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All Journal Jurnal Informa: Jurnal Penelitian dan Pengabdian Masyarakat Jurnal Nasional Ilmu Komputer
Jakak, Pamuji M.
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Computer Science & IT

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Sistem Informasi Manajemen Wisuda Menggunakan Metode Waterfall Rizki, Uli; Mustofa, M Iqbal; Jakak, Pamuji M.; Khoiriyah, Septi
Jurnal Informa : Jurnal Penelitian dan Pengabdian Masyarakat Vol 9 No 1 (2023): Juni
Publisher : Politeknik Indonusa Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46808/informa.v9i1.246

Abstract

The background of this research was several problems that were often encountered during the graduation period, such as inefficiencies in graduation registration due to having to go back and forth to campus, manually entering registration data, and long and crowded graduation lines. The goal is to overcome these obstacles with the help of today's website-based technology which is then called SIMUDA. Simuda was built using the PHP (Hypertext Preprocessor) programming language with the Laravel framework. The graduation information system research method uses the waterfall method, with the stages of needs analysis, modeling, and development (coding). The actors involved in using the system are students as graduation registrars of course and faculty administrative staff. In conclusion, this system has been able to overcome the problems underlying the development of this system. students are greatly helped because they can register for graduation without having to bother going back and forth to campus, it becomes easier for staff to see data recap of prospective graduates without having to check manually.
Penerapan Metode K-Means Clustering Dalam Pengembangan Strategi Promosi Berbasis Data Penerimaan Mahasiswa Baru (Studi Kasus :Universitas Nurul Huda) indra, Indra Irawan; Rizki, Uli; Jakak, Pamuji M.; Prayogi, M. Bagus; Rahman, Miftakhul
Jurnal Nasional Ilmu Komputer Vol. 5 No. 1 (2024): Jurnal Nasional Ilmu Komputer
Publisher : Training and Research Institute Jeramba Ilmu Sukses (TRI - JIS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47747/jurnalnik.v5i1.1656

Abstract

The admission of new students is a key element in the success of a university. In its effort to enhance efficiency in admitting new students, Nurul Huda University proposes applying the K-Means Clustering method as a solution to manage candidate student data more effectively and intelligently. The data used in this research is derived from the Admission of New Students process for the academic years 2021/2022 and 2022/2023, totaling 1275 entries, which will then be processed using data mining techniques to generate analysis. The goal is to determine promotional strategies based on the origin of profiles of newly enrolled students. The method applied is clustering with the K-Means algorithm. After data processing, analysis is conducted using the Knowledge Discovery in Databases (KDD) technique, consisting of five stages: selection, preprocessing, transformation, data mining, and evaluation. The implementation in this research utilizes Rapidminer software, resulting in three data clusters: Cluster 1 with 345 entries, covering 27% of the total; Cluster 2 with 86 entries (7%); and Cluster 3 with 835 entries (66%). For promotion, the marketing team is deployed to districts dominant in the East OKU region and potential areas outside the East OKU District. They conduct direct visits to introduce Nurul University to students, distribute brochures, display pamphlets, and adapt strategies using a promotion mix strategy
Co-Authors indra, Indra Irawan Khoiriyah, Septi Mustofa, M Iqbal Prayogi, M. Bagus Rahman, Miftakhul