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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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Data Interoperability Model in Integrated Public Service Applications Based on Government Service Bus (Case Study: Tangerang Regency Communication and Information Office) Dudy Fathan Ali; Nenden Siti Fatonah; Gerry Firmansyah; Habibullah Akbar
Jurnal Indonesia Sosial Sains Vol. 4 No. 09 (2023): Jurnal Indonesia Sosial Sains
Publisher : CV. Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59141/jiss.v4i09.877

Abstract

The Tangerang Regency Government, as part of its digital transformation efforts, has been working to enhance public services through the development and implementation of e-Government initiatives. This research aims to conduct an in-depth analysis of data interoperability service modeling in e-Government applications based on Web Services using the Government Service Bus (GSB). The study will address the advantages and challenges associated with using the Government Service Bus, and provide practical recommendations for implementing the Government Service Bus as an effective application integration solution. COBIT 2019 is used as an assessment tool for the current condition. The research results reveal that a total of 138 applications have been identified, with 74 of them being public service applications. While 80% of the public service sector has been incorporated into integrated public service applications, their utilization remains limited. The current capability level of APO11 is at level 1, with an expected level of 2. Similarly, APO14 is at level 1, expected to reach level 2, and MEA01 is at level 0, with an expected level of 2. The author has proposed a data interoperability model that can be implemented within the Tangerang Regency Communication and Information Office, utilizing GSB as the middleware for interoperability processes, particularly for public service applications. Based on the proposed data interoperability model, the author also concludes that with its implementation, the Communication and Information Office will be able to address a significant portion of the technical recommendations derived from the gap analysis, although not necessarily all of them.
Disaster Recovery Plan Analysis Based on the NIST SP 800-34 Framework (Case Study: PT Wijaya Karya (Persero) Tbk.) Eric Dwi Pamungkas; Nenden Siti Fatonah; Gerry Firmansyah; Habibullah Akbar
Jurnal Indonesia Sosial Sains Vol. 4 No. 09 (2023): Jurnal Indonesia Sosial Sains
Publisher : CV. Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59141/jiss.v4i09.879

Abstract

PT Wijaya Karya (Persero) Tbk. (WIKA) is a state-owned company engaged in the construction sector and EPC is currently developing its business in the mining and investment sectors both at home and abroad. Information Technology is one of the supports to achieve its goals. The use of Information Technology is urgently needed by WIKA in order to increase the effectiveness and efficiency of the company's operational activities. In this regard, it is necessary to develop procedures for managing information technology resources to support WIKA's business continuity, which includes services for internal or external users. In the use of information technology, the Disaster Recovery Plan (DRP) is an important part of IT services in efforts to prevent Data Center Fail-Over caused by disasters. With the DRP procedure, it is expected that the Information Systems Bureau as the manager of WIKA's information technology can immediately anticipate if a Disturbance or Disaster occurs that has the potential to disrupt a large number (the majority) of processes or activities that are very critical for business continuity. This Disaster Recovery Plan is guided by the NIST SP 800-34 framework which begins with identifying and assessing risk, Business Impact Analysis (BIA), identification of preventive controls and preparation of contingency strategies.
Journal Series on Governance and Management of IT in Electronic-Based Government Systems (SPBE) in Indonesia Andriyanti Asianto; Nenden Siti Fatonah; Gerry Firmansyah; Habibullah Akbar
Jurnal Indonesia Sosial Sains Vol. 4 No. 09 (2023): Jurnal Indonesia Sosial Sains
Publisher : CV. Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59141/jiss.v4i09.880

Abstract

SPBE Governance and Management is a framework that guarantees the implementation of regulation, direction and control in the implementation of SPBE in an integrated manner. SPBE Governance and Management aims to ensure that SPBE elements consist of the National SPBE Master Plan, SPBE Architecture, SPBE Roadmap, SPBE Program Plan and Budget, Business Process, Data and Information, SPBE Infrastructure, SPBE Application, SPBE Security, and Services SPBE. to achieve SPBE goals. In implementing all SPBE elements, integration and harmonization between the National SPBE and Regional SPBE are required. Therefore, this thesis research raises SPBE Governance and Management in accordance with COBIT 2019 as a governance framework that is set globally. Thus, this research will provide recommendations for the implementation of SPBE in Indonesia which can provide appropriate benefits for SPBE users, namely the community, business actors, civil servants, and other government agencies, and have detailed objectives and activities in accordance with COBIT 2019.
Audit of Information Technology Governance on School Operational Cost Flow in SMKN West Jakarta Using COBIT 2019 Narul Sakron; Gerry Firmansyah; Habibullah Akbar; Budi Tjahjono
Jurnal Indonesia Sosial Sains Vol. 4 No. 09 (2023): Jurnal Indonesia Sosial Sains
Publisher : CV. Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59141/jiss.v4i09.881

