Application Information Technology For Posyandu Cadres: SI-MASTING For Early Detection of Stunting

Authors

  • Rina Sri Widayati Department of Mitwifery, Universitas ‘Aisyiyah Surakarta, Indonesia
  • Nur Amalina Department of Retail Management, Universitas ‘Aisyiyah Surakarta, Indonesia
  • Galih Pramuja Inngam Fanani Department of System and Technology Information, Universitas ‘Aisyiyah Surakarta, Indonesia
  • Suratman Suratman Department of Biology, Universitas Sebelas Maret, Indonesia
  • Aulia Uswatun Khasanah Department of Retail Management, Universitas ‘Aisyiyah Surakarta, Indonesia
  • Riyani Wulandari Department of Nursing, Universitas ‘Aisyiyah Surakarta, Indonesia

DOI:

https://doi.org/10.51601/ijcs.v5i4.906

Abstract

Stunting remains a major public health issue in Indonesia, with a prevalence of 21.6% in 2022 (SSGI). Early detection at Posyandu is often constrained by manual recording, which is time-consuming, error-prone, and difficult to integrate with health systems. This study aimed to implement SI-MASTING (Stunting Early Detection Information System) to improve the effectiveness and accuracy of child growth monitoring. The study was conducted at Posyandu Sanggrahan, Sukoharjo, involving 95 cadres through Focus Group Discussions (FGDs) and User Acceptance Testing (UAT), along with trials on 11 toddlers. Results showed that SI-MASTING reduced the average recording time from 7.1 minutes to 2.4 minutes per child (66.2% efficiency) and decreased the error rate from 15.4% to 2.1% (86.3% accuracy improvement). Detection of children at risk of stunting increased from 48% to 92% (44% improvement). Cadre satisfaction was high, with an average score of 4.52 out of 5; ease of use received the highest rating of 4.67, followed by application speed at 4.58. In case testing, 45% of toddlers were identified as stunted, with the highest prevalence of 50% in the 12–18 month age group. In conclusion, SI-MASTING effectively accelerates early stunting detection, enhances data accuracy, and empowers cadres in nutritional interventions. The system has strong potential for integration with e-Puskesmas and replication in other regions as part of the national strategy to accelerate stunting reduction.

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Author Biographies

Rina Sri Widayati, Department of Mitwifery, Universitas ‘Aisyiyah Surakarta, Indonesia

<em>Stunting remains a major public health issue in Indonesia, with a prevalence of 21.6% in 2022 (SSGI). Early detection at Posyandu is often constrained by manual recording, which is time-consuming, error-prone, and difficult to integrate with health systems. This study aimed to implement SI-MASTING (Stunting Early Detection Information System) to improve the effectiveness and accuracy of child growth monitoring. The study was conducted at Posyandu Sanggrahan, Sukoharjo, involving 95 cadres through Focus Group Discussions (FGDs) and User Acceptance Testing (UAT), along with trials on 11 toddlers. Results showed that SI-MASTING reduced the average recording time from 7.1 minutes to 2.4 minutes per child (66.2% efficiency) and decreased the error rate from 15.4% to 2.1% (86.3% accuracy improvement). Detection of children at risk of stunting increased from 48% to 92% (44% improvement). Cadre satisfaction was high, with an average score of 4.52 out of 5; ease of use received the highest rating of 4.67, followed by application speed at 4.58. In case testing, 45% of toddlers were identified as stunted, with the highest prevalence of 50% in the 12–18 month age group. In conclusion, SI-MASTING effectively accelerates early stunting detection, enhances data accuracy, and empowers cadres in nutritional interventions. The system has strong potential for integration with e-Puskesmas and replication in other regions as part of the national strategy to accelerate stunting reduction.</em>

Nur Amalina, Department of Retail Management, Universitas ‘Aisyiyah Surakarta, Indonesia

