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All Journal Jurnal Teknik Informatika (JUTIF) Jurnal Ilmiah Teknik Mesin, Elektro dan Komputer (JURITEK) JOMPA ABDI: Jurnal Pengabdian Masyarakat CSRID Journal of Informatics and Interactive Technology (JIITE)
Primandani Arsi
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Humanities Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Engineering Languange, Linguistic, Communication & Media Social Sciences Other

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Analisis Sentimen Game Genshin Impact pada Play Store Menggunakan Naïve Bayes Clasifier Primandani Arsi; Pungkas Subarkah; Bagus Adhi Kusuma
Jurnal Ilmiah Teknik Mesin, Elektro dan Komputer Vol. 3 No. 1 (2023): Maret: Jurnal Ilmiah Teknik Mesin, Elektro dan Komputer
Publisher : Pusat Riset dan Inovasi Nasional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/juritek.v3i1.1962

Abstract

Online games are an entertainment medium that cannot be separated from some groups of people, especially during the co-19 pandemic. The existence of a policy of violence reduces the interaction of people in the world, including in Indonesia, resulting in an increase in online activity, especially playing games. Game is an interesting online gaming platform, where players can still interact socially boldly. Genshin Impact is a mobile game that provides other platforms such as PC, PlayStation and Nintendo Switch. Although some people like this game, others are not satisfied with the game play. Sentiment analysis is also very useful when game developers want to know what users think about the game experience. This research aims to build a model of the classification of reviews on the Genshin Impact game available on the Google Play platform, so that the resulting model can provide recommendations for developers for improvement. The results obtained are reviews on the Google Play Store tend to be positive with an accuracy score of 87%, precision of 67%, memory of 98%, and f1 score of 67%. Evaluation is done by comparing the model that has been obtained in this study with the previous model with the same algorithm.
Perancangan UI/UX Aplikasi Repairo Sebagai Jasa Perbaikan dan Pembangunan Rumah Menggunakan Metode Design Thinking Hanswaran Fathul Khakim; Primandani Arsi
Journal of Informatics and Interactive Technology Vol. 2 No. 1 (2025): April
Publisher : ACSIT

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63547/jiite.v2i1.17

Abstract

Beberapa bangunan sudah mulai usang dikarenakan kayu-kayu yang membentuk struktur bangunan meregang akibat suhu yang ekstrem, dan atap rumah menjadi rumah panas yang tak tertahankan. Perancangan UI/UX menggunakan pendekatan metode Design Thinking. Design Thinking merupakan metode kolaborasi yang mengumpulkan banyak ide dari disiplin ilmu untuk memperoleh sebuah solusi. Pada metode yang digunakan terdapat lima tahapan yaitu Emphatize, Define, Ideate, Prototype, dan Test. Hasil dari kuesioner aspek user, pada tampilan antarmuka pengguna dari aplikasi ini 67% pengguna merasa Sangat Mudah dalam menavigasi dan menemukan informasi yang dibutuhkan.Berdasarkan hasil pengujian yang dilakukan, dapat diambil kesimpulan dengan menggunakan Design Thinking untuk merancang dan menganalisis User Interface (UI) dan User Experience dapat membuat prototype yang berfungsi dengan baik, mudah, dan memenuhi kebutuhan.
Literasi Digital Penggunaan Media Sosial Dalam Menangani Cyberbullying Di SD Al Izzah Primandani Arsi; Subarkah, Pungkas; Riyanto, Riyanto; Kusuma, Bagus Adhi; Riandini, Dini; Widi Lestari, Tri Endah; Hermanto, Nandang
Jompa Abdi: Jurnal Pengabdian Masyarakat Vol. 4 No. 2 (2025): Jompa Abdi: Jurnal Pengabdian Masyarakat
Publisher : Yayasan Jompa Research and Development

