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      "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 \r\ndifficulties 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, \r\nidentify 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), \r\nprocessed 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) \r\nenhancements to sustainably improve the quality of academic information services.",
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      "title": "USULAN PERBAIKAN APLIKASI SIAKANG BERDASARKAN ANALISIS SENTIMEN MENGGUNAKAN PENDEKATAN \r\nQUALITY FUNCTION DEPLOYMENT (QFD)",
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      "department": "TEKNIK INDUSTRI",
      "datestamp": "2026-04-08 08:10:52",
      "corp_creators": [
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      "note": "Implementasi Sistem Informasi Akademik New Generation (SIAKANG) di \r\nUniversitas Sultan Ageng Tirtayasa menghadapi berbagai keluhan mahasiswa \r\nterkait kualitas layanan, dengan permasalahan spesifik berupa kendala teknis \r\nproses login, ketidaksesuaian data nilai akademik, lambatnya waktu pemuatan \r\n(loading), sistem yang sering error, serta tampilan antarmuka yang kurang \r\nresponsif pada perangkat seluler. Penelitian ini bertujuan untuk mengelompokkan \r\nopini mahasiswa melalui analisis sentimen, mengidentifikasi topik permasalahan \r\nutama, serta menyusun usulan perbaikan layanan yang terstruktur berdasarkan \r\nkebutuhan pengguna. Metode yang digunakan adalah pendekatan kuantitatif \r\ndengan pengumpulan data melalui kuesioner terbuka (104 responden), yang diolah \r\nmelalui tahap text preprocessing, representasi numerik Term Frequency–Inverse \r\nDocument Frequency (TF–IDF), dan pengelompokan menggunakan algoritma K\r\nMeans Clustering. Penentuan jumlah klaster optimal melalui Elbow Method \r\nmenghasilkan k=3, dengan validasi Silhouette Score sebesar 0,111, yang kemudian \r\ndiintegrasikan ke dalam metode Quality Function Deployment (QFD) melalui \r\npenyusunan matriks House of Quality (HoQ). Penelitian menyimpulkan bahwa \r\nmeskipun kombinasi TF-IDF dan K-Means belum optimal dalam memisahkan \r\npolaritas sentimen karena ketidakseimbangan data, metode ini sangat efektif \r\nmemetakan titik lemah sistem, di mana prioritas utama perbaikan layanan \r\nSIAKANG meliputi penguatan keamanan sistem, audit data akademik berkala, \r\noptimasi infrastruktur server, dan peningkatan desain antarmuka pengguna \r\n(UI\/UX) demi meningkatkan kualitas layanan secara berkelanjutan.",
      "lastmod": "2026-04-08 08:10:52",
      "subjects": [
        "H1",
        "HA"
      ],
      "type": "thesis",
      "institution": "Fakultas Teknik Universitas Sultan Ageng Tirtayasa",
      "divisions": [
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        "Industri"
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            "family": "Bahauddin"
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