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Supplier Evaluation at Small-Medium Enterprise Using Simple Additive Weighting Raymond Sunardi Oetama; Fernando Jose Armando
Journal of Information System and Informatics Vol 5 No 2 (2023): Journal of Information Systems and Informatics
Publisher : Universitas Bina Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51519/journalisi.v5i2.479

This study focuses on the importance of information systems in today's intensely competitive business landscape. Companies of all sizes rely on information systems to stay afloat, streamline operations, and make informed decisions based on accurate data. To remain competitive, a medium-sized company specializing in vending motorcycle accessories and spare parts faced various challenges, including determining the best supplier for each item. To address this issue, a decision support system was developed using the Simple Additive Weighting technique. This method calculates the weighted sum of performance evaluations for each option based on all qualities. The system underwent user acceptance testing and achieved a flawless success rate of 100%. Overall, this study highlights the crucial role of decision support systems in enabling businesses to make strategic decisions based on accurate and reliable data.

UNVEILING CHURN PREDICTION AT BANK IVORY Raymond Sunardi Oetama
Jurnal Informatika dan Teknik Elektro Terapan Vol 11, No 3s1 (2023)
Publisher : Universitas Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/jitet.v11i3s1.3394

The banking industry faces significant challenges in tackling customer churn within its credit card services. Customer churn refers to the situation where customers discontinue using a bank's services and migrate to another financial institution. To proactively address this critical issue, the present research endeavors to predict customer attrition in credit card services. To achieve this goal, the study extensively employs the CRISP-DM framework and diligently compares the performance of two predictive models, namely Gradient Boosting and Random Forest. The research endeavors to identify potential churn customers by analyzing crucial variables, including customer age, marital status, gender, income category, credit limit, and total transactions. The preferred modeling approach, determined based on the lowest misclassification rate, serves as a vital component of the research's analytical process. Remarkably, the research findings unequivocally demonstrate the superior performance of the Gradient Boosting model, which attains a misclassification rate of 0.1118 in predicting customer attrition.Â

Material Requirement Planning Information System: Prototype And Lead Time Analysis Mikhael Billy Tanaga; Raymond Sunardi Oetama
Journal of Information System and Informatics Vol 5 No 3 (2023): Journal of Information Systems and Informatics
Publisher : Universitas Bina Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51519/journalisi.v5i3.535

In the pharmaceutical manufacturing industry, efficient and accurate production processes ensure quality products and meet customer demands. However, many companies still rely on manual systems, such as Microsoft Excel, which can lead to challenges and inefficiencies. The problems identified include a lack of integration between product data and manufacturing documents, error-prone manual data entry, document mix-ups, and time-consuming processes. The study aimed to design and implement a web-based material requirement planning system to address the challenges of a manual manufacturing system in a pharmaceutical company. The objectives were to improve integration, streamline production processes, and reduce lead time for enhanced operational efficiency. The study employed a prototyping approach to design and develop a web-based material requirement planning system. User feedback and requirements guided iterative design cycles, while User Acceptance Testing evaluated system performance and usability. The impact on operational efficiency was assessed by measuring lead time before and after implementation. The implemented web-based material requirement planning system successfully resolved integration issues, reduced manual data entry errors, and minimized document mix-ups within the pharmaceutical manufacturing company. User Acceptance Testing achieved a 100% average percentage. The lead time was improved from 207-251 minutes to 122-159 minutes, demonstrating enhanced operational efficiency.

Evaluation and Solution for SAP Implementation Using Technology Acceptance Model: A Case Study in an Indonesian Food Trading Company Mayang Ayu Andila; Raymond Sunardi Oetama
G-Tech: Jurnal Teknologi Terapan Vol 7 No 4 (2023): G-Tech, Vol. 7 No. 4 Oktober 2023
Publisher : Universitas Islam Raden Rahmat, Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33379/gtech.v7i4.2488

Several companies have implemented an end-to-end SAP system, but are experiencing problems. To find the root cause of this problem, this study evaluates employee user acceptance of SAP in one company in Indonesia. The variables used are taken from the Technology Acceptance Model which includes Perceived Usefulness, Perceived Ease of Use, Attitude Toward Use, and also Behavioral Intention to Use. Furthermore, it was also found that the training did not affect Cooperation and the Perceived Ease of Use of the SAP System. The training was chosen as the root cause of the constraints on SAP implementation in this company. After the root cause of the problem is found, a solution is designed in the form of a website that aims to improve SAP training at this company.

Utilization of Online Village Administration Services: Training on the use of Cihuni Village Website Features Jansen Wiratama; Rudi Sutomo; Raymond Sunardi Oetama; Samuel Ady Sanjaya; Santo Fernandi Wijaya
I-Com: Indonesian Community Journal Vol 3 No 4 (2023): I-Com: Indonesian Community Journal (Desember 2023)
Publisher : Fakultas Sains Dan Teknologi, Universitas Raden Rahmat Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33379/icom.v3i4.3486

Public administration services are important for urban and rural communities. With a large population, it is difficult for administrative service processes using conventional methods to run optimally, so they need to be transformed into digital form. Current technology should support optimizing administrative services from village officers to the community. However, limitations related to the use of technology still need to be solved by village officers. Therefore, training is needed for village officers in using administrative service features via the Cihuni village website resulting from previous research. This training activity was carried out in Cihuni Village, a village supported by Multimedia Nusantara University (UMN). The training process involved the UMN Lecturer Team as community outreach members and Cihuni Village officers. This community outreach activity increases the understanding of village officials regarding using the Cihuni village website, which has various features for public administration services.

