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All Journal Sistemasi: Jurnal Sistem Informasi JURNAL PENDIDIKAN TAMBUSAI Darmabakti Cendekia: Journal of Community Service and Engagements Journal of Innovation and Future Technology (IFTECH) HEALTH FRONTIERS (MULTIDISCIPLINARY JOURNAL FOR HEALTH PROFESSIONALS) SISFOTENIKA Jurnal Ilmu Ekonomi, Pendidikan dan Teknik (IDENTIK) Jurnal Abdimas Kesehatan ILKOMEDIA: Jurnal Ilmu Komputer dan Multimedia Journal of Emerging Information Systems and Business Intelligence (JEISBI)
Cendra Devayana Putra
Information Systems Study Program, Universitas Negeri Surabaya - Indonesia
Religion Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Health Professions Languange, Linguistic, Communication & Media Library & Information Science Medicine & Pharmacology Nursing Public Health Social Sciences Veterinary

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Application of Naïve Bayes Method for Student Performance Classification Prayoga, Riza Akhsani Setyo; Basatha, Rizky; Akbar, Muhammad Sonhaji; Elfaiz, Ersha Aisyah; Putra, Cendra Devayana
Sistemasi: Jurnal Sistem Informasi Vol 14, No 2 (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.v14i2.4852

Abstract

In every school, students exhibit varying levels of performance, influenced by several factors such as parental support and involvement, participation in extracurricular activities, motivation levels, internet access for learning, teacher quality, peer influence, and learning difficulties. This study aims to classify student performance to identify those who may need additional support for improvement. The classification method employed in this research is the Naïve Bayes algorithm. The results indicate that the trained model successfully classified 25 out of 30 tested data points. The evaluation metrics achieved include a precision of 100%, recall of 80%, specificity of 100%, accuracy of 83%, and an F1-score of 89%.
The Optimisation of Stock Management: Design of an AI-Driven Inventory System Putra, Cendra Devayana; Utami, Ardhini Warih; Dwi, I Kadek; Prayoga, Riza Akhsani Setyo; Basatha, Rizky; Muhammad Sonhaji Akbar
SISFOTENIKA Vol. 15 No. 2 (2025): SISFOTENIKA
Publisher : STMIK PONTIANAK

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30700/sisfotenika.v15i2.543

Abstract

The frozen food industry has witnessed remarkable growth in recent years, driven by increasing urbanization and the demand for convenient, ready-to-eat meals. Despite this upward trend, many businesses in the sector struggle with inefficient stock management, particularly in forecasting daily demand due to fluctuating consumer behavior and unpredictable external factors. This study proposes an end-to-end artificial intelligence-based stock forecasting system aimed at optimizing inventory management for frozen food businesses. By adopting the Design Thinking approach, this research places users—both consumers and internal stakeholders—at the center of the problem-solving process to uncover key operational pain points. The study explores recent technological advancements, including augmented reality, RFID, and blockchain, and integrates them into a practical framework tailored to small and medium enterprises (SMEs). Through qualitative analysis and system prototyping, the research identifies essential features for an intelligent stock management system and demonstrates how a user-centric approach can drive innovation and improve business performance. The findings offer valuable insights into the development of adaptive, data-driven solutions in the rapidly evolving frozen food sector.
Penerapan Data Mining untuk Peminjaman Buku dengan Menggunakan Algoritma Apriori PRAYOGA, RIZA AKHSANI; Basatha, Rizky; Akbar, Muhammad Sonhaji; Elfaiz, Ersha Aisyah; Putra, Cendra Devayana
Jurnal Ilmu Komputer dan Multimedia Vol. 1 No. 2 (2024): ILKOMEDIA Edisi Desember 2024
Publisher : Akademi Komunitas Negeri Putra Sang Fajar Blitar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46510/ilkomedia.v1i2.18

