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Rancang Bangun Sistem Inventaris pada UMKM Girimulyo, Kabupaten Lampung Timur Anggraini, Leslie; Bagaskara, Radhinka; Verdiana, Miranti; Afriansyah, Aidil; Idris, Mohamad
Nemui Nyimah Vol. 5 No. 1 (2025): Nemui Nyimah Vol. 5 No. 1 2025
Publisher : FT Universitas Lampung

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Abstract

We discuss the design and implementation of an Inventory Management System developed specifically for Javamart Girimulyo to enhance accuracy and efficiency in stock control. The primary objective of the system is to automate inventory tracking, monitor stock levels in real time, and generate detailed inventory reports, thus minimizing manual errors and improving overall inventory oversight. The development followed the Modified Waterfall methodology, which provided a clear and systematic process across stages of requirements gathering, system design, coding, testing, and deployment. Key functionalities include automatic stock updates upon item inflow and outflow, low-stock alerts, flexible item categorization, and secure access controls for administrators. The system also offers an intuitive graphical user interface and integrates with a MySQL database backend to ensure data reliability and consistency. Testing outcomes indicate that the system delivers the necessary performance and stability, confirming its suitability for deployment. By digitizing and streamlining stock management processes, this project offers a practical and scalable solution to support inventory operations at Javamart Girimulyo.
Analysis Comparison of Depression Levels Based on Gender and Academic Factors of Students Verdiana, Miranti; Nugroho, Eko Dwi; Anggraini, Leslie; Bagaskara, Radhinka; Yulita, Winda; Afriansyah, Aidil; Algifari, Muhammad Habib
APPLIED SCIENCE AND TECHNOLOGY REASERCH JOURNAL Vol. 4 No. 2 (2025): Applied Science and Technology Research Journal
Publisher : Lembaga Penelitian dan Pengabdian Mayarakat (LPPM) Universitas PGRI Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31316/astro.v4i2.7975

Abstract

This study aims to analyze the level of depression among university students by examining gender and several academic indicators. The dataset includes responses from 27,901 students across various regions, with variables covering age, gender, academic pressure, study satisfaction, work/study hours, CGPA, and depression status. The analytical methods applied in this study include the chi-square test to evaluate the association between gender and depression status, point-biserial correlation to examine the relationship between numeric variables and depression, and logistic regression to develop a prediction model. The chi-square test results revealed no significant relationship between gender and depression (p = 0.774), indicating that depression affects both genders. In contrast, academic pressure exhibited the strongest correlation with depression status (r = 0.47), followed by work/study hours (r = 0.209) and study satisfaction (r = -0.168). The Logistic Regression model constructed using the four most relevant variables demonstrated satisfactory performance, achieving 75.5% accuracy and 82.1% recall in identifying students experiencing depression. These findings highlight the critical role of academic-related factors—particularly academic pressure—in influencing students' mental health. Therefore, targeted academic support strategies are essential to mitigate depression risks in higher education environments.