yang digunakan meliputi IPK kumulatif, jumlah SKS yang telah ditempuh, dan total nilai rendah (D/E). Proses pemetaan sepenuhnya dilakukan oleh algoritma FCM dan menghasilkan tiga kategori mahasiswa, yaitu unggul, stabil, dan berisiko. Evaluasi menggunakan Silhouette Score dan Davies–Bouldin Index menunjukkan kualitas pengelompokan yang cukup baik. Kata kunci: fuzzy c-means; clustering; mahasiswa; pencapaian akademik
Co-Authors Barus, Rizky Dini, Juan Nur Rizky, Ishlahiyah Prahasti, Rosa