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Polyscopia
Published by Medan Resource Center
ISSN : -     EISSN : 30467152     DOI : 10.57251
Core Subject : Religion, Humanities, Education, Art, Social,
Religion Arts Humanities Social Sciences Other
Polyscopia is an open-access journal by Medan Resource Center. The journal publishes research articles from multidisciplinary and various types, methods, or approaches of research in education, applied sciences, natural or social sciences, philosophy, economics, law, politics, religions, as well as arts and humanities, etc. The journal is published quarterly in January, April, July, and October and accepts articles in Bahasa Indonesia or English.
Arjuna Subject : Umum - Umum
Articles 4 Documents
 1 
Search results for , issue "Vol. 3 No. 2 (2026)" : 4 Documents clear
Analisis Pengaruh Pembagian Data terhadap Kinerja Algoritma Naive Bayes dalam Prediksi Penyakit Diabetes pada Wanita Amelia, Rika
Polyscopia Vol. 3 No. 2 (2026)
Publisher : Medan Resource Center

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57251/polyscopia.v3i2.1992

Abstract

This study examines how variations in training–testing data partition ratios influence the performance of the Naive Bayes algorithm in predicting diabetes among women, addressing the problem of whether different split proportions meaningfully affect classification outcomes. Employing a quantitative experimental design, the research utilizes the Pima Indians Diabetes dataset comprising 768 records, which undergo preprocessing prior to model development using the Gaussian Naive Bayes method across three partition scenarios: 70:30, 60:40, and 50:50. Model performance is assessed through accuracy, precision, recall, and F1-score to capture both predictive correctness and class sensitivity. The findings demonstrate that variations in data partitioning exert no statistically significant effect on overall model performance, as accuracy consistently ranges between 76% and 79% across all scenarios. Models trained with as little as 50% of the dataset still achieve comparable predictive capability, indicating stable generalization of the algorithm. The study argues that once a minimum threshold of training data is achieved, increasing data proportion does not substantially enhance performance, while class imbalance emerges as a more decisive factor influencing the effectiveness of diabetes prediction.
Fenomena Korupsi Berulang di Indonesia: Apakah Pendidikan Anti Korupsi Gagal? Azzahra, Kania; Nasution, Qeysa Amruny
Polyscopia Vol. 3 No. 2 (2026)
Publisher : Medan Resource Center

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57251/polyscopia.v3i2.2040

Abstract

Corruption in Indonesia continues to demonstrate persistent and increasingly complex recurrence despite the implementation of various preventive strategies, positioning Anti-Corruption Education as a central instrument for long-term character formation. This study investigates the underlying factors contributing to the persistence of corrupt practices and evaluates the effectiveness of Anti-Corruption Education in achieving its normative objectives. A qualitative descriptive approach was employed through a systematic literature review of scholarly sources published between 2017 and 2025. The findings indicate that Anti-Corruption Education cannot be categorically deemed ineffective; however, its impact remains constrained by structural weaknesses, cultural normalization of corruption, and inconsistencies between normative educational values and real-world governance practices. The absence of credible role models among political elites further undermines its transformative potential. The study argues that corruption perpetuates illegitimate power structures, erodes public trust, weakens democratic institutions, and fosters socio-political instability. Strengthening Anti-Corruption Education requires a contextual, practice-oriented approach supported by an integrated integrity ecosystem involving educational institutions, government bodies, and society at large.
Peran Media Sosial dalam Menanamkan Nilai Anti Korupsi pada Generasi Z Aprilia, Resti; Salsabila T, Lulu
Polyscopia Vol. 3 No. 2 (2026)
Publisher : Medan Resource Center

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57251/polyscopia.v3i2.2041

Abstract

Corruption continues to pose a pervasive challenge across social, political, and economic domains, requiring innovative preventive strategies that engage younger generations. Generation Z, characterized by high digital connectivity and active participation in online environments, represents a strategic demographic for the dissemination of anti-corruption values. This study investigates how social media functions as a medium for instilling anti-corruption values among Generation Z and examines the extent of its effectiveness in shaping attitudes and behaviors. Employing a qualitative approach through a literature review of recent scholarly works, this study analyzes patterns of digital engagement, content dissemination, and value internalization. The findings indicate that social media serves as a dynamic platform for education, advocacy campaigns, and character formation through interactive and visually engaging content. Its effectiveness, however, is contingent upon users’ digital literacy, the credibility of information sources, and the level of participatory engagement. The study argues that when strategically utilized, social media can operate as a transformative tool in fostering critical awareness and strengthening anti-corruption character among young people.
Perancangan Sistem Dinding Penahan Banjir Otomatis Berbasis Internet of Things (IoT) Menggunakan ESP32 Panjaitan, Farhan Fadillah; Basri, Mhd
Polyscopia Vol. 3 No. 2 (2026)
Publisher : Medan Resource Center

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57251/polyscopia.v3i2.2051

Abstract

Floods frequently cause significant environmental and infrastructural damage, while conventional monitoring systems often experience delayed responses. This study aims to design an automatic flood barrier system based on the Internet of Things using Espressif Systems 32 as the primary microcontroller. The research investigates how real-time monitoring and automated control can improve flood mitigation effectiveness. The system employs a load cell sensor integrated with the HX711 module to detect water pressure as an indicator of flood risk. Data are processed by the microcontroller and classified into normal, alert, and danger conditions. A linear actuator automatically activates the flood barrier when critical thresholds are reached. The system also transmits data via Wi-Fi using the Hypertext Transfer Protocol to a web-based monitoring dashboard for real-time observation. The results indicate that the system can accurately detect water pressure changes, activate the actuator automatically, and deliver monitoring data efficiently in real time. The study concludes that the proposed system offers an effective and responsive solution for automated flood mitigation.

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