Abstract

Buku merupakan jendela ilmu yang dimana banyak diminati oleh masyarakat. Setiap perpustakaan memiliki koleksi buku yang cukup banyak namun tidak banyak pemilik buku yang memberikan rekomendasi buku yang sering dipinjam kepada pengunjung perpustakaan. Rekomendasi peminjaman buku ini bisa digunakan untuk membantu pengunjung agar tidak bingung dalam memilih buku sehingga dengan cepat bisa memilih buku sesuai dengan kebutuhan. Selain itu dengan adanya rekomendasi peminjaman buku ini bisa membantu bagi pemilik perpustakaan dalam menyediakan buku yang sering dipinjam sehingga memiliki stok yang cukup. Metode yang digunakan dalam rekomendasi pemilihan buku ini memakai algoritma apriori sehingga nanti hasilnya berupa rekomendasi pemilihan buku beserta aturan asosiasi. Pada perhitungan algoritma ini memerlukan perhitungan support baik satu item maupun dua item dimana support memiliki minimum support 40 %. Perhitungan support ini digunakan untuk menghitung kombinasi item baik satu kombinasi item dan dua kombinasi item . Kemudian dilanjutkan untuk membuat aturan asosiasinya menggunakan perhitungan confidence serta dalam menguji keakuratan aturan asosiasi dengan perhitungan lift. Hasil yang muncul dari rekomendasi peminjaman buku berupa Buku Politik dan Buku Ekonomi dengan nilai confidence 83% dan nilai lift 1,25. Kemudian ada Buku Politik dan Buku Fiksi dengan nilai confidence 67% serta nilai lift 1,18. Lalu ada Buku Ekonomi dan Buku Fiksi dengan nilai confidence 60% dengan nilai lift 1,06.
Pengembangan Program Pembelajaran Keterampilan Berpikir Komputasional Untuk Siswa Sekolah Indonesia Davao (SID) Filipina Wibawa, Ramadhan Cakra; Sujatmiko, Bambang; Anistyasari, Yeni; Basatha, Rizky; Akbar, Muhammad Sonhaji; Elfaiz, Ersha Aisyah; Putra, Cendra Devayana; Abdillah, Rifqi; Habibi, Mohammad Wildan
Jurnal Pendidikan Tambusai Vol. 8 No. 3 (2024)
Publisher : LPPM Universitas Pahlawan Tuanku Tambusai, Riau, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Pada era globalisasi yang berkembang pesat, pendidikan abad ke-21 menuntut integrasi literasi, pengetahuan, keterampilan, sikap, dan penguasaan teknologi sebagai komponen esensial dalam proses pembelajaran. Salah satu keterampilan kunci yang perlu dikuasai adalah berpikir komputasional sebagai fondasi dalam mempersiapkan generasi muda menghadapi dunia kerja yang semakin canggih dan kompleks. Tujuannya untuk melaksanakan dan mengevaluasi program pelatihan pembelajaran keterampilan berpikir komputasional di Sekolah Indonesia Davao (SID). Melalui metode offline/luring berupa ceramah, diskusi, tanya jawab, dan project-based learning, program ini dirancang untuk meningkatkan pemahaman guru serta mengembangkan kesiapan siswa dalam menghadapi tantangan era digital. Hasil pelaksanaan menunjukkan peningkatan signifikan dalam pemahaman guru melalui penyampaian materi yang relevan, metode yang efektif, serta alokasi waktu yang terstruktur. Secara keseluruhan, program ini memberikan kontribusi positif terhadap pengembangan kompetensi guru dan kesiapan siswa menjadi individu yang kompeten, adaptif, dan inovatif di tengah perkembangan teknologi yang dinamis.
INCREASING SCHOLARSHIP OPPORTUNITIES IN TAIWAN: TIPS AND TRICKS: MENINGKATKAN PELUANG BEASISWA DI TAIWAN: TIPS DAN TRIK Devayana Putra, Cendra; Lavita Angelina, Clara
Darmabakti Cendekia: Journal of Community Service and Engagements Vol. 6 No. 1 (2024): JUNE 2024
Publisher : Faculty of Vocational Studies, Universitas Airlangga

