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REKAYASA PERANGKAT LUNAK SISTEM INFORMASI PENGIRIMAN DAN PENERIMAAN SURAT ATAU PAKET BERBASIS WEB (Studi Kasus : PT. Jaya Trade Indonesia) Benni Triyono; Sri Purwanti; Verdi Yasin
Journal of Information System, Applied, Management, Accounting and Research Vol 1 No 1 (2017): JISAMAR : Volume 1, Nomor 1, December 2017
Publisher : Sekolah Tinggi Manajemen Informatika dan Komputer Jayakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (497.653 KB)

Abstract

Penerimaan dan pengiriman surat atau paket merupakan kegiatan pengelolaan pendataan surat atau paket pada suatu organisasi atau instansi dengan pihak lain yang berkepentingan. Pengamatan yang dilakukan secara deskriptif kualitatif, yang memberikan gambaran keadaan obyek pengamatan berdasarkan fakta yang ada. Teknik pengumpulan data menggunakan teknik wawancara langsung, observasi data, dokumentasi data, analisis dokumen, penarikan kesimpulan dan verifikasi. Sistem informasi Penerimaan dan pengiriman surat atau paket pada PT. Jaya Trade Indonesia sudah menggunakan sistem terkomputerisasi, yaitu dengan menggunakan aplikasi berbasis dekstop. Dalam penyusunan jurnal ini, akan diusulkan program untuk penerimaan dan pengiriman surat atau paket dengan menggunakan aplikasi pemrograman berbasis web. Diharapkan aplikasi ini dapat memperbaiki sistem penerimaan atau pengiriman yang masih kurang memenuhi kebutuhan instansi, dalam mengembangkan studi kasus ini menggunkan metode pengembanan System Development Life Cycle (SDLC) sedangkan metode analisis dan perancangan nya mengunakan pendekatan Rekayasa Perangkat Lunak Berorientasi Obyek.
PREDIKSI KELULUSAN MAHASISWA MENGGUNAKAN MACHINE LEARNING Hasbullah, M.Imam; Verdi Yasin
JURNAL TEKNOLOGI INFORMASI DAN KOMUNIKASI Vol. 16 No. 2 (2025): September
Publisher : UNIVERSITAS STEKOM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/jtikp.v16i2.1025

Abstract

Predicting student graduation is an essential component in academic management within higher education institutions. The growing issue of delayed graduations and dropouts (DO) has raised significant concerns in the educational field. By utilizing machine learning methods, predictions regarding student graduation can be made with high accuracy, based on historical data such as academic performance, attendance, background, and social factors. This paper aims to explore various machine learning methods applied in previous studies for predicting student graduation, including Decision Tree, Random Forest, SVM, and Neural Networks. The findings of these studies suggest that models like Random Forest and XGBoost tend to provide the highest accuracy in predicting student outcomes. This review is intended to serve as a foundational reference for the development of data-driven systems for predicting graduation rates in academic environments.  
Pengembangan Aplikasi Pemanfaatan Barang Milik Negara Berbasis Website Menggunakan Metode Waterfall Nuril Qomaryah; Verdi Yasin; Anton Zulkarnain Sianipar
Jurnal Informatika dan Teknologi Komputer (J-ICOM) Vol 6 No 2 (2025): Jurnal Informatika dan Teknologi Komputer ( J-ICOM)
Publisher : E-Jurnal Universitas Samudra

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55377/j-icom.v6i2.10695

Abstract

Good management of State Property (BMN) is expected to be owned by every government agency, one of which is in the activity of borrowing goods. However, in the process, several obstacles were found, such as errors in recording goods due to manual processes, difficulties in searching for data, the length of time required to provide reports, frequent stock shortages, and difficulties in data processing. To overcome these problems, a BMN utilization information system has been built. Data was collected through interviews, observations, and literature studies. System development was carried out using the SDLC Waterfall method which consists of five stages, namely needs analysis, design, implementation, testing, and maintenance. System design was carried out using UML diagrams, such as use cases, activity diagrams, class diagrams, and mock-ups. Implementation was carried out using the PHP programming language with the Laravel framework and MySQL database. Testing was carried out using the black-box method and System Usability Scale with a test result score of 89.8 which means the application is suitable for use. A website-based BMN utilization application with the waterfall method and Laravel framework was produced from this study. From the research that has been conducted, it is concluded that the application that has been created is able to make it easier for agencies to manage BMN and is more optimal, especially borrowing activities and requests for inventory of goods become more effective and efficient.