<em>Stunting remains a major public health issue in Indonesia, with a prevalence of 21.6% in 2022 (SSGI). Early detection at Posyandu is often constrained by manual recording, which is time-consuming, error-prone, and difficult to integrate with health systems. This study aimed to implement SI-MASTING (Stunting Early Detection Information System) to improve the effectiveness and accuracy of child growth monitoring. The study was conducted at Posyandu Sanggrahan, Sukoharjo, involving 95 cadres through Focus Group Discussions (FGDs) and User Acceptance Testing (UAT), along with trials on 11 toddlers. Results showed that SI-MASTING reduced the average recording time from 7.1 minutes to 2.4 minutes per child (66.2% efficiency) and decreased the error rate from 15.4% to 2.1% (86.3% accuracy improvement). Detection of children at risk of stunting increased from 48% to 92% (44% improvement). Cadre satisfaction was high, with an average score of 4.52 out of 5; ease of use received the highest rating of 4.67, followed by application speed at 4.58. In case testing, 45% of toddlers were identified as stunted, with the highest prevalence of 50% in the 12–18 month age group. In conclusion, SI-MASTING effectively accelerates early stunting detection, enhances data accuracy, and empowers cadres in nutritional interventions. The system has strong potential for integration with e-Puskesmas and replication in other regions as part of the national strategy to accelerate stunting reduction.</em>

Galih Pramuja Inngam Fanani, Department of System and Technology Information, Universitas ‘Aisyiyah Surakarta, Indonesia

<em>Stunting remains a major public health issue in Indonesia, with a prevalence of 21.6% in 2022 (SSGI). Early detection at Posyandu is often constrained by manual recording, which is time-consuming, error-prone, and difficult to integrate with health systems. This study aimed to implement SI-MASTING (Stunting Early Detection Information System) to improve the effectiveness and accuracy of child growth monitoring. The study was conducted at Posyandu Sanggrahan, Sukoharjo, involving 95 cadres through Focus Group Discussions (FGDs) and User Acceptance Testing (UAT), along with trials on 11 toddlers. Results showed that SI-MASTING reduced the average recording time from 7.1 minutes to 2.4 minutes per child (66.2% efficiency) and decreased the error rate from 15.4% to 2.1% (86.3% accuracy improvement). Detection of children at risk of stunting increased from 48% to 92% (44% improvement). Cadre satisfaction was high, with an average score of 4.52 out of 5; ease of use received the highest rating of 4.67, followed by application speed at 4.58. In case testing, 45% of toddlers were identified as stunted, with the highest prevalence of 50% in the 12–18 month age group. In conclusion, SI-MASTING effectively accelerates early stunting detection, enhances data accuracy, and empowers cadres in nutritional interventions. The system has strong potential for integration with e-Puskesmas and replication in other regions as part of the national strategy to accelerate stunting reduction.</em>

Suratman Suratman, Department of Biology, Universitas Sebelas Maret, Indonesia

<em>Stunting remains a major public health issue in Indonesia, with a prevalence of 21.6% in 2022 (SSGI). Early detection at Posyandu is often constrained by manual recording, which is time-consuming, error-prone, and difficult to integrate with health systems. This study aimed to implement SI-MASTING (Stunting Early Detection Information System) to improve the effectiveness and accuracy of child growth monitoring. The study was conducted at Posyandu Sanggrahan, Sukoharjo, involving 95 cadres through Focus Group Discussions (FGDs) and User Acceptance Testing (UAT), along with trials on 11 toddlers. Results showed that SI-MASTING reduced the average recording time from 7.1 minutes to 2.4 minutes per child (66.2% efficiency) and decreased the error rate from 15.4% to 2.1% (86.3% accuracy improvement). Detection of children at risk of stunting increased from 48% to 92% (44% improvement). Cadre satisfaction was high, with an average score of 4.52 out of 5; ease of use received the highest rating of 4.67, followed by application speed at 4.58. In case testing, 45% of toddlers were identified as stunted, with the highest prevalence of 50% in the 12–18 month age group. In conclusion, SI-MASTING effectively accelerates early stunting detection, enhances data accuracy, and empowers cadres in nutritional interventions. The system has strong potential for integration with e-Puskesmas and replication in other regions as part of the national strategy to accelerate stunting reduction.</em>

