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All Journal J-Icon : Jurnal Komputer dan Informatika Inspiration: Jurnal Teknologi Informasi dan Komunikasi
Enggar Novianto
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Computer Science & IT

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KEAMANAN INFORMASI (INFORMATION SECURITY) PADA APLIKASI SISTEM INFORMASI MANAJEMEN KEPEGAWAIAN DENGAN DEFENSE IN DEPTH Enggar Novianto; Erik Iman Heri Ujianto; Rianto Rianto
J-ICON : Jurnal Komputer dan Informatika Vol 11 No 1 (2023): Maret 2023
Publisher : Universitas Nusa Cendana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35508/jicon.v11i1.9139

Abstract

The rapid development of Information Technology (IT) has made IT the most important aspect to meet organizational needs. The existence of IT is believed to be able to provide solutions related to the organization's business processes, so that many organizations offer their resources to increase efficiency by relying on information technology support. Information system security is an internal organizational subsystem tasked with managing the risks associated with computerized information systems. Information system security is the application of international control principles, which are specifically used to trigger problems in information systems. Important information leads to protected information structures, more information is now available from the internet, so information management now includes computer and network technology. The goal of information security is to strengthen business operations and protect against falling business prices by minimizing the risks associated with internal security. The purpose of this study is to understand information security in the implementation of the Personnel Management Information System (SIMPEG) at Sebelas Maret University. The research method used is the application of Defense In Depth to analyze information security, including many layers of security to ensure information security. The results of the descriptive analysis explain that the design and development of SIMPEG pays attention to the principles and aspects of data and information security. However, information security vulnerabilities can occur at the server protection layer, network protection layer, and physical protection layer.
User Analysis of Info BMKG Application in The Perspective of Human Computer Interaction Using Support Vector Machine Algorithm Ilham Fannani; Enggar Novianto; Alfin Syarifuddin Syahab
Inspiration: Jurnal Teknologi Informasi dan Komunikasi Vol. 13 No. 1 (2023): Inspiration: Jurnal Teknologi Informasi dan Komunikasi
Publisher : Pusat Penelitian dan Pengabdian Pada Masyarakat Sekolah Tinggi Manajemen Informatika dan Komputer AKBA Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35585/inspir.v13i1.42

Abstract

On the Google Play Store, users often read other users' app reviews and reputations, before downloading an app. This makes the analysis of user reviews very interesting for app owners to make future decisions. This study aims to analyze user reviews of the Info BMKG application on the Google Play Store, using sentiment analysis. This user review analysis uses the Support Vector Machine (SVM) method. The evaluation proposal was made from more than 3,000 user reviews collected from the INFOBMKG application on the Google Play Store. The results of the analysis using the Support Vector Machine produce an accuracy of 85.54 % and the most frequently reviewed positive review results are "Good", while the most frequently reviewed negative reviews are "Error". Which indicates a complaint against INFOBMKG users, and from the negative words that appear most often, there are two combinations of the two words that appear most often together, namely the word "very helpful" and the word "less accurate", which indicates that user often complain about problems related to application performance. The results of the sentiment analysis process of testing 3000 review data using the fold = 5 test value in the Support Vector Machine (SVM) method obtained an accuracy of 85.54 % which produces predictions on data testing, namely 1500 positive reviews and 1500 negative reviews 1500 reviews.
Co-Authors Alfin Syarifuddin Syahab Erik Iman Heri Ujianto Ilham Fannani Rianto Rianto