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All Journal Jurnal Komputer Teknologi Informasi Sistem Komputer (JUKTISI)
Nicky Dwi Kurnia
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Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Engineering

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Analisis Sentimen Multi-Kelas untuk Menilai Kepuasan Mahasiswa terhadap Aplikasi Manajemen Akademik Berbasis Web di Lingkungan Perguruan Tinggi Nicky Dwi Kurnia; Kholifah, Binti; Nur Ani, Febi Warta; Nafii’, Ayu Fernanda Nurun
Jurnal Komputer Teknologi Informasi Sistem Komputer (JUKTISI) Vol. 4 No. 1 (2025): Juni 2025
Publisher : LKP KARYA PRIMA KURSUS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62712/juktisi.v4i1.363

Abstract

Abstrak Penelitian ini bertujuan untuk menganalisis sentimen multi-kelas guna menilai tingkat kepuasan mahasiswa terhadap penggunaan aplikasi manajemen akademik berbasis web di lingkungan perguruan tinggi. Dengan menggunakan metode pemrosesan bahasa alami (Natural Language Processing, NLP) dan algoritma machine learning seperti Random Forest, Support Vector Machine (SVM), dan Neural Network, penelitian ini mengklasifikasikan komentar mahasiswa ke dalam beberapa kelas sentimen: positif, netral, dan negatif. Data dikumpulkan melalui survei online dan ulasan aplikasi yang tersedia selama semester genap tahun akademik 2023/2024. Hasil penelitian menunjukkan bahwa metode SVM memberikan akurasi terbaik sebesar 87,5% dalam klasifikasi sentimen multi-kelas. Temuan ini memberikan gambaran empiris mengenai persepsi mahasiswa dan dapat menjadi acuan bagi pengembang aplikasi akademik untuk meningkatkan kualitas layanan. Penelitian ini juga mengkaji faktor-faktor yang mempengaruhi kepuasan mahasiswa serta rekomendasi pengembangan aplikasi ke depan. Abstract This study aims to analyze multi-class sentiment to assess student satisfaction with web-based academic management applications in higher education institutions. Utilizing natural language processing (NLP) techniques and machine learning algorithms such as Random Forest, Support Vector Machine (SVM), and Neural Networks, this research classifies student comments into several sentiment categories: positive, neutral, and negative. Data were collected via online surveys and application reviews during the even semester of the 2023/2024 academic year. Results indicate that the SVM method achieved the highest accuracy of 87.5% in multi-class sentiment classification. These findings provide empirical insights into student perceptions and serve as a reference for academic application developers to improve service quality. The study also examines factors influencing student satisfaction and offers recommendations for future application development.
Analisis Implementasi Google Drive Terhadap Produktivitas Operasional Excisia Photography Fendy Bayu Firmansyah; Imam Thoib; Nafis Sururi; Beda Puspita; Danang Satya Nugraha; Nicky Dwi Kurnia
Jurnal Komputer Teknologi Informasi Sistem Komputer (JUKTISI) Vol. 5 No. 1 (2026): Juni 2026
Publisher : LKP KARYA PRIMA KURSUS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62712/juktisi.v5i1.963

Abstract

Excisia Photography, a professional photography service business in Kediri City, faced various operational obstacles hindering productivity, including slow file delivery to clients, difficulty in team coordination for file sharing, risk of data loss due to reliance on physical storage media, and inefficient manual archiving systems. This study aims to analyze the effect of Google Drive implementation as a cloud storage solution on the operational productivity of Excisia Photography, encompassing aspects of file distribution speed, team collaboration ease, data storage security, and work time efficiency. A descriptive quantitative approach was employed using total sampling of five core team members. Data were collected through a Likert-scale questionnaire (1–5) and semi-structured interviews. Results indicate that all productivity indicators achieved very good average scores, with the highest on the file delivery speed dimension (average 4.80), followed by file accessibility, data security, and work efficiency (each 4.60), and team collaboration (4.40). Interview data revealed a 35–40% reduction in project cycle completion time and nearly a twofold increase in production capacity following implementation. It is concluded that Google Drive has a significantly positive effect on the operational productivity of Excisia Photography and can serve as a strategic recommendation for similar photography businesses undergoing digital transformation.
Co-Authors Beda Puspita Danang Satya Nugraha Fendy Bayu Firmansyah Imam Thoib Kholifah, Binti Nafii’, Ayu Fernanda Nurun Nafis Sururi Nur Ani, Febi Warta