Joko Soebagyo

@uhamka.ac.id

Department of Mathematics Education
Universitas Muhammadiyah Prof. Dr. HAMKA



              

https://researchid.co/jokosoebagyo

EDUCATION

Mathematics Education

RESEARCH INTERESTS

Mathematics Education

5

Scopus Publications

Scopus Publications

  • A Psychometric Validation of the Sociomathematical Norm Scale for Senior High School Students in Mathematics Learning
    Samsul Maarif, Joko Soebagyo, Trisna Roy Pradipta, and Sri Adi Widodo

    Eurasian Society of Educational Research
    <p style="text-align: justify;">Students in mathematics classes do not understand the importance of sociomathematical norms in learning mathematics. This causes sociomathematical norms not to be teachers' focus when learning mathematics. Besides, there is no standardized instrument for assessing this norm, so developing this instrument is necessary to measure socio-mathematical norms in learning mathematics. This study aims to create and verify the psychometric validity of the sociomathematical norm scale. This research used a survey method with 505 senior high school students from Jakarta and West Java as respondents. The results showed that 25 items had convergent validity, with a loading factor value of > 0.700, meaning they could be declared valid. Concurrent validity indicates that each sociomathematical norms indicator is valid as a whole. Discriminant validity shows that the average variance extracted value on the diagonal is higher than the other values, so each item is declared valid. It was concluded that each item of the sociomathematical norms instrument has accuracy in its measurement function. The reliability test shows that each sociomathematical norms item is declared reliable. The reliability value of the sociomathematical norm item is .99, and the person's reliability is .86. Thus, the instruments developed can measure sociomathematical norms in learning mathematics.</p>

  • Critical review on mathematics virtual classroom practice in private university
    S. Maarif, K. Umam, J. Soebagyo and T. Pradipta


    A study has proven the benefits of mathematics classes learning mathematics at university. However, there is still a lack of evidence regarding its benefits in mathematics teacher education programs. This study aims to test the flipped class in a mathematics teacher education program at a private university in Indonesia. The data source comes from thirty-one students of the mathematics education program in this study. Various data methods were used, including observation, journals, and tests. Then the data were analyzed quantitatively and qualitatively. The findings showed that a reverse classroom encourages students to learn independently, with students working together with peers and increasing learning awareness. However, some of the challenges presented in flipped classroom applications include technical issues, record editing skills, and longer time consumed. The recommendations offered to refer to the findings.

  • Rainfall forecasting using PSPline and rice production with ocean-atmosphere interaction
    Rezzy Eko Caraka, Budi Darmawan Supatmanto, Muhammad Tahmid, Joko Soebagyo, M Ali Mauludin, Akbar Iskandar, and Bens Pardamean

    IOP Publishing
    The role of climate can be affected by plants. The weather can accelerate and multiply the existence of various plant pests and diseases, accelerate the growth and development of grass among plants, and encourage the emergence of infection and significant damage to plants. The elements of climate that affect the growth of plants are one of them is rainfall. In this paper, we performed the simulation using the non-parametric penalized spline (PSPLINE) method and studied the effect on rice production in Lampung. It can be concluded that the increasing fluctuation, frequency, and intensity of climate anomalies in the last decade caused by the ENSO phenomenon have an impact on changes in distribution patterns, intensity, and period of the wet season so that the start of the rainy season and the dry season becomes too late. As a result, there is a seasonal shift from normal average conditions that can ultimately have severe implications for food crops. In a nutshell penalized spline gives high accuracy with R 2 = 96.227% and MAPE = 1.62%.

  • Ensemble Time Series Modified Generalized Regression Neural Network Rainfall Forecasting
    Toni Toharudin, Rezzy Eko Caraka, Gumgum Darmawan, Akbar Iskandar, Oman Somantri, Arnita, Joko Soebagyo, Noor Ell Goldameir, and S. Asmawati

    IEEE
    Information about the predictionof the rainy season is vital for the community. The precise and accurate level of predicting the start of the season will certainly greatly assist various community activities in multiple sectors such as transportation, agriculture, forestry, health, public works, and others. SST controls the ability of the oceans to regulate heating and to regulate water distribution. The condition of local SST can be used as an indicator of the minimum amount of moisture in the atmosphere and is closely related to cloud formation in Indonesia. If the cold SST supply of water vapor in the atmosphere will be reduced, on the contrary, if the SST is warmer than average then the water vapor in the atmosphere will tend to be more. The warmer or hotter the sea surface temperature, the higher the availability of water vapor which causes cloud formation and of course the atmospheric conditions will become more humid. Time series data is a group of observations obtained at different time points with the same time interval, and the data sequence is assumed to be interconnected with each other. In this paper, we analyze the rainfall data in Sulawesi, which begins with the formation of spatial correlation and uses modified generalized regression neural network method to forecast. Get the best model with MSE testing values of 2. 77 * 10-4 and MAD testing of 0.00017 with the number of layer units 5-5-1.

  • Table-sized matrix model in fractional learning
    J Soebagyo, Wahyudin, and E C Mulyaning

    IOP Publishing