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Astri Ayu Purwati
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jtisi.almatani@gmail.com
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+6282253358243
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jtisi.almatani@gmail.com
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Kantor Lembaga Riset dan Inovasi Al-Matani Pekanbaru, Riau, Indonesia
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Jurnal Testing dan Implementasi Sistem Informasi
Published by Lembaga Riset dan Inovasi Al-Matani
ISSN : -     EISSN : 29867991     DOI : 10.55583/jtisi
Core Subject : Science,
Computer Science & IT
Jurnal Testing dan Implementasi Sistem Informasi includes research in the field of Information Technology, Information Systems Engineering, Intelligent Business Systems, and others. Editors invite research lecturers, the reviewer, practitioners, industry, and observers to contribute to this journal. The language used in English. Jurnal Testing dan Implementasi Sistem Informasi is a national scientific journals are open to seeking innovation, creativity and novelty. Either letters, research notes, articles, supplemental articles, or review articles. Jurnal Testing dan Implementasi Sistem Informasi aims to achieve state-of-the-art in theory and application of this field. Jurnal Testing dan Implementasi Sistem Informasi provide platform for scientists and academics across Indonesia to promote, share, and discuss new issues and the development of information systems and information technology. E-ISSN : 2986-7991
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 22 Documents
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Rancang Bangun Sistem Kepuasan Pengguna Pada Layanan Akademik Menggunakan Metode Rapid Application Development Safira, Dina Pani; Chaniago, M. Eric; Sandi, Kelvin Mei; Hasibuan, Radja Ardhiansyah
Jurnal Testing dan Implementasi Sistem Informasi Vol. 2 No. 2 (2024): Jurnal Testing dan Implementasi Sistem Informasi
Publisher : Lembaga Riset dan Inovasi Almatani

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55583/jtisi.v2i2.907

Abstract

Dalam standar ISO 9001:2015 klausul 9.1.2, organisasi diwajibkan untuk memantau persepsi pelanggan untuk memastikan kebutuhan dan harapan mereka terpenuhi. Universitas Islam Negeri Sultan Syarif Kasim Riau menggunakan Google Form untuk mengumpulkan data kepuasan pengguna terhadap layanan administrasi. Namun, berdasarkan survei, sebagian besar responden menyatakan bahwa Google Form memiliki keterbatasan dalam desain, format, keamanan, dan transparansi data. Untuk mengatasi permasalahan ini, penelitian ini mengusulkan pembangunan sistem kepuasan pengguna yang lebih terstruktur dan sistematis. Metode Rapid Aplication Development (RAD) digunakan untuk membuat sistem ini menjadi aplikasi web yang menggunakan PHP dan MySQL. Hasil pengujian menunjukkan bahwa sistem ini berhasil memenuhi persyaratan fungsional dan non-fungsional di Universitas Islam Negeri Sultan Syarif Kasim Riau dan mampu meningkatkan kualitas layanan administrasi.
Implementation of Local Mean Distance Weighting k-Nearest Neighbor in Determining Vocational High School Majors in Pekanbaru Syaliman, Khairul Umam; Gunawan, Dwi
Jurnal Testing dan Implementasi Sistem Informasi Vol. 2 No. 2 (2024): Jurnal Testing dan Implementasi Sistem Informasi
Publisher : Lembaga Riset dan Inovasi Almatani

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55583/jtisi.v2i2.965

Abstract

Vocational High School is a formal education at the secondary education level. SMK X Pekanbaru is one of the private vocational schools in Pekanbaru that provides IT-based education. There are 5 (five) majors in SMK X Pekanbaru, namely Computer and Network Engineering (TKJ), Software Engineering (RPL), Accounting and Financial Institution (AKL), Office Automation and Governance (OTKP), and Online Business and Marketing (BDP). During the registration period, prospective SMK students will enter their score data and will also choose the majors they want to take. In the absence of a system that can determine majors for prospective SMK students, obstacles will arise including errors in determining majors and requiring a long time to process prospective student data. Based on the above problems, a system will be built that can speed up and simplify the determination of new student majors by using Supervised Learning algorithms in Machine Learning, namely Local Mean Distance Weight k-Nearest Neighbor (LMDWkNN). Based on the results of the confusion matrix testing carried out, the accuracy results were 88.89%, the precision, recall and F1 score were 89%, which states that the model is good enough to determine majors

Page 3 of 3 | Total Record : 22

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