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All Journal Jurnal Konseling dan Pendidikan Jurnal Media Infotama Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control IJIS - Indonesian Journal On Information System JURIKOM (Jurnal Riset Komputer) Jurnal Sistem Cerdas JSAI (Journal Scientific and Applied Informatics) Jurnal Teknologi Informasi dan Pendidikan Journal of Technopreneurship and Information System (JTIS) Cyber Security dan Forensik Digital (CSFD) JATI (Jurnal Mahasiswa Teknik Informatika) SINTA Journal (Science, Technology, and Agricultural) Djtechno: Jurnal Teknologi Informasi Multidiciplinary Output Research for Actual and International Issue (Morfai Journal) Jurnal Sistem Informasi Dan E-Bisnis JURNAL BESEMAH Mestaka: Jurnal Pengabdian Kepada Masyarakat PEDAMAS (Pengabdian Kepada Masyarakat) El-Mujtama: Jurnal Pengabdian Masyarakat Jurnal Al-Maun Jurnal Pengabdian Masyarakat Mentari Jurnal Riset Multidisiplin Edukasi Jurnal TAM (Technology Acceptance Model) JCOSIS (Journal Computer Science and Information Systems) Jurnal Komputer, Informasi dan Teknologi
Guntur Alam
Universitas Muhammadiyah Bengkulu
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Analisis Pengembangan Perangkat Lunak Berbasis AI (Gemini) Menggunakan Penerapan ACM Code of Ethics Rexcy Elsan; Andi Lala; RG. Guntur Alam
JSAI (Journal Scientific and Applied Informatics) Vol 8 No 2 (2025): Juni
Publisher : Fakultas Teknik Universitas Muhammadiyah Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36085/jsai.v8i2.7811

Abstract

This research aims to analyze the application of the ACM Code of Ethics in the development of AI Gemini software by Google DeepMind. With the development of artificial intelligence (AI) technology, developers need to pay attention to ethical aspects in every stage of system development. This research uses a qualitative approach with a data triangulation method, which includes document analysis, interviews with AI experts, and a literature study. The results show that although Gemini AI has complied with some key ethical principles in the ACM Code of Ethics, such as data security and privacy (90%) and human well-being (85%), there are still challenges related to transparency (60%) and bias mitigation (70%). Lack of transparency in algorithms and training data as well as potential bias in results generated by AI are the main issues that need to be improved. Based on the results, overall the Gemini AI has shown fairly good ethical compliance with an average of 76.67% but still requires improvement in the aspects of transparency, bias mitigation, and usage regulation.
Analisis Kepuasan Pengguna Canva Dan Gamma Dikalangan Mahasiswa Menggunakan Metode System Usability Scale (SUS) Helen Anggraini; RG. Guntur Alam; Agung Kharisma Hidayah
JSAI (Journal Scientific and Applied Informatics) Vol 8 No 2 (2025): Juni
Publisher : Fakultas Teknik Universitas Muhammadiyah Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36085/jsai.v8i2.8214

Abstract

Canva and Gamma are web-based graphic design platforms widely used by students to create brochure, presentations, and social media content in a simple and efficient way. The purpose of this study is to evaluate user satisfaction. with both applications using the System Usability Scale (SUS) method. The study involved 100 students from Universitas Muhammadiyah Bengkulu who had used both platforms. The results indicate that Canva achieved a SUS score of 80.2, categorized as Excellent, while Gamma received an average score of 72.4, categorized as OK. These findings suggest that although both applications demonstrate good usability, Canva is perceived to be superior in terms of ease of use, feature integration, and learning curve. The outcomes of this study can serve as a reference for’s developers with educational institutions on selecting or developing design tools that are more responsive to user needs.
Analisis Kepuasan Pengguna Canva Dan Slidego Dikalangan Mahasiswa Menggunakan Metode Costumer Satisfaction Index (CSI) melzan sabri sabri; RG. Guntur Alam; Gunawan
JSAI (Journal Scientific and Applied Informatics) Vol 8 No 2 (2025): Juni
Publisher : Fakultas Teknik Universitas Muhammadiyah Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36085/jsai.v8i2.8273

Abstract

Canva and slidego are graphic design platforms that are widely used by students. This study uses the Customer Satisfaction Index (CSI) method to measure and understand how satisfied students are with the Canva and Slidego presentation design platforms. This is based on the fact that these platforms are the main choice for students to create attractive professional presentations. This study uses a quantitative, descriptive method by collecting data from students who use both applications through an online questionnaire. To measure overall user satisfaction, but there are also important attributes that affect user satisfaction. such as ease of use, completeness of features. The results of the calculations carried out using the (CSI) method show a value of the percentage of user satisfaction of 85.4115773 Based on the CSI scale, the results are categorized as "very satisfied" with the Canva application. While the Slidego application gets a value of 80.920309% categorized as "Satisfied", so in the results of this CSI calculation, the Canva application has a value greater than the Slidego application value, so the conclusion is that the Canva application is more and more often used by users.
Deteksi Dini Indikasi Risiko Keamanan Siber pada Game Online Berdasarkan Ulasan Pengguna Menggunakan Naive Bayes jely estianti; RG Guntur Alam; Agung Kharisma Hidayah
Cyber Security dan Forensik Digital Vol. 9 No. 1 (2026): Edisi Mei 2026
Publisher : Fakultas Sains dan Teknologi UIN Sunan Kalijaga Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14421/csecurity.2026.9.1.6034

