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Pelatihan Penyusunan Soal HOTS Berbasis Kurikulum Merdeka Belajar bagi Guru MTs Kecamatan Danau Teluk Jambi A.A Musyaffa; Siti Asiah; Umil Muhsinin; Siti Ubaidah; Sunarto Sunarto
Solusi Bersama : Jurnal Pengabdian dan Kesejahteraan Masyarakat Vol. 2 No. 3 (2025): Solusi Bersama : Jurnal Pengabdian dan Kesejahteraan Masyarakat
Publisher : Lembaga Pengembangan Kinerja Dosen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/solusibersama.v2i3.1890

Abstract

The purpose of this community service is to improve the understanding and competence of teachers at MTs in Teluk Lake District Jambi City in compiling HOTS questions based on the independent learning curriculum. The implementation method of this community service uses participatory training, with stages of providing a pretest on the HOTS concept, providing training materials and practice in compiling HOTS questions, providing a posttest, and providing an evaluation sheet for the implementation of the training. The data analysis technique uses descriptive statistical techniques using a percentage approach and graphics in presenting data. The partners of this community service are teachers at MTs Muhammadiyah Tajurhalang Bogor. The results of this community service show that MTs in Teluk Lake District Jambi City teachers have a good conceptual understanding of HOTS questions and increased skills in compiling HOTS questions based on the Independent Learning curriculum, so that they can be practiced in every learning evaluation in the classroom.
Annual Rainfall Prediction in Indonesia Using A Hybrid Artificial Neural Network and Fuzzy Algorithm Model Siti Asiah; Wanda Riana; Dika Chryston Purba; M Ilham Azharsum; Victor Asido Elyakim P
JOMLAI: Journal of Machine Learning and Artificial Intelligence Vol. 4 No. 2 (2025): Juni 2025
Publisher : Yayasan Literasi Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55123/jomlai.v4i2.5964

Abstract

Rainfall is an essential meteorological parameter that affects various sectors of life. Accurately predicting rainfall has become crucial, and artificial intelligence-based models are increasingly popular in this field. Artificial Neural Networks (ANNs) have been widely used due to their ability to identify non-linear patterns in complex data. However, ANN-based predictions have limitations in optimally handling uncertainty or data variability. To address this issue, this study proposes a hybrid model that combines ANNs with fuzzy algorithms. Fuzzy algorithms are capable of managing uncertainty and providing flexible decision-making. This research proposes a hybrid model that integrates Artificial Neural Networks (ANNs) and fuzzy algorithms to predict annual rainfall based on meteorological data from 2019 to 2024. ANNs are used to detect non-linear patterns in temperature, humidity, and atmospheric pressure data, while fuzzy algorithms handle the uncertainty in input data. The model was tested using data from local meteorological stations and evaluated using MAE, RMSE, and the coefficient of determination (R²) metrics. The evaluation results show that the hybrid model achieved the best performance, with an MAE of 3.17 mm, RMSE of 3.4 mm, and R² of 0.98. These findings indicate that the combination of ANN and fuzzy logic significantly improves the accuracy of rainfall prediction compared to individual methods. This model has the potential to be applied in early warning systems and more precise climate management.
Efektivitas Pijat Punggung Atas terhadap Tekanan Sistol Diastol Ibu Hamil Trimester III di RSUD Kota Cilegon Tahun 2024: Effectiveness of Upper Bac Massage on 3rd Trimester Pregnant Women’s Diastal Systolic Pressure in Hospital Cilegon City in 2024 Dewi Rostianingsih; Wiwit Desi Intarti; Siti Asiah
Jurnal Kebidanan Harapan Ibu Pekalongan Vol. 12 No. 2 (2025): Jurnal Kebidanan Harapan Ibu Pekalongan
Publisher : LPPM Akademi Kebidanan Harapan Ibu Pekalongan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37402/jurbidhip.vol12.iss2.396

Abstract

Maternal health is measured by the Maternal Mortality Rate (MMR), where hypertension in pregnancy is one of the leading causes of maternal death worldwide. In 2020, approximately 302,000 maternal deaths were recorded in developing countries, some of which were caused by complications of hypertension. Approximately 10% of pregnancies globally are affected by hypertension, which can cause acute morbidity, long-term disability, and even maternal and infant death. Hypertension management is not only through pharmacological therapy, but also through non-pharmacological approaches such as upper back massage. This study aims to evaluate the effectiveness of upper back massage on reducing systolic and diastolic blood pressure in third-trimester pregnant women at Cilegon City Hospital in 2024. The study design used a quasi-experimental approach with a pretest-posttest approach without a control group and involved 25 respondents selected through purposive sampling. The results of the paired t-test showed a decrease in mean systolic pressure from 144 mmHg to 133 mmHg, and diastolic from 93 mmHg to 83 mmHg, with a significance value of p= 0.001 (p < 0.05). It can be concluded that upper back massage is effective in reducing blood pressure in pregnant women in the third trimester, so it can be used as a supporting intervention in the management of gestational hypertension.