Ivan Hintoro
STMIK Pontianak

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SISTEM PENDUKUNG KEPUTUSAN PEMILIHAN SEPEDA MENGGUNAKAN METODE PROMETHEE Ivan Hintoro; David
PROGRESS Vol 14 No 2 (2022): September
Publisher : P3M STMIK Profesional Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56708/progres.v14i2.337

Abstract

Toko Sepeda Super Top is a shop that sells various kinds of bicycles in Sekadau Regency. Not a few consumers are confused in choosing a bicycle. Based on the survey, 59.3% of respondents stated that it is difficult to choose a new bicycle. To assist consumers in choosing a bicycle, we need a system that can support consumers in making decisions. This study utilizes a Decision Support System (DSS) to support Toko Sepeda Super Top consumers in choosing a bicycle that suits their needs. The DSS method used is the Promethee type I method with the criteria used in the form of brand, price, durability, design, weight, and accessories. The form of research used in this research is a case study with a software design method, namely the prototype method. The result of this research is a bicycle selection DSS software that can be accessed by two levels of users. Admin can process bicycle data by inputting, updating, and deleting data. Then ordinary users can use a decision support system with the Promethee method to assist in bicycle selection.
Genetic Algorithm Application in Route Optimization Using Google Maps API Ivan Hintoro; Sandy Kosasi; David David; Susanti Margaretha Kuway; Gat Gat
CCIT Journal Vol 16 No 2 (2023): CCIT JOURNAL
Publisher : Universitas Raharja

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/ccit.v16i2.2603

Abstract

Route planning from several locations is a common problem encountered. Google Maps provides a feature to plan routes from multiple location but does not provide a feature to find the optimal route from these locations. Based on the survey, 61.9% of respondents have a low level of confidence when planning the optimal route from several locations. So we need software that can help in planning the route. This research utilizes genetic algorithms to help plan routes from several locations. The genetic algorithm used includes components in the form of chromosomes, fitness values, selection, crossover, and mutations. In addition, Google Maps API used as the data source that provides maps, directions, and distance matrices. The design method used extreme programming. The software is made using HTML, CSS, PHP, and JavaScript programming languages with MySQL DBMS. In addition, Black-box and White-box testing method is used in this research. The results of this study are route optimization software that works by using genetic algorithm components to obtain optimal route from several locations with the advantages of using Google Maps API and selecting location points and starting points that are flexible. This study aims to highlight the benefits, limitations, and future prospects of route optimization. The findings of this research will contribute to assist decision-makers in adopting effective strategies related to route optimization.