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All Journal Jutisi: Jurnal Ilmiah Teknik Informatika dan Sistem Informasi Jurnal Algoritma, Logika dan Komputasi
Sipayung, Evasaria Magdalena
Universitas Bunda Mulia
Computer Science & IT Engineering

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Decision Support System for Building Material Supplier Selection using Simple Additive Weighting (SAW) Method Sipayung, Evasaria Magdalena; Lokasurya, Erik; Kristina, Sonna
Jurnal Algoritma, Logika dan Komputasi Vol 5, No 1 (2022): Jurnal ALU, Maret 2022
Publisher : Universitas Bunda Mulia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30813/j-alu.v5i1.3628

Abstract

XYZ Store is a retail store that sells goods in the form of building materials located in Bandung Regency. This shop sells types of cement products, water pumps and PVC pipes where this shop gets its products by ordering from suppliers. This shop is having difficulty choosing a supplier because it takes time to determine a supplier. Suppliers are contacted by telephone to ask about the availability and price of the building materials needed. If the supplier has the goods, he will buy them immediately and not ask other suppliers. The criteria used in determining suppliers are based on price and availability of goods. The criteria required by this shop are price, product availability, expiry date and delivery speed in accordance with the shop's condition when the goods are needed. The aim of this research is to create a decision support system that can provide supplier recommendations so as to help in selecting suppliers that match the criteria using the Simple Additive Weighting (SAW) method. Supplier selection decision support systems can provide the best alternative suppliers by ranking suppliers with the best performance. This web-based SPK was developed using the programming language PHP, Javascript and using an SQL database.
IMPLEMENTASI APRIORI PADA PENJUALAN BARANG DENGAN METODE ASOSIASI UNTUK STRATEGI MARKETING Putra, Josef Cristian Adi; Sipayung, Evasaria Magdalena
Jurnal Algoritma, Logika dan Komputasi Vol 7, No 1 (2024): Maret 2024
Publisher : Universitas Bunda Mulia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30813/j-alu.v7i1.5991

Abstract

Technological developments have led to significant changes in various sectors, including business. The way of trading has also gone digital through e-commerce platforms and social media. Business competition is getting tougher with the emergence of many startups. Entrepreneurs must innovate in order to survive the fierce competition. Association analysis is used in Data mining to find rules for combining items. The advantage of this technique lies in the use of efficient algorithms through high-frequency pattern analysis or frequent pattern mining. This algorithm examines candidate itemsets that evolve from the results of frequency itemsets through support-based pruning, to eliminate insignificant itemsets with a Minimum Support value of 1. The Apriori algorithm association method is used to determine item relationships and identify consumer buying patterns, as well as help entrepreneurs increase product sales. This research proves the effectiveness of the Apriori algorithm in managing transaction data and generating valuable information for companies. This research provides input to companies that want to utilize transaction data to improve business effectiveness. The main goal of the Apriori algorithm is to find itemsets that frequently co-occur in the data. The algorithm adopts a bottom-up approach, where smaller itemsets are analyzed first and larger itemsets are built from smaller itemsets. The steps in creating itemsets using the association method include problem identification, transaction data collection, itemset identification, determining the Minimum Support and confidence values, and establishing association rules. This research develops an application that calculates the Apriori algorithm with the associative method through a calculation table and a summary of the calculation results. After testing, the application shows accurate calculation results and can be checked manually. The drawback of this application is that the notification of errors in the data is only displayed one by one.
VEHICLE LICENSE PLATE DETECTION USING YOLO ALGORITHM Nugraha, Kenneth Christoper; Sipayung, Evasaria Magdalena
Jurnal Algoritma, Logika dan Komputasi Vol 6, No 2 (2023): Jurnal ALU, September 2023
Publisher : Universitas Bunda Mulia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30813/j-alu.v6i2.4739

Abstract

Urban population growth has created challenges in efficient parking space management. Manual data collection is time-consuming and error-prone, especially at night. Modern technology-based solutions are urgently needed. This research focuses on an innovative parking management system using YOLO for real-time object detection, including license plates. The objective is to assess the YOLO algorithm's accuracy in license plate detection. The methodology follows software development best practices, utilizing Python and Tkinter GUI for an intuitive interface. YOLO and EasyOCR enable object detection and character recognition. Results show high accuracy: 88.8% for HD and 86.3% for sub-HD resolutions. YOLO proves reliable for license plate data collection, reducing manual intervention and enhancing parking management.
Perancangan Prototype Pendeteksi Lokasi Pencurian Baterai Tower Berbasis Internet of Things Kusuma, Kevin; Sipayung, Evasaria Magdalena
Jutisi : Jurnal Ilmiah Teknik Informatika dan Sistem Informasi Vol 13, No 2: Agustus 2024
Publisher : STMIK Banjarbaru

