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Analisis Prediksi Kecepatan Angin di Kabupaten Pekalongan dengan Algoritma Decision Tree Regression Safira, Noviana; Yuniarto, Abdul Hakim Prima
Jurnal Studi Multidisiplin Qomaruna Vol 2 No 2 (2025): 2025
Publisher : Lembaga Penelitian dan Pengabdian Masyarakat (LPPM), Universitas Qomaruddin, Gresik, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62048/qjms.v2i2.88

Abstract

The coastal characteristics of Pekalongan Regency indicate substantial wind potential, prompting the need for studies on renewable energy utilization. This study aims to forecast wind speed and estimate the electrical power that can be generated using a Decision Tree Regression algorithm. Eleven years of historical climate data (2013–2023) from the Indonesian Meteorology, Climatology, and Geophysics Agency (BMKG) were used to build the model. Evaluation results show a Mean Squared Error (MSE) of 4.108 and a coefficient of determination (R²) of 0.049, indicating the model has limited predictive performance. The 2024 wind speed forecast ranges from 3.8 to 7 m/s, with an average of 4.5 m/s. This wind speed translates into estimated electrical power ranging from 844 to 5,277 watts, averaging 1,599 watts per month, equivalent to a potential monthly energy output of 191.88 kWh. This study concludes that while there is potential for small-scale Wind Power Plant (PLTB) development, such as for public street lighting, the accuracy of the predictive model needs to be significantly improved for more critical applications.
Pengungkapan Diri Gen Z dalam “Komunitas Marah Marah” di Twitter Safira, Noviana; Sumardjijati, Sumardjijati
Hulondalo Jurnal Ilmu Pemerintahan dan Ilmu Komunikasi Vol 5 No 1 (2026): Januari - Juni 2026
Publisher : Fakultas Ilmu Sosial dan Ilmu Poliitik Universitas Ichsan Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59713/jipik.v5i1.1545

Abstract

This study examines the practice of self disclosure, which is the disclosure of personal information to others, carried out by Generation Z through komunitas marah marah on Twitter. The background of this study is formed by the increasing emotional openness and intense use of language. The objective of the study is to understand the forms of self disclosure that emerge and the factors influencing them, such as personality, gender, post topics, media anonymity, and social environment. This study employs a descriptive qualitative approach, using in-depth interviews and documentation of informants' posts. The results show that komunitas marah marah serve as an alternative space for Gen Z to anonymously express personal experiences and emotions. Social media anonymity provides a sense of safety when expressing sensitive topics, especially for introverted individuals. The lack of support in the real world also drives them to seek validation, empathy, and solutions through online communities. Thus, komunitas marah marah function as safe spaces that allow Gen Z to express themselves more freely, free from the pressure of social norms.