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All Journal Electro Luceat JURNAL TEKNIK INFORMATIKA DAN SISTEM INFORMASI Media Aplikom INCODING: Journal of Informatics and Computer Science Engineering Inovasi Pendidikan Fisika Jurnal Teknik Mesin, Industri, Elektro dan Informatika Jurnal Elektronika dan Teknik Informatika Terapan International Journal of Technology and Education Research Prosiding Seminar Nasional Ilmu Sosial dan Teknologi (SNISTEK)
mahendra, christy
Sekolah Tinggi Ilmu Komputer (STIKOM) Yos Sudarso Purwokerto
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Physics Social Sciences Other

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Pengukuran Kualitas Pengalaman Pengguna dan Ketepatan Diagnosa Sistem Pakar untuk Penyakit Ikan Nila Berbasis Android Christy Mahendra; Putu Samuel Prihatmajaya; Suyudi; Eduardus Gerry Henri; Agnes Florentina Santoso; Jonathan Briant Wijaya
Prosiding Vol 7 No 1 (2025): SNISTEK
Publisher : LPPM Universitas Putera Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33884/psnistek.v7i1.10739

Abstract

This study aims to evaluate the user experience quality and diagnostic accuracy of an Android-based expert system application developed to assist in diagnosing diseases in tilapia fish. The evaluation employed the User Experience Questionnaire (UEQ) and the Certainty Factor (CF) approach. UEQ results indicate that the application delivers a highly satisfying user experience, with the highest scores on stimulation (1.68) and attractiveness (1.60), both categorized as Excellent. These results suggest that the application provides an engaging and enjoyable interactive experience. Other dimensions such as clarity (1.34), efficiency (1.37), accuracy (1.18), and novelty (1.20) fall into the Good category, indicating the system is intuitive, functional, and reliable, though there is still room for improvement.In terms of expert system performance, the Certainty Factor method successfully delivered relevant diagnostic results. Tricodiniasis emerged as the primary diagnosis with 100% confidence based on the user's selected symptoms. However, the appearance of several other diseases with similarly high confidence scores indicates the existence of overlapping symptoms across different conditions. This highlights the importance of using probabilistic approaches to manage uncertainty in disease diagnosis. Overall, the application demonstrates strong performance in user interface design, user interaction, and expert system accuracy, making it suitable as a supporting tool for diagnosing tilapia fish diseases
Co-Authors Agnes Florentina Santoso Akhiles Shyantica Wisnumurti Altech Octaviaus Angelica Lulu Setiani Annawati, Bergitta Dwi Brigita Maila Feriyani Wensen Eduardus Gerry Henri Endang Setyawati Fransiska Delsiana Gerson Manuel Sugianto Hengky Wijaya Jonathan Brian Wijaya Jonathan Briant Wijaya Mardi Utomo, Vinsensius Alvianto Mili, Wilson Nasumi Paath, David Kritian Putu Samuel Prihatmajaya Romanus Edy Prabowo Rosalina Yani Suyudi Yosita Lianawati