UNVEILING CHURN PREDICTION AT BANK IVORY Raymond Sunardi Oetama
Jurnal Informatika dan Teknik Elektro Terapan Vol 11, No 3s1 (2023)
Publisher : Universitas Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/jitet.v11i3s1.3394

The banking industry faces significant challenges in tackling customer churn within its credit card services. Customer churn refers to the situation where customers discontinue using a bank's services and migrate to another financial institution. To proactively address this critical issue, the present research endeavors to predict customer attrition in credit card services. To achieve this goal, the study extensively employs the CRISP-DM framework and diligently compares the performance of two predictive models, namely Gradient Boosting and Random Forest. The research endeavors to identify potential churn customers by analyzing crucial variables, including customer age, marital status, gender, income category, credit limit, and total transactions. The preferred modeling approach, determined based on the lowest misclassification rate, serves as a vital component of the research's analytical process. Remarkably, the research findings unequivocally demonstrate the superior performance of the Gradient Boosting model, which attains a misclassification rate of 0.1118 in predicting customer attrition.

Sales Information System: A Case Study at an Indonesian Pharmaceutical Manufacturing Bonfilio Wilson Atmadja; Raymond Sunardi Oetama
Jurnal Informatika dan Rekayasa Perangkat Lunak Vol 6, No 1 (2024): Maret
Publisher : Universitas Wahid Hasyim

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36499/jinrpl.v6i1.9309

The effective design of information systems plays a crucial role in enhancing productivity and efficiency across various industries, particularly in the business sector. For numerous companies, integrating a comprehensive information system has become indispensable, effectively reducing risks such as human errors, fraud, and data inaccuracies. This study suggests developing a web-based information system specifically optimizing the sales process. The Rapid Application Development methodology has been chosen for system design to achieve this objective. This approach utilizes XAMPP as the web server, Visual Studio Code as the code editor, PHP as the programming language, CodeIgniter as the framework, and MySQL for the database. Implementing this information system offers several advantages for the organization, addressing current issues and enhancing operations. It streamlines the management of sales-related data by automating various processes. Additionally, the system simplifies the generation of crucial documents like sales reports, invoices, component selection, and delivery orders. These reports serve as invaluable resources for analysis and decision-making, empowering the company to plan and develop future business processes efficiently. The data reveals an impressive average user acceptance score of 97.1%, highlighting substantial user satisfaction and endorsement.

Empowering Pregnant Women with Tailored Food Recommendations through K-Nearest Neighbors in Android Application Stevanus Kurniawan; Raymond Sunardi Oetama
G-Tech: Jurnal Teknologi Terapan Vol 8 No 2 (2024): G-Tech, Vol. 8 No. 2 April 2024
Publisher : Universitas Islam Raden Rahmat, Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33379/gtech.v8i2.4084

When at a restaurant, pregnant women often face difficulties in choosing healthy and appropriate foods during pregnancy, primarily due to lack of knowledge, uncertainty about food ingredients, and difficulty in remembering the list of foods to avoid. This research aims to assist restaurants and pregnant women in avoiding consuming foods containing unhealthy ingredients for pregnant women. Our solution is to develop an Android-based application that can detect foods containing ingredients that pregnant women should not consume and then offer alternative foods that are similar to those foods. The application is developed using the Rapid Application Development method, and the algorithm used is the K-nearest Neighbor. The application has been tested with a User Acceptance Test with an 84-90% acceptance rate.

Inventory Management System Using Economic Order Quantity And Reorder Point Ignatius Ivan; Raymond Sunardi Oetama
G-Tech: Jurnal Teknologi Terapan Vol 8 No 4 (2024): G-Tech, Vol. 8 No. 4 Oktober 2024
Publisher : Universitas Islam Raden Rahmat, Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70609/gtech.v8i4.4780

The inventory management system for car workshops is still using Excel, which makes it inefficient and inaccurate for complex stock calculations. The solution is to design an inventory application that uses the Economic Order Quantity and Reorder Point methods. The application will provide timely stock replenishment information and optimize order quantities, increasing inventory management efficiency and accuracy. The Software Development Life Cycle used in this study is Rapid Application Development, a process emphasizing short development cycles. User Acceptance Test results show that users received the inventory management system very well, with an average satisfaction level of 98.44% for Admins and 97% for general users, indicating high satisfaction with the system's features and functionality.

Preparing Better Data for Oil Price Prediction Using Long Short-Term Memory Raymond Sunardi Oetama
G-Tech: Jurnal Teknologi Terapan Vol 8 No 4 (2024): G-Tech, Vol. 8 No. 4 Oktober 2024
Publisher : Universitas Islam Raden Rahmat, Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70609/gtech.v8i4.5668

Fluctuating oil prices require a prediction model that can capture complex patterns more accurately than traditional methods. This study aims to apply the Long Short-Term Memory (LSTM) model to predict crude oil prices by assessing the effect of the training-test data ratio and window size on model performance. Daily data from 2000 to 2023 were taken from Yahoo Finance, which was then trained and tested on five data ratios and various window sizes. The evaluation was carried out using Mean Squared Error (MSE), Root Mean Squared Error (RMSE), Mean Absolute Error (MAE), Mean Absolute Percentage Error (MAPE), and R². The results show that the 90:10 ratio with a window size of 3 provides the best performance, with an MSE of 6.2100, RMSE of 2.4920, MAE of 1.8430, MAPE of 2.1363%, and R² of 0.9606. These findings confirm that LSTM can effectively capture temporal dependencies and outperform traditional statistical methods.

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