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Muhammad Nur Faiz
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Journal of Innovation Information Technology and Application (JINITA)
Published by Politeknik Negeri Cilacap
ISSN : 27160858     EISSN : 27159248     DOI : https://doi.org/10.35970/jinita.v2i01.119
Core Subject : Science, Engineering,
Computer Science & IT Decision Sciences, Operations Research & Management Engineering
Software Engineering, Mobile Technology and Applications, Robotics, Database System, Information Engineering, Interactive Multimedia, Computer Networking, Information System, Computer Architecture, Embedded System, Computer Security, Digital Forensic Human-Computer Interaction, Virtual/Augmented Reality, Intelligent System, IT Governance, Computer Vision, Distributed Computing System, Mobile Processing, Next Network Generation, Natural Language Processing, Business Process, Cognitive Systems, Networking Technology, and Pattern Recognition
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 160 Documents
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Decision Support System for Selecting Exemplary Students with Simple Additive Weighting Method Nurahman Nurahman; Minarni Minarni; Nindi Ernawati Nindi Ernawati; Nadia Sari Nadia Sari
Journal of Innovation Information Technology and Application (JINITA) Vol 5 No 1 (2023): JINITA, June 2023
Publisher : Politeknik Negeri Cilacap

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35970/jinita.v5i1.1755

Abstract

The selection of exemplary students carried out by the school is expected to trigger the enthusiasm of students to be able to develop their interests, talents, and abilities in the academic and non-academic fields. However, decision-making has not been measured with data so a decision support system is needed. With the use of this method, it is hoped that it can make it easier and minimize the occurrence of errors in making decent decisions therefore this system is needed to be able to make good decisions. In this study, one of the decision support system methods that are often used was chosen, namely Simple Additive Weighting (SAW). The use of the SAW method is due to its uncomplicated calculations. Research conducted at this school in determining decisions is still done manually so it is less effective and efficient. Therefore, this decision support system must be able to calculate exemplary students to be more effective and efficient. This system displays the final results of the ranking of exemplary students using the SAW method. From the overall results of the research that has been carried out, the calculation results that got rank 1 were obtained, namely Kenzo Ecclesio Taha with a total score of 0.9025. From the results of the study, it can be concluded that the results meet the criteria, so this study can be considered in calculations to determine exemplary students in the future
Exploring the Intersection of Software Engineering and Mobile Technology from 2010 to 2021: A Review of Recent Research S M Nazmuz Sakib
Journal of Innovation Information Technology and Application (JINITA) Vol 5 No 1 (2023): JINITA, June 2023
Publisher : Politeknik Negeri Cilacap

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35970/jinita.v5i1.1761

Abstract

This paper presents a comprehensive review of recent research on the intersection of software engineering and mobile technology. The review method involves a systematic literature search and analysis of relevant research articles. The study identifies key trends and challenges in the field, including the need for better testing and debugging tools, and the emergence of new technologies such as mobile cloud computing. Innovative solutions are proposed to address these challenges. The research focuses on topics such as mobile application development, mobile databases, and mobile security. The paper provides a concise summary of the major findings and proposed solutions. The study concludes that the field of software engineering and mobile technology is rapidly evolving, and further research is needed to effectively address the challenges and keep pace with the dynamic nature of the field
Exploring the Implication of ChatGPT AI for Business: Efficiency and Challenges Md Arman; Umama Rashid Lamiya
Journal of Innovation Information Technology and Application (JINITA) Vol 5 No 1 (2023): JINITA, June 2023
Publisher : Politeknik Negeri Cilacap

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35970/jinita.v5i1.1828

Abstract

This empirical study aims to examine the impact of ChatGPT AI on various business sectors, evaluating its benefits and challenges. Specifically, the study analyzes how ChatGPT AI is transforming business operations and enhancing customer experience in customer service, e-commerce, healthcare, finance, marketing, and developer business sectors. Using a comprehensive literature review approach, this study draws on relevant academic articles to identify and analyze the key applications of AI in the business sector, the benefits realized, and the challenges faced in adopting this technology. The study explores the implications of ChatGPT AI for businesses, including its potential to improve efficiency, reduce costs, and enhance competitiveness. Additionally, ethical and legal considerations surrounding the use of ChatGPT AI in business operations are evaluated, including issues related to data privacy, bias, and transparency. The study provides insights into future directions for the application of ChatGPT AI in business and the potential impact of this technology on various business sectors. The objective is to provide a comprehensive review of the impact of ChatGPT AI on businesses, its potential benefits, and challenges for businesses looking to adopt this technology. Overall, this study highlights the importance of considering both the benefits and limitations of AI adoption in businesses, as well as the ethical and legal implications of its use.
Towards automatic Maude specifications generation from C functions fateh boutekkouk
Journal of Innovation Information Technology and Application (JINITA) Vol 5 No 1 (2023): JINITA, June 2023
Publisher : Politeknik Negeri Cilacap

