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  1. Local wisdom in wound treatment practice in Tengger tribe farmers
    Istiqomah IN, Azizah LN, Mashuri M, Abidin Z, Pebriyanti DO
    Med J Malaysia, 2023 Jul;78(4):491-494.
    PMID: 37518918
    INTRODUCTION: Farmers have a high risk of injury either due to the use of agricultural tools, or chemicals, or the geographical conditions of the agricultural area. This study aimed to describe the use of local wisdom in the practice of wound treatment among Tengger tribal farmers in Indonesia.

    MATERIALS AND METHODS: This qualitative study used accidental sampling, conducted in the agricultural land of Ngadisari Village, Sukapura District, Probolinggo Regency, East Java for 3 weeks in November 2020. This study involved all farmers who were working on the land at the time of the study (n=30). The questionnaires consist of demographic, wound characteristics and wound treatment processes.

    RESULTS: The practice of wound treatment for the Tengger Tribe farmers is divided into two stages, namely the initial wound stage (stopping bleeding) using gums of medical plants and the wound healing stage, which is divided into treatment for the outer body using mashed leaf herbs and for the inner body using herbs that function to increase body stamina.

    CONCLUSION: The local wisdom Tengger ethnic-based wound treatment uses whatever is in nature to stop the bleeding and increase the wound healing process.

  2. Performance of T2-based PCA mix control chart with KDE control limit for monitoring variable and attribute characteristics
    Ahsan M, Mashuri M, Prastyo DD, Lee MH
    Sci Rep, 2024 Mar 28;14(1):7372.
    PMID: 38548881 DOI: 10.1038/s41598-024-58052-4
    In this work, the mixed multivariate T2 control chart's detailed performance evaluation based on PCA mix is explored. The control limit of the proposed control chart is calculated using the kernel density approach. Through simulation studies, the proposed chart's performance is assessed in terms of its capacity to identify outliers and process shifts. When 30% more outliers are included in the data, the proposed chart provides a consistent accuracy rate for identifying mixed outliers. For the balanced percentage of attribute qualities, misdetection happens because of the high false alarm rate. For unbalanced attribute qualities and excessive proportions, the masking effect is the key issue. The proposed chart shows the improved performance for the shift in identifying the shift in the process.
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