@phdthesis{eprintuntirta59504,
          school = {Fakultas Teknik Universitas Sultan Ageng Tirtayasa},
            note = {Implementasi Sistem Informasi Akademik New Generation (SIAKANG) di 
Universitas Sultan Ageng Tirtayasa menghadapi berbagai keluhan mahasiswa 
terkait kualitas layanan, dengan permasalahan spesifik berupa kendala teknis 
proses login, ketidaksesuaian data nilai akademik, lambatnya waktu pemuatan 
(loading), sistem yang sering error, serta tampilan antarmuka yang kurang 
responsif pada perangkat seluler. Penelitian ini bertujuan untuk mengelompokkan 
opini mahasiswa melalui analisis sentimen, mengidentifikasi topik permasalahan 
utama, serta menyusun usulan perbaikan layanan yang terstruktur berdasarkan 
kebutuhan pengguna. Metode yang digunakan adalah pendekatan kuantitatif 
dengan pengumpulan data melalui kuesioner terbuka (104 responden), yang diolah 
melalui tahap text preprocessing, representasi numerik Term Frequency?Inverse 
Document Frequency (TF?IDF), dan pengelompokan menggunakan algoritma K
Means Clustering. Penentuan jumlah klaster optimal melalui Elbow Method 
menghasilkan k=3, dengan validasi Silhouette Score sebesar 0,111, yang kemudian 
diintegrasikan ke dalam metode Quality Function Deployment (QFD) melalui 
penyusunan matriks House of Quality (HoQ). Penelitian menyimpulkan bahwa 
meskipun kombinasi TF-IDF dan K-Means belum optimal dalam memisahkan 
polaritas sentimen karena ketidakseimbangan data, metode ini sangat efektif 
memetakan titik lemah sistem, di mana prioritas utama perbaikan layanan 
SIAKANG meliputi penguatan keamanan sistem, audit data akademik berkala, 
optimasi infrastruktur server, dan peningkatan desain antarmuka pengguna 
(UI/UX) demi meningkatkan kualitas layanan secara berkelanjutan.},
           month = {April},
           title = {USULAN PERBAIKAN APLIKASI SIAKANG BERDASARKAN ANALISIS SENTIMEN MENGGUNAKAN PENDEKATAN 
QUALITY FUNCTION DEPLOYMENT (QFD)},
          author = {Maulana Farid Muhammad},
            year = {2026},
        abstract = {The implementation of the New Generation Academic Information System (SIAKANG) at Universitas Sultan Ageng Tirtayasa has faced various student complaints regarding service quality, with specific issues including technical 
difficulties in the login process, inaccuracies in academic grade data, slow loading times, frequent system errors, and a non-responsive user interface on mobile devices. This study aims to classify student opinions through sentiment analysis, 
identify key problem topics, and formulate structured service improvement recommendations based on user needs. The method employed is a quantitative approach with data collection via open-ended questionnaires (104 respondents), 
processed through text preprocessing stages, Term Frequency?Inverse Document Frequency (TF?IDF) numerical representation, and clustering using the K-Means algorithm. The determination of the optimal number of clusters via the Elbow Method resulted in k=3, with a Silhouette Score validation of 0.111, which was then integrated into the Quality Function Deployment (QFD) method through the construction of the House of Quality (HoQ) matrix. The study concludes that although the combination of TF-IDF and K-Means was not optimal in separating sentiment polarity due to data imbalance, the method was highly effective in mapping system weaknesses. The primary priorities for SIAKANG service improvement include strengthening system security, periodic academic data audits, server infrastructure optimization, and user interface/experience (UI/UX) 
enhancements to sustainably improve the quality of academic information services.},
             url = {https://eprints.untirta.ac.id/59504/}
}