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20473/dc.V6.I1.2024.21-25

Abstract

Background: COVID-19 has significantly impacted education, resulting in low acceptance rates at universities in Taiwan and Indonesia. These low acceptance rates contribute to a shortage of human resources, which could have far-reaching consequences for the economy, education, health, and political stability. Nations with limited human capital may become dependent on foreign labor to meet their workforce needs, leading to local unemployment and heightened competition between local and foreign workers. Therefore, investing heavily in education and training is crucial. Objective: To address this issue, community services have been conducted in Indonesia to provide students with information on scholarships and technical strategies. Method: The community services were organized in several steps, including preparation, planning, implementation, and evaluation. Results: The effectiveness of the event was assessed through pre-test and post-test questionnaires. Conclusion: Through a series of scholarship webinars, it was observed that knowledge and awareness about scholarships increased, providing students with greater opportunities for securing scholarships.
Mengembangkan Chatbot Empatik untuk Dukungan Kesehatan Mental: Solusi Inovatif dalam Pendampingan Psikologis Putra, Cendra Devayana; Prayoga, Riza Akhsani Setyo; Cinthya, Monica; Basatha, Rizky; Akbar, Muhammad Sonhaji; Elfaiz, Ersha Aisyah
Jurnal Ilmu Komputer dan Multimedia Vol. 1 No. 2 (2024): ILKOMEDIA Edisi Desember 2024
Publisher : Akademi Komunitas Negeri Putra Sang Fajar Blitar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46510/ilkomedia.v1i2.19

Abstract

Studi ini merupakan langkah maju yang penting dalam pengembangan sistem dialog kesehatan mental, yang membahas pengaruh besar kesehatan mental terhadap fungsi manusia dan terbatasnya ketersediaan psikolog untuk memberikan dukungan. Studi ini menyediakan kumpulan data baru yang menggunakan analisis sentimen untuk mengevaluasi respons. Dengan menyadari pentingnya respons emosional dalam meningkatkan pengalaman pengguna, studi ini menganalisis respons sentimen menggunakan berbagai algoritme kategorisasi sentimen yang umum digunakan. Lebih jauh, penelitian ini mengusulkan paradigma urutan ke urutan untuk membahas masalah dialog kesehatan mental, dengan fokus pada penyertaan kesadaran tahap. Model ini bekerja dengan sangat baik di beberapa fase wacana, yang menegaskan keefektifannya di bidang kesehatan mental. Meskipun penelitian ini masih dalam tahap awal, penelitian ini meletakkan dasar untuk pengembangan sistem diskusi yang berkaitan dengan kesehatan mental. Metode yang kami usulkan dapat meningkatkan skor F-1 rata-rata sebesar 0,6%. Studi mendatang akan menyelidiki beberapa pendekatan, seperti pembelajaran transfer, model multidialog, dan analisis sentimen dalam kerangka seq-to-seq. Model yang diusulkan dimaksudkan untuk menjadi standar untuk mengevaluasi sistem diskusi multi-tahap dalam penelitian masa mendatang.
PENENTUAN DOSIS KOAGULAN PADA PENGOLAHAN AIR MINUM: PENDEKATAN FUZZY BERBASIS DATA DAN PENENTUAN FUZZY SET BERBASIS Z-SCORE Monica Cinthya; Retno Aulia Vinarti; Nisa Dwi Septiyanti; Cendra Devayana Putra; Erik Rahman; Rifqi Abdillah
Journal of Innovation And Future Technology Vol. 7 No. 2 (2025): Vol 7 No 2 (Agustus 2025): Journal of Innovation and Future Technology (IFTECH)
Publisher : LPPM Unbaja

