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All Journal Jurnal Teknologi dan Manajemen Informatika Jurnal Informatika dan Teknik Elektro Terapan Journal of Information System JOIV : International Journal on Informatics Visualization International Journal of New Media Technology Jurnal ULTIMA InfoSys Journal of Information Systems and Informatics JISA (Jurnal Informatika dan Sains) Indonesian Journal of Electrical Engineering and Computer Science Journal of Mutidisciplinary Issues IJISCS (International Journal of Information System and Computer Science)
Oetama, Raymond Sunardi
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Agriculture, Biological Sciences & Forestry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Law, Crime, Criminology & Criminal Justice Library & Information Science

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Battery Performance Evaluation through Decision Tree Jevelin, Jevelin; Oetama, Raymond Sunardi
JISA(Jurnal Informatika dan Sains) Vol 7, No 1 (2024): JISA(Jurnal Informatika dan Sains)
Publisher : Universitas Trilogi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31326/jisa.v7i1.1796

Abstract

This study addresses the pervasive concern surrounding battery performance degradation in electronic devices. While some attribute this decline to device aging, a significant portion of the population lacks awareness of the precise factors contributing to diminished battery efficiency. Consequently, the research investigates the factors related to battery performance, aiming to identify the determinants of reduced efficiency. Decision trees are used to meticulously analyze the intricate relationships between variables and discern the factors that respondents perceive as causative of diminished battery performance. This algorithm is chosen since, in predicting high-capacity lithium-ion battery performance, the decision tree outperforms other algorithms in machine learning in accuracy. The study elucidates diverse user preferences, with 55.38% favoring Android and 44.62% expressing a preference for iOS, indicating disparate perceptions of battery health: 61.54% consider their batteries as "Good," while 38.46% acknowledge a decline. The decision tree analysis of 195 participants underscores the pronounced impact of prolonged usage on battery health, revealing that 95% maintain good battery performance. In contrast, 27.69% of Android users face reduced battery performance, emphasizing the need for targeted user education and Android manufacturers to prioritize device longevity. The ultimate objective is to give readers a comprehensive understanding of the dynamics of battery performance in the context of device aging and its contributing factors and give some input to manufacturers and service providers. 
Web-Based Inventory and Sales Information System: Indonesian Micro Small Medium Enterprise Case Study Angellin, Kevina; Oetama, Raymond Sunardi; Amri, Mahfudz
JOINS (Journal of Information System) Vol. 8 No. 1 (2023): Edisi Mei 2023
Publisher : Fakultas Ilmu Komputer, Universitas Dian Nuswantoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33633/joins.v8i1.7977

Abstract

Information systems have a very important role in increasing productivity values that provide effectiveness and efficiency in the business sector. Cik Cik MSME Meatshop and Frozenfood is still using a manual system for recording their inventory and sales data, which causes several problems such as human error, human fraud, and inaccurate data. To overcome the problems, a solution is provided, that is a web-based information system, focused on the inventory and sales business processes. The information system is designed using Rapid Application Development method. The tools used are XAMPP as a web server and Visual Studio Code as a code editor. The programming language to be used is PHP, CodeIgniter as a framework, and MySQL as a database storage. The results obtained from the development of this information system are this system can help Cik Cik MSME Meatshop and Frozenfood in overcoming problems related to sales and inventory become easier to manage the data so that it is more automated compared to the previous manual system.
Enterprise Resource Planning (ERP) Evaluation and Implementation: A Case Study Yosevine, Prisca; Oetama, Raymond Sunardi; Setiawan, Johan; Princes, Elfindah
Journal of Multidisciplinary Issues Vol 1 No 1 (2021): Journal of Multidisciplinary Issues
Publisher : APPS Publications

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (464.883 KB) | DOI: 10.53748/jmis.v1i1.10