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57218/jompaabdi.v4i2.1571

Abstract

Kegiatan pengabdian masyarakat ini bertujuan untuk meningkatkan kesadaran dan pemahaman orang tua wali murid SD Al Izzah Purwokerto, Kabupaten Banyumas, terhadap pentingnya media sosial untuk menangani anti cyberbullying, karena saat ini banyak anak-anak atau remaja menjadi korban dan pelaku cyberbullying. Metode yang digunakan dalam kegiatan ini yaitu tahap persiapan, tahap pelaksanaan dan tahap evaluasi. Kegiatan ini diikuti oleh 42 peserta orang tua wali murid, dengan hasil evaluasi mengalami peningkatan secara signifikan. Hal ini dibuktikan dengan adanya pre test dan post test dengan memperoleh hasil mengalami kenaikan 40%. Kegiatan ini direkomendasikan untuk dilanjutkan dengan cakupan permasalahan yang lebih luas dan pelibatan instansi lain. Rekomendasi setelah pelatihan ini yaitu harapannya ada tindak lanjut secara berkala salah satunya kerja sama dengan dinas terkait agar pelatihan sejenis dilaksanakan kembali.
PERFORMANCE COMPARISON OF SVM, NAIVE BAYES, AND LOGISTIC REGRESSION CLASSIFICATION ALGORITHMS IN ANALYZING NOICE APP USER REVIEWS Ahmad Bahar; Tri Astuti; Primandani Arsi
Jurnal Teknik Informatika (Jutif) Vol. 5 No. 4 (2024): JUTIF Volume 5, Number 4, August 2024 - SENIKO
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2024.5.4.2061

Abstract

In the rapidly growing digital era, user reviews on distribution platforms such as the Google Play Store are a key indicator in assessing the popularity, quality, and user satisfaction of applications. This study aims to compare the performance of SVM, Naive Bayes, and Logistic Regression classification algorithms in analyzing user reviews of the Noice app, an audio content platform. The research involves steps such as data collection, data pre-processing, word embedding, modeling, model evaluation, and sentiment analysis. Testing was conducted using 1877 data. The data from the reviews were divided into scenarios, with training and testing data divided in ratios of 90:10, 80:20, and 70:30. The results showed that the SVM algorithm achieved the highest accuracy rate (80%) in the 90:10 data split scenario. However, Naive Bayes also showed competitive results with 78% accuracy in the same scenario. Meanwhile, Logistic Regression achieved 78% accuracy when the data was split in an 80:20 ratio. Evaluation was done using metrics such as accuracy, precision, recall, and F1-score. Sentiment analysis showed a positive trend with 1194 positive data compared to 683 negative data. From the comparison of data sharing scenarios and algorithms, SVM at 90:10 data sharing gave the best results.
Analisis Tanggapan Customer Service Laptop Di Instal Murah Purwokerto Menggunakan Algoritma Naïve Bayes Pratiwi, Widya Dian; Debby Ummul Hidayah; Primandani Arsi
CSRID (Computer Science Research and Its Development Journal) Vol. 16 No. 3 (2024): October 2024
Publisher : LPPM Universitas Potensi Utama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22303/csrid-.16.3.2024.367-380

Abstract

The development of the digital era is dominated by advances in information technology, so customer service is becoming increasingly important in the technology industry. This research aims to analyze customer responses to customer service using the Naïve Bayes classification method, with a focus on the Purwokerto Cheap Installation service. The Naïve Bayes algorithm is used to systematically understand customer response patterns, which is important for companies in increasing customer satisfaction. In the context of the continuously developing information technology industry, understanding customer response patterns is crucial for maintaining competitive advantage. The Naïve Bayes classification method is used in the analysis, with stages including data collection, data labeling, preprocessing, classification using Naïve Bayes, and analysis of the results. The data used are customer ratings and reviews of the Purwokerto Cheap Installation Shop, with a total of 50 data. After data labeling, the research results show that around 66% of customers describe their satisfaction through the ratings and reviews given, which are classified as positive. This research is expected to provide theoretical and practical contributions in understanding customer responses to technology services. Using the Naïve Bayes classification method, this research reveals customer response patterns that are important for companies to maintain a competitive advantage in the ever-growing information technology industry.
Co-Authors Ahmad Bahar Bagus Adhi Kusuma Hanswaran Fathul Khakim Hidayah, Debby Ummul Kusuma, Bagus Adhi Nandang Hermanto Pratiwi, Widya Dian Pungkas Subarkah Riandini, Dini Riyanto Riyanto Subarkah, Pungkas TRI ASTUTI WIDI LESTARI, TRI ENDAH