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All Journal Abdimas Galuh: Jurnal Pengabdian Kepada Masyarakat Indonesian Journal of Industrial Engineering & Management RISTEC : Research in Information Systems and Technology
Krisnawanti
Universitas Logistik Dan Bisnis Internasional
Agriculture, Biological Sciences & Forestry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Engineering Industrial & Manufacturing Engineering Law, Crime, Criminology & Criminal Justice Nursing

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Journal : RISTEC : Research in Information Systems and Technology

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Inventory Control at The Perintis Cimaung Pharmacy Using Open Source Enterprise Resource Planning System: Odoo 14.0 Krisnawanti Krisnawanti; Nava Gia Ginasta; Muhammad Faisal Nasrudin; Amida Anis Nasution
RISTEC : Research in Information Systems and Technology Vol 4, No 1 (2023): Riset Sistem dan Teknologi Informasi
Publisher : Institut Pendidikan Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31980/ristec.v4i1.3112

Abstract

Along with the times and technology, more and more companies are switching from manual management of business processes to integrated information systems. Perintis Pharmacy is a pharmacy located in the Bandung district. Perintis Pharmacy has been serving its customers since 2010. However, Perintis Pharmacy has experienced several problems, where all business processes are still carried out manually. Errors frequently occur in both the service process and the inventory management system. Errors in stock calculations and ordering are the main obstacles. This causes the Pharmacy to experience losses both in terms of service quality and financially. So it is necessary to implement an integrated system so that inventory management becomes more effective and efficient, namely the application of an Enterprise Resource Planning (ERP) system that is integrated with forecasting simulations to obtain a more accurate amount of drug procurement. Demand forecasting is done using Time Series data with the Single Exponential Smoothing method, given the fluctuating demand every month. Then the forecasting results are integrated with the ERP system using the Odoo 14.0 application in the invoice, purchase, and inventory modules. By using the Odoo 14.0 application, it is expected that Perintis Pharmacy can increase efficiency and effectiveness in managing drug supplies so as to improve service quality and financial benefits.
Comparison of Support Vector Machines and Multilayer Perceptrons in the Classification Process: A Case Study of Heart Disease Analysis krisnawanti, Krisnawanti
RISTEC : Research in Information Systems and Technology Vol. 5 No. 2 (2024): RISTEC: Research in Information Systems and Technology
Publisher : RISTEC : Research in Information Systems and Technology

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

Abstract

Pattern Recognition is an important area in computer science that maps data to predefined concepts. Support Vector Machines (SVM) are particularly effective due to their ability to identify the optimal hyperplane that separates two classes in the feature space. Unlike neural networks, which look for a separating hyperplane, SVM determines the best hyperplane in the input space. SVM primarily serves as a linear classifier but can also address non-linear problems through the kernel trick, enabling high-dimensional operations. This paper delves into the foundational principles of SVM and its applications, specifically in classifying heart disease symptoms in individuals. The research includes the implementation of Gaussian Radial Basis Function (RBF) and Polynomial (POLY) kernel functions, along with various parameters affecting SVM performance. Additionally, a comparative analysis with Multilayer Perceptron (MLP) for data classification is presented to evaluate the effectiveness of the proposed kernel functions.
Co-Authors Amida Anis Nasution Dodi Permadi, Dodi Erna Mulyati Fathurohman, Dimas Mukhlis Hidayat Intan Novitas Dewi Maniah, Maniah Muhammad Faisal Nasrudin Nava Gia Ginasta Wawan Herwanta