Jurnal Teknosains Jurnal Ilmiah Sains dan Teknologi最新文献_第8页

Model for Coupling Scheme and its Impact on Neurons Behaviour 耦合方案模型及其对神经元行为的影响

Jurnal Teknosains Jurnal Ilmiah Sains dan Teknologi Pub Date : 2023-06-08 DOI: 10.34312/euler.v11i1.19964

Afifurrahman Afifurrahman

引用次数: 0

Model Discovery Learning Pada Pembelajaran Matematika Sekolah Menengah Pertama: A Bibliometric Review

Jurnal Teknosains Jurnal Ilmiah Sains dan Teknologi Pub Date : 2023-06-05 DOI: 10.34312/euler.v11i1.20042

Ilham Muhammad, Dadang Juandi

{"title":"Model Discovery Learning Pada Pembelajaran Matematika Sekolah Menengah Pertama: A Bibliometric Review","authors":"Ilham Muhammad, Dadang Juandi","doi":"10.34312/euler.v11i1.20042","DOIUrl":"https://doi.org/10.34312/euler.v11i1.20042","url":null,"abstract":"In the context of learning mathematics, the Discovery Learning method provides an effective approach to developing students' understanding and mathematical skills at the junior high school level. There have been many studies related to Discovery Learning. This study aims to determine the focus of research related to Discovery Learning in mathematics learning, especially at the junior high school level and its novelty. The method used is descriptive bibliometric analysis. A total of 21 data were taken from the Scopus database which had been refined with 4 stages (identification, screening, eligibility, and inclusion). The results showed that the number of publications related to this field reached its highest peak in 2017 and 2019. The publications made in 2017 had a significant influence on research related to Discovery Learning in mathematics learning in junior high schools. The Indonesian University of Education and Sebelas Maret University have a great influence in publications related to this field. The research focus related to Discovery Learning in mathematics learning is divided into two parts, namely, 1) educational computing, problem based learning, problem solving and self regulated learning; 2) geometry, and self-efficacy . New themes and novelty of research related to this context have been discussed in this article.","PeriodicalId":30843,"journal":{"name":"Jurnal Teknosains Jurnal Ilmiah Sains dan Teknologi","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82800502","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Penerapan Model Pembelajaran Treffinger untuk Meningkatkan Kemampuan Pemahaman Konsep Matematis Siswa berdasarkan Self-Efficacy Treffinger学习模式的应用，以提高学生基于自我efficacy的数学概念理解能力

Jurnal Teknosains Jurnal Ilmiah Sains dan Teknologi Pub Date : 2023-06-02 DOI: 10.34312/euler.v11i1.19879

Nindi Eliza Putri, A. Fatah

{"title":"Penerapan Model Pembelajaran Treffinger untuk Meningkatkan Kemampuan Pemahaman Konsep Matematis Siswa berdasarkan Self-Efficacy","authors":"Nindi Eliza Putri, A. Fatah","doi":"10.34312/euler.v11i1.19879","DOIUrl":"https://doi.org/10.34312/euler.v11i1.19879","url":null,"abstract":"In order to understand the content of mathematics, students must have an understanding of mathematical concepts. This study aims to examine how Treffinger learning can improve students' ability to understand mathematical concepts in terms of self-efficacy. This type of quantitative research is an approach designed for this experimental research. Class VII students of MTsN 1 Pandeglang are the population or object under study. The research design applied to the study was the Pretest-Posttest Nonequivalent Control Group Design. Sampling was determined using purposive sampling technique, class VII B and VII F were selected to serve as the experimental class and control class. Validated questionnaires and tests are useful research tools for collecting data on students' self-efficacy and ability to understand mathematical concepts. The hypothesis test in this study applies the Two-Way ANOVA test. The results of the study revealed that the Treffinger learning model provided an increase in the ability to understand mathematical concepts. What's more, there is a contribution between self-efficacy towards students' understanding of mathematics concepts.","PeriodicalId":30843,"journal":{"name":"Jurnal Teknosains Jurnal Ilmiah Sains dan Teknologi","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85621320","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Algoritma Dijkstra dan Algoritma Greedy Untuk Optimasi Rute Pengiriman Barang Pada Kantor Pos Gorontalo Dijkstra算法和Greedy算法，以优化Gorontalo邮局的货运路线

