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APLIKASI PENGELOLAAN KEGIATAN KAMPUS BERBASIS MOBILE MENGGUNAKAN METODE AGILE Manalu, Ester; Simbolon, Yoel; Manihuruk, Rifaldi; Napitupulu, Virzinia; Surbakti, Efrans; Lumbanbatu, Vio
Jurnal Manajamen Informatika Jayakarta Vol 5 No 1 (2025): JMI Jayakarta (Februari 2025)
Publisher : Sekolah Tinggi Manajemen Informatika dan Komputer Jayakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52362/jmijayakarta.v5i1.1785

Abstract

Students in the campus environment often miss important information conveyed through WhatsApp or unstructured communication media. In addition, lecturers are not always able to monitor every message in the group, causing announcements to get lost among many other messages. This issue requires a solution in the form of a centralized and efficient campus activity management application. This application aims to make it easier for lecturers to deliver announcements directly and in an organized manner, while also serving as an integrated platform that supports communication between lecturers, students, and campus administration. The methodology used in this study includes internal data analysis based on daily operational observations on campus, as well as consultations with lecturers and students without involving surveys or questionnaires. The analysis is conducted to assess the technical, economic, operational, legal, and scheduling feasibility of the application development.The results of this study show that this application is feasible to develop using React Native for cross-platform development, Java script for the backend, and Firebase as the database. This application is also designed to comply with data security and privacy standards in accordance with regulations in Indonesia. With a simple and user-friendly interface, this application is expected to facilitate information delivery, save time, and improve the efficiency of campus activity management.
Penerapan Algoritma K-Means dalam Pengelompokan Indeks Harga Perdagangan Besar (IHPB)Produk Logam,Mesin, dan Perlengkapannya Tahun 2025 LumbanBatu, Vio Br; Napitupulu, Virzinia; Sipayung, Sardo Pardingotan
Jurnal Ilmu Komputer dan Informatika | E-ISSN : 3063-9026 Vol. 2 No. 3 (2026): Januari - Maret
Publisher : GLOBAL SCIENTS PUBLISHER

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

The Wholesale Price Index (WPI) is an important economic indicator used to measure price changes at the wholesale level. The metal, machinery, and equipment product group plays a strategic role in supporting the industrial and national development sectors. Price fluctuations in this product group need to be analyzed systematically to identify their movement patterns. This study aims to classify the Wholesale Price Index (WPI) of metal, machinery, and equipment products in 2025 using the K-Means clustering algorithm. The data used in this study consist of annual WPI values obtained from the official publications of Statistics Indonesia (BPS). The research stages include data collection, data preprocessing, data normalization using the Min-Max method, determination of the optimal number of clusters, application of the K-Means algorithm, and analysis of clustering results. The number of clusters used is K = 3, representing low, medium, and high price index groups. The results show that the K-Means algorithm is effective in grouping WPI data based on the similarity of price index values. The clustering results provide a clearer overview of price movement patterns and can be used to support economic analysis, price monitoring, and policy decision-making in the industrial sector.