Abstract

IT governance is a process that aims to carry out the process of aligning business objectives in an agency in accordance with the business strategy applied to that agency. One sector that is trying to improve IT in improving its governance is the education sector including all SMKNs in West Jakarta. The problem with data management within the West Jakarta Vocational High School is that there is no analysis and research on good and relevant information technology governance in every budget the boss funds issue. This study aims to determine the level of capability and gaps in information technology governance that is currently being implemented, namely the boss fund management information system (Rkas, Arkas, Ready Bop Bos and Headquarters). This study uses analysis based on the 2019 COBIT standard with a focus on the APO12 (Managed Risk) and APO13 (Managed Security) domains to produce a value of capability level that can be used as a reference for analyzing risk management and security management in boss fund management at all West Jakarta Vocational High Schools. The data used in this study came from interviews, questionnaires and direct observation to the research site. The audit results show. APO12 level 2 capability level with a value of 89.29% (Fully Achieved). The capability level of APO12 is level 3 with a value of 77.36% (Largely Achieved) where the capability level of Level 3 APO12 does not reach Fully Achieved so that the capability level of APO12 is at level 3 The capability level of APO13 level 2 with a value of 61.43% (largely Achieved) which does not reach Fully Achieved so The capability level of APO13 is at level 2. The results of this study provide recommendations for aligning the vision, mission, and objectives of boss fund management, so as to improve the function of the boss fund management information system in all SMKN West Jakarta.
Analysis of Time Series Water Level Data Prediction Using Deep Learning Method at the Water Gate of DKI Jakarta Water Resources Office Supriyade Supriyade; Gerry Firmansyah; Habibullah Akbar; Budi Tjahjono
Jurnal Indonesia Sosial Sains Vol. 4 No. 09 (2023): Jurnal Indonesia Sosial Sains
Publisher : CV. Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59141/jiss.v4i09.883

Abstract

Indonesia has 2 seasons, namely the dry season and the rainy season. During the rainy season, many points in the DKI Jakarta area experience flooding or inundation. The reason why Jakarta often experiences flooding is caused by several factors, including local rain floods, shipment floods and tidal floods. The DKI Jakarta Water Resources Agency currently does not have a system that can predict future water levels by referring to past and present water level data. Through this background, the author tries to conduct research in one of the floodgates in the northern area of DKI Jakarta in predicting water levels using deep learning methods , namely Recurrent Neural Network (RNN) and Long Short Term Memory (LSTM). The purpose of this research is to analyze the best deep learning models and predict water level time series data. From the results of the analysis carried out, the best deep learning model is Long Short Term Memory (LSTM) using several tests such as n-input, split data with a composition of 90.33% train data and 9.67% test data , as well as testing of different parameters including epoch, batch size, learning rate, dropout , so the results obtained are the lowest error values with RMSE (17.65), MAPE (0.29), MAE (3.37) and the time needed in the process (runtime) is 39 minutes
Analysis of Tuberculosis Disease Case Growth From Medical Record Data, Viewed Through Clustering Algorithms (Case Study: Islamic Hospital Bogor) La Dodo; Nenden Siti Fatonah; Gerry Firmansyah; Habibullah Akbar
Jurnal Indonesia Sosial Sains Vol. 4 No. 09 (2023): Jurnal Indonesia Sosial Sains
Publisher : CV. Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59141/jiss.v4i09.884

Abstract

Tuberculosis is a chronic infectious disease caused by Mycobacterium tuberculosis infection. Tuberculosis can spread from one person to another through airborne transmission. This disease is most commonly found in the Asian region. Currently, Indonesia ranks second after India in terms of tuberculosis cases. The discovery of tuberculosis cases by province in Indonesia reveals that West Java Province is one of the contributors to the highest tuberculosis cases. It is known that the tuberculosis case rate in Bogor Regency is one of the highest in West Java. This serves as the foundation for the focus of this research, which will be conducted at Islamic Hospital Bogor, to determine the average age and gender of patients who are more susceptible to tuberculosis. One way to understand the growth of tuberculosis cases is through clustering using Data Mining Techniques, specifically several clustering algorithms such as k-means clustering, fuzzy c-means, and Gaussian mixture. These techniques aim to identify the growth of tuberculosis cases based on age range and gender. Therefore, the research results are expected to provide new insights, which could be valuable for decision-makers in various capacities, such as preventive measures, healthcare facility provision, and medication considerations.
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