The Measurement of Rare Plants Learning Media using Backward Chaining Integrated with Context-Input-Process-Product Evaluation Model based on Mobile Technology

Abstract

This research was aimed to know the effectiveness level of learning media utilization to the introduction of rare plants in Alas Kedaton tourism forest in Tabanan-Bali based on backward chaining for students and the general public. The type of this research includes explorative and evaluative research types. The population in this study was the plants species that exist in the Alas Kedaton tourism forest. The human population was the entire society in the area of Alas Kedaton tourism forest. The sampling method of plants species used the quadratic method, while for the human samples used purposive sampling method. The data has been collected then analyzed descriptively. The results of this study indicate that through the utilization of learning media obtained related information about the number of rare plants species in Alas Kedaton tourism forest as many as 48 species of plants with 26 families, and also the factors causing the scarcity of those plants species. Through the use of CIPP (Context-Input-Process-Product) evaluation model assisted by mobile technology, the overall average effectiveness of learning media utilization to the introduction of rare plant in Alas Kedaton tourism forest in Tabanan-Bali based on backward chaining amount of 88.20%, so that was included into the good categorization.

Authors and Affiliations

Nyoman Wijana, Ni Nyoman Parmithi, I Gede Astra Wesnawa, I Made Ardana, I Wayan Eka Mahendra, Dewa Gede Hendra Divayana

Keywords

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  • EP ID EP375785
  • DOI 10.14569/IJACSA.2018.090834
  • Views 101
  • Downloads 0

How To Cite

Nyoman Wijana, Ni Nyoman Parmithi, I Gede Astra Wesnawa, I Made Ardana, I Wayan Eka Mahendra, Dewa Gede Hendra Divayana (2018). The Measurement of Rare Plants Learning Media using Backward Chaining Integrated with Context-Input-Process-Product Evaluation Model based on Mobile Technology. International Journal of Advanced Computer Science & Applications, 9(8), 265-277. https://www.europub.co.uk/articles/-A-375785