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All Journal Jurnal Penelitian dan Pendidikan IPS Jurnal Sistem Informasi (JSI)
Narti Narti
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Computer Science & IT Education

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PENGARUH PEMBELAJARAN KOOPERATIF DAN MINAT TERHADAP PRESTASI BELAJAR Narti Narti
Jurnal Penelitian dan Pendidikan IPS Vol. 10 No. 3 (2016): JPPI
Publisher : Direktorat Pascasarjana Universitas PGRI Kanjuruhan Malang

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Abstract

The purpose of this study is to know how: 1) the influence of cooperative learning to learning achievement in IPS subject of student of SDN I Banjarjo District of Pudak Ponorogo Regency, 2) the influence of interest in learning to learning achievement in IPS subject of student of SDN I Banjarjo District of Pudak Ponorogo Regency, 3) the influence of cooperative learning and interest in learning simultaneously to learning achievement in IPS subject of student of SDN I Banjarjo District of Pudak Ponorogo Regency. This research is a quantitative research by using stratified proportional random sampling with the amount of samples are 30 respondents. Data collection techniques is using questionnaires and documentation. The analysis is using multiple linear regression analysis. Based on the multiple linear regression analysis, obtained the equation: Y = 55,632 + 0,369X1 + 0,162X2. The results showed that there is a significant influence of cooperative learning to learning achievement in IPS subject of student of SDN I Banjarjo District of Pudak Ponorogo Regency because of tstatistic (9,456) > ttable (2,052) or tsig (0,000) < α (0,05). And a significant influence of interest in learning to learning achievement in IPS subject of student of SDN I Banjarjo District of Pudak Ponorogo Regency because of tstatistic (3,018) > ttable (2,052) or tsig (0,005) < α (0,05). In addition, there is significant influence of cooperative learning and interest in learning simultaneously to learning achievement in IPS subject of student of SDN I Banjarjo District of Pudak Ponorogo Regency because of Fstatistic (21,733) > Ftable (3,354) or Fsig (0,000) < α (0,05) with the amount of influence is 79%. While the remaining 21% is influenced by other variables. .
Penerapan Metode Nueral Network dan Particle Swarm Optimization (PSO) untuk Prediksi Penjualan Bahan Kimia Asri Wahyuni; Narti Narti; Eka Puspita Sari
Jurnal Sistem Informasi Vol 7 No 2 (2018): JSI Periode Agustus 2018
Publisher : LPPM STMIK ANTAR BANGSA

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (447.291 KB) | DOI: 10.51998/jsi.v7i2.280

Abstract

AbstractË—Ë— Many chemical production companies are competing to continue producing mainly Hydrated Lime chemicals. Hydrated Lime is used to mix paper making one of them. The development of paper marketing is now progressing rapidly, hence the company makes a great opportunity in the production of Hydrated Lime chemicals. An increase in the number of paper mills not accompanied by the supply of Hydrated Lime chemicals may result in scarcity. In this case will encourage the company continues to increase its production volume to meet growing consumer demand. Prediction is a source of information that can be used by companies to prepare themselves in determining the strategy for the future better. In this study, predicted sales of Hydrated Lime with Neural Network method and Particle Swarm Optimization (PSO) optimization to predict time series data, so as to minimize RMSE value. From the test results obtained the average mean Root Mean Square Error (RMSE) Neural Network based Particle Swarm Optimization (PSO) with 7 neurons of 1.279. Intisari- Banyak perusahaan produksi bahan kimia yang bersaing untuk terus memproduksi bahan kimia terutama Hydrated Lime. Hydrated Lime digunakan untuk campuran pembuatan kertas salah satunya. Perkembangan pemasaran kertas saat ini semakin maju pesat, maka dari itu perusahan menjadikan suatu peluang yang besar dalam produksi bahan kimia Hydrated Lime. Pertambahan jumlah pabrik kertas yang tidak disertai dengan supply bahan kimia Hydrated Lime sehingga bisa terjadi kelangkaan. Dalam hal ini akan mendorong perusahaan terus meningkatkan volume produksinya untuk memenuhi permintaan konsumen yang semakin hari semakin besar. Prediksi merupakan sumber informasi yang dapat digunakan oleh perusahaan untuk mempersiapkan diri dalam menentukan strategi ke depan yang lebih baik. Pada penelitian ini, dilakukan prediksi penjualan Hydrated Lime dengan metode Neural Network dan optimasi Particle Swarm Optimization (PSO) untuk memprediksi data time series, sehingga dapat meminimalkan nilai RMSE. Dari hasil pengujian didapatkan nilai rata-rata Root Mean Square Error (RMSE) terkecil Neural Network berbasis Particle Swarm Optimization (Pso) dengan 7 neuron sebesar 1.279. Kata Kunci: Neural Network, Particle Swarm Optimization (PSO), Prediksi Penjualan, Time Series
Co-Authors Asri Wahyuni Eka Puspita Sari