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SISTEM PENUNJANG KEPUTUSAN PEMILIHAN KETUA RT 10 DESA SUKAJAYA RW 15 DENGAN METODE SIMPLE ADDITIVE WEIGHTING (SAW) Sulistiawan, Sulistiawan; Solihin, Gesit; Fitria, Farhana; Widyastuti, Reni
SIBATIK JOURNAL: Jurnal Ilmiah Bidang Sosial, Ekonomi, Budaya, Teknologi, Dan Pendidikan Vol. 3 No. 6 (2024): May
Publisher : Penerbit Lafadz Jaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54443/sibatik.v3i6.2060

Abstract

The selection of the Head of RT in Sukajaya Village RW 15 is a crucial process in the development of the local community. This research aims to evaluate the effectiveness of implementing the Decision Support System (DSS) based on the Simple Additive Weighting (SAW) method in the selection of the Head of RT. The focus of the research is on the role of DSS in improving the transparency, objectivity, and efficiency of the selection process, as well as its impact on community participation and community development. The research method involves direct observation, interviews, and literature review. The results show that the use of SAW in DSS can improve the objectivity and efficiency of the selection process of the Head of RT, and positively impact community participation in village development. This study contributes to the development of a more modern and transparent leadership selection system at the local level.
The Effect of Quality Product, Price Perception, and Promotion onVivo Smartphone Purchase Decisions: A Study at the Archa PhoneCounter in Bekasi Melyani, Melyani; Swastika, Rahayu; Widyastuti, Reni; Shaura, Rizkiana Karmelia; Pramularso, Eigis Yani; Anggarini, Desy Tri; Tambunan, Diana
Journal of Management and Informatics Vol. 4 No. 3 (2025): December Season | JMI: Journal of Management and Informatics
Publisher : University of Science and Computer Technology

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/jmi.v4i3.203

Abstract

This study investigates the influence of product quality, price perception, and promotion on Vivosmartphone purchase decisions. A quantitative survey was administered to 100 consumers at the ArchaPhone Counter in Bekasi using purposive sampling. Multiple linear regression analysis revealed thatall three variables have a significant positive partial effect on the purchase decision. The modelexplained 85% of the variance (Adjusted R² = 0.726), confirming their simultaneous influence. Productquality was identified as the most dominant predictive factor, validating its critical role in consumerchoice. 
PERANCANGAN SISTEM INFORMASI PELAYANAN JASA LAUNDRY BERBASIS ANDROID PADA LAUNDRY EXPRESS Widyastuti, Reni; Fahri Lubis, Zidanne Zulkifli
JIPETIK:Jurnal Ilmiah Penelitian Teknologi Informasi & Komputer Vol 3, No 1 (2022): JIPETIK : Jurnal Ilmiah Pendidikan Teknologi Informasi & Komputer
Publisher : Universitas PGRI Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26877/jipetik.v3i1.11893

Abstract

Laundry Express is a business unit that provides washing and drying services for fabrics such as clothes, bed linen, curtains and others with the Jabotabek area of operation. This laundry service is provided to consumers in the form of washing services consisting of ironing and dry cleaning as well as laundry pick-up and drop-off services by couriers. Currently services at Laundry Express are carried out conventionally where all recording and reports are done manually so that problems occur such as shipping transaction records and laundry services that are lost or forgotten to be recorded so that Laundry Express consumers complain as a result of not optimal service and the difficulty of making a recap of the reports provided. for laundry owners. The author in this study designed a system that functions to overcome the problems of Laundry Express services by using an object-oriented approach where the waterfall is a system development method. System depiction with UML using the Java programming language and an android-based editor, namely Android Studio, which functions to build applications provided that users can use it with a minimum requirement of Android 5.0 lollipop version. This research is a solution for Laundry Express for better service by providing easy access to data, fast and accurate transactions and report generation
The Effect of Compensation on Employee Performance Through Work Motivation as an Intermediary Variable (Case Study at Archa Beauty Clinic Bekasi) Shaura, Rizkiana Karmelia; Handoko, Melyani; Widyastuti, Reni; Swastika, Rahayu; Tambunan, Diana; Anggarini, Desy Tri; Kurniawan, Hendra
Journal of Management and Informatics Vol. 5 No. 1 (2026): April Season | JMI: Journal of Management and Informatics
Publisher : University of Science and Computer Technology

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/jmi.v5i1.335

Abstract

The rapid growth of digital payment systems has increased the complexity of financial transactions, making credit card fraud detection more challenging, particularly due to evolving fraud patterns and highly imbalanced datasets. Conventional machine learning approaches often struggle to capture temporal dependencies and adapt to new fraud behaviors, while centralized data processing raises privacy concerns. This study proposes a hybrid fraud detection framework that integrates Bidirectional Long Short-Term Memory (BiLSTM), Autoencoder, and Federated Learning to improve detection performance while preserving data confidentiality. The BiLSTM component models sequential transaction behavior from both forward and backward directions, while the autoencoder identifies anomalies based on reconstruction errors. Federated Learning enables collaborative model training across multiple institutions without sharing sensitive data. Experimental evaluation using benchmark datasets shows that the proposed model achieves high classification performance, with improved precision, recall, and overall stability compared to traditional and standalone deep learning models. The framework effectively handles class imbalance and detects both known and emerging fraud patterns. This study contributes a scalable and privacy-preserving solution for real-world fraud detection, supporting secure collaboration and enhancing model generalization in distributed financial environments.