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All Journal JITU : Journal Informatic Technology And Communication Jurnal Informatika: Jurnal Pengembangan IT
Aulia, Narisa
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Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Library & Information Science

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Analisis Sentimen Aplikasi Get Contact di APP Store Menggunakan Metode SVM (Support Vector Machine) Aulia, Narisa; Sari, S N; Wakhidah, N
Jurnal Informatika: Jurnal Pengembangan IT Vol 10, No 1 (2025)
Publisher : Politeknik Harapan Bersama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30591/jpit.v10i1.8057

Abstract

Current technological developments have led to a variety of new innovations to create applications that make it easier for users to manage phone calls, one of which is the Get Contact application. By managing phone calls, it is hoped that it will help users to minimize the occurrence of fraud or the like. The goal is to analyze user sentiment towards the Get Contact application by classifying user reviews into positive and negative categories through sentiment analysis. The Support Vector Machine method is used in this analysis process with a linear kernel approach to determine the accuracy of the Get Contact application review classification. The stages used in this research include data collection, preprocessing, labeling, split data, SVM model training, and model evaluation. This study shows that the Support Vector Machine (SVM) method classification of sentiment analysis of Get Contact application reviews on the App Store produces an accuracy value of 95.50%, negative precision 0.96, positive precision 0.95, negative recall 0.95, positive recall 0.96, positive and negative f-1 scores are the same, amounting to 0.95. As for the results of the most reviews are negative reviews with a negative review percentage of 94.8%, while for positive reviews it is 5.2%.
Analisis Efektivitas Teknik File Carving pada Pemulihan Data Digital Menggunakan PhotoRec Susanto; Hanafi, Irfan; Aulia, Narisa; Fardani, Muhammad Jauhar; Irfan, Muhammad Nur
JITU Vol 10 No 1 (2026)
Publisher : Universitas Boyolali

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36596/jitu.v10i1.2245

Abstract

Data loss is a critical issue in the digital era, both in everyday computing and in forensic investigations. This study aims to evaluate the effectiveness of PhotoRec, an open-source file carving tool, in recovering lost files from a FAT32 storage medium. A strict digital forensic approach was applied by performing disk imaging, preserving evidence integrity, and documenting each stage in detail. Data loss was simulated through logical deletion and by scanning unallocated sectors to closely replicate real-case conditions. PhotoRec was then utilized to select the target media, identify partitions, determine the file system type, and scan free space to extract files based on signature recognition. The findings show that PhotoRec successfully recovered a total of 50 files, including all primary files deleted during the experiment. In addition, several system-related files such as ELF were also recovered, illustrating the aggressive nature of carving techniques that extract any recognizable data structure. These results confirm that PhotoRec can operate effectively in data loss scenarios on FAT32 media, even when file metadata is no longer available. This study contributes to a deeper understanding of PhotoRec’s performance within the context of digital forensics and highlights its relevance as an investigative tool that prioritizes accuracy, integrity, and procedural traceability.
Co-Authors Fardani, Muhammad Jauhar Hanafi, Irfan Irfan, Muhammad Nur Sari, S N Susanto Susanto Wakhidah, N