Jurnal Teknosains Jurnal Ilmiah Sains dan Teknologi Pub Date : 2023-06-01 DOI: 10.34312/euler.v11i1.18244

Novria Fatmawati Lakutu, Sri Lestari Mahmud, M. R. Katili, Nisky Imansyah Yahya

引用次数: 0

Implementasi Long Short Term Memory (LSTM) dan Bidirectional Long Short Term Memory (BiLSTM) Dalam Prediksi Harga Saham Syariah

Jurnal Teknosains Jurnal Ilmiah Sains dan Teknologi Pub Date : 2023-05-29 DOI: 10.34312/euler.v11i1.19791

Dian Islamiaty Puteri

{"title":"Implementasi Long Short Term Memory (LSTM) dan Bidirectional Long Short Term Memory (BiLSTM) Dalam Prediksi Harga Saham Syariah","authors":"Dian Islamiaty Puteri","doi":"10.34312/euler.v11i1.19791","DOIUrl":"https://doi.org/10.34312/euler.v11i1.19791","url":null,"abstract":"The development of the stock market in Indonesia is currently growing quite rapidly. This can be seen based on the number of investors who have increased every year. In 2011, sharia stocks were launched for the first time in Indonesia, and it can be seen that the price of the stock is not always stable or can experience increases or decreases. For investors, a strategy is needed to predict stock prices in order to make the right decisions in investing. In this study, stock prediction was carried out using the Long Short-Term Memory (LSTM) and Bidirectional Long Short-Term Memory (BiLSTM) methods. The data used in this study is historical closing price data for three Sharia stocks, namely PT Aneka Tambang Tbk, PT Unilever Indonesia Tbk, and PT Indofood Sukses Makmur Tbk. In building the best predictive model in this study based on tuning parameters such as epoch, batch, neurons, as well as an optimizer and dropout regulation techniques to prevent overfitting of the model. The test results show that from the three stock data used, the smallest MAPE value is obtained in the BiLSTM model. The MAPE values obtained for each stock data in this study are sequentially 2,59%, 1,77%, and 1,05%. Based on the MAPE value criteria, the prediction model is included in the very accurate criteria.","PeriodicalId":30843,"journal":{"name":"Jurnal Teknosains Jurnal Ilmiah Sains dan Teknologi","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73936417","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

Uji Performa Prediksi Gempa Bumi di Jawa Timur dengan Artificial Neural Network

Jurnal Teknosains Jurnal Ilmiah Sains dan Teknologi Pub Date : 2023-05-29 DOI: 10.34312/euler.v11i1.19291

J. Matematika, Sains dan, Teknologi, Muhammad Aji Permana, M. Faisal, Jurusan Magister Informatika

{"title":"Uji Performa Prediksi Gempa Bumi di Jawa Timur dengan Artificial Neural Network","authors":"J. Matematika, Sains dan, Teknologi, Muhammad Aji Permana, M. Faisal, Jurusan Magister Informatika","doi":"10.34312/euler.v11i1.19291","DOIUrl":"https://doi.org/10.34312/euler.v11i1.19291","url":null,"abstract":"East Java Province is an area directly adjacent to the Eurasian and Indo-Australian plate subduction zones, this has resulted in East Java province being an area prone to earthquakes. Predictions regarding the frequency of earthquake occurrences are very interesting to study. This needs to be done in order to increase our preparedness in an effort to reduce the risk of earthquakes. Research on earthquake prediction has been carried out, one of which is the artificial neural network method. The purpose of this study is to obtain the best network architecture that is applied to the data on the frequency of earthquake occurrences per month in East Java Province. Data on earthquake occurrences come from the BMKG Nganjuk Geophysics Station, which was recorded during the 2016-2021 period. The data was then grouped into the total frequency of events per month. The criteria for selecting the best network architecture are carried out by comparing each possible architecture's error values. The test method uses SSE (sum square error) criteria for each architectural model of the artificial neural network. The test results show that the input variation has a significant contribution and a greater correlation than the variation in the number of hidden neurons. The best prediction results are obtained in the model with 9-30-1 architecture with an error value of 0.1958.","PeriodicalId":30843,"journal":{"name":"Jurnal Teknosains Jurnal Ilmiah Sains dan Teknologi","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72795184","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Implementasi Struktur Aljabar Besar Pada Reaksi Kimia: Reduksi – Oksidasi 化学反应的大代数结构:还原——氧化

