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PENGARUH MODEL PEMBELAJARAN PROBLEM POSING TIPE PRE SOLUTION POSING UNTUK MENINGKATKAN KETERAMPILAN KOMUNIKASI DAN HASIL BELAJAR SISWA KELAS VII MTS Fatmawati, Fatmawati; Nurdiana, Nurdiana; Hanapi, Hanapi
Eksakta : Jurnal Penelitian dan Pembelajaran MIPA Vol 7, No 1 (2022): Eksakta : Jurnal Penelitian dan Pembelajaran MIPA
Publisher : Fakultas Keguruan Dan Ilmu Pendidikan, UM-Tapsel

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31604/eksakta.v7i1.95-99

Abstract

AbstractThis study aims to determine the effect of the Pre-Solution Posing Problem Posing learning model to improve communication skills and biology science learning outcomes for seventh grade students of MTs Darussalimin NW Sengkol Mantang. The research method used is Quasi Experiment Design. The population in this study were all students of class VII B and VII C, totaling 41 students at MTs Darussalimin NW Sengkol Mantang. While the samples in this study were class VII B as the control class and class VII C as the experimental class. The instrument in this study used tests and rubrics, to measure students' communication skills using rubrics and to measure student learning outcomes using multiple-choice tests.Based on the results of the study to determine the effect of the pre-solution posing type of problem posing learning model to improve communication skills and learning outcomes of class VII students of MTs Darussalimin NW Sengkol Mantang for the 2020/2021 academic year, a hypothesis test was carried out using an independent sample t test, which obtained the results sig 0.000 which means sig 0.05, so H0 is rejected and Ha is accepted. So the results show that there is an effect of the pre-solution posing type of problem posing learning model to improve communication skills and learning outcomes for class VII students of MTs Darussalimin NW Sengkol Mantang for the 2020/2021 academic year.Keywords: Learning Model Problem Posing Type Pre-Solution Posing,                        Communication Skills, Learning OutcomesAbstrakPenelitian ini bertujuan untuk mengetahui pengaruh model pembelajaran Problem Posing Tipe Pre- Solution Posing untuk meningkatkan keterampilan komunikasi dan hasil belajar IPA Biologi siswa kelas VII MTs Darussalimin NW Sengkol Mantang. Metode penelitian yang digunakana dalah Quasi Eksperimen Design. Populasi pada penelitian ini adalah seluruh peserta didik kelas VII B dan VII C yang berjumlah 41 siswa di MTs Darussalimin NW Sengkol Mantang. Sedangkan sampel pada penelitian ini adalah kelas VII B sebagai kelas kontrol dan kelas VII C sebagai kelas eksperimen. Instrument pada penelitian ini menggunakan tes dan rubrik, untuk mengukur keterampilan komunikasi siswa menggunakan rubrik dan untuk mengukur hasil belajar siswa menggunakan tes berupa soal pilihan ganda.Berdasarkan hasil penelitian untuk mengetahui adanya pengaruh model pembelajaran problem posing tipe pre solution posing untuk meningkatkan keterampilan komunikasi dan hasil belajar siswa kelas VII MTs Darussalimin NW Sengkol Mantang Tahun Pelajaran 2020/2021 dilakukan uji hipotesis menggunakan uji independent sampel t test, yang dimana didapatkan hasil nilai sig 0,000 yang berarti sig 0,05, sehingga H0 ditolak dan Ha diterima. Sehingga hasil menunjukkan bahwa ada pengaruh model pembelajaran problem posing tipe pre-solution posing untuk meningkatkan keterampilan komunikasi dan hasil belajar siswa kelas VII MTs Darussalimin NW Sengkol Mantang Tahun Pelajaran 2020/2021.Kata Kunci: Model Pembelajaran Problem Posing Tipe Pre-Solution Posing,                        Keterampilan Komunikasi, Hasil Belajar 
Ritual Perang Topat sebagai Praktik Ekologis: Kepercayaan Masyarakat dalam Pelestarian Alam Hanapi, Hanapi; Zulkarnain, Zulkarnain; Rasyidi, Ahyar; Istiqlal, Lalu M.
Jurnal Humanitas: Katalisator Perubahan dan Inovator Pendidikan Vol 12 No 1 (2026): Maret
Publisher : Universitas Hamzanwadi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29408/jhm.v12i1.33941

