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All Journal International Journal of Electrical and Computer Engineering Jurnal Buana Informatika Journal of Information Systems and Informatics Jurnal Ilmiah Betrik : Besemah Teknologi Informasi dan Komputer JIIP (Jurnal Ilmiah Ilmu Pendidikan) Teknomatika: Jurnal Informatika dan Komputer
Ahmad Luthfie
Universitas Islam Indonesia
Humanities Computer Science & IT Education Electrical & Electronics Engineering Mathematics Other

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Journal : Journal of Information Systems and Informatics

 1 
Towards Privacy by Design on the Internet of Things (IoT) Use: A Qualitative Descriptive Study Ahmad Luthfi; Emigawaty Emigawaty
Journal of Information System and Informatics Vol 4 No 2 (2022): Journal of Information Systems and Informatics
Publisher : Universitas Bina Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51519/journalisi.v4i2.302

Abstract

From remote control and surveillance to energy and health monitoring, IoT devices provide cutting-edge services to improve our lives. Nevertheless, IoT technologies raise complicated, innovative privacy-related issues that might limit their widespread adoption. Due to the passive nature of many IoT devices, it may be challenging for users to understand that their personal information is being gathered. Therefore, this paper aims to examine the Privacy by Design IoT application idea. We adapted the seven principles of Ann Cavoukian's Privacy by Design, which were first developed. In this study's qualitative descriptive methodology with interview sections are used. The results indicate that the majority of IoT users agree with and have high expectations for the Privacy by Design concept to be one of the remedies to the imbalance between concerns about the risks and benefits of using IoT.
Information System Project Development Management Ratio Set Assy GP Using Scrum Method Muchammad Abdulloh Munib; Ahmad Luthfi
Journal of Information System and Informatics Vol 5 No 1 (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.v5i1.456

Abstract

In April 2011, the term Industry 4.0 was introduced at the Hannover Fair. PT Yamaha Indonesia was an early adopter, implementing it in their piano manufacturing process. To achieve production targets, it is necessary to monitor the production series, including the assembly of piano components into a complete unit. SAP, a software platform, is used to improve efficiency, with one of its modules being K-STAFF, which has four derivative applications: K-Master, K-Ticket, K-Score, and K-Tiptop. However, the current production process is monitored through scanning input using a SAP derivative application, which is not visualized in the production area, leading to failed targets. To address this issue, a system is required to visualize input scan results to enable direct monitoring of the production process and achieve production targets. As a result, PT Yamaha Indonesia developed the Ratio Set Assy Grand Piano system using the SCRUM method. This system includes an MIS that monitors the ratio set of piano, visualized with Apache E-Charts, manages planning, and identifies priority spare parts in real-time. This research contributes to the development of a more efficient and effective production process
Development of Logistics Driver Tenko System (ORIENT) Application Using Scrum Framework Adelia Maharani; Ahmad Luthfi
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.v5i2.522

Abstract

Occupational safety and health hold significant importance for both agencies and individuals alike. A crucial aspect of assessing driver readiness involves examining their physical well-being. Truck drivers who possess unhealthy physical conditions face a four-fold higher risk of work accidents compared to those with sound physical health. PT. Toyota Motor Manufacturing Indonesia (TMMIN), being a manufacturing company, must prioritize occupational safety and health, particularly within the logistics domain. Presently, some logistics partners collaborating with TMMIN adhere to their own standards when conducting checks, relying on paper records for documenting the results. Unfortunately, this approach hinders proper archiving of inspection records and fails to establish a direct link with logistics partner customers in cases involving drivers with health issues. Hence, PT. Toyota Motor Manufacturing Indonesia is dedicated to enhancing the quality of driver health checks through logistics partners by implementing an integrated recording system called the Logistics Driver Tenko System Application (ORIENT). The development of ORIENT is based on the Scrum framework. This research aims to offer insights into the direct implementation of the Scrum method in project development.
Comparison of Naïve Bayes and Logistic Regression in Sentiment Analysis on Marketplace Reviews Using Rating-Based Labeling Satya Abdul Halim Bahtiar; Chandra Kusuma Dewa; Ahmad Luthfi
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.v5i3.539

Abstract

This research focuses on sentiment analysis in the marketplace reviews in Google Play Store, a platform for downloading Android applications and providing reviews. Sentiment analysis is essential for understanding user responses to applications, particularly in the app marketplace. In this study, two machine learning algorithms, Naïve Bayes and Logistic Regression, are employed to classify user reviews. The application rating is used as a reference to determine the sentiment of each comment. The dataset is divided into two conditions: using 2 labels (positive & negative) and 3 labels (positive, neutral, & negative). The test results indicate that the highest performance is achieved by classifying with Logistic Regression on the Shopee dataset with 2 labels. The accuracy reaches 84.58%, precision reaches 84.66%, and recall reaches 84.63%. Additionally, the fastest processing time occurs when testing the Lazada 2-label dataset with Naïve Bayes, taking only 0.038 seconds. Overall, the research suggests that datasets with 2 labels tend to yield higher accuracy compared to datasets with 3 labels.
Co-Authors Abdul Haris Muhammad Adelia Maharani Bambang Sugiantoro Chandra Kusuma Dewa Emigawaty Imam Riadi Imam Riadi Isriade Putra Muchammad Abdulloh Munib Nur Widiyasono Nuril Anwar Satya Abdul Halim Bahtiar Yudi prayudi