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35970/jinita.v5i1.1846

Abstract

In this paper, we aim to contribute to the knowledge about how imperative C functions can be transformed to Maude functional and system modules respectively. Maude is a formal specification language characterized by simplicity, expressivity and good performance. It is a multi-paradigm meta-language based on rewriting logic and equational theories used to specify, simulate and formally verify concurrent and distributed systems. Maude has been used to define the operational semantics of many programming and specification languages. In particular, the addition of this paper is to close the gap between a subset of the C standard language and Maude relying on a transformational approach.
Spatial Analysis of Flood Prone Areas in Fena Leisela Subdistrict, Buru Regency Philia Christi Latue
Journal of Innovation Information Technology and Application (JINITA) Vol 5 No 1 (2023): JINITA, June 2023
Publisher : Politeknik Negeri Cilacap

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35970/jinita.v5i1.1865

Abstract

Fena Leisela sub-district is often hit by floods in the rainy season. Floods that often occur in the Siwalalat sub-district are caused by the overflowing of the Waegeren river. The research used DEMNAS data and analysis using the Topographic Wetness Index method. The results of the inundation potential analysis are divided into three classes, namely low potential class with an area of 92,196.09 or 63.04%, medium class of 45,769.48 ha or 31.29%, and a high potential class of 936.12 ha or 5.67%. Waelana-Lana village (3,291.78 ha), Wamana Baru (1,349.33 ha), and Waspait (936.12 ha) are villages that have the largest area in the high flood hazard class in Fena Leisela Sub-district. In the medium flood class, Raheriat village (8,243.39 ha) is the village that has the largest area presentation compared to other villages and for the low flood hazard class, Wamlana village (14,811.98 ha), Waemite village (12,305.48 ha) and Waelana-lana village (1,680.33 ha) are the villages that have the largest area compared to other villages in Fena Leisela Sub-district. The results of this study are expected to be a reference for the government and the community in handling future floods to minimize the impact that occurs.
Analysis of Vegetation Index in Ambon City Using Sentinel-2 Satellite Image Data with Normalized Difference Vegetation Index (NDVI) Method based on Google Earth Engine Heinrich Rakuasa; Daniel Anthoni Sihasale
Journal of Innovation Information Technology and Application (JINITA) Vol 5 No 1 (2023): JINITA, June 2023
Publisher : Politeknik Negeri Cilacap

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35970/jinita.v5i1.1869

Abstract

Rapid urban development and increasing human activities in the city can affect the decline in the Vegetation Index in Ambon City. The research aims to analyze the vegetation index using sentinel-2 satellite image data with the Normalized Difference Vegetation Index (NDVI) method based on Google Earth Engine (GEE) in Ambon City in 2023. This research uses Sentinel-2 Satellite Image data which is analyzed using Google Earth Engine with the Normalized Difference Vegetation Index (NDVI) method. The results showed that the vegetation index value in Ambon City in 2023 was the lowest value of -0.672381 and the highest value of 0.949297. The vegetation index value is then divided into four classes, namely No Vegetation which has an area of 4,448.99 ha or 13.67%, Low Vegetation areas have an area of 1,611.06 ha or 4.95%, Moderate Vegetation areas have an area of 2,895.12 ha or 8.89% and High Vegetation areas have an area of 23,597.35 ha or 72.49%. Analysis of the vegetation index in Ambon City is very important to maintain environmental balance and a healthy and sustainable environment.
Big Data Architectures and Concepts Audrey Tembo Welo; Hervé Lubaki Kinzonzi; Noel Bila Khonde; Eugène Mbuyi Mukendi
Journal of Innovation Information Technology and Application (JINITA) Vol 5 No 2 (2023): JINITA, December 2023
Publisher : Politeknik Negeri Cilacap

