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All Journal Neptunus: Jurnal Ilmu Komputer dan Teknologi Informasi Prosiding Seminar Nasional Ilmu Teknik Journal of Golden Generation Multidisciplinary Jurnal Publikasi Ilmu Komputer dan Multimedia
Tengku Syahvina Rival Dini
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Perancangan Sistem Informasi Manajemen Aplikasi Pendaftaran Rekening Bank Baru Nasabah Tengku Syahvina Rival Dini; Puji Sri Alhirani; Mhd.Furqan
Neptunus: Jurnal Ilmu Komputer Dan Teknologi Informasi Vol. 3 No. 2 (2025): Mei: Neptunus: Jurnal Ilmu Komputer Dan Teknologi Informasi
Publisher : Asosiasi Riset Teknik Elektro dan Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61132/neptunus.v3i2.743

Abstract

This research was designed using Unified Modeling Language (UML) as a tool for visualizing system requirements. The system designed is expected to improve efficiency, accuracy and speed of service, thereby providing a better experience for customers and making it easier for Bank Sumut officers to manage registration data. The system development method used is waterfall. The research results show that the designed information system can automate various manual processes such as collecting prospective customer data, document validation, and managing account data. It is hoped that this management information system can be used to provide an overview of the applications that will be created to increase the Bank's operational productivity and minimize the potential for administrative errors, as well as supporting the digital transformation of Bank North Sumatra in facing competition in the banking sector.
APLIKASI WEB UNTUK ANALISIS SEKUENS FASTA BERBASIS PYTHON Pebi Mina Husania; Tengku Syahvina Rival Dini; Rani Chantika; Puji Sri Alhirani
Journal of Golden Generation Multidisciplinary Vol. 2 No. 1 (2026): Februari 2026 : Journal of Golden Generation Multidisciplinary
Publisher : PT. Lembaga Penerbit Penelitian Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.65244/jggm.v2i1.363

Abstract

Perkembangan teknologi sekuensing telah menghasilkan data sekuens DNA, RNA, dan protein dalam jumlah besar yang umumnya disimpan dalam format FASTA. Meskipun format ini sederhana dan banyak digunakan, perangkat lunak bioinformatika yang tersedia masih didominasi oleh aplikasi berbasis desktop atau command line interface yang kurang ramah bagi pengguna pemula. Penelitian ini bertujuan untuk mengembangkan aplikasi web sederhana berbasis Python untuk analisis dasar file FASTA. Aplikasi dibangun menggunakan framework Flask dan pustaka BioPython untuk melakukan analisis panjang sekuens, komposisi basa nukleotida, serta persentase GC melalui antarmuka web yang mudah digunakan. Metode pengembangan sistem yang digunakan adalah model Waterfall, meliputi analisis kebutuhan, perancangan, implementasi, dan pengujian. Hasil pengujian menunjukkan bahwa aplikasi mampu memproses file FASTA secara akurat dan cepat tanpa memerlukan instalasi perangkat lunak tambahan di sisi pengguna. Aplikasi ini diharapkan dapat menjadi media pembelajaran bioinformatika serta mendukung analisis awal sekuens biologis bagi mahasiswa dan peneliti.
Model Machine Learning untuk Klasifikasi Loyalitas Pelanggan Menggunakan Random Forest Tengku Syahvina Rival Dini; Rani Chantika; Pebi Mina Husania; Puji Sri Alhirani
Prosiding Seminar Nasional Ilmu Teknik Vol. 2 No. 2 (2025): Desember: Prosiding Seminar Nasional Ilmu Teknik
Publisher : Asosiasi Riset Ilmu Teknik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61132/prosemnasproit.v2i2.202

Abstract

This research develops a machine learning model to classify customer loyalty using the Random Forest algorithm. Customer churn is a critical issue that reduces revenue and increases acquisition costs. A dataset of 50,000 customers from global e-commerce and subscription platforms was processed through data cleaning, imputation, outlier handling, and class balancing with SMOTE. The Random Forest model was built as a baseline and optimized with hyperparameter tuning. Evaluation using accuracy, precision, recall, and F1-score shows that the optimized model achieved 90.81% accuracy and 83.87% F1-score, outperforming previous Naïve Bayes approaches. Feature importance analysis highlights customer service interactions, lifetime value, and demographic factors as key predictors of churn. These findings demonstrate Random Forest’s effectiveness in churn prediction and provide practical insights for customer retention strategies
Penerapan Python dalam Perbandingan Metode Deteksi Tepi (Sobel, Prewitt, Canny) untuk Analisis Pengenalan Pola pada Gambar Daun Tengku Syahvina Rival Dini; Lailan Sofinah Harahap; Pebi Mina Husania
Jurnal Publikasi Ilmu Komputer dan Multimedia Vol. 4 No. 2 (2025): Mei: Jurnal Publikasi Ilmu Komputer dan Multimedia
Publisher : Pusat Riset dan Inovasi Nasional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/jupikom.v4i2.4062

Abstract

Digital image processing plays an important role in extracting visual information from natural objects, including the morphological structure of leaves. One of the crucial techniques in this process is edge detection, which is used to emphasize object boundaries and support pattern analysis. This study aims to compare three edge detection methods, namely Sobel, Prewitt, and Canny in recognizing patterns in leaf images using the Python programming language and the OpenCV library. The methods used include quantitative experiments by implementing the three edge detection techniques on grayscale leaf images, followed by visual result analysis based on the criteria of edge sharpness, morphological detail, noise, and computational efficiency. The results show that the Canny method produces the most accurate and clean edge detection, with the ability to capture small details and reduce noise significantly. Sobel shows quite good performance in highlighting the main structure of the leaf, while Prewitt produces simpler and less precise results. Based on the evaluation results, the Canny method is considered the most effective for the purposes of digital leaf pattern classification and analysis. This study provides an important contribution in selecting the optimal edge detection method for computer vision applications in the field of digital botany..
Dampak Warna dan Tipografi terhadap Kenyamanan Pengguna dalam Desain Antarmuka Digital Rani Chantika; Pebi Mina Husania; Tengku Syahvina Rival Dini; Silfia Rahmadani Sitorus; Puji Sri Alhirani; M. Khalil Gibran
Jurnal Publikasi Ilmu Komputer dan Multimedia Vol. 4 No. 2 (2025): Mei: Jurnal Publikasi Ilmu Komputer dan Multimedia
Publisher : Pusat Riset dan Inovasi Nasional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/jupikom.v4i2.4073

Abstract

Digital interface design plays a vital role in user interaction with software, especially through visual elements such as color and typography. This study was motivated by the need to understand how these visual elements affect user comfort while interacting with an application or website. The purpose of this study was to analyze user perceptions of the use of color and typography, and their impact on visual comfort. The method used was a descriptive quantitative approach by distributing online questionnaires to 20 respondents from various age groups. The collected data were analyzed descriptively by comparing preferences and comfort based on the age of the respondents. The results showed that the majority of respondents felt that color and typography greatly influenced the comfort of using digital interfaces. Dark background colors and sans-serif fonts with proportional sizes proved to be the most preferred choices because they provided reading comfort and reduced eye fatigue. A balanced combination of color and typography was also considered important to improve readability and the overall user experience. In conclusion, the selection and use of appropriate visual elements contribute greatly to creating a friendly and comfortable interface design for users of various age ranges.
Co-Authors Lailan Sofinah Harahap M. Khalil Gibran Mhd.Furqan Pebi Mina Husania Puji Sri Alhirani Rani Chantika Silfia Rahmadani Sitorus