/home/webperpus/repositori.untidar.ac.id/htdocs/repositori_neo/lib/SearchEngine/DefaultEngine.php:610 "Search Engine Debug 🔎 🪲"
Engine Type ⚙️: "SLiMS\SearchEngine\DefaultEngine"
SQL ⚙️: array:2 [ "count" => "select count(distinct b.biblio_id) from biblio as b left join mst_publisher as mp on b.publisher_id=mp.publisher_id left join mst_place as mpl on b.publish_place_id=mpl.place_id where b.opac_hide=0 and (b.biblio_id in(select ba.biblio_id from biblio_author as ba left join mst_author as ma on ba.author_id=ma.author_id where ma.author_name like ?))" "query" => "select b.biblio_id, b.title, b.image, b.isbn_issn, b.publish_year, mp.publisher_name as `publisher`, mpl.place_name as `publish_place`, b.labels, b.input_date, b.edition, b.collation, b.series_title, b.call_number from biblio as b left join mst_publisher as mp on b.publisher_id=mp.publisher_id left join mst_place as mpl on b.publish_place_id=mpl.place_id where b.opac_hide=0 and (b.biblio_id in(select ba.biblio_id from biblio_author as ba left join mst_author as ma on ba.author_id=ma.author_id where ma.author_name like ?)) order by b.last_update desc limit 10 offset 0" ]
Bind Value ⚒️: array:1 [ 0 => "%SELLY MUSTIKA NING TYAS%" ]
Penyusunan Master Production Schedule (MPS) secara konvensional masih rentan terhadap kesalahan dan keterlambatan keputusan sehingga berpotensi mengganggu jadwal produksi dan efisiensi operasional sehingga diperlukan sistem prediksi berbasis machine learning. XGBoost dipilih karena kemampuannya menangani data besar, hubungan non-linear, missing values, serta mengurangi overfitting mel…