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35970/jinita.v5i2.1876

Abstract

Nowadays, the processing of big data has become a major preoccupation for businesses, not only for storage and processing but also for operational requirements such as speed, maintaining performance with scalability, reliability, availability, security, and cost control; ultimately enabling them to maximize their profits by using the new possibilities offered by Big Data. In this article, we will explore and exploit the concepts and architectures of Big Data, in particular through the Hadoop open-source framework, and see how it meets the needs set out above, in its cluster structure, its components, its Lambda and Kappa architectures, and so on. We are also going to deploy Hadoop in a virtualized Linux environment, with several nodes, under the Oracle Virtual Box virtualization software, and use the experimental method to compare the processing time of the MapReduce algorithm on two DataSets with successively one, two, and three and four Datanodes, and thus observe the gains in processing time with the increase in the number of nodes in the cluster
Machine Learning based on Probabilistic Models Applied to Medical Data: The Case of Prostate Cancer Anaclet Tshikutu Bikengela; Remy Mutapay Tshimona; Pierre Kafunda Katalay; Simon Ntumba Badibanga; Eugène Mbuyi Mukendi
Journal of Innovation Information Technology and Application (JINITA) Vol 5 No 2 (2023): JINITA, December 2023
Publisher : Politeknik Negeri Cilacap

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35970/jinita.v5i2.1879

Abstract

The growth in the amount of data in companies puts analysts in difficulties when extracting hidden knowledge from data. Several models have emerged that focus on the notion of distances while ignoring the notion of conditional probability density. This research study focuses on segmentation using mixture models and Bayesian networks for medical data mining. As enterprise data becomes large, there is a way to apply data mining methods to make sense of it using classification methods. We designed different models with different architectures and then applied these models to the medical database. The algorithms were implemented for the real data. The objective is to classify individuals according to the conditional probability density of random variables, in addition to identifying causalities between traits from tests of conditional independence and a correlation measure, both based on χ2. After a quick illustration of several models (decision tree, SVM, K-means, Bayes), we applied our method to data from an epidemiological study (done at the University of Kinshasa University clinics) of case-control of prostate cancer. Thus, we found after interpretation of the results followed by discussion that our model allows us to classify a new individual with an accuracy of 96%.
Autocomplete recommendation plugin and Summarizing Text using Natural Language Processing Aryaan Shaikh; Nikita Newalkar; Sakshi Gaikwad; Namrata Kadav; Chaitali Shewale
Journal of Innovation Information Technology and Application (JINITA) Vol 5 No 2 (2023): JINITA, December 2023
Publisher : Politeknik Negeri Cilacap

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35970/jinita.v5i2.1912

Abstract

Expert-caliber documents, reports, letters, and resumes can be easily developed using Microsoft Office. Microsoft Office offers capabilities such as grammar check, text and font checking & formatting, HTML compatibility, advanced page layout, image support, and more in contrast to a plain text editor, however, it does not have the autocomplete abbreviations feature. The paper proposes an Autocomplete abbreviation Recommendation System that will integrate the benefits of getting automatic suggestions of either full forms, abbreviations, or both by clicking on the option that is being suggested. This will provide more flexibility to the user using existing Microsoft Office platforms. To create this feature, we have examined the JavaScript JQuery functions to implement a basic autocomplete feature. Information overloading is also one of the most important problems brought on by the Internet's explosive expansion. Massive quantities of text are difficult for people to manually summarise. Thus, there is now a greater need for summarizers that are more sophisticated and potent. Hence, Python's packages, methods, and NLP are used in this work to implement Text Summarization. By using this technique, the phrase's overall meaning is enhanced and the reader's comprehension is enhanced.
A Survey of Applications of Blockchain in Collective Decision-Making Scenarios in Swarm Robotics Theviyanthan Krishnamohan
Journal of Innovation Information Technology and Application (JINITA) Vol 5 No 2 (2023): JINITA, December 2023
Publisher : Politeknik Negeri Cilacap

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35970/jinita.v5i2.1950

Abstract

Blockchain is a distributed ledger that was introduced to decentralize monetary systems. However, with time, the applications of blockchain in different realms have been identified. Swarm robotics is a field that combines swarm intelligence and robotics to solve real-world problems that cannot be solved by monolithic robots. Collective decision-making is one of the major behaviors implemented by swarm robotics. This study analyzes existing literature on the applications of blockchain in the collective decision-making scenarios in swarm robotics. Consequently, this study introduces a novel taxonomy to study the different applications effectively. The taxonomy categorizes existing literature into (i) application of blockchain in other areas of swarm robotics, (ii) application of blockchain in continuous collective decision-making scenarios, (iii) application of blockchain in discrete collective decision-making scenarios, (iv) application of blockchain in other discrete collective decision-making scenarios, and (v) application of blockchain in the collective perception scenario. Finally, the limitations of existing work such as excessive resource consumption and violation of swarm robotics principles are discussed.

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