{
      "department": "FAKULTAS SAINS DAN TEKNOLOGI",
      "subjects": [
        515.6
      ],
      "eprintid": 79710,
      "thesis_type": "skripsi",
      "date": "2026-08-14",
      "userid": 12460,
      "documents": [
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            "language": "id",
            "placement": 1,
            "eprintid": 79710,
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                  "filesize": 8457354,
                  "filename": "21106010041_BAB-I_IV-atau-V_DAFTAR-PUSTAKA.pdf"
                }
            ],
            "content": "published",
            "rev_number": 3,
            "uri": "http:\/\/digilib.uin-suka.ac.id\/id\/document\/1087898",
            "main": "21106010041_BAB-I_IV-atau-V_DAFTAR-PUSTAKA.pdf",
            "mime_type": "application\/pdf",
            "docid": 1087898,
            "format": "text",
            "security": "public",
            "pos": 1,
            "formatdesc": "PEMODELAN PERTUMBUHAN EKONOMI DI INDONESIA DENGAN PERSAMAAN SIMULTAN DATA PANEL STATIS DAN DINAMIS"
          },
          {
            "language": "id",
            "placement": 2,
            "eprintid": 79710,
            "files": [
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                  "datasetid": "document",
                  "fileid": 1895103,
                  "objectid": 1087899,
                  "uri": "http:\/\/digilib.uin-suka.ac.id\/id\/file\/1895103",
                  "mime_type": "application\/pdf",
                  "hash": "3955d3057e8f16456a3504a3db8e514d",
                  "filesize": 15576001,
                  "filename": "21106010041_BAB-II_sampai_SEBELUM-BAB-TERAKHIR.pdf"
                }
            ],
            "content": "published",
            "rev_number": 3,
            "uri": "http:\/\/digilib.uin-suka.ac.id\/id\/document\/1087899",
            "main": "21106010041_BAB-II_sampai_SEBELUM-BAB-TERAKHIR.pdf",
            "mime_type": "application\/pdf",
            "docid": 1087899,
            "format": "text",
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            "pos": 2,
            "formatdesc": "PEMODELAN PERTUMBUHAN EKONOMI DI INDONESIA DENGAN PERSAMAAN SIMULTAN DATA PANEL STATIS DAN DINAMIS"
          }
      ],
      "rev_number": 10,
      "creators": [
        {
          "name": {
            "lineage": null,
            "given": "NIM.: 21106010041",
            "honourific": null,
            "family": "Cindy Lauren Marentesa"
          }
        }
      ],
      "dir": "disk0\/00\/07\/97\/10",
      "keywords": "PDRB, IPM, Persamaan Simultan, Data Panel, Metode 2SLS,\r\nMetode 2SLS GMM Arellano-Bond, MAPE, MSE",
      "lastmod": "2026-11-05 04:38:11",
      "ispublished": "pub",
      "metadata_visibility": "show",
      "date_type": "published",
      "eprint_status": "archive",
      "status_changed": "2026-11-05 04:38:11",
      "datestamp": "2026-11-05 04:38:11",
      "uri": "http:\/\/digilib.uin-suka.ac.id\/id\/eprint\/79710",
      "thesis_name": "other",
      "note": "Arya Fendha Ibnu Shina, M.Si. dan Arif Munandar, M.Sc.",
      "full_text_status": "restricted",
      "contact_email": "muh.khabib@uin-suka.ac.id",
      "divisions": [
        "jur_mat"
      ],
      "abstract": "Economic growth and human development are two main indicators of regional\r\ndevelopment success that influence each other in a complex manner. This study\r\naims to examine the simultaneous relationship between economic growth through\r\nGross Regional Domestic Product (GRDP) and human development measured by\r\nthe Human Development Index (HDI) in Indonesia. In addition to testing the twoway\r\ncausality, this research focuses on comparing the forecasting accuracy\r\nbetween the static panel data simultaneous equation model using the Two-Stage\r\nLeast Squares (2SLS) method and the dynamic panel data simultaneous equation\r\nmodel using the 2SLS Generalized Method of Moments Arellano Bond (GMM\r\nAB) method to determine the best estimation model. The data used covers 33\r\nprovinces in Indonesia, sourced from Statistics Indonesia (BPS). The simultaneity\r\ntest results indicate a significant simultaneous relationship between GRDP and\r\nHDI. The accuracy calculation is evaluated using the Mean Absolute Percentage\r\nError (MAPE) and Mean Squared Error (MSE) indicators. The 2SLS GMM AB\r\nmethod shows a MAPE value of 4.83% in the GRDP equation and 40.13% in the\r\nHDI equation. The testing results demonstrate that the 2SLS GMM Arellano Bond\r\nmethod is able to control time dynamic bias more optimally, thereby producing a\r\nlower error rate and more precise prediction accuracy compared to the 2SLS\r\nmethod.",
      "type": "thesis",
      "title": "PEMODELAN PERTUMBUHAN EKONOMI DI INDONESIA DENGAN PERSAMAAN SIMULTAN DATA PANEL STATIS DAN DINAMIS",
      "institution": "UIN SUNAN KALIJAGA YOGYAKARTA",
      "pages": 140
    }