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All Journal Jurnal Mandiri IT Jurnal Sains dan Teknologi
Ramadhan, Rio Fadli
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Aerospace Engineering Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Electrical & Electronics Engineering Energy Industrial & Manufacturing Engineering Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering

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Analisis Kerentanan Keamanan Data Pada Balai Diklat Keagamaan Medan Ramadhan, Rio Fadli
Jurnal Sains dan Teknologi (JSIT) Vol. 5 No. 1 (2025): Januari-april
Publisher : CV. Information Technology Training Center - Indonesia (ITTC)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47233/jsit.v5i1.2619

Abstract

Penelitian ini bertujuan untuk menganalisis sistem keamanan data di Balai Diklat Keagamaan Medan melalui audit terhadap penerapan standar ISO 27001. Hasil audit menunjukkan bahwa meskipun sebagian besar elemen ISO 27001 telah diimplementasikan, terdapat kelemahan dalam beberapa aspek penting, seperti alokasi tanggung jawab keamanan informasi, kajian independen terhadap keamanan, serta pengelolaan log kesalahan. Pemetaan ini mengidentifikasi perlunya perbaikan dalam kebijakan, pengawasan, dan penerapan audit tambahan untuk memperkuat sistem keamanan data. Data yang merupakan aset penting membutuhkan perlindungan menyeluruh untuk menjaga integritas, ketersediaan, dan kerahasiaannya. Oleh karena itu, penelitian ini merekomendasikan peningkatan kebijakan keamanan dan pengawasan yang lebih ketat guna mengurangi risiko kebocoran data dan mendukung operasional yang lebih aman di masa depan
Sentiment analysis of privacy issues in the digital era using the naïve bayes method Ramadhan, Rio Fadli; Kurniawan, Rakhmat
Jurnal Mandiri IT Vol. 14 No. 2 (2025): Computer Science and Field
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/mandiri.v14i2.450

Abstract

The development of information technology has triggered public concern about data privacy issues, especially on social media such as X (formerly Twitter). The rampant leaks of personal data have driven the need for a deeper understanding of public opinion. This study aims to analyze public sentiment towards data privacy issues by applying the Naïve Bayes algorithm. The formulation of the problem includes how the public perceives data privacy, how the algorithm performs in classifying sentiment, and how the evaluation results of the model used are. This study uses a quantitative method with a text mining and machine learning approach. Data were taken through crawling techniques on 1,500 tweets related to data privacy. The pre-processing stages were carried out through cleaning, tokenizing, normalization, stopword removal, and stemming. Furthermore, the data was labeled using the InsetLexicon dictionary and weighted using the TF-IDF method. The classification model was built using the Naïve Bayes algorithm and evaluated using accuracy, precision, recall, and f1-score metrics. The results showed that the majority of public opinion on data privacy issues was negative, reflecting concerns over the weak protection of personal data. The Naïve Bayes model performed quite well in sentiment classification. This research is useful in providing insight to the government and digital service providers in developing data protection policies that are more responsive to public opinion.
Co-Authors Rakhmat Kurniawan R