Abstract

Objective – To understand the success rate of ERP in the company by using the Ifinedo method and provide proposals that can improve ERP implementation in the company based on the unfulfilled Ifinedo method. Methodology – This research uses Quantitative method research distributed to 50 end users at Indoporcelain using surveys and interviews. Findings – The research found one point that is less valued in the company, namely vision and mission factors in organizational variables compared to other factors. Therefore, proposals in this sector are indispensable in order to increase the success of ERP implementation in the company. Furthermore, lack of IT support due to the management’s ignorance has made the ERP implementation did not reach the optimum performance expected. Novelty – By measuring the success rate of ERP in the company, the company can know how the success rate of ERP implementation in its company. The company can make corrections and quality improvements to existing ERP systems based on proposals with unmet Ifinedo method.
Enhancing Sales Strategies In Prime Market Retail Business Using Tuned Gradient Boosting Nurdiyansyah, Dudi; Oetama, Raymond Sunardi; Prasetiawan, Iwan
ULTIMA InfoSys Vol 15 No 1 (2024): Ultima Infosys : Jurnal Ilmu Sistem Informasi
Publisher : Universitas Multimedia Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31937/si.v15i1.3595

Abstract

In the retail sector, comprehending customer behavior and employing effective customer segmentation is pivotal for refining marketing strategies and augmenting profits. This study delves into predictive modeling for customer segmentation at Prime Market, a prominent retail entity. The research initially yields a classification error rate of 25.10% by employing Gradient Boosting for customer classification. However, through meticulous parameter tuning, this rate dramatically improves to 8.6%, achieving an impressive accuracy of 91.4%. This refined model furnishes invaluable insights into Prime Market's customer segments, enabling the customization of marketing tactics and strategic business approaches. Armed with these insights, Prime Market can make data-driven decisions to enhance customer segmentation accuracy, better comprehend customer preferences, and pinpoint potential avenues for revenue growth. Leveraging advanced data analytics and predictive modeling empowers Prime Market to maintain a competitive edge and deliver its clientele a personalized, gratifying shopping experience.
Fuzzy Multiple Attribute Decision Making and Simple Additive Weighting for Supplier Measurement In Furniture Business Rwanda, Rwanda; Oetama, Raymond Sunardi
Journal of Information System and Informatics Vol 5 No 4 (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.v5i4.589

Abstract

This study delves into the complexities of supplier selection in the furniture industry, where Decision Support Systems play a pivotal role in achieving data-driven, sustainable supplier choices. It underscores the Fuzzy Multiple Attribute Decision Making and Simple Additive Weighting approach, particularly emphasizing Price, response time, and delivery fees as critical factors. The overarching objective is to elevate supplier selection in alignment with furniture companies' specific requirements and strategic goals. Additionally, the Supplier Ranking System leverages Fuzzy Multiple Attribute Decision Making and Simple Additive Weighting techniques, ranking the third Supplier as the top Supplier with a high preference score of 0.90 and the fourth Supplier as the lowest-ranked Supplier with a score of 0.50. Notably, User Acceptance Tests affirm the System's outstanding performance and intense user satisfaction.
Digital Innovation and Rapid Application Development: A New Approach to Staff and Lecturer Recruitment at University Enzelin, Lola Naomi; Oetama, Raymond Sunardi; Anggina, Rhauma Syira
Journal of Information System and Informatics Vol 6 No 1 (2024): March
Publisher : Universitas Bina Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51519/journalisi.v6i1.657

Abstract

The University encountered challenges with its manual recruitment processes, characterized by inefficient record-keeping, decreased productivity, and prolonged hiring periods. To address these issues, a recruitment application was developed using the Rapid Application Development (RAD) methodology, prioritizing swift iterations and comprehensive stakeholder involvement. We have implemented many features to improve the user experience for job seekers and employers. It includes sign-up and login options for both, CV uploading for job seekers, and the ability to view vacancies. Employers can also view and upload vacancies, delete them if needed, and schedule interviews through the system. Both job seekers and employers can easily edit their profiles and passwords, ensuring flexibility and usability throughout the recruitment process. Notably, User Acceptance Tests revealed high satisfaction levels among users, confirming the application's effectiveness in meeting their requirements and enhancing the overall recruitment experience. The application's user-centric design and agile development approach represent a substantial advancement in the University's recruitment practices.
Enhancement Campus Office Supplies Requests Website Utilizing Rapid Application Development Setiawan, Jovanka Suryajaya; Oetama, Raymond Sunardi; Andersen, James
Journal of Information System and Informatics Vol 6 No 2 (2024): June
Publisher : Universitas Bina Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51519/journalisi.v6i2.769

