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All Journal Jurnal Ilmiah Teknik Industri International Journal of Research and Applied Technology (INJURATECH)
Resviani, Devi
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Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Transportation

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PERANCANGAN SISTEM ENTERPRISE RESOURCE PLANNING (ERP) TERHADAP PENGADAAN BAHAN BAKU, PENJUALAN, DAN PRODUKSI PADA CV. JAYA LOGAM MENGGUNAKAN SOFTWARE ODOO Resviani, Devi; Sulaksono, Agus
Jurnal Ilmiah Teknik Industri Vol. 12 No. 2 (2024): Jurnal Ilmiah Teknik Industri : Jurnal Keilmuan Teknik dan Manajemen Industri
Publisher : Program Studi Teknik Industri, Fakultas Teknik Universitas Tarumanagara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24912/jitiuntar.v12i2.31677

Abstract

CV. Jaya Logam faced various operational challenges caused by ineffective sales and raw material inventory recording systems, leading to production delays, errors in information delivery, and difficulties in monitoring and decision-making. This research was conducted to address these issues through system needs analysis, design, and testing of an Enterprise Resource Planning (ERP) system using Odoo software. The methodological process involved a detailed analysis of system requirements, system design using Unified Modelling Language (UML) diagrams to visualize the system architecture, and system testing using the Black Box Testing method to ensure the reliability and effectiveness of the designed system. The testing results showed that the developed ERP system successfully met all 12 test class parameters, indicating that the system is valid and can be implemented effectively. The implementation of this ERP system at CV. Jaya Logam resulted in significant improvements in operational efficiency and data accuracy, better business process integration, and the provision of real-time information that supports faster and more accurate decision-making processes.
Analysis of Heart Disease Risk Factors Based on Clinical Data Using Descriptive Correlation and Logistic Regression Harjono, Risqi Windu; Afrianto, Irawan; Kurniawan, Bobi; Resviani, Devi
International Journal of Research and Applied Technology (INJURATECH) Vol. 5 No. 1 (2025): Vol 5 No 1 (2025)
Publisher : Universitas Komputer Indonesia

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Abstract

Heart disease is one of the major causes of death, often progressing without any visible signs of the onset of the disease, thereby warranting the need for a data-intensive solution in support of its early screening. This paper proposes an analysis of risk factors for heart diseases using clinical data through the application of descriptive statistics, correlation analysis, and logistic regression. The proposed clinical data for analysis is a secondary clinical dataset that contains information about 918 patients with 12 numerical and categorical variables, with one target or dependent variable: heart disease. Descriptive statistics were employed to reveal information about the characteristics of the provided clinical data, Pearson correlation analysis, as well as Chi-Square tests, were used to examine the association of heart clinical parameters. A logistic regression analysis was employed as the core solution for determining the risk of heart diseases. This paper showed that among 918 patients, 55.3% were diagnosed with heart diseases, with a peak among middle-aged patients. Pearson correlation analysis revealed that no numerical variables were strongly correlated with heart diseases, but among the categorical variables, ChestPainType, ExerciseAngina, and ST_Slope were significantly related to heart diseases. An accuracy of 88.59% with a recall value of 0.93 for heart diseases classes was achieved by using logistic regression analysis. This paper clearly shows that an interpretive approach through statistics could potentially provide support for developing a decision support system for an early heart disease screen for cardiac patients.
Co-Authors Agus Sulaksono Bobi Kurniawan, Bobi Harjono, Risqi Windu Irawan Afrianto