Article Per Year (5 Year)
p-Index From 2021 - 2026
0.702
P-Index
This Author published in this journals
All Journal Merkurius: Jurnal Riset Sistem Informasi dan Teknik Informatika
Melri Deswina
Unknown Affiliation
Computer Science & IT

Published : 4 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 4 Documents
Search

 1 
Design of Travel Ticket Booking Application with Web-Based Chatbot Using Dialogflow Natural Language Processing (NLP) Desi Susanti; Resmi Darni; Yeka Hendriyani; Melri Deswina
Merkurius : Jurnal Riset Sistem Informasi dan Teknik Informatika Vol. 3 No. 1 (2025): Merkurius : Jurnal Riset Sistem Informasi dan Teknik Informatika
Publisher : Asosiasi Riset Teknik Elektro dan Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61132/merkurius.v3i1.684

Abstract

The rapid development of information technology and telecommunications has driven companies and MSMEs to adopt desktop, mobile, and web-based applications to enhance operational performance. PT HPS Painan Padang, previously relying on manual ticket bookings, faced challenges in efficiency and susceptibility to brokering practices. To address this, a web-based travel ticket booking application was developed, enabling customers to book tickets online more practically, quickly, and conveniently, anytime and anywhere. The integration of Natural Language Processing (NLP) technology in the form of a chatbot further enhances service efficiency and responsiveness. This feature provides real-time information on departure schedules, seat selection, and payment transactions while also supporting sentiment analysis and swift responses to customer feedback, ultimately improving service quality. The application, built using PHP, MySQL, and CodeIgniter with a Prototype development approach, adapts to changing market demands. Testing via GTmetrix on the https://desistravel.xyz/backend page demonstrated excellent performance with an 88% Performance score, 95% Structure score, and optimal Web Vitals metrics, indicating a fast, responsive, and stable platform. The final product is a user-friendly web-based ticket booking application supported by an intelligent chatbot, offering a seamless user experience, enhancing customer satisfaction, and streamlining the travel booking process efficiently.
Implementasi Algoritma K-Means Clustering untuk Pengelompokan Pola Permintaan Barang dalam Sistem Manajemen Inventori PT Semen Padang Ifdal Lisyukri; Melri Deswina
Merkurius : Jurnal Riset Sistem Informasi dan Teknik Informatika Vol. 3 No. 4 (2025): Juli : Merkurius : Jurnal Riset Sistem Informasi dan Teknik Informatika
Publisher : Asosiasi Riset Teknik Elektro dan Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61132/merkurius.v3i4.805

Abstract

This research aims to implement the K-Means Clustering algorithm in clustering patterns of goods demand in the inventory management system at PT Semen Padang. With the development of industrial technology and the need for an efficient inventory management system, this research identifies problems faced by the company, such as manual records that are prone to errors and delays. The developed web-based system allows real-time data integration, automation of the goods request process, and analysis of demand patterns using the K-Means algorithm. The results show that the implementation of this system can improve the efficiency of inventory management, minimize recording errors, and support better decision-making in the procurement of goods.
Penerapan Algoritma Apriori dalam Pengembangan Sistem Rekomendasi Produk untuk Meningkatkan Penjualan Impulsif melalui Analisis Pola Pembelian Rahma Hidayani, Elsa; Melri Deswina
Merkurius : Jurnal Riset Sistem Informasi dan Teknik Informatika Vol. 3 No. 4 (2025): Juli : Merkurius : Jurnal Riset Sistem Informasi dan Teknik Informatika
Publisher : Asosiasi Riset Teknik Elektro dan Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61132/merkurius.v3i4.1006

Abstract

This research aims to develop a recommendation system that can help retail business owners design more effective, data-driven promotional strategies. This system utilizes data mining techniques and the Apriori algorithm to extract association rules from consumer transaction data, thereby identifying more specific and accurate consumer purchasing patterns. Based on these patterns, the system can provide relevant promotional recommendations, such as product bundling, buy-one-get-one offers, or special discounts, which can attract consumer interest and increase sales. The system's implementation process is presented in the form of an interactive dashboard, which allows business owners to upload their transaction data, adjust analysis parameters, and visualize the promotional recommendation results in a way that is easier to understand and can be directly applied to their marketing strategies. This system not only provides well-structured promotional recommendations but also enables retail business owners to make more informed and efficient decisions in determining the type of promotion to implement, based on insights gained from analyzing their own transaction data. By utilizing this system, business owners can optimize their promotional strategies more efficiently and effectively, because they can quickly identify promotions that best suit consumer purchasing patterns. This can increase impulse sales, as relevant promotions will encourage consumers to purchase more products. Furthermore, this system shows great potential in increasing consumer engagement, as the promotions provided are more personalized and tailored to each consumer's preferences. Therefore, the implementation of this recommendation system has the potential to drive significant sales growth and help retail business owners achieve greater profits, as well as accelerate their business decision-making process. This system, ultimately, not only benefits business owners but also enhances the consumer shopping experience with promotions that are more tailored to their needs and preferences.
Implementation of the Advanced Encryption Standard (AES) Cryptographic Algorithm in Library Information Systems for Member Data Security at the Cipanas Presidential Palace Putri Maharani; Jusmardi Jusmardi; Ahmaddul Hadi; Melri Deswina
Merkurius : Jurnal Riset Sistem Informasi dan Teknik Informatika Vol. 3 No. 4 (2025): Juli : Merkurius : Jurnal Riset Sistem Informasi dan Teknik Informatika
Publisher : Asosiasi Riset Teknik Elektro dan Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61132/merkurius.v3i4.1009

Abstract

This study aims to develop a data security system for the Pancadaya Waste Bank web-based application by implementing a hybrid cryptography algorithm combining AES and RSA. The main problem identified is the vulnerability of manually recorded and unsecured transaction data. The research applied a qualitative approach through interviews with system users and the Environmental Agency, as well as literature reviews on hybrid cryptography algorithms. The system was developed using the Rapid Application Development (RAD) method and implemented using PHP, MySQL, and the OpenSSL library. The results show that the system successfully encrypts transaction data using AES and secures the AES key with RSA, thereby enhancing data security. Testing with GTmetrix indicates excellent application performance. Furthermore, the system can display and decrypt real-time transaction data in receipt form for both deposit and withdrawal processes. This application provides an innovative solution to data management and transaction security issues in digital-based waste bank systems.
Co-Authors Ahmaddul Hadi Desi Susanti Ifdal Lisyukri Jusmardi Putri Maharani Rahma Hidayani, Elsa Resmi Darni Yeka Hendriyani