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The Legal Aspect of Consumers' Protection from Pop-Up Advertisements in Indonesia Prastyanti, Rina Arum; Yafi, Eiad; Wardiono, Kelik; Budiono, Arief
Lentera Hukum Vol 8 No 1 (2021): LENTERA HUKUM
Publisher : University of Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19184/ejlh.v8i1.23479

Abstract

Pop-up advertisements have become prevalent on websites. When users click on the banner, they navigate a separate window; banner and pop-up advertisements contain attractive audio-visual and animated graphics. This intrusive advertising has not explicitly regulated Indonesia's current legislation, including Electronic Transaction and Information Law 11/2008 (ITE Law). Also, it is exempted in the Indonesian Pariwara Ethics, guidelines for advertising ethics and procedure in Indonesia. This study aimed to revisit consumers’ protection toward pop-up advertisements in Indonesia, with two main discussions. First, it discussed online consumers' perceptions of pop-up advertisements and the classification of their responses. Second, it enquired to what extent the legal and ethics protection for online consumers in Indonesia. By using empirical legal research, this study concluded that the ITE Law prohibits anyone from spreading online information with content that violates immorality and gambling, as it often contains in pop-up advertisements. Through the lens of business ethics, pop-up advertisements are new media and they should not be installed in such a way as to interfere with the freedom of internet users, given that pop-up advertisements do not reflect the ethics of honesty, trust, and advice in business. KEYWORDS: Consumers’ Protection, Online Advertisements, Business Ethics.
A hybrid deep learning optimization for predicting the spread of a new emerging infectious disease Nastiti, Faulinda Ely; Musa, Shahrulniza; Yafi, Eiad
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 13, No 2: June 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v13.i2.pp2036-2048

Abstract

In this study, a novel approach geared toward predicting the estimated number of coronavirus disease (COVID-19) cases was developed. Combining long short-term memory (LSTM) neural networks with particle swarm optimization (PSO) along with grey wolf optimization (GWO) employ hybrid optimization algorithm techniques. This investigation utilizes COVID-19 original data from the Ministry of Health of Indonesia, period 2020-2021. The developed LSTM-PSO-GWO hybrid optimization algorithm can improve the performance and accuracy of predicting the spread of the COVID-19 virus in Indonesia. In initiating LSTM initial weights with weaknesses, using the hybrid optimization algorithm helps overcome these problems and improve model performance. The results of this study suggest that the LSTM-PSO-GWO model can be utilized as an effective and reliable predictive tool to gauge the COVID-19 virus’s spread in Indonesia. 
Hexahelix collaboration in developing halal tourism in Indonesia Yudithia, Yudithia; Sentosa, Ilham; Yafi, Eiad
Indonesian Tourism Journal Vol. 1 No. 1 (2024): May 2024
Publisher : CV. Austronesia Akademika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69812/itj.v1i1.13

Abstract

Tourism collaboration is to create a series of tourism programs or activities that are more diverse, attractive, and sustainable to attract tourists to visit an area or tourist destination on an ongoing basis. The purpose of the Hexahelix collaborative research in the development of halal tourism in Indonesia is to examine the potential for halal tourism in Indonesia and how this potential can be optimally and sustainably developed through collaboration between Government, community, academia, private sector, law and the mass media which have their respective roles. The method of using post-positivism qualitative research sees reality as a construction continuously developed through subjective experiences, so post-positivism qualitative research emphasizes in-depth interpretation and understanding related to phenomena. Logical analysis can identify errors or weaknesses in an argument or ensure that the conclusions drawn from the argument are correct and consistent. The results show that the hexahelix collaboration significantly contributes to accelerating halal tourism development in Indonesia. In this study, it was also found that the development of halal tourism in Indonesia has enormous potential as a type of tourism trending and experiencing rapid growth in Indonesia and the world. Thus, it is hoped that the development of halal tourism in Indonesia can be successful and provide greater benefits for economic development and people's welfare.
The Penta-Helix Approach in Implementing the Policy of Revitalizing Traditional Markets in Tanjungpinang City Yudithia, Yudithia; Yafi, Eiad; Khan, Muhammad Shahid
Journal Governance Society Vol. 1 No. 2 (2024): November, 2024
Publisher : CV. Austronesia Akademika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69812/jgs.v1i2.47

Abstract

Traditional markets are crucial centers for trade and economic activities within the community. However, the rise of modern markets has led to a decline in the popularity of traditional markets among the public. Therefore, revitalization policies for traditional markets are necessary to enhance their quality and provide significant benefits to the community. This study employs a descriptive qualitative research method with a post-positivist approach. The findings indicate that the Penta-Helix approach is effective in implementing revitalization policies for traditional markets in Tanjungpinang City. The Penta-Helix model can engage five key actors: the government, industry, academia, society, and media, in formulating, executing, and evaluating the revitalization programs for traditional markets in Tanjungpinang. The impact of revitalizing traditional markets in Tanjungpinang is quite significant, including increased visitor numbers, improved environmental health, enhanced product quality, job creation, and heightened community pride in their traditional markets. The implementation of revitalization policies involves reorganizing merchandise, providing cleaning services, controlling product quality, developing local products, and introducing derivative programs. Strong support and commitment from local government and all stakeholders are essential in overcoming challenges such as political factors, limited resources, and a lack of public awareness. Recommendations emphasize the need for proactive efforts and active roles from local government and all stakeholders in executing effective and sustainable policies.
EPIDEMIC PROGNOSIS: COMPARATIVE PERFORMANCE OF MACHINE LEARNING AND DEEP LEARNING MODELS FOR PREDICTING VIRUS TRANSMISSION DYNAMICS Ely Nastiti, Faulinda; Musa, Shahrulniza; Yafi, Eiad; Ardiyanto, Marta
Proceeding of the International Conference Health, Science And Technology (ICOHETECH) 2023: Proceeding of the 4th International Conference Health, Science And Technology (ICOHETECH)
Publisher : LPPM Universitas Duta Bangsa Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47701/icohetech.v4i1.3401

Abstract

The transmission of viral diseases, such as COVID-19, influenza, and other viral strains, poses a substantial worldwide challenge. In the context of health, it is necessary to possess a comprehensive comprehension, meticulous examination, and precise anticipation of the dissemination of this infectious disease. Nonetheless, the presence of diverse data characteristics among different nations poses a considerable obstacle in the development of prediction models for assessing the transmission, mortality, and recovery rates in Indonesia. Understanding the intricacies of viral transmission poses a significant hurdle because to the fluctuating nature of the generalization rate, which is contingent upon country-specific data.The research entailed a comparison of different predictive models, including Random Forest, Simple Linear Regression (SLR), Gaussian Naive Bayes, Multi-Layer Perceptron (MLP), H2O, and Long Short-Term Memory (LSTM), with the purpose of predicting viral transmission. The evaluation metrics encompass MAE, RMSE, and MAPE. The outcomes of the examination of comparison models will aid in identifying the most suitable model for forecasting the transmission of the virus, encompassing the rates of recovery, death, and positive cases, within the specific setting of Indonesia. This work has significance in elucidating the inherent trade-off between efficiency and accuracy within the realm of dynamic data modeling, specifically in the context of COVID-19 viral data.