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All Journal TELKOMNIKA (Telecommunication Computing Electronics and Control) Indonesian Journal of Science and Technology Aiti: Jurnal Teknologi Informasi
Rung Ching Chen
Chaoyang University of Technology
Computer Science & IT Environmental Science

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Consumer Behavior based on APP use for Food and Beverage Consumption Hendry Hendry; Rung Ching Chen
AITI Vol 15 No 1 (2018)
Publisher : Fakultas Teknologi Informasi Universitas Kristen Satya Wacana

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (303.396 KB) | DOI: 10.24246/aiti.v15i1.1-13

Abstract

McDonalds is one of the brands that release the APP on the Smartphone, the APP is called McDonalds McDelivery APP. It suitable for the way of today’s society way of life, where people are busy and don’t want to line and queue in store to buy foods and beverages for too long. People have a freedom to choose and to order through their Smartphone. The mobile APP offers the advantages, it is easy to operate, easy to use, and doesn’t spend a lot of money. In order to understand the consumers behaviour of using APP, this study conduct the descriptive statistical analysis, variance analysis and regression analysis to detect technology acceptance model for perceived usefulness, ease of use, behaviour intention and actual of use. This study conduct the questionnaire through online google forms and obtained 109 valid questionnaires for analysis. We finds that there was no significant effect on degree of the users, and frequencies of using internet. Perceived usefulness and ease of use of behavioural intentions, behavioural intentions and actual of use had significantly difference.
Hybrid Vector Autoregression Feedforward Neural Network with Genetic Algorithm Model for Forecasting Space-Time Pollution Data Rezzy Eko Caraka; Rung Ching Chen; Hasbi Yasin; Suhartono Suhartono; Youngjo Lee; Bens Pardamean
Indonesian Journal of Science and Technology Vol 6, No 1 (2021): IJOST: VOLUME 6, ISSUE 1, April 2021
Publisher : Universitas Pendidikan Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17509/ijost.v6i1.32732

Abstract

The exposure rate to air pollution in most urban cities is really a major concern because it results to a life-threatening consequence for human health and wellbeing. Furthermore, the accurate estimation and continuous forecasting of pollution levels is a very complicated task.  In this paper, one of the space-temporal models, a vector autoregressive (VAR) with neural network (NN) and genetic algorithm (GA) was proposed and enhanced. The VAR could tackle the issue of multivariate time series, NN for nonlinearity, and GA for parameter estimation determination. Therefore, the model could be used to make predictions, such as the information of series and location data. The applied methods were on the pollution data, including NOX, PM2.5, PM10, and SO2 in Taipei, Hsinchu, Taichung, and Kaohsiung. The metaheuristics genetic algorithm was used to enhance the proposed methods during the experiments. In conclusion, the VAR-NN-GA gives a good accuracy when metric evaluation is used. Furthermore, the methods can be used to determine the phenomena of 10 years air pollution in Taiwan.
Geographically weighted regression analysis of electricity consumption in Indonesian households: aligning with SDG 7 Tommy Novianto; Rezzy Eko Caraka; Prana Ugiana Gio; Rumanintya Lisaria Putri; Agung Sutoto; Rung Ching Chen; Maengseok Noh; Bens Pardamean
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 22, No 6: December 2024
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v22i6.26051

Abstract

The objective of this study is to establish a thorough comprehension of the interaction of population dynamics, poverty rates, minimum wage levels, and regional GDP in relation to household electricity consumption. The main objective is to improve the precision of electricity demand predictions and prevent planning mistakes, such as the considerable surplus of 6-7 GW in the Java Bali system between 2020 and 2023, resulting in major financial losses. We evaluate and compare the models by employing several approaches, such as ordinary least square (OLS) and geographically weighted regression (GWR) with fixed and adaptive bandwidths. We use modified R-squared and corrected Akaike Information Criterion (AICc) values for this assessment. The GWR with adaptive bandwidth is shown to be the most resilient method and is subsequently chosen for modeling. The results indicate that there is a strong correlation between the number of impoverished individuals and electricity use, with a coefficient range of 0.35-0.55. Furthermore, the correlation between poverty rates and power usage is defined by a coefficient that varies between -0.0010 and -0.0030. There is a direct relationship between regional GDP and power growth, as indicated by coefficients ranging from 1,000,000 to 5,000,000. Moreover, the impact of minimum wage levels differs among different locations.
Unlocking insights from Ministry of Marine Affairs and Fisheries annual reports using LDA: a deep dive into SDG 14 Ahmad Marzuqi; Rezzy Eko Caraka; Prana Ugiana Gio; Rung Ching Chen; Maengseok Noh; Bens Pardamean
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 22, No 4: August 2024
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v22i4.26063

Abstract

Annual reports serve as vital instruments for government ministries and agencies, enabling transparency and accountability in managing state budgets (APBN) and activities, thereby fulfilling a crucial role in public accountability, particularly in the context of sustainable development goal (SDG) 14. However, due to their extensive nature, it becomes imperative to conduct topic modeling analysis to discern trends and topics within these reports. In this study, latent Dirichlet allocation (LDA), a prominent topic modeling technique, is employed to analyze the annual reports of the Ministry of Marine Affairs and Fisheries (KKP) Indonesia from 2015 to 2022. Utilizing the coherence score as an evaluation metric, we assess the quality of topic models across each report year. Our findings underscore the consistent emphasis on fisheries and marine-related initiatives, emphasizing their relevance to SDG 14 and Indonesia’s maritime landscape. Ultimately, this study offers valuable insights to inform strategic planning and decision-making processes within the KKP, contributing to the advancement of SDG 14 and promoting sustainable development in Indonesia’s fisheries and marine sectors.
Co-Authors Agung Sutoto Ahmad Marzuqi Bens Pardamean Hasbi Yasin Hendry Maengseok Noh Prana Ugi Rezzy Eko Caraka Rezzy Eko Caraka Rumanintya Lisaria Putri Suhartono Suhartono Tommy Novianto Youngjo Lee