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All Journal Teika CogITo Smart Journal
Obaja Marum Lumbanraja
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Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Languange, Linguistic, Communication & Media

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Perancangan Sistem Informasi Administrasi Jasa Keamanan Berbasis Web Studi Kasus: PT Pasopati Guardian Security Services Obaja Marum Lumbanraja
TeIKa Vol 11 No 1 (2021): TeIKa: April 2021
Publisher : Fakultas Teknologi Informasi - Universitas Advent Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36342/teika.v11i01.2480

Abstract

Companies need integrated information technology capable of supporting the company's performance. Information Technology continues to grow rapidly, fills every field of the company with the system. One area or field that did not miss from Information Technology is field of Administration. PT Pasopati Guardian Security Services need an administration information system that help them to improve the company's performance and reduce the loss for the company. There were 4 goals of this research: 1) Improving the employee performance in doing his job. 2) Reducing unnecessary losses due to irregular available data. 3) Reducing the use of paper in the recording of data security force members, clients, financial expenses and income. 4) Saves time in searching existing data when needed. The methodology used in this research is SDLC (System Development Life Cycle) method which consists of five phases there are: (1) Requirement Analysis, (2) System Design, (3) Coding, (4) Testing and (5) Implementation. From the research that has been done, the authors conclude that: (1) The system that was built is able to improve the performance of employees in doing his job, (2) The system that was built is able to store and display data of financial expenses and income in accordance with the actual data so the data of old and new can be analyzed properly, (3) The system that was built is able to integrate data between members of the security force and client so we can know the number of members in the client's location, and (4) The system that was built is able to help users to make the invoice before the due date of payment by the client and reduce losses that may occur.
Funnel-Based Predictive Modeling for Forecasting Student Admissions in Higher Education Lumbanraja, Obaja Marum
CogITo Smart Journal Vol. 11 No. 2 (2025): Cogito Smart Journal
Publisher : Fakultas Ilmu Komputer, Universitas Klabat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31154/cogito.v11i2.1002.337-348

Abstract

Forecasting student admissions remains a challenge due to fluctuating online engagement and complex administrative processes. Existing predictive models rarely integrate website behavioral data with institutional admission funnels, resulting in lower accuracy. This study bridges that gap by combining web analytics from Google Analytics 4 (GA4) with administrative enrollment funnel data from the admission of new students (Penerimaan Mahasiswa Baru/PMB) system to develop a unified predictive framework. The approach strengthens forecasting by aligning digital behavior with verified enrollment milestones. A quantitative explanatory design was employed, applying Pearson correlation to identify linear relationships and Seasonal ARIMA (SARIMA) to model cyclical admission trends. The dataset includes GA4 metrics sessions, engagement rate, bounce rate, and events per session and PMB funnel stages from account creation to confirmed enrollment. Results reveal strong correlations (r > 0.9, p < 0.001) between digital engagement and mid-funnel conversions, while SARIMA achieved its highest accuracy for early-stage predictions (MAPE ≈ 19%). Forecasts for final outcomes were less accurate, reflecting administrative variability. These findings confirm that web engagement metrics are reliable leading indicators of student interest and mid-stage commitment. This research establishes a reproducible pipeline unifying web analytics (GA4) with institutional funnel data (PMB), providing empirical evidence that digital engagement is a reliable leading indicator of early and mid-stage commitment, thereby forming a novel and adaptable foundation for data-driven enrollment planning.
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