TEKNIK IMPUTASI DATA: Teori dan Penerapan pada Dataset Smartphone
Keywords:
imputasi, smartphone, datasetSynopsis
Dalam analisis data modern, kualitas dataset menjadi faktor penting yang menentukan akurasi hasil analisis dan model yang dibangun. Salah satu permasalahan yang sering muncul dalam dataset adalah keberadaan missing value atau data yang hilang. Jika tidak ditangani dengan tepat, missing value dapat menyebabkan bias dalam analisis serta menurunkan kualitas pengambilan keputusan berbasis data.
Buku ini membahas secara sistematis konsep missing value serta berbagai teknik imputasi data yang digunakan untuk mengatasi permasalahan data yang tidak lengkap. Melalui studi kasus pada dataset spesifikasi smartphone, buku ini menyajikan analisis komparatif beberapa metode imputasi seperti mean, median, modus, KNN, regression, dan MICE untuk melihat pengaruhnya terhadap kualitas dataset.
Ditulis dengan pendekatan teoritis sekaligus praktis, buku ini dapat menjadi referensi bagi mahasiswa, peneliti, dan praktisi di bidang ilmu komputer, data science, serta sistem pendukung keputusan yang ingin memahami teknik pengolahan missing value secara lebih mendalam.
Chapters
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KATA PENGANTAR
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DAFTAR ISI
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BAB 1 PENDAHULUAN
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BAB 2 KONSEP DASAR DATA DAN MISSING VALUE
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BAB 3 TEKNIK IDENTIFIKASI DAN ANALISIS MISSING VALUE
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BAB 4 METODE IMPUTASI DATA / TEKNIK PENANGANAN MISSING VALUE
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BAB 5 IMPLEMENTASI IMPUTASI MENGGUNAKAN PYTHON
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BAB 6 EVALUASI KUALITAS DATA SETELAH IMPUTASI
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DAFTAR PUSTAKA
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GLOSARIUM
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LAMPIRAN
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PROFIL PENULIS
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References
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