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Rancang Bangun Website Sekolah Menggunakan Google Sites Sebagai Media Informasi dan Komunikasi Imam Mualim; Rudi Hartono; Ismi Laras Wati; Suci Khotimah
Merkurius : Jurnal Riset Sistem Informasi dan Teknik Informatika Vol. 1 No. 5 (2023): September: Merkurius : Jurnal Riset Sistem Informasi dan Teknik Informatika
Publisher : Asosiasi Riset Teknik Elektro dan Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61132/merkurius.v1i5.1220

Abstract

This study aims to design and develop a school website using Google Sites as an effective medium of information and communication for both the school community and the public. The website development process was carried out through several stages, including needs analysis, content design, page creation, integration of supporting features, and functional evaluation. Google Sites was selected due to its ease of use, design flexibility, and its ability to integrate with various Google services such as Drive, Calendar, and Forms. The results of the development show that the resulting website is capable of providing structured school information, including the school profile, activity programs, administrative services, as well as news and announcement publications. In addition, communication features such as online forms and integrated school contact information enhance accessibility and interaction between the school and users. Based on limited trials, the website was considered feasible and easy to use as an information and communication medium that supports transparency, openness, and effective dissemination of information within the school environment.
Prediksi Prestasi Belajar Mahasiswa menggunakan Algoritma Naïve Bayes Nuari Anisa Sivi; Fathoni Dwiatmoko2; Suci Khotimah
Jurnal Ilmiah Teknik Informatika dan Komunikasi Vol. 3 No. 1 (2023): Maret : Jurnal Ilmiah Teknik Informatika dan Komunikasi
Publisher : Lembaga Pengembangan Kinerja Dosen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/juitik.v3i1.1822

Abstract

This study aims to predict students’ academic performance using the Naïve Bayes algorithm. The problem arises because academic assessment processes in many universities are still carried out manually, which can lead to subjectivity and inefficiency. Several factors—such as assignment scores, quizzes, examinations, attendance, motivation, and learning activities—significantly influence student performance, yet they have not been optimally utilized in prediction processes. The methods used in this research include data collection, preprocessing, splitting the dataset into training and testing sets, and applying the Naïve Bayes algorithm to classify student performance into categories of good, fair, and poor. The results indicate that the Naïve Bayes algorithm is capable of producing sufficiently accurate predictions and can be used as a decision-support tool to help improve the quality of learning in higher education institutions