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47080/0ffxq425

Abstract

direct use of raw water has serious health risks. Therefore, various water treatment processes are needed to make the raw water safe for use in domestic purposes. One important stage in such processing processes is coagulation and flocculation, where chemicals (coagulants) are used to remove colloidal particles and form larger floc that can be easily precipitated through sedimentation and filtration. Determination of the optimal coagulant dosage is essential to achieve the desired water quality. However, jer-test problems, the non-linear nature of water, and the complexity of coagulation theory can make it difficult to determine the optimal dose. Therefore, in this study, a system is proposed that uses a data-based fuzzy approach and fuzzy set determination using z-score to study data patterns and relationships between parameters in the coagulation process. The proposed method utilizes a fuzzy approach to address the non-linear nature of water and the complexity of coagulation theory. The system uses the collected data patterns to develop fuzzy models that can predict optimal coagulant doses based on specific conditions. This approach allows the system to learn from existing data and identify patterns of relationships that may be hidden between relevant parameters. The results showed that the proposed system achieved an RMSE value of 0.7639589866827494, while the MSE value was 0.5836333333333333333. This suggests that the system can provide a fairly accurate prediction of the dose of coagulant required in the coagulation process.
Knowledge and Awareness of Radiation Protection Among Healthcare Workers: A Cross-Sectional Study Berliana Devianti Putri; Anisa Dewi Setiawati; Winda Kusumawardani; Cendra Devayana Putra; Gabriel Loi
Health Frontiers: Multidisciplinary Journal for Health Professionals Vol. 4 No. 1 (2026)
Publisher : Tarqabin Nusantara Group

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62255/mjhp.v4i1.253

Abstract

Ionising radiation from diagnostic procedures poses significant occupational risks to healthcare workers (HCWs), yet awareness remains suboptimal in many settings, particularly in low- and middle-income countries. This cross-sectional study assessed radiation protection knowledge and awareness among 140 HCWs from inpatient, intensive care, and emergency units in Indonesia, identifying independent predictors of awareness. Knowledge was evaluated using a validated 15-item instrument (categorized as poor, acceptable, or good), while awareness was measured as a binary outcome. Data were analyzed using Pearson’s chi-square test and multivariable binary logistic regression, adhering to STROBE guidelines. The sample was predominantly female (69.3%) with bachelor’s degrees (57.1%). Overall, 46.4% demonstrated good knowledge, 48.6% acceptable, and 5.0% poor, while 68.6% were classified as aware. Multivariable analysis revealed that knowledge level was the sole independent predictor of awareness: compared to poor knowledge, acceptable knowledge significantly increased awareness odds (aOR = 3.48; 95% CI: 1.12–10.80; p = 0.031), as did good knowledge (aOR = 8.65; 95% CI: 2.10–35.60; p = 0.003). These findings confirm that radiation protection knowledge strongly and independently drives awareness among clinical staff. Consequently, healthcare institutions must prioritize continuous, evidence-based radiation safety education—particularly for personnel in high-exposure units—as the foundational strategy to effectively bridge the knowledge–awareness gap and mitigate occupational radiation risks.
Public Opinion on MyTelkomsel Using DeLone and McLean Model on X Bagas Setya Wicaksono; Cendra Devayana Putra; I Kadek Dwi Nuryana; Monica Cinthya
Journal of Emerging Information Systems and Business Intelligence (JEISBI) Vol. 7 No. 3 (2026): Vol. 07 Issue 03
Publisher : Universitas Negeri Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26740/jeisbi.v7i3.78043

