{
      "department": "FAKULTAS SAINS DAN TEKNOLOGI",
      "subjects": [
        6.3
      ],
      "eprintid": 76466,
      "thesis_type": "skripsi",
      "date": "2026-04-22",
      "userid": 12460,
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            "uri": "http:\/\/digilib.uin-suka.ac.id\/id\/document\/1056155",
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            "pos": 1,
            "formatdesc": "IMPLEMENTASI HYBRID ASSISTED GENETIC ALGORITHM DAN HILL CLIMBING UNTUK PENJADWALAN MATA PELAJARAN SEKOLAH DASAR"
          },
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                  "filename": "22106050079_BAB-II_sampai_SEBELUM-BAB-TERAKHIR.pdf"
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            "rev_number": 3,
            "uri": "http:\/\/digilib.uin-suka.ac.id\/id\/document\/1056156",
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            "formatdesc": "IMPLEMENTASI HYBRID ASSISTED GENETIC ALGORITHM DAN HILL CLIMBING UNTUK PENJADWALAN MATA PELAJARAN SEKOLAH DASAR"
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      ],
      "rev_number": 10,
      "creators": [
        {
          "name": {
            "lineage": null,
            "given": "NIM.: 22106050079",
            "honourific": null,
            "family": "Aulia Miftah Razak"
          }
        }
      ],
      "dir": "disk0\/00\/07\/64\/66",
      "keywords": "Penjadwalan Otomatis, Genetic Algorithm, Hill Climbing, Hybrid Metaheuristics, Timetabling",
      "lastmod": "2026-05-19 03:59:18",
      "ispublished": "pub",
      "metadata_visibility": "show",
      "date_type": "published",
      "eprint_status": "archive",
      "status_changed": "2026-05-19 03:59:18",
      "datestamp": "2026-05-19 03:59:18",
      "uri": "http:\/\/digilib.uin-suka.ac.id\/id\/eprint\/76466",
      "thesis_name": "other",
      "note": "Ir. Maria Ulfah Siregar, S.Kom., MIT., Ph.D.",
      "full_text_status": "restricted",
      "contact_email": "muh.khabib@uin-suka.ac.id",
      "divisions": [
        "Informatika(S1)"
      ],
      "abstract": "Timetable scheduling is a complex combinatorial optimization problem because it involves various resource constraints—such as teachers, classrooms, and time slots—that must be allocated simultaneously while satisfying a number of operational constraints. This complexity increases at the elementary school level due to the implementation of the homeroom teacher model, which creates dependencies between subjects within a single class. Manual scheduling approaches often result in schedule conflicts and difficulties in verifying multiple constraints simultaneously. This study aims to develop a web-based automatic scheduling system using a Hybrid Metaheuristics approach. The method integrates the Evolutionary Assisted Genetic Algorithm (EAGA) as a global search mechanism with the Matrix Locking technique to form an initial population closer to a feasible solution, as well as the Hill Climbing algorithm as a local optimization to improve the quality of the schedule structure. The system was developed using the Python programming language with the Extreme Programming methodology. Test results show that the system is capable of generating feasible schedules with a 100% success rate without violating hard constraints. The average computation time required is 10.97 seconds for a population size of 40 individuals. The integration of the Hill Climbing algorithm resulted in an average improvement in solution quality of 440 fitness points compared to the results of the pure Genetic Algorithm, achieved through the reduction of schedule fragmentation and the formation of more structured subject blocks. An evaluation by the school’s curriculum team indicated that the generated schedules are not only computationally valid but also suitable for use in school operations.",
      "type": "thesis",
      "title": "IMPLEMENTASI HYBRID ASSISTED GENETIC ALGORITHM DAN HILL CLIMBING UNTUK PENJADWALAN MATA PELAJARAN SEKOLAH DASAR",
      "institution": "UIN SUNAN KALIJAGA YOGYAKARTA",
      "pages": 131
    }