{
      "userid": 46,
      "subjects": [
        "QA"
      ],
      "eprint_status": "archive",
      "date_type": "published",
      "ispublished": "pub",
      "lastmod": "2026-07-29 01:50:31",
      "department": "Fakultas Matematika dan Pengetahuan Alam",
      "institution": "Universitas Pakuan",
      "type": "thesis",
      "status_changed": "2026-07-29 01:50:31",
      "thesis_type": "Skripsi",
      "full_text_status": "none",
      "corp_creators": [
        "Universitas Pakuan",
        "Fakultas Matematika dan Ilmu Pnegetahuan Alam",
        "Program Studi Matematika"
      ],
      "divisions": [
        "sch_mat"
      ],
      "title": "ANALISIS FAKTOR-FAKTOR YANG MEMPENGARUHI\r\nKEJADIAN BALITA STUNTING DI INDONESIA\r\nMENGGUNAKAN REGRESI SEMIPARAMETRIK SPLINE",
      "date": 2025,
      "creators": [
        {
          "NPM": 64119009,
          "name": {
            "honourific": null,
            "family": "Ocsiella",
            "given": "Saskia Yety",
            "lineage": null
          }
        }
      ],
      "datestamp": "2026-07-29 01:50:31",
      "rev_number": 6,
      "metadata_visibility": "show",
      "uri": "http:\/\/eprints.unpak.ac.id\/id\/eprint\/11067",
      "eprintid": 11067,
      "contributors": [
        {
          "name": {
            "honourific": null,
            "family": "Erika",
            "given": "Yasmin",
            "lineage": null
          },
          "type": "http:\/\/www.loc.gov\/loc.terms\/relators\/THS"
        },
        {
          "name": {
            "honourific": null,
            "family": "Wijayanti",
            "given": "Hagni",
            "lineage": null
          },
          "type": "http:\/\/www.loc.gov\/loc.terms\/relators\/THS"
        }
      ],
      "thesis_name": "Sarjana",
      "abstract": "ANALISIS FAKTOR-FAKTOR YANG MEMPENGARUHI\r\nKEJADIAN BALITA STUNTING DI INDONESIA\r\nMENGGUNAKAN REGRESI SEMIPARAMETRIK SPLINE\r\nSakia Yety Ocsiella*, Yasmin Erika Faridhan, Hagni Wijayanti\r\nFMIPA, Universitas Pakuan, Jl. Pakuan, RT.02\/RW.06, Tegallega, Kecamatan Bogor Tengah,\r\nKota Bogor, Jawa Barat 16129\r\ne-mail: sakiayocsiella@gmail.com\r\nAbstract: This study aims to model the percentage of stunting and to analyze the factors influencing stunting\r\nprevalence in Indonesia. The explanatory variables considered include the percentage of animal-source\r\ncomplementary feeding (MPASI), child nutritional status (weight-for-age), access to improved sanitation,\r\naccess to unimproved drinking water, and the percentage of pregnant women consuming iron\r\nsupplementation (TTD). The scatter plots between the response and explanatory variables indicate nonlinear patterns; therefore, a semiparametric spline regression approach is employed. Semiparametric\r\nspline regression offers flexibility in capturing both linear and non-linear relationships through the use of\r\nknot points. In this study, models are constructed using one, two, three, four, and a combination of knot\r\npoints. The optimal model is selected based on the minimum value of Generalized Cross Validation (GCV).\r\nThe data used are secondary data obtained from the Ministry of Villages, Development of Disadvantaged\r\nRegions, and Transmigration, covering 38 provinces in Indonesia in 2023. The results show that the best\r\nmodel is achieved using a combination of knot points (2,3,4), with a minimum GCV value of 30.5424 and\r\na coefficient of determination (R²) of 89.42%. The findings indicate that all explanatory variables\r\nsignificantly influence the percentage of stunting. In conclusion, the semiparametric spline regression\r\nmodel is effective in modeling stunting prevalence in Indonesia and provides a flexible approach to\r\ncapturing complex relationships between variables.\r\nKeywords: stunting, semiparametric regression, spline, GCV, explanatory variables",
      "dir": "disk0\/00\/01\/10\/67"
    }