Aulia Uswatun Khasanah, Department of Retail Management, Universitas ‘Aisyiyah Surakarta, Indonesia

<em>Stunting remains a major public health issue in Indonesia, with a prevalence of 21.6% in 2022 (SSGI). Early detection at Posyandu is often constrained by manual recording, which is time-consuming, error-prone, and difficult to integrate with health systems. This study aimed to implement SI-MASTING (Stunting Early Detection Information System) to improve the effectiveness and accuracy of child growth monitoring. The study was conducted at Posyandu Sanggrahan, Sukoharjo, involving 95 cadres through Focus Group Discussions (FGDs) and User Acceptance Testing (UAT), along with trials on 11 toddlers. Results showed that SI-MASTING reduced the average recording time from 7.1 minutes to 2.4 minutes per child (66.2% efficiency) and decreased the error rate from 15.4% to 2.1% (86.3% accuracy improvement). Detection of children at risk of stunting increased from 48% to 92% (44% improvement). Cadre satisfaction was high, with an average score of 4.52 out of 5; ease of use received the highest rating of 4.67, followed by application speed at 4.58. In case testing, 45% of toddlers were identified as stunted, with the highest prevalence of 50% in the 12–18 month age group. In conclusion, SI-MASTING effectively accelerates early stunting detection, enhances data accuracy, and empowers cadres in nutritional interventions. The system has strong potential for integration with e-Puskesmas and replication in other regions as part of the national strategy to accelerate stunting reduction.</em>

Riyani Wulandari, Department of Nursing, Universitas ‘Aisyiyah Surakarta, Indonesia

<em>Stunting remains a major public health issue in Indonesia, with a prevalence of 21.6% in 2022 (SSGI). Early detection at Posyandu is often constrained by manual recording, which is time-consuming, error-prone, and difficult to integrate with health systems. This study aimed to implement SI-MASTING (Stunting Early Detection Information System) to improve the effectiveness and accuracy of child growth monitoring. The study was conducted at Posyandu Sanggrahan, Sukoharjo, involving 95 cadres through Focus Group Discussions (FGDs) and User Acceptance Testing (UAT), along with trials on 11 toddlers. Results showed that SI-MASTING reduced the average recording time from 7.1 minutes to 2.4 minutes per child (66.2% efficiency) and decreased the error rate from 15.4% to 2.1% (86.3% accuracy improvement). Detection of children at risk of stunting increased from 48% to 92% (44% improvement). Cadre satisfaction was high, with an average score of 4.52 out of 5; ease of use received the highest rating of 4.67, followed by application speed at 4.58. In case testing, 45% of toddlers were identified as stunted, with the highest prevalence of 50% in the 12–18 month age group. In conclusion, SI-MASTING effectively accelerates early stunting detection, enhances data accuracy, and empowers cadres in nutritional interventions. The system has strong potential for integration with e-Puskesmas and replication in other regions as part of the national strategy to accelerate stunting reduction.</em>

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Published

2025-11-28

How to Cite

Sri Widayati, R., Amalina, N., Pramuja Inngam Fanani, G. ., Suratman, S., Uswatun Khasanah, A. ., & Wulandari, R. . (2025). Application Information Technology For Posyandu Cadres: SI-MASTING For Early Detection of Stunting. International Journal Of Community Service, 5(4), 476–485. https://doi.org/10.51601/ijcs.v5i4.906

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Vol. 5 No. 4 (2025): November 2025 ( Indonesia - Thailand - Malaysia - Timor Leste - Philippines )

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Copyright (c) 2025 Rina Sri Widayati, Nur Amalina, Galih Pramuja Inngam Fanani, Suratman Suratman, Aulia Uswatun Khasanah, Riyani Wulandari

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