Jurnal Teknosains Jurnal Ilmiah Sains dan Teknologi Pub Date : 2023-05-29 DOI: 10.34312/euler.v11i1.19021

Fakhry Asad Agusfrianto, Yudi Mahatma

引用次数: 0

Model Problem Based Learning: Efektivitasnya Dalam Meningkatkan Hasil Belajar Sistem Persamaan Linear Dua Variabel 基于学习的问题模型:它在提高两个变量线性方程系统结果方面的有效性

Jurnal Teknosains Jurnal Ilmiah Sains dan Teknologi Pub Date : 2023-05-29 DOI: 10.34312/euler.v11i1.18387

Hendro Budi Santoso, Lailany Yahya, Dewi rahmawaty Isa

引用次数: 0

Pemodelan Numerik Tsunami untuk Mengestimasi Waktu Tiba dan Ketinggian Maksimum Gelombang Tsunami di Teluk Amurang

Jurnal Teknosains Jurnal Ilmiah Sains dan Teknologi Pub Date : 2023-05-29 DOI: 10.34312/euler.v11i1.19463

A. Fatimah, Rigolda Djamaluddin, Suria Darwisito, Jane M. Mamuaja, A. S. Wantasen, J. Schaduw

{"title":"Pemodelan Numerik Tsunami untuk Mengestimasi Waktu Tiba dan Ketinggian Maksimum Gelombang Tsunami di Teluk Amurang","authors":"A. Fatimah, Rigolda Djamaluddin, Suria Darwisito, Jane M. Mamuaja, A. S. Wantasen, J. Schaduw","doi":"10.34312/euler.v11i1.19463","DOIUrl":"https://doi.org/10.34312/euler.v11i1.19463","url":null,"abstract":"Amurang Bay is a coastal area of South Minahasa Regency which is densely populated but faces the subduction zone of North Sulawesi which has the potential to generate earthquakes that trigger a tsunami. The process of the tsunami disaster occurred quickly, but the impact was very destructive and caused many casualties. This study aims to determine the propagation of tsunami waves with the worst scenario Mw 8.5 in Amurang Bay. Numerical methods in COMCOT software are used to model the propagation of tsunami waves in order to obtain an estimate of arrival time and maximum height of tsunami waves. Based on this modeling, the estimated arrival time of tsunami waves at the virtual tide gauge point in Amurang Bay is in the range of 8–11 minutes. The maximum height of tsunami waves is included in the alert category, which is 9.55 meters to 11.44 meters. The fastest estimated arrival time was recorded in Amurang Barat District and maximum height of tsunami waves was found in Tumpaan District. The results of this modeling can be used as one of the steps for mitigating tsunami disaster by preparing the surrounding community and assisting the evacuation process when a tsunami disaster occurs.","PeriodicalId":30843,"journal":{"name":"Jurnal Teknosains Jurnal Ilmiah Sains dan Teknologi","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77315730","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Algoritma Genetika Untuk Penjadwalan Karyawan Ira Stationary 配置Ira Stationary员工的基因算法

Jurnal Teknosains Jurnal Ilmiah Sains dan Teknologi Pub Date : 2023-05-29 DOI: 10.34312/euler.v11i1.17364

Kurniasari Abram, N. Achmad, Muhammad Rezky Friesta Payu, Nurwan Nurwan, D. Wungguli, Asriadi Asriadi

引用次数: 0