Abstract

Game online merupakan platform digital yang mengelola data sensitif pengguna, termasuk informasi akun, data pribadi, dan transaksi digital, sehingga rentan terhadap berbagai ancaman keamanan siber. Sebagian besar penelitian sebelumnya memanfaatkan ulasan pengguna untuk analisis sentimen dan kualitas layanan, sementara pemanfaatannya sebagai indikator dini risiko keamanan siber masih terbatas. Penelitian ini bertujuan mengidentifikasi indikasi risiko keamanan siber pada game online berdasarkan ulasan pengguna sebagai bentuk user-reported cybersecurity signals. Sebanyak 3.069 ulasan pengguna Mobile Legends diproses melalui tahapan text mining (case folding, tokenizing, stopword removal, dan stemming), direpresentasikan menggunakan pembobotan TF-IDF, dan diklasifikasikan dengan algoritma Naïve Bayes. Kategori risiko meliputi Account Security Risk, Data Privacy Risk, Phishing & Fraud Risk, Malware Risk, serta Non-Security Issue. Evaluasi menggunakan skenario pembagian data 80:20 menunjukkan akurasi keseluruhan sebesar 76,5% berdasarkan confusion matrix, dengan variasi performa antar kategori. F1-score tertinggi diperoleh pada kategori Non-Security Issue (0,92), sedangkan Malware Risk terendah (0,67) akibat ambiguitas linguistik dalam narasi pengguna. Temuan ini menunjukkan bahwa ulasan pengguna berpotensi dimanfaatkan sebagai mekanisme deteksi dini berbasis komunitas. Secara teoretis, penelitian ini memperkenalkan pendekatan community-based cyber risk identification sebagai bentuk komplementer terhadap mekanisme deteksi teknis dalam manajemen risiko keamanan siber pada platform digital.  Kata kunci: keamanan siber, game online, text mining, naïve bayes, deteksi dini risiko  ---------------------------------------------------------------------- Early Detection of Cybersecurity Risk Indications in Online Games Based on User Reviews Using Naive Bayes Online games are digital platforms that manage sensitive user data, including account information, personal data, and digital transactions, making them vulnerable to various cybersecurity threats. Most previous studies have utilized user reviews for sentiment analysis and service quality evaluation, while their use as early indicators of cybersecurity risk remains limited. This study aims to identify indications of cybersecurity risks in online games based on user reviews as user-reported cybersecurity signals. A total of 3,069 user reviews of Mobile Legends were processed using text mining techniques, including case folding, tokenizing, stopword removal, and stemming. The textual data were represented using TF-IDF weighting and classified using the Naïve Bayes algorithm. The risk categories included Account Security Risk, Data Privacy Risk, Phishing & Fraud Risk, Malware Risk, and Non-Security Issue. Evaluation using an 80:20 data split scenario resulted in an overall accuracy of 76.5% based on the confusion matrix, with performance variations across categories. The highest F1-score was achieved in the Non-Security Issue category (0.92), while the Malware Risk category showed the lowest performance (0.67) due to linguistic ambiguity in user narratives. These findings indicate that user reviews have the potential to serve as a community-based early detection mechanism for cybersecurity risks. Theoretically, this study introduces a community-based cyber risk identification approach as a complementary mechanism to technical detection systems in cybersecurity risk management for digital platforms. Keywords: cybersecurity; online games, text mining, naïve bayes, early risk detection
Co-Authors AA Sudharmawan, AA Abdullah, Dedy Abid Aprialdi Adinda Trisista Akfarelta, Akfarelta Amrul Faruq Andi Lala Andilala, Andilala ANDRI KURNIAWAN Apridiansyah, Yovi Arbeiansah Pratama Putra Ariyanti, Widya Caca Andika Cahyo Prihantoro Dedy Abdullah Dia Komalla ewika dwi wulandari Fikri Agnesa Putra Fransiska, Nora Geri Rizki Ramadani Gufron, Muhammad Ale Gunawan Gunawan Gunawan Gunawan Gunawan Handayani, Sri Harianto, Ozi Harry Witriyono Hary Witriyono Helen Anggraini Heri Sulasono Hidayah, Aditia Hidayah, Agung Karisma hidayah, agung kharisma Jaka Rapino jely estianti Juhardi, Ujang Karnedi, Gunawan Khairullah Khairullah, Khairullah Kirman Kirman Kirman Kirman, Kirman Lena Utami Lestari, Putri Dwi Lety Lestari Lingga, Ravi Putra Lorensya, Cintia Novita Machmud Effendy Mahendra, Yusril Mahfuzhi, A.R Walad Mahfuzi, AR. Walad Marissa Utami mawanti, desti melzan sabri sabri Monsya Juansen muhammad fikri Muntahanah, Muntahanah Mutiara Hikmah Nathania, Nabela Hermy Nengsi, Elta Putri Setia Netra Ayu Nita, Taura Puji Rahayu Kurniasih Putra, Arbeiansah Pratama Putra, Fikri Agnesa Rahmadani, Reza Nur Rajes Andika Putra Ramayanti, Imelia Okta Ramzi, Reja Muhamad Randi Riski Ananda Rexcy Elsan Rido Syahputra Rifqo, Muhammad Husni Rojandra, Hajar Saputra, Ahmat Fahry Saputra, Kreshna Ady Selta Jaya Putra selviani, pebi Sigit Muryono Sri Handayani Sulasono, Heri Supriadi Supriadi Surya Ade Saputera Tauhid, Muhammad Ikhsan Toyib, Rozali Tri Rahayu Trisista, Adinda ujang juhardi Vendy Handoyo Veronika, Adelia Wicaksono, Rama Iqbal Wijaya, Ardi Wulandari, Ardeya Yetman Erwadi Yunus Hidayat Yusril Mahendra Yuza Reswan Zhonata, Jerry Ario