Abstract

This study aims to analyze the Perang Topat ritual as a form of local ecological practice and as an expression of the community’s belief system in environmental conservation. The research employs a qualitative approach using an ethnoecology-based case study design. Data were collected through observation, semi-structured interviews with customary leaders, religious figures, and local community members, as well as document analysis. Data analysis was conducted using an interpretative thematic approach through coding, categorization, and inductive identification of ecological values. The findings indicate that the Perang Topat ritual functions as both a religious and social practice while embodying ecological values, including respect for nature, sustainable resource management, and the strengthening of collective awareness regarding environmental preservation. The belief systems of the Sasak (Islam) and Balinese (Hindu) communities concerning the sacredness of nature foster ecological behaviors that are transmitted intergenerationally through ritual practices. Perang Topat can therefore be understood as a form of local ecological practice that contributes to environmental conservation grounded in local wisdom.
Model Prediksi Permintaan Produk Berbasis Big Data Analytics untuk Pengendalian Persediaan Multi-Produk Almayandi, Almayandi; Hanapi, Hanapi; Azmi, Haerul
Indonesian Journal of Engineering (IJE) Vol. 5 No. 2 (2025): Edisi Maret
Publisher : Fakultas Teknik Universitas Nahdlatul Ulama Nusa Tenggara Barat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69503/ije.v5i2.1624

Abstract

Abstrak: Penelitian ini bertujuan mengembangkan model prediksi permintaan produk berbasis Big Data Analytics untuk meningkatkan efektivitas pengendalian persediaan multi-produk. Permasalahan utama terletak pada rendahnya akurasi metode prediksi tradisional dalam menangani data kompleks dan dinamika permintaan yang tinggi. Penelitian ini menggunakan pendekatan kuantitatif berbasis data-driven dengan memanfaatkan data historis penjualan, perilaku konsumen, serta faktor eksternal seperti musim dan promosi. Model yang dikembangkan mengintegrasikan metode statistik, machine learning, dan deep learning dalam kerangka hybrid untuk menangkap pola linear dan non-linear secara simultan. Tahapan penelitian meliputi pengumpulan data, preprocessing, feature engineering, pelatihan model, serta evaluasi menggunakan metrik Mean Absolute Error (MAE) dan Root Mean Square Error (RMSE). Selain itu, teknik ensemble learning dan clustering diterapkan untuk meningkatkan akurasi dan stabilitas model. Hasil penelitian menunjukkan bahwa model hybrid berbasis Big Data Analytics mampu menghasilkan prediksi dengan tingkat akurasi lebih tinggi dibandingkan model tunggal. Model ini juga mampu menangkap interdependensi antar produk dalam sistem multi-produk secara lebih efektif. Integrasi hasil prediksi dengan kebijakan pengendalian persediaan seperti safety stock dan reorder point menunjukkan peningkatan efisiensi operasional melalui penurunan risiko overstock dan stockout. Selain itu, sistem yang dikembangkan mampu merespons perubahan permintaan secara lebih cepat dan adaptif. Penelitian ini memberikan kontribusi dalam pengembangan model prediksi yang tidak hanya akurat, tetapi juga aplikatif dalam mendukung pengambilan keputusan inventory di era digital. Abstract: This study aims to develop a product demand forecasting model based on Big Data Analytics to improve the effectiveness of multi-product inventory control. The main problem lies in the low accuracy of traditional forecasting methods in handling complex data and high demand variability. This study employs a quantitative, data-driven approach by utilizing historical sales data, consumer behavior, and external factors such as seasonality and promotions. The proposed model integrates statistical methods, machine learning, and deep learning within a hybrid framework to simultaneously capture linear and non-linear patterns. The research stages include data collection, preprocessing, feature engineering, model training, and evaluation using Mean Absolute Error (MAE) and Root Mean Square Error (RMSE). In addition, ensemble learning and clustering techniques are applied to enhance model accuracy and stability. The results indicate that the hybrid model based on Big Data Analytics produces higher prediction accuracy compared to single models. The model effectively captures interdependencies among products within a multi-product system. The integration of forecasting results with inventory control policies, such as safety stock and reorder point, improves operational efficiency by reducing the risks of overstock and stockouts. Furthermore, the developed system responds more quickly and adaptively to demand fluctuations. This study contributes to the development of forecasting models that are not only accurate but also practical in supporting inventory decision-making in the digital era.