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KOMPUTEK
Published by Universitas Muhammadiyah Ponorogo
ISSN : 26140985     EISSN : 26140977     DOI : -
Core Subject : Science, Engineering,
Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Mechanical Engineering
Jurnal Mahasiswa Teknik (Mesin, Elektro dan Informatika) Universitas Muhammadiyah Ponorogo ISSN : 2614-0985 (media cetak) ISSN : 2614-0977 (media online)
Arjuna Subject : -
Articles 213 Documents
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Pengembangan Aplikasi Web untuk Resize Citra Digital dengan Fitur Batch Processing Menggunakan Next.Js dan Sharp Waeisul Bismi; Muhammad Qomaruddin; Nila Hardi; Musriatun Napiah; Astrid Noviriandini
KOMPUTEK Vol. 10 No. 1 (2026): April
Publisher : Universitas Muhammadiyah Ponorogo

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Abstract

The exponential growth of digital content has increased the demand for efficient and accessible image processing tools. This research aims to develop a web-based image resize application with batch processing features using Next.js and Sharp. The research method employs Research and Development (R&D) with a Software Development Life Cycle (SDLC) approach using the Waterfall model, encompassing requirements analysis, system design, implementation, testing, deployment, and maintenance phases. The application was developed by integrating Next.js 16 framework for full-stack development, Sharp library for high-performance image processing, and JSZip for archive handling. Implemented features include flexible upload (file, folder, ZIP), downsampling and upsampling options, pixel dimension input, JPEG/JPG/PNG format conversion, and batch processing with progress monitoring. Testing results demonstrated that 100% of features were successfully implemented with a functional testing success rate of 100%. The average response time achieved 1.76 seconds per image, 41% faster than the 3-second target. The quality of the test results shows that the quality of the resized images meets very good quality standards with high structural similarity to the original images for both downsampling and upsampling. This research has produced a web application for image resizing that is accessible without installation, efficient for batch processing, and produces optimal output quality by utilizing the Mitchell interpolation kernel for downsampling and Lanczos for upsampling
Hubungan Pemahaman Digital Marketing dan E-Commerce terhadap Niat Adopsi Moniqca Sandha Iskandar
KOMPUTEK Vol. 10 No. 1 (2026): April
Publisher : Universitas Muhammadiyah Ponorogo

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Abstract

This study aims to analyze the relationship between digital marketing understanding and perceived benefits of e-commerce on the intention to adopt online selling among dried snack MSMEs in Cikampek District, Karawang Regency. Amid the increasing digitalization of MSMEs, some business actors have not yet optimized online sales. This research applies a quantitative approach using the Technology Acceptance Model (TAM) framework and involves 42 respondents through a 1–4 Likert scale questionnaire. The results indicate that all research instruments are valid and reliable. Descriptive analysis shows that the levels of digital marketing understanding, perceived benefits of e-commerce, and intention to adopt online selling are in the moderately high category. Spearman correlation analysis reveals a positive and moderate relationship between digital marketing understanding and adoption intention (r = 0.523), as well as between perceived benefits of e-commerce and adoption intention (r = 0.520). These findings suggest that improving digital literacy and understanding the benefits of e-commerce plays an important role in encouraging MSMEs to sustainably adopt online selling systems.
Analisis Sentimen Masyarakat terhadap Isu Redenominasi Rupiah pada Platform YouTube Menggunakan Algoritma Naïve Bayes Alfieny Putri Heriyanto; Nono Heryana; Apriade Voutama
KOMPUTEK Vol. 10 No. 1 (2026): April
Publisher : Universitas Muhammadiyah Ponorogo

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Abstract

Isu redenominasi rupiah merupakan salah satu topik ekonomi yang banyak dibahas oleh masyarakat dan menimbulkan berbagai opini di ruang publik. Perkembangan media sosial, khususnya YouTube, memungkinkan pengguna menyampaikan pandangan secara terbuka melalui kolom komentar. Penelitian ini bertujuan menganalisis sentimen publik terhadap isu redenominasi rupiah di YouTube menggunakan algoritma Naïve Bayes Classifier. Metode yang digunakan adalah Knowledge Discovery in Database (KDD) yang meliputi tahap data selection, preprocessing, transformasi, data mining, dan evaluasi. Pendekatan Inset Lexicon diterapkan untuk memberikan label sentimen berdasarkan kamus positif dan negatif, serta pelabelan manual yang divalidasi oleh ahli linguistik. Hasil penelitian menunjukkan bahwa kedua metode pelabelan didominasi sentimen positif. Pelabelan Inset Lexicon mengidentifikasi 2.157 data positif, 1.562 data negatif, dan 1.600 data netral. Sementara itu, pelabelan manual menghasilkan 2.784 data positif, 1.214 data negatif, dan 1.214 data netral. Hasil evaluasi menunjukkan bahwa pelabelan Inset Lexicon memiliki kinerja lebih baik dibandingkan pelabelan manual. Dengan penerapan SMOTE dan rasio pembagian data 90:10, model mencapai akurasi 69%, presisi 68%, dan recall 68%. Sebaliknya, pelabelan manual hanya mencapai akurasi 52%, presisi 33%, dan recall 33% dalam pengujian model.

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