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Mariska Putri Pratiwi
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Computer Science & IT

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IMPLEMENTASI PENGENALAN SISTEM UNTUK PEMANDU OBJEK WISATA MANDAILING NATAL BERBASIS GEOGRAPHIC INFORMATION SYSTEM Dian Araya; Mariska Putri Pratiwi
Computer Science and Industrial Engineering Vol 11 No 4 (2024): Comasi Vol 11 No 4
Publisher : LPPM Universitas Putera Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33884/comasiejournal.v11i4.9158

Abstract

The tourism industry is one of the most dynamic and rapidly growing economic sectors in the world. Every year, millions of tourists travel to various destinations around the world, bringing a significant economic impact to destination countries. Apart from contributing to national income and job creation, this industry also encourages cultural exchange and understanding between nations. In the research process, researchers design research designs to provide structure to research activities from beginning to end. This includes steps such as determining the research problem, formulating research objectives, asking research questions, choosing research methods, collecting and analyzing data, and formulating conclusions and research results. This system uses Google MapsAPI to determine distribution points in the Tourism Geographic Information System in Mandailing Natal Regency. The system that has been built makes it easy for users to access distribution points and related information regarding natural tourist attractions in Mandailing Natal Regency. A Geographic information system has been built which includes tourist location points, tourist descriptions, detailed images, news, events and visitor services.
RANCANG BANGUN SISTEM PAKAR UNTUK MENDIAGNOSA PENYAKIT PADA KULIT DENGAN METODE FOWARD CHAINING Lisnauli Saragih; Mariska Putri Pratiwi
Computer Science and Industrial Engineering Vol 12 No 4 (2025): Comasie Vol 12 No 4
Publisher : LPPM Universitas Putera Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33884/comasiejournal.v12i4.9847

Abstract

This study aims to develop an artificial intelligence-based expert system to help diagnose skin diseases. This system is designed to help users, especially the general public, identify the type of skin disease based on the symptoms they experience. By collecting data from dermatologists and medical literature, this system is built using the forward chaining method. The system's knowledge base contains rules that link symptoms to certain skin diseases. System testing shows high accuracy in diagnosing various types of skin diseases, such as psoriasis, eczema, and fungal infections. With this expert system, it is expected to increase public access to skin health information and help early detection of skin diseases.
PENERAPAN METODE FIFO (FIRST IN FIRST OUT) DALAM MERANCANG SISTEM PERGUDANGAN BERBASIS WEB Peter Fernando; Mariska Putri Pratiwi
Computer Science and Industrial Engineering Vol 12 No 4 (2025): Comasie Vol 12 No 4
Publisher : LPPM Universitas Putera Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33884/comasiejournal.v12i4.9877

Abstract

Overstock and delays in fulfilling requests for spare parts at Hyundai Nagoya can occur due to ineffective stock management. The objective of this research is to develop a web-based platform warehousing system that increases the efficiency of goods rotation using the First In First Out (FIFO) method. In addition, the Random Forest algorithm is used to categorize components according to goods movement patterns. The movement patterns of goods are divided into three categories: fast moving, medium moving and slow moving categories. The data analysed includes order history, frequency of use, and stock of goods for the last six months. By implementing a web-based system, real-time stock monitoring and order recommendations based on historical demand patterns can be made. The study's findings demonstrate that the FIFO approach effectively lowers the chance of old products piling up, increasing recording accuracy, and speeding up spare parts distribution. With a classification model accuracy of 75%, this method can improve warehouse management and help make more accurate decisions. In conclusion, the FIFO method can be used in a web-based warehousing system to optimize spare parts stock management at Hyundai Nagoya. Keywords: FIFO, Hyundai Nagoya, Random Forest, Stock Management, Warehousing System
Co-Authors Dian Araya Lisnauli Saragih Peter Fernando