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Empowering Eight Through a Web-Based Repository System in Improving Student Research Performance Kania, Raden; Solihati, Tifani Intan; Hidayanti, Nur; Bisri, Achmad; Roza Marmay; Edy Rakhmat
Jurnal Informatika Universitas Pamulang Vol 9 No 4 (2024): JURNAL INFORMATIKA UNIVERSITAS PAMULANG
Publisher : Teknik Informatika Universitas Pamulang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32493/informatika.v9i4.36842

Abstract

Preliminary. The Banten Jaya University Library repository system still uses the conventional method of storing it on a shelf in the reference room, this makes it difficult for students who are completing their final project/thesis to access it online. Moreover, with the closure of the campus due to the COVID-19 pandemic, the PSBB and PPKM were continued. Research purposes. This research makes it easier for students to access library repository collections wherever they are, measure the extent of students' literacy skills in utilizing information sources, and show the impact on their research performance. Research methods. The data collection method uses a questionnaire, with statistical analysis, a model for assessing student literacy skills with Empowering 8, which is a research method used to produce products and test the effectiveness of these products, with the Waterfall system development model, which consists of analysis, design, implementation, and testing. Data Analysis. Metadata obtained from the repository application, distributing questionnaires to students taking Thesis/Final Project courses from each faculty. Results and Discussion. The literacy level of Banten Jaya University students is quite good, especially after the online repository has been built, there is a significant correlation between student literacy levels and student performance results. Conclusions and suggestions. A good literacy level is the basic capital in solving student problems while doing their research, it is necessary to have a Research Information Literacy program for students that is integrated with Research Methods courses so that student research performance increases in accessing the repository that has been built.
Implementasi Algoritma K-Means dalam Pengelompokan Data Harga Laptop Roza Marmay; Ridha Luthvina; Okti Ulandari
Journal Scientific of Mandalika (JSM) e-ISSN 2745-5955 | p-ISSN 2809-0543 Vol. 7 No. 1 (2026)
Publisher : Institut Penelitian dan Pengembangan Mandalika Indonesia (IP2MI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36312/10.36312/vol7iss1pp236-243

Abstract

TThis study aims to cluster laptop price data using the K-Means algorithm to obtain a more structured and interpretable price segmentation. The data used in this study consist of laptop price data that have undergone a preprocessing stage, including data cleaning, data transformation, and data normalization to ensure optimal data quality. The determination of the optimal number of clusters was conducted using the Elbow Method by analyzing the Within Cluster Sum of Squares (WCSS) values, which indicated that the optimal number of clusters is k = 3. Subsequently, the K-Means algorithm was applied to group the laptop price data into three clusters based on price characteristics. The clustering results reveal three main groups, namely low-price, mid-price, and high-price laptop clusters. This segmentation provides a clear overview of the laptop market conditions and highlights the differences in price ranges among the clusters. The results demonstrate that the K-Means algorithm is able to cluster laptop price data effectively and consistently. The resulting segmentation can be utilized as a basis for decision-making for consumers as well as business stakeholders in developing marketing strategies and determining appropriate laptop pricing