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Journal : Jurnal Teknik Informatika (JUTIF)

DEVELOPMENT OF AN E-CANTEEN SYSTEM WITH EXTREME PROGRAMMING TO OPTIMIZE EFFICIENCY, TRANSPARENCY, AND ACCOUNTABILITY IN CANTEEN MANAGEMENT AT THE FACULTY OF ENGINEERING, MATARAM UNIVERSITY Murpratiwi, Santi Ika; Al Qadri, Ramadhani; Widiartha, Ida Bagus Ketut; Irmawati, Budi; Afwani, Royana; Agitha, Nadiyasari; Rassy, Regania Pasca
Jurnal Teknik Informatika (Jutif) Vol. 5 No. 6 (2024): JUTIF Volume 5, Number 6, Desember 2024
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2024.5.6.3449

Abstract

The e-Canteen system enhances efficiency and user experience in electronic-based canteen services. The study aimed to develop a platform streamlining transactions, inventory management, and interaction between customers and canteen service providers. Before implementation, critical issues identified included manual inventory management and slow ordering processes, which created inefficiencies. The system allows customers to order, pay, and track stock availability online, leading to a more efficient and convenient purchasing process. For canteen service providers, automated inventory management helps optimize stock control and reduces manual errors, promising a more streamlined and error-free operation. The E-Canteen system offers significant benefits to both customers and service providers. Customers enjoy a more efficient and convenient purchasing process, while service providers benefit from optimized stock control and reduced manual errors, fostering a more productive and error-free work environment. Additionally, BLU Unram can monitor canteen performance, enabling data-driven decisions to improve services and policies. The system was developed using the Extreme Programming (XP) method, which ensured a user-centered design and rapid adaptation to feedback. Findings from the study demonstrated a 30% improvement in operational efficiency, with user satisfaction significantly increased according to internal surveys. The E-Canteen system addresses the operational challenges of managing canteen services and integrates smoothly with modern technological advancements, providing a scalable and adaptive solution for future growth. This system effectively resolves issues in traditional canteen management, offering benefits to customers and service providers regarding efficiency, convenience, and service quality.
PERFORMANCE COMPARISON OF NAIVE BAYES AND BIDIRECTIONAL LSTM ALGORITHMS IN BSI MOBILE REVIEW SENTIMENT ANALYSIS Ma'we, Hannatul; Husodo, Ario Yudo; Irmawati, Budi
Jurnal Teknik Informatika (Jutif) Vol. 6 No. 1 (2025): JUTIF Volume 6, Number 1, February 2025
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2024.5.6.4178

Abstract

Currently, almost all banks have used mobile banking in conducting banking transactions, one of which is Bank Syariah Indonesia (BSI). BSI mobile is still classified as a new mobile banking application compared to other mobile banking, this certainly still has a low rating and really needs feedback from users which can be seen through reviews on the Google Play Store application. Input in the form of criticism and suggestions from BSI mobile users can be used by BSI mobile as a suggestion for careful supervision and evaluation material in improving its services. This study aims to find the best algorithm to analyze review sentiment on the Google Play Store for the BSI mobile application and provide an overview of the response of application users to application developers based on the results of review data processing. The data mining methodology used in this study is CRISP-DM, using a dataset collected for 6 years (2018-2023) which is annotated into positive and negative labels manually, then modeled using 2 algorithms, namely Naïve Bayes (NB) and Bidirectional LSTM (BiLSTM). The contribution of this study is to test, evaluate and compare the two algorithms (NB and BiLSTM) using the K-Fold Cross Validation (NB) testing model and over-sampling techniques to the minority class (negative) then provide recommendations for the best algorithm. The conclusion of the study is that the BiLSTM algorithm is superior to NB with an accuracy of 94.90 % while the NB algorithm is 94%. In addition, the over-sampling technique is more optimal in increasing the accuracy of the algorithm's performance compared to without over-sampling.