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35889/jutisi.v13i2.2135

Abstract

Tower battery theft is a problem that can cause large losses in Indonesia. Therefore, this research aims to overcome the problem of tower battery theft based on the Internet of Things (IoT). The type of method used in this research is designing a prototype to detect tower battery theft locations. The designed prototype consists of NodeMCU Esp8266, PIRm sensor and GPS Neo 6Mv2 with the Telegram application as a communication module. The PIR sensor will detect movement that occurs around the area where this sensor is placed and provide notifications in the form of a Google Maps link via the Telegram application to the user's cellphone if theft or movement occurs. In this research trial, it was carried out to ensure the performance and accuracy of the system in detecting the location of tower battery theft. From the test results, the average distance between the default coordinates from Google Maps and the prototype coordinates is 0.9963 meters from 30 different locations. The average response time of this prototype is 7.73 seconds from 30 different locations and 12.67 seconds based on prototype simulations.Keyword: Internet of things; Sensor; Prototype; Sensor PIR; Telegram AbstrakPencurian baterai tower merupakan masalah yang dapat menyebabkan kerugian yang besar di Indonesia. Oleh karena itu, penelitian ini bertujuan untuk mengatasi masalah pencurian baterai tower berbasis Internet of Things (IoT). Jenis metode yang dilakukan pada penelitain ini berupa perancangan prototype pendeteksi lokasi pencurian baterai tower. Prototype yang dirancang terdiri dari NodeMCU Esp8266, sensor PIR, dan GPS Neo 6Mv2 dengan aplikasi Telegram sebagai modul komunikasi. Sensor PIR akan mendeteksi gerakan yang terjadi pada sekitar area sensor ini ditempatkan dan memberikan notifikasi berupa link Google Maps melalui aplikasi Telegram ke ponsel pengguna jika terjadi pencurian dan pergerakan. Dalam uji coba penelitian ini, dilakukan untuk memastikan kinerja dan akurasi sistem dalam mendeteksi lokasi pencurian baterai tower. Dari hasil pengujian, jarak rata-rata antara koordinat default dari Google Maps dan koordinat prototype sejauh 0,9963 meter dari 30 lokasi yang berbeda. Waktu respon rata-rata dari prototype ini selama 7,73 detik dari 30 lokasi yang berbeda dan 12,67 detik berdasarkan simulasi prototype. 
IMPLEMENTASI ALGORITMA FUZZY MAMDANI DAN FISHER-YATES SHUFFLE PADA GAME CITY STREET RUN Chandra, Kelvin; Sipayung, Evasaria Magdalena
Jurnal Algoritma, Logika dan Komputasi Vol 7, No 2 (2024)
Publisher : Universitas Bunda Mulia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30813/j-alu.v7i2.7876

Abstract

This City Street Run game is made by taking a city street background and characters running to collect coins and pass obstacles to get the highest score. The character will run through object obstacles in the form of orange cones and red barriers while collecting coins which will affect the player's score. The reason the author makes this game is that it is expected to improve thinking power, improve concentration, solve problems and improve brain memory. This study uses the Mamdani Fuzzy Algorithm because this algorithm can make scores affect the character's running speed. Then this research also uses the Fisher-Yates Shuffle Algorithm so that coins can be spawned randomly in the City Street Run game. As well as implementing the Multimedia Development Life Cycle Method for the City Street Run game because the City Street Run game combines text, images and audio. Based on the test results with Black Box Testing, it can be concluded that all the features contained in the City Street Run game have run as expected and based on the test results with User Acceptance Testing through a questionnaire, with a percentage value of 85.5%, so it can be concluded that the City Street Run game is classified as very good and can be accepted and played by users. Based on these results, it can be concluded that the design of the City Street Run game was successfully implemented using the Multimedia Development Life Cycle method, the fuzzy mamdani algorithm and the Fisher-Yates Shuffle algorithm.
Co-Authors Chandra, Kelvin Kristina, Sonna Kusuma, Kevin Lokasurya, Erik Nugraha, Kenneth Christoper Putra, Josef Cristian Adi