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All Journal Sistemasi: Jurnal Sistem Informasi PREDATECS: Public Research Journal of Engineering, Data Technology and Computer Science Jurnal Informatics Nivedita
Mutia, Risma
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Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Engineering

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Sentiment Analysis of Twitter Reviews on Google Play Store Using a Combination of Convolutional Neural Network and Long Short-Term Memory Algorithms Ningrum, Meriana Prihati; Mutia, Risma; Azmi, Habil; Khalifah, Habibah Dian
Public Research Journal of Engineering, Data Technology and Computer Science Vol. 2 No. 2: PREDATECS January 2025
Publisher : Institute of Research and Publication Indonesia (IRPI).

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57152/predatecs.v2i2.1625

Abstract

In this era of rapidly evolving technology, the use of social media has become widespread and has become a major platform for sharinhabibahdian.khalifah@ogr.deu.edu.trg people's opinions and views. Google Play Store, as one of the main platforms for digital content, provides access to various applications including Twitter, which allows users to provide reviews and ratings. This research aims to conduct sentiment analysis of Twitter reviews on the Google Play Store using two algorithms namely Convolutional Neural Network (CNN) and Long Short-Term Memory (LSTM). The data used is 4999 reviews after the scraping process. From the experimental results, an accuracy value of 84.67%, recall of 81%, and precision of 84% were obtained on CNN, and an accuracy of 82.19% recall of 69%, and precision of 87% on LSTM. From these results, it can be seen that the highabibahdian.khalifah@ogr.deu.edu.trhest accuracy value is obtained in the CNN algorithm. Although the difference in accuracy is small, the CNN algorithm provides better results in classifying sentiment analysis data on Twitter reviews on the Google Play Store.
Analysis of User Adaptation to the My Capella Application based on the Coping Model of User Adaptation (CMUA) Mutia, Risma; Megawati, Megawati; Afdal, M.; Permana, Inggih
SISTEMASI Vol 14, No 4 (2025): Sistemasi: Jurnal Sistem Informasi
Publisher : Program Studi Sistem Informasi Fakultas Teknik dan Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32520/stmsi.v14i4.5328

Abstract

The My Capella application developed by PT Capella Dinamik Nusantara was designed to facilitate customer access to digital services, particularly for booking Honda motorcycle servicing. However, its use still encounters several challenges, especially regarding user adaptation. These include difficulties in understanding and utilizing features, a complex interface, and insufficient user guidance. This study aims to analyze and identify user adaptation behavior toward the My Capella application in the Pekanbaru area using the Coping Model of User Adaptation (CMUA), which evaluates how users respond to new technologies through cognitive and emotional processes. The research findings support four accepted hypotheses: opportunity appraisal significantly influences problem-focused adaptation; secondary appraisal significantly influences both problem-focused and emotion-focused adaptation; and threat appraisal significantly influences problem-focused adaptation. The strongest effect was observed in the relationship between secondary appraisal and problem-focused adaptation, with a t-statistic of 7.259 > 1.960. These findings indicate that users respond to the My Capella application both cognitively and emotionally, aligning with the CMUA framework and reflecting adaptation processes that are both problem-focused and emotion-focused. Therefore, it is recommended that application developers provide interactive training modules, regular outreach or user engagement sessions, and improvements to the user interface (UI/UX) design to make it more intuitive. These efforts can enhance users' understanding and comfort in using application features—especially during system updates.
Pengukuran Risiko Sistem Informasi Tugas Akhir Universitas XYZ Menggunakan Metode Octave Allegro Wulandari, Aulia; Mutia, Risma; Megawati
Journal Informatics Nivedita Vol 1 No 1 (2024): Journal Informatics Nivedita
Publisher : Universitas Hindu Negeri I Gusti Bagus Sugriwa Denpasar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25078/nivedita.v1i1.4363

Abstract

Sistem Informasi Tugas Akhir ditawarkan oleh Program Studi Sistem Informasi Universitas XYZ untuk membantu mahasiswa mengelola tugas akhir mereka. Sistem ini memiliki banyak fitur, termasuk menu umum, berkas, alur, jadwal sesi, seleksi judul, dan survei pengguna. Namun, salah satu masalah umum adalah masalah server yang terjadi saat mengunggah proposal, yang menghambat penerbitan SK pembimbing. Akibatnya, banyak mahasiswa terlambat mendaftar seminar proposal. Tujuan dari penelitian ini adalah untuk menemukan ancaman, mengevaluasi risiko, dan menilai bagaimana hal itu berdampak pada aset kampus. Permasalahan saat ini akan ditangani dengan metode Octave Allegro. Hasilnya menunjukkan bahwa ada tiga hal yang menjadi perhatian dan empat hal yang berdampak besar: reputasi, produktivitas, keuangan, dan keamanan. Empat langkah mitigasi dibuat untuk masalah yang mengkhawatirkan potensi eksploitasi celah keamanan sistem oleh pihak internal dan eksternal. Tiga langkah mitigasi dibuat untuk masalah kapasitas penyimpanan server, dan empat langkah mitigasi dibuat untuk masalah koneksi internet yang tidak stabil. Koneksi internet yang tidak stabil menunjukkan nilai risiko tertinggi, dengan skor 35. Penelitian ini bermanfaat untuk mengidentifikasi dan mengurangi risiko pada Sistem Informasi Tugas Akhir (SITASI) Universitas XYZ, khususnya dalam meningkatkan stabilitas dan keamanan sistem. Penelitian selanjutnya dapat difokuskan pada implementasi mitigasi lebih komprehensif dan pemantauan efektivitas langkah yang telah diterapkan.
Co-Authors Aulia Wulandari Azmi, Habil Inggih Permana Khalifah, Habibah Dian M. Afdal Megawati Megawati - Ningrum, Meriana Prihati