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All Journal KOMPUTA : Jurnal Ilmiah Komputer dan Informatika Jurnal Tata Kelola dan Kerangka Kerja Teknologi Informasi International Journal of Informatics, Information System and Computer Engineering (INJIISCOM) Journal Of World Science
Dwiguna Sumitra, Irfan
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Computer Science & IT Economics, Econometrics & Finance Electrical & Electronics Engineering Engineering Health Professions Industrial & Manufacturing Engineering Law, Crime, Criminology & Criminal Justice Mechanical Engineering Social Sciences

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Journal : International Journal of Informatics, Information System and Computer Engineering (INJIISCOM)

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Predicting Selling Product of Single Variant Using Arima, Trend Analysis, And Single Exponential Smoothing Methods (Case Study: Swalayan Xyz Store) Dwiguna Sumitra, Irfan; Sidqi, Fajar
International Journal of Informatics, Information System and Computer Engineering (INJIISCOM) Vol. 5 No. 1 (2024): INJIISCOM: VOLUME 5, ISSUE 1, JUNE 2024
Publisher : Universitas Komputer Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34010/injiiscom.v5i1.12486

Abstract

The availability of goods in a store is very important. Predicting is a tool that is used to help predict the data needed by an organization or company. The purpose of this study is to predict the sale of a product that has a high risk of damage and fast expiration time by using existing techniques in forecasting. Forecasting can also be used to make product stock safety at the XYZ Supermarket. The results of this study are in the form of forecasting the sale of a product in a store by using the existing methods of forecasting that are adjusted to the sales data of one product. The method used in forecasting is the ARIMA method, Trend Analysis, and Single Exponential Smoothing. Trend Analysis Method has the highest accuracy with MAPE 9.91%, which means that forecasting is very good, compared to ARIMA with MAPE 37.21% and Single Exponential Smoothing with MAPE 10%. So that the results of the Trend Analysis forecasting will be used for the decision-making process about forecasting stockpiles and stock safety in the future.
Systematic Review of Blockchain Technology in Electronic Medical Record Management: Trends, Challenges, and Future Research Directions Irmayanti, Hani; Atin, Sufa; Heryandi, Andri; Afrianto, Irawan; Rijanto, Estiko; Dwiguna Sumitra, Irfan
International Journal of Informatics, Information System and Computer Engineering (INJIISCOM) Vol. 7 No. 2 (2026): INJIISCOM: VOLUME 7, ISSUE 2, DECEMBER 2026 (Online First)
Publisher : Universitas Komputer Indonesia

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Abstract

This study explores the role of blockchain technology in addressing security and integration challenges within Electronic Medical Record (EMR) systems. Using a Systematic Literature Review (SLR) of 143 selected articles, the research highlights blockchain’s potential to provide decentralized, transparent, and secure data exchange. Key findings indicate that permissioned blockchains, specifically Hyperledger Fabric, are preferred for maintaining data integrity and managing access via smart contracts. To handle big data scalability, the study recommends a hybrid architecture, while identifying the integration of AI and IoT as the future of "smart healthcare”. Despite its promise, the primary hurdle remains the lack of global semantic standardization, which is essential for achieving full interoperability across diverse healthcare facilities. These insights offer a strategic roadmap for developing integrated, patient-centric, and secure medical record systems.
Co-Authors Atin, Sufa Budi Sulistioyuwono, Ahmad Estiko Rijanto Hardyanto, Chrismika Heryandi, Andri Irawan Afrianto Irmayanti, Hani Mukharil Bachtiar, Adam Prapenan, Galih Gustika Reza, Donny Rizki Galang Rahmadani Setiyadi, Angga Sidqi, Fajar Soeryanto Soegoto, Eddy Wahdiniwaty , Rahma