Abstract

The MyTelkomsel application is a digital service used by Telkomsel customers to access telecommunications information and services. The high number of users is accompanied by the emergence of various user opinions and complaints expressed through social media. This study aims to analyze user satisfaction with the MyTelkomsel application based on public opinions on the X (Twitter) platform using the DeLone and McLean Information Systems Success Model. The research data consist of 1,500 Indonesian-language tweets collected through a crawling process. The data then underwent a text preprocessing stage to improve analysis quality. Sentiment analysis was conducted using the RoBERTa model to classify user opinions into positive, neutral, and negative sentiments. Subsequently, each tweet was labeled into six dimensions of the DeLone and McLean model, namely System Quality, Information Quality, Service Quality, Use, User Satisfaction, and Net Benefits. Sentiment scores were used as quantitative values for each dimension. The relationships among variables were analyzed using the Structural Equation Modeling–Partial Least Squares (SEM-PLS) method. The results indicate that System Quality and Information Quality significantly influence User Satisfaction, while Service Quality shows a lower level of influence. This study is expected to provide academic contributions to the application of the DeLone and McLean model based on social media data and offer practical insights for the development of the MyTelkomsel application in improving service quality and user experience. Keywords : MyTelkomsel, Sentiment Analysis, Social Media, DeLone and McLean, User Satisfaction, SEM-PLS
Sentiment Analysis And UTAUT2 Classification On Maxim Application User Reviews Using IndoBERT And Zero-Shot Hilal Hindi Saputra; Cendra Devayana Putra; I Kadek Dwi Nuryana; Monica Cinthya
Journal of Emerging Information Systems and Business Intelligence (JEISBI) Vol. 7 No. 3 (2026): Vol. 07 Issue 03
Publisher : Universitas Negeri Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26740/jeisbi.v7i3.78304

Abstract

The rapid growth of ride-hailing services has intensified competition, making user feedback on digital platforms a critical asset for service improvement. This study addresses the challenge of managing and extracting actionable insights from large volumes of unstructured user reviews on the Google Play Store for the Maxim application. To overcome this, a comprehensive text-mining framework is proposed, integrating sentiment analysis and technology acceptance modeling. A dataset of 2.000 Indonesian-language user reviews from July to September 2025 was retrieved via web scraping. Data preprocessing was executed using case folding, filtering, and normalization. Subsequently, sentiment classification was performed using the IndoBERT model, while the mapping of user text to the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) framework was automated using a Zero-Shot Classification approach. Finally, Structural Equation Modeling–Partial Least Squares (SEM-PLS) via SmartPLS 4.0 was utilized to test the structural hypotheses. The analytical findings reveal that negative sentiments slightly dominate the dataset (48.05%), heavily driven by system stability and sudden fare adjustments. Furthermore, the structural model proves that behavioral intention, effort expectancy, facilitating conditions, habit, performance expectancy, price value, and social influence exert positive and significant effects on adoption, whereas hedonic motivation exhibits no significant influence.
Co-Authors Abdillah, Rifqi Aisyah Widayani Akbar, Muhammad Sonhaji Alif Majid Firdaus Andyka Salom Anisa Dewi Setiawati Anistyasari, Yeni Ardhini Warih Utami, Ardhini Warih Aryawangi Rahmawanto Bagas Setya Wicaksono BAMBANG SUJATMIKO Bartolomeus Priya Perkasa Utama Widada Berliana Devianti Putri Cinthya, Monica Clara Lavita Angelina Daniel Evan Rusli Dwi, I Kadek Edwyn Wahyu Prasetya Elfaiz, Ersha Aisyah Endah Sekar Palupi Gabriel Loi Hilal Hindi Saputra Husna Lathifunisa Arif I Kadek Dwi Nuryana I Kadek Dwi Nuryana, I Kadek Dwi Medawati, Riris Mohammad Faiz Rakhman Mohammad Wildan Habibi, Mohammad Wildan Monica Cinthya Monica Cinthya Muhamad Aris Burhanudin Muhammad Sonhaji Akbar Muhammad Sonhaji Akbar Nadia Alfi Ni’amah Nevitya Elmaira Nurjannah Nisa Dwi Septiyanti Pandu Dwi Luhur Pambudi‬‬‬‬‬‬ Rahadian Bisma Rahman, Erik Retno Aulia Vinarti Rifqi Abdillah Riza Akhsani Setyo Prayoga Rizky Basatha Rizqiyatul Khoiriyah Tesa Eranti Putri Wibawa, Ramadhan Cakra Winda Kusumawardani Winda Kusumawardani