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All Journal Jurnal Indonesia Sosial Sains Eduvest - Journal of Universal Studies Asian Journal of Social and Humanities
Habibullah Akbar
Universitas Esa Unggul, Indonesia
Aerospace Engineering Humanities Astronomy Biochemistry, Genetics & Molecular Biology Chemistry Computer Science & IT Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Energy Environmental Science Health Professions Immunology & microbiology Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Neuroscience Physics Social Sciences

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Journal : Asian Journal of Social and Humanities

 1 
Analysis and Design of a Knowledge Management System Using the Fernandez Method in the IT Operation Center Unit (Case Study: PT Citilink Indonesia) Gilang Banuaji; Husni Sastra Mihardja; Gerry Firmansyah; Habibullah Akbar
Asian Journal of Social and Humanities Vol. 1 No. 12 (2023): Asian Journal of Social and Humanities
Publisher : Pelopor Publikasi Akademika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59888/ajosh.v1i12.111

Abstract

The effect of improving business quality on companies is influenced by developments in technology and information. Utilization of Knowledge Management System (KMS) is one of the efforts to improve the quality of the company's business. In a company, the role of knowledge management is very important so that the company can grow rapidly. For the application of good organizational knowledge requires a planned and systematic knowledge management. The benefits derived from implementing knowledge management in companies are that it can improve service to customers, increase efficiency in processes and work methods, increase the number of services or products and save costs and time. The study of this matter, the IT Operation Center (ITOC) unit has difficulties in terms of sharing knowledge in the company, therefore a study is needed entitled "Analysis of Knowledge Management System Design Using the Fernandez Method in the IT Operation Center Unit (Case Study: PT Citilink Indonesia)” then the application of this Knowledge Management System can provide convenience for employees who have some problems related to IT operations.
Analysis and Design of Serviced Oriented Architecture (SOA) with Service-Oriented Modeling And Architechture (SOMA) Method in Trucking Services Company (Case Study: PT Argo Kencana Transindo) Intan Setya Palupi; Husni Satra Mihardja; Habibullah Akbar; Gerry Firmansyah
Asian Journal of Social and Humanities Vol. 1 No. 12 (2023): Asian Journal of Social and Humanities
Publisher : Pelopor Publikasi Akademika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59888/ajosh.v1i12.128

Abstract

Service Oriented Architecture (SOA) is an architectural approach which uses basic construction in the form of services to support rapid system development at low cost and has the ease of managing the composition of distributed applications even in heterogeneous environments. PT Argo Kencana Transindo (PT AKT) is a company in the field of transportation services or freight forwarding. Until now, the company in carrying out its operations still uses an information system that is only integrated with computerized applications, namely Microsoft excel, Microsoft word and also a simple system but there is no information system that is integrated between departments to be able to manage a lot of existing work. For the trucking industry, fast and efficient delivery times are essential to meet customer needs and maintain competitiveness in a competitive market. Facing the opportunity of changing business process needs in the future, SOA offers adaptive and reactive to the environment and offers solutions to business complexity, system diversity and technology. This research analyzes and designs SOA using the SOMA method which is expected to contribute to making it easier to integrate with other systems and services, helping to streamline communication and data sharing throughout the supply chain, leading to more efficient and effective operations.
Emotional Classification Based on Facial Expression Recognition Using Convolutional Neural Network Method Arif Pami Setiaji; Gerry Firmansyah; Habibullah Akbar; Budi Tjahjono; Agung Mulyo Widodo
Asian Journal of Social and Humanities Vol. 1 No. 12 (2023): Asian Journal of Social and Humanities
Publisher : Pelopor Publikasi Akademika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59888/ajosh.v1i12.139

Abstract

In recent years, the development of human-computer interaction technology has reached remarkable levels, particularly in the field of facial expression recognition. This technology utilizes human facial images to identify and classify emotional expressions such as happiness, sadness, fear, and more through computer image processing. Active research in facial expression recognition yields substantial benefits for individual and societal advancement, especially in the context of its application within Smart City environments. This study demonstrates that well- configured Convolutional Neural Network (CNN) models empowered by TensorFlow exhibit higher accuracy compared to models utilizing PyTorch. The TensorFlow model achieves the highest accuracy of 93% in recognizing emotional expressions, whereas the PyTorch model achieves 69% accuracy. The TensorFlow model also displays lower accuracy loss and shorter training times compared to the PyTorch model. In the context of calculating happiness indices within Smart City environments, the appropriate choice of technology significantly influences measurement accuracy and efficiency. Therefore, the TensorFlow platform, proven to deliver superior performance in this study, can be a strategic choice for integrating facial expression detection technology into happiness index measurements in such locations
Utilization of LSTM (Long Short Term Memory) Based Sentiment Analysis for Stock Price Prediction Muhammad Fajrul Aslim; Gerry Firmansyah; Budi Tjahjono; Habibullah Akbar; Agung Mulyo Widodo
Asian Journal of Social and Humanities Vol. 1 No. 12 (2023): Asian Journal of Social and Humanities
Publisher : Pelopor Publikasi Akademika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59888/ajosh.v1i12.141

Abstract

This study aims to utilize sentiment analysis in predicting stock price movements. Sentiment analysis can provide information to investors to understand market sentiment. This study uses a text-based approach by pre-processing data, constructing a sentiment analysis model and evaluating model performance. The collected data is analyzed to identify the text's positive, negative, or neutral sentiments. The approach used in scoring sentiment analysis is the Text blob approach and the Lexicon approach. Differences in the results of the accuracy of the two Sentiment Analysis approaches with the LSTM model have an influence on the prediction results with a better increase in accuracy using the Lexicon Sentiment Analysis approach. Then the LSTM model is implemented to classify texts into the desired sentiment categories. The results of this study are insight into the use of sentiment analysis in predicting stock price movements. The implemented sentiment analysis model can be a useful predictive tool for investors and stock practitioners in making investment decisions.
Co-Authors Agung Mulyo Widodo Andriyanti Asianto Arif Pami Setiaji Arisandi Langgeng Tardiana Budi Tjahjono Dudy Fathan Ali Eric Dwi Pamungkas Gerry Firmansyah Gilang Banuaji Gilang Romadhanu Tartila Husni Sastra Mihardja Husni Satra Mihardja Intan Setya Palupi La Dodo Muhammad Fajrul Aslim Narul Sakron Nenden Siti Fatonah Supriyade Supriyade