Claim Missing Document
Check
Articles

Found 2 Documents
Search

Implementasi Standar K3 Di Ketinggian Sebagai Upaya Pencegahan Kecelakaan Kerja Di Proyek Pembangunan Gedung X (Studi Kasus Proyek Pembangunan Gedung X Kota Semarang) Prasetyo, Rizky Dwi; Widowati, Evi
HIGEIA (Journal of Public Health Research and Development) Vol 6 No 4 (2022): October 2022
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/higeia.v6i4.58444

Abstract

Abstrak Proyek gedung sangat berkaitan dengan pekerjaan di ketinggian. Pekerjaan ketinggian pada pekerjaan struktur diketahui bahwa memiliki tingkat risiko yang tinggi. Berdasarkan data Canadian Centre for Occupational Health and Safety tahun 2021, lebih dari 42.000 pekerja cedera setiap tahun karena jatuh. Sekitar 67% jatuh terjadi pada tingkat yang sama akibat terpeleset dan tersandung. 33% sisanya jatuh dari ketinggian. Tujuan penelitian ini untuk mengetahui implementasi standar K3 di ketinggian sebagai upaya pencegahan kecelakaan kerja di Proyek Pembangunan Gedung X Kota Semarang. Jenis Penelitian ini adalah deskriptif kualitatif yang dilaksanakan pada bulan Februari 2022 sampai bulan Maret 2022. Hasil Penelitian ini diketahui bahwa dari 22 poin indikator, presentase indikator yang sesuai sejumlah 9,09% (2 indikator), tidak sesuai sejumlah 59,09% (13 indikator), dan tidak dilakukan sejumlah 31,81% (7 indikator). Simpulan dari penelitian ini yaitu implementasi standar K3 di ketinggian sebagai upaya pencegahan kecelakaan kerja di Proyek Pembangunan Gedung X Kota Semarang Belum Maksimal. Saran dari penelitian ini yaitu manajemen proyek Pembangunan Gedung X, melaksanakan indikator yang tidak sesuai dan tidak dilaksanakan. Abstract The building project is closely related to the work at height. Work at height on structural work is known to have a high level of risk. Based on 2021 Canadian Centre for Occupational Health and Safety data, more than 42,000 workers are injured each year from falls. About 67% of falls occur at the same rate as a result of slipping and tripping. The remaining 33% fell from a height. The purpose of this study is to determine the implementation of the K3 standard at high altitudes to prevent work accidents in the Semarang City Building X Construction Project. This type of research is descriptive and qualitative and will be carried out from February 2022 to March 2022. The results of this study are known that from 22 indicator points, the percentage of corresponding indicators amounted to 9.09% (2 indicators), did not match the number of 59.09% (13 indicators), and did not do 31.81% (7 indicators). This study concludes that the implementation of the K3 standard at high altitudes as an effort to prevent work accidents in the Semarang City Building X Construction Project has not been maximized. The advice from this study is the project management of Building X Construction, implementing indicators that are not appropriate and not implemented.
Pengaruh Optimasi Hyperparameter Random Forest terhadap Akurasi Prediksi Magnitudo Gempa Bumi Berdasarkan Hasil Klasterisasi DBSCAN Prasetyo, Rizky Dwi; Maori, Nadia Anissa; Zyen, Akhmad Khanif
Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) Vol 10 No 1 (2026): JANUARY 2026
Publisher : Lembaga Otonom Lembaga Informasi dan Riset Indonesia (KITA INFO dan RISET)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/jtik.v10i1.5555

Abstract

Indonesia is a country with high seismic activity due to its location at the convergence of three major tectonic plates. This condition creates a strong need for earthquake pattern analysis and magnitude prediction to support disaster mitigation. This study aims to cluster earthquake data using the Density-Based Spatial Clustering of Applications with Noise (DBSCAN) algorithm and to predict earthquake magnitude using the Random Forest algorithm optimized through hyperparameter tuning. The Indonesian earthquake dataset was obtained from Kaggle with a total of 92,887 valid entries. The DBSCAN clustering results revealed several active seismic zones, particularly in Sumatra, Java, Sulawesi, and Papua. The comparison of R² between the Baseline Random Forest and the Tuned Random Forest shows a significant improvement after the parameter tuning process. The Tuned Random Forest model achieves an R² value of 0.478, which is higher than the Baseline Random Forest's 0.442. This indicates that the tuned model is better able to explain the variance in the data and provides more accurate predictions.