Abstract

The web-based office supplies requisition application is a significant step in modernizing office equipment procurement in various organizations, including universities. However, this website encounters problems due to immature planning and less effective implementation. The current website faces some problems with requesting office supplies on campus, where the current process lacks efficiency and transparency in the status of user requests. It often results in discrepancies between the registered stock of office supplies and the actual stock in the warehouse. Our research aims to improve this website using the Rapid Application Development methodology. We also include user feedback when designing this website. The result is a new web-based application that provides a much better user experience when requesting office supplies. This update is expected to increase the efficiency of office equipment request services, provide users with more transparent request status information, and ensure accurate stock availability.
Unveiling Gold Membership Classification Using Machine Learning Christiano Tjokro, Vincencius; Oetama, Raymond Sunardi; Prasetiawan, Iwan
JOIV : International Journal on Informatics Visualization Vol 8, No 4 (2024)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/joiv.8.4.2023

Abstract

The main challenge in loyalty programs is selecting customers with limited funding. To address it, we explore various machine learning-based classification models. This study aims to enhance the effectiveness of a marketing strategy that promotes gold membership to customers with prior transaction history. Previously, much research applied decision trees, random forests, and logistic regression for classification, but gradient boosting is still unpopular. However, in this study, the Gradient Boost algorithm exhibits the best performance among these models, achieving an impressive accuracy of around 88%. This result underscores the model's capability to classify customers, thereby suggesting its potential to significantly enhance the marketing strategy's effectiveness. The analysis identifies crucial features that influence the model's predictive capabilities. Notably, the recency of the last visit, the number of transactions involving wine and meat, marital status, and the number of offline store transactions are identified as influential factors. Leveraging machine learning techniques enables the automation of the customer selection process, facilitating the attraction of a more extensive customer base. By targeting those customers most likely to respond positively to the gold membership offer, efficient resource allocation can be achieved. This research provides valuable insights and practical recommendations for implementing an effective marketing strategy under resource constraints. Combining machine learning algorithms and feature identification enables efficient targeting of potential customers, maximizing the impact of the gold membership offering. Implementing the findings of this study could lead to increased customer acquisition and improved overall business performance.
The Effect of Video Games Towards the Students' Academic Performance Lala, Yohanes Brian Caesaryano; Oetama, Raymond Sunardi; Lvina, Kimberly
IJNMT (International Journal of New Media Technology) Vol 11 No 2 (2024): Vol 11 No 2 (2024): IJNMT (International Journal of New Media Technology)
Publisher : Universitas Multimedia Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31937/ijnmt.v11i2.3638

Abstract

Video games have remained popular ever since the video game industry boom in the 1980s. It has remained popular, especially for children, teenagers, and adults. However, video games have also sparked controversies among the population. Concerns have been raised regarding the harmful effects of video games, particularly regarding addictions. Video games have been accused by many of being the cause of lowering academic performance. Therefore, this study aims to explore the relationship between video games and the overall academic performance of university students in depth. We applied several statistical methods using a questionnaire, which 100 university students filled out. The insights uncovered from this study may help determine if and how much video games affect the academic performance of university students.
Enhancement of Coronary Heart Disease Prediction using Stacked Long Short Term Memory Cinthiya, Cinthiya; Oetama, Raymond Sunardi
Jurnal Teknologi dan Manajemen Informatika Vol. 9 No. 1 (2023): Juni 2023
Publisher : Universitas Merdeka Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26905/jtmi.v9i1.9707

Abstract

The high incidence of death caused by coronary heart disease has become a global concern in the world of health, where patients with coronary heart disease are no longer only adults and the elderly, yet there are now so many cases of coronary heart disease experienced by underage patients. As a result, it is critical to be able to prevent and reduce the number of instances. One of them is the ability to predict a person's risk of coronary heart disease so that patients can be treated and provided early therapy. The risk of coronary heart disease will be predicted in this study utilizing Stacked long short-term memory algorithms. By appling this algorithm, the accuracy of 81.3% from previous study can be increased to 91.8% by this study. 
Co-Authors Amri, Mahfudz Andersen, James Angelie Tania, Valencia Eurelia Angellin, Kevina Anggina, Rhauma Syira Christiano Tjokro, Vincencius Cinthiya, Cinthiya Enzelin, Lola Naomi Jevelin, Jevelin Lala, Yohanes Brian Caesaryano Lvina, Kimberly Nurdiyansyah, Dudi Prasetiawan, Iwan Princes, Elfindah Rwanda, Rwanda Setiawan, Johan Setiawan, Jovanka Suryajaya Yosevine, Prisca