Garuda - Garba Rujukan Digital

Marcelli Indriana

Universitas Multimedia Nusantara

Author-ID : 3791862

Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Engineering

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Articles

Analisis Tingkat Penerimaan Mahasiswa Terhadap Cloud File Hosting Services dengan Metode Technology Acceptance Model Andrianus Bennyanto; Marcelli Indriana
ULTIMA InfoSys Vol 6 No 2 (2015): UltimaInfoSys :Jurnal Ilmu Sistem Informasi
Publisher : Universitas Multimedia Nusantara

There are many mobile and desktop apps available to use for free. Starting from games to productivity apps. One type of productivity apps is cloud file hosting services such as Dropbox and Google Drive. This study aims to determine how Dropbox and Google Drive are accepted to the users. Not just want to get the factors of acceptance, but to get the root of the acceptance. By using the methodology of technology acceptance model and relying on statistical calculations of structural equation modeling software LISREL, the level of acceptance of these two popular applications will be known. Index Terms - Cloud Fire Hosting Services, Level of Acceptance, Technology Acceptance Model, Structural Equation Modelling, LISREL.

Analisis Tingkat Penerimaan Pengguna Layanan Music as a Service Berbayar dengan Metode Unifed Theory Acceptance and Use of Technology Jonathan Cristopher; Marcelli Indriana
ULTIMA InfoSys Vol 9 No 2 (2018): Ultima InfoSys : Jurnal Ilmu Sistem Informasi
Publisher : Universitas Multimedia Nusantara

This study aims to determine the factors that influence the intentions of user behavior in using paid music as a service with the case studies of JOOX VIP apps. The framework of this research is UTAUT2 that has been modified by altering and adding existing constructs, perceived usefulness, effort expectancy, social influence, facilitating conditions, hedonic motivation, price value, habit, and search cost that will influence behavioral intention.Data was obtained by questionnaires collected from 155 respondents, whom use JOOX VIP. The collected data were analyzed by using the SEM method and the results indicates that hedonic motivation, habit, and search cost as a significant determinants of user’s behavior intention to use JOOX VIP.

Applying Neural Network Model to Hybrid Tourist Attraction Recommendations Marcelli Indriana; Chein-Shung Hwang
Ultimatics : Jurnal Teknik Informatika Vol 6 No 2 (2014): Ultimatics: Jurnal Ilmu Teknik Informatika
Publisher : Faculty of Engineering and Informatics, Universitas Multimedia Nusantara

Recently, recommender systems have been developed for a variety of domains. Recommender systems also can be applied in tourism industry to help tourists organizing their travel plans. Recommender systems can be developed by a variety of different techniques such as Content-Based filtering (CB), Collaborative filtering (CF), and Demographic filtering (DF). However, the uses of these techniques individually will have some disadvantages. In this research, we propose a hybrid recommender system to combine the predictions from CB, CF and DF approaches using neural network model. Neural network model will learn by processing a training dataset, comparing the network’s prediction for each dataset with the actual known target value. For each training dataset, the weights are modified to minimize the mean-squared error between the network’s prediction and the actual target value. The experimental results showed that the neural network model outperforms each individual recommendation techniques. Index Terms - Colaborative Filtering, Content-based filtering, Data Mining, Demographic Filtering, Hybrid Recommender System, Neural Network

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