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INDONESIA
Jurnal Mandiri IT
Published by Institute of Computer Science
ISSN : 23018984     EISSN : 28091884     DOI : https://doi.org/10.35335/mandiri
Core Subject : Science, Education,
Computer Science & IT Library & Information Science Mathematics
The Jurnal Mandiri IT is intended as a publication media to publish articles reporting the results of Computer Science and related research.
Arjuna Subject : Ilmu Komputer (semua kategori) - Kecerdasan Buatan
Articles 5 Documents
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Search results for , issue "Vol. 8 No. 2 (2020): January: Coputer Science and related." : 5 Documents clear
Analysis Of Acceptance Of E-Service Using Unified Theory Of Acceptance And Use Of Technology (Utaut) Faculty Of Engineering, Yogyakarta State University Byan Dicky Novaldi
Jurnal Mandiri IT Vol. 8 No. 2 (2020): January: Coputer Science and related.
Publisher : Institute of Computer Science (IOCS)

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Abstract

This study aims to determine the factors that influence the acceptance and use of the application of E-Service services at the Faculty of Engineering, Yogyakarta State University. The model used in this study is The Unified Theory of Acceptance and Use of Technology (UTAUT). This research method uses an explanative quantitative approach. The population in this study were students using E-Service at the Faculty of Engineering, Yogyakarta State University. Sampling of 100 students. The data collection method used is a questionnaire. The analysis technique uses Partial least square (PLS) analysis. The results of this study are that performance expectations have a positive effect on student interest in using E-Service, (Effort expectations have a positive effect on student interest in using E-Service.
Selection Decision Support System Pon Hockey Athletes Central Java Contingent Using Ahp And Promethee Methods Afif Setyo Nugroho
Jurnal Mandiri IT Vol. 8 No. 2 (2020): January: Coputer Science and related.
Publisher : Institute of Computer Science (IOCS)

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Abstract

Hockey is one of the sports that will be competed in the National Sports Week (PON). In the selection process for the Central Java contingent hockey athletes involved many criteria that were assessed, so that in the selection a multi-criteria decision support system was needed for more objective results. The method used in the decision support system for the selection of the Central Java contingent hockey athletes is a combination of the AHP method and the Promethee method. The AHP method is used to weight the criteria and test the consistency of the pairwise comparison matrix, while the Promethee method is used to rank in determining the best alternative. The purpose of the study was to determine the design and build a decision support system for the selection of Central Java contingent PON hockey athletes using a combination of AHP and Promethee methods, and to find out the results of implementing a combination of AHP and Promethee methods of decision support for the selection of PON hockey athletes from the Central Java contingent. The result obtained is a decision support system that has the output of a hockey athlete ranking from the highest net flow value to the lowest net flow value. From the ranking results, it was found that male hockey athletes who had the highest score were athletes with code A3 with a value of 0.564 and female hockey athletes who had the highest score were athletes with code A23 with a value of 0.172,
Application Of Data Mining For Prediction Of Sales Of Best-Selling Electronic Products Using K-Nearest Neighbor Method Yulia Rizki Amalia
Jurnal Mandiri IT Vol. 8 No. 2 (2020): January: Coputer Science and related.
Publisher : Institute of Computer Science (IOCS)

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Abstract

PT. Bintang Multi Sarana Palembang is one of the largest electronics companies in South Sumatra. This company has a wide variety of electronic products on offer. Judging from the large number of consumer demands for electronic products based on sales data for the last 3 years, predictions are needed for sales of the best-selling electronic products, in order to make it easier for the company to plan stock supply. To determine the sales of the best-selling electronic products, data mining classification techniques and the K-Nearest Neighbor algorithm are used. The results of this study are predictions of the best selling electronics sales as many as 6 types of products from 22 types of products sold, namely CTV, Refrigerator, DVD, Speaker, Washing Machine and LCD. Based on the accuracy value of the best-selling product sales classification of 92.51%.
Multimedia Web Development As Video Viewing Media With Php In Local Network Tiara Putra
Jurnal Mandiri IT Vol. 8 No. 2 (2020): January: Coputer Science and related.
Publisher : Institute of Computer Science (IOCS)

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Abstract

Exploring content collections is one of the things that internet cafe users do that is highly expected by managers. Activities carried out to select collections that are interesting and entertaining or even needed by users. This research was conducted with the aim of developing a web-based software to help explore the available film collections, (2) ensuring the quality of the software developed in accordance with the ISO 25010 standard on aspects of functional suitability, usability, and reliability. The research methodology used is Research and Development (R&D) with a waterfall development model. This development model has stages starting from analysis, design, implementation and research testing. The results of this study are: (1) an information system to assist the browsing of film collections for internet café users. (2) the system has met the software quality standard according to the ISO 25010 standard in the functional suitability aspect of 100% (very good), usability aspect of 75.97% (good), and 100% reliability aspect.
Information System Data Mining Market Basket Analysis of Purchase Patterns at Mariden Stores Bandar Lampung Raynaldi Yudhia
Jurnal Mandiri IT Vol. 8 No. 2 (2020): January: Coputer Science and related.
Publisher : Institute of Computer Science (IOCS)

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Abstract

The tendency of customers to buy goods at the same time is one of the factors in setting the self-service layout to optimally place goods. A strategic and precise product layout in its arrangement will be more easily accessible by consumers and will not waste time. For this reason, it is necessary to create a system model that can determine product layout patterns in supermarkets by seeking the highest confidence. Data mining is one field that is growing rapidly because of the large need for added value from large-scale databases that are increasingly being accumulated. For this reason, the market basket analysis method is used. The market basket is defined as an itemset that is purchased simultaneously by customers in a transaction. This method begins with calculating the Apriori Algorithm to find a number of frequent itemsets and continues with the formation of association rules. The results will produce rules that are very useful for providing information to Mariden stores about the placement of goods according to consumer consumption patterns, providing convenience to consumers in the process of finding goods to be purchased without having to ask the shop owner, being able to see the stock of goods that will run out and can determine the stock of goods because this can actually affect consumer spending tastes and sales of a product.

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