Technology performance of Indonesia tsunami early warning system: technometric approach

Indonesia tsunami early warning system (Ina TEWS) is used for detecting earthquakes and tsunamis. The system currently is still under development and the government really needs information regarding the technological capabilities of the system in order to provide protection to the community from the threat of tsunamis and earthquakes. To produce the system and its components on an industrial scale, it is important to assess the extent of performance and readiness for technological development. The assessment used the technometric method which groups technological components into technoware, humanware, infoware, and orgaware, integrated with analytic hierarchy process. The results showed that the highest technology component contribution is technoware, and the lowest is infoware. Based on the magnitude of the contribution of technology components and intensity of technology, the priority order is technoware, humanware, orgaware, and infoware. The technology contribution coefficient is 0.522 (Good). The technology level is semi modern. Infoware is the lowest technological component, therefore improvement efforts are needed, namely structuring an integrated document system and improving standard operating procedures for manufacturing operational activities, especially in the testing and data validation.

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Publication Details

Journal
International Journal of Power Electronics and Drive Systems/International Journal of Electrical and Computer Engineering
Published
2024-11-18
DOI
https://doi.org/10.11591/ijece.v15i1.pp129-145
Primary Topic
Big Data and Business Intelligence
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article
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article

Technology performance of Indonesia tsunami early warning system: technometric approach

Hardono Hardono, Jaizuluddin Mahmud, Irawan Santoso, Gani Soehadi et al.
International Journal of Power Electronics and Drive Systems/International Journal of Electrical and Computer Engineering
Big Data and Business Intelligence
article

Technology performance of Indonesia tsunami early warning system: technometric approach

Hardono Hardono, Jaizuluddin Mahmud, Irawan Santoso, Gani Soehadi, Satrio Utomo, Budi Setiadi Sadikin, Fitriana Tiolita, Helen Fifianny
article en

Abstract

Indonesia tsunami early warning system (Ina TEWS) is used for detecting earthquakes and tsunamis. The system currently is still under development and the government really needs information regarding the technological capabilities of the system in order to provide protection to the community from the threat of tsunamis and earthquakes. To produce the system and its components on an industrial scale, it is important to assess the extent of performance and readiness for technological development. The assessment used the technometric method which groups technological components into technoware, humanware, infoware, and orgaware, integrated with analytic hierarchy process. The results showed that the highest technology component contribution is technoware, and the lowest is infoware. Based on the magnitude of the contribution of technology components and intensity of technology, the priority order is technoware, humanware, orgaware, and infoware. The technology contribution coefficient is 0.522 (Good). The technology level is semi modern. Infoware is the lowest technological component, therefore improvement efforts are needed, namely structuring an integrated document system and improving standard operating procedures for manufacturing operational activities, especially in the testing and data validation.

International Journal of Power Electronics and Drive Systems/International Journal of Electrical and Computer EngineeringVol. 15(1)
National Research and Innovation Agency (ID)
Openalex Percentile: Top 68%
Big Data and Business Intelligence
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Technology performance of Indonesia tsunami early warning system: technometric approach — Hardono Hardono, Jaizuluddin Mahmud, et al. · International Journal of Power Electronics and Drive Systems/International Journal of Electrical and Computer Engineering (2024) | TGRS Research Map | TGRS