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All Journal Jurnal Mahasiswa Kreatif Journal of Social Work and Science Education Bulletin of Intelligent Machines and Algorithms
Ardiansyah, Fachrizal
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Religion Humanities Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Environmental Science Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Public Health Social Sciences

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Kedekatan Judi dengan Layanan Benda Acak Gacha(Lootbox) pada Video Game Ardiansyah, Fachrizal; Wahyu, Ahmad
Jurnal Mahasiswa Kreatif Vol. 2 No. 1 (2024): Januari : Jurnal Mahasiswa Kreatif
Publisher : Lembaga Pengembangan Kinerja Dosen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59581/jmk-widyakarya.v2i1.2461

Abstract

ABSTRACT. This article discussess the closeness between random object service gacha(lootbox) with gambling which raises concerns about plunging players, especially children. This article aims to see the closeness between gacha system and gambling, made by the method of literature study, namely through recording, literature review and data processing. The data taken is seen from the current situation and then collects information about the topic being discussed. The similarity between gacha and gambling systems shows the closeness between, players who paid for gacha can be said to be gambling. Meanwhile, players who don’t pay and just have fun are not decisive called a gambler. However, there needs to be a deeper analysis of this matter. Keyword : Game, Gacha, and Gambling Abstrak. Artikel ini membahas kedekatan antara layanan benda acak gacha(lootbox) dengan judi yang memunculkan kekhawatiran akan menjerumuskan pemain terutama anak – anak. Artikel ini bertujuan untuk melihat kedekatan antara sistem gacha dengan judi, dibuat dengan metode studi literatur yakni melalui pencatatan, kajian Pustaka dan pengolahan data. Data yang diambil dilihat dari keadaan yang sedang terjadi saat ini kemudian mengumpulkan informasi mengenai topik yang dibahas. Kesamaan antara sistem gacha dan judi menunjukkan kedekatan antara keduanya, pemain yang membayar untuk melakukan gacha dapat dianggap sebagai perjudian. Sedangkan pemain yang tidak membayar dan hanya bersenang – senang tidak mutlak disebut sebagai penjudi. Meskipun begitu, perlu adanya analisis lebih dalam mengenai hal tersebut. Kata Kunci : Game, Gacha, dan Judi
Recognition and Prediction of Rice Variety–Climate Suitability Using YOLOv9 and Naïve Bayes in Agricultural Lands Marwondo, Marwondo; Danestiara, Venia Restreva; Badar, Arif Adnan; Ardiansyah, Fachrizal
Journal of Social Work and Science Education Vol. 7 No. 1 (2026): Journal of Social Work and Science Education
Publisher : Yayasan Sembilan Pemuda Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52690/jswse.v7i1.1390

Abstract

The suitability of rice varieties to agroclimatic conditions is a key factor in determining rice productivity in Indonesia. Climate variability and land limitations require a decision support system capable of assisting farmers in selecting rice varieties suitable for local environmental conditions. This study aims to develop an integrated artificial intelligence-based system that combines YOLOv9 for image-based rice variety recognition and Naïve Bayes for climate suitability prediction based on temperature and humidity parameters. Image data of five rice varieties Ciherang, Inpari 32, Inpari Nutrizinc, Mekongga, and Baroma were collected directly from agricultural fields in Bandung Regency and processed through annotation, augmentation, and model training stages. The YOLOv9 model performed well in distinguishing rice varieties with relatively similar morphological characteristics, with an mAP@50 value of 0.8932. Meanwhile, the Naïve Bayes model achieved 78% accuracy in predicting climate suitability based on altitude, temperature, and humidity, and produced predictions consistent with agronomic recommendations. Both models were then integrated into a Gradio-based interactive interface to facilitate use by non-technical users. The results indicate that this integrated approach has the potential to be an effective decision support system for assisting in the selection of rice varieties that are adaptive to microclimate conditions, thereby supporting more efficient and sustainable rice cultivation practices.
Machine Learning Based Cervical Cancer Risk Prediction with SHAP-Driven Feature Interpretation Ardiansyah, Fachrizal; Raka Deny Abdi Putra; Budiman
Bulletin of Intelligent Machines and Algorithms Vol. 1 No. 3 (2026): BIMA March 2026 Issue
Publisher : Maheswari Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.65780/bima.v1i3.16

Abstract

Cervical cancer remains a critical public health problem, particularly in developing countries where early detection is often limited. This study presents a machine learning–based approach for cervical cancer risk prediction that emphasizes both predictive accuracy and interpretability. Several supervised algorithms, namely K-Nearest Neighbors, Random Forest, XGBoost, and CatBoost, were evaluated using the Cervical Cancer (Risk Factors) dataset from the UCI Machine Learning Repository following comprehensive data preprocessing and systematic hyperparameter optimization. The experimental results show that CatBoost achieved the best overall performance, with an optimized accuracy of 97.01% and improved sensitivity in detecting high-risk cases, supported by stable k-fold cross-validation results. To enhance clinical transparency, explainable artificial intelligence was incorporated via SHAP, revealing that key predictors such as the Schiller test, age, and reproductive factors played dominant roles in the model’s decisions. These findings demonstrate that the proposed framework is not only accurate and stable but also interpretable and clinically relevant, making it well-suited to support early detection and decision-making in cervical cancer screening, especially in resource-limited healthcare settings.
Co-Authors Badar, Arif Adnan Budiman Marwondo Raka Deny Abdi Putra Venia Restreva Danestiara Wahyu, Ahmad