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ICES 2021
  • Language: en
  • Pages: 399

ICES 2021

We are delighted to introduce the proceedings of the third edition of the International Conference on of Education and Science. The 3rd International Conference of Education and Science (ICES) Universitas Kristen Indonesia will be an annual event hosted by Education and Teacher Training Faculty, Universitas Kristen Indonesia. This year (2021), will be the third ICES UKI will be held on 17-18 November 2021 at Education and Teacher Training Faculty, Universitas Kristen Indonesia, Indonesia. This conference has brought researchers, developers and practitioners around the world. The theme of ICES 2021 was “Research and Education Sustainability Post COVID-19 in Asian Context” . The 3rd Intern...

Konsep Sistem Basis Data
  • Language: id
  • Pages: 247

Konsep Sistem Basis Data

Bukunya memperkenalkan konsep dasar yang diperlukan untuk merancang, menggunakan, dan mengimplementasikan sistem basis data dan aplikasi basis data. Presentasi kami menekankan dasar-dasar pemodelan dan desain basis data, bahasa dan model yang disediakan oleh sistem manajemen basis data, dan teknik implementasi sistem basis data. Buku ini dimaksudkan untuk digunakan sebagai buku teks pada matakuliah sistem basis data sebagai buku referensi. Tujuan buku ini memberikan presentasi yang mendalam dan terkini tentang aspek terpenting dari sistem basis data, serta teknologi terkait. Ada dua bab baru mengenai kemajuan terkini dalam sistem basis data dan pemrosesan data besar; satu bab baru (Bab 13) mencakup pengenalan kelas sistem basis data baru yang dikenal sebagai basis data NOSQL, dan bab baru lainnya (Bab 14) mencakup teknologi untuk memproses data besar, termasuk MapReduce dan Hadoop. Bab mengenai pemrosesan dan optimalisasi kueri telah diperluas dan disusun ulang pada bab 11 Bab 11 berfokus pada strategi dan algoritma untuk pemrosesan kueri sedangkan Bab 12 berfokus pada teknik pengoptimalan kueri.

IMPLEMENTASI DATA MINING (Clastering, Association, Prediction, Estimation, Classification)
  • Language: id
  • Pages: 124

IMPLEMENTASI DATA MINING (Clastering, Association, Prediction, Estimation, Classification)

Judul : IMPLEMENTASI DATA MINING (Clastering, Association, Prediction, Estimation, Classification) Penulis : 1. Rulin Swastika 2. Siti Mukodimah 3. Ferry Susanto 4. Muhamad Muslihudin 5. Sri Ipnuwati Editor : Didi Susianto, M.Kom Suyono, M.T.I Ukuran : 15,5 x 23 cm Tebal : 124 Halaman No ISBN : 978-623-497-285-6 Sinopsis Pada dasarnya keberadaan data mining dibutuhkan mengingat semakin banyaknya informasi di era teknologi seperti data transaksi bisnis, data ilmiah, gambar, video dan data-data lainnya. Dengan banyaknya data tersebut dibutuhkan sistem yang mampu mengekstraksi esensi dari semua informasi yang tersedia dan membuat ringkasan untuk membantu pengambilan keputusan yang lebih baik. A...

MODEL REKOMENDASI KARIR MAHASISWA SISTEM INFORMASI MENGGUNAKAN SISTEM PAKAR
  • Language: id
  • Pages: 258

MODEL REKOMENDASI KARIR MAHASISWA SISTEM INFORMASI MENGGUNAKAN SISTEM PAKAR

  • Type: Book
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  • Published: 2022-05-03
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  • Publisher: Samudra Biru

Tersusunnya buku ini merupakan hasil dari penelitian yang telah diuji dan telah dilakukan kevalidannya oleh para ahli di bidangnya. Buku ini berisikan bagaimana model karier mahasiswa menggunakan sistem pakar yang telah diterapkan pada mahasiswa Sistem Informasi. Buku ini merekomendasikan bagaimana mahasiswa setelah menjadi sarjana dapat berkarier sesuai dengan profil lulusan Sistem Informasi dengan melakukan percobaan menggunakan konsep sistem pakar sebagai rekomendasinya.

Proceedings of the 9th International Conference on Technical and Vocational Education and Training (ICTVET 2022)
  • Language: en
  • Pages: 278

Proceedings of the 9th International Conference on Technical and Vocational Education and Training (ICTVET 2022)

This is an open access book. Indonesia, as a member of ASEAN, is now facing the ASEAN Economic Community (AEC) 2016. The AEC will support the ASEAN’s transformation into a region that guarantees free movement of goods, services, capital, and skilled labors. This will make ASEAN an even more dynamic and competitive region. In preparation for the AEC, the ASEAN member countries have ventured to improve the comparability and connectivity of their TVET systems. As an important component of human resources development, TVET is expected to play an active role in preparing the successful EAC. The implications of technological, economic and social trends are intervening factors that refine pedagogical strategies, leading to the molding of TVET as a more effective platform to catalyze pragmatic approaches to prepare the workforce for the new imperatives of the world of work. Regional integration and harmonization of TVET in the region have become key concerns and at the same time the strength of the ASEAN region. They are considered the overarching interventions needed in TVET to address major issues and challenges.

Proceedings of the Unima International Conference on Social Sciences and Humanities (UNICSSH 2022)
  • Language: en
  • Pages: 2046

Proceedings of the Unima International Conference on Social Sciences and Humanities (UNICSSH 2022)

This is an open access book. The Unima International Conference on Social Sciences and Humanity (UNICSSH) 2022 was conducted on October, 11th – 13th 2022, at The Grand Kawanua International City, Manado, North Sulawesi, Indonesia. In 2022, Universitas Negeri Manado will host the Indonesian National Education Convention (KONASPI) X. Konaspi is a routine activity of the PPTKN which is held once every four years. The fourth industrial revolution (4.0) is marked by technological advances and supported by artificial intelligence that creates opportunities and challenges for the education system. University and vocational school graduates are facing a world transformed by technology which in tur...

Intelligent Systems and Applications
  • Language: en
  • Pages: 727

Intelligent Systems and Applications

description not available right now.

Data Mining
  • Language: en
  • Pages: 364

Data Mining

The knowledge discovery process is as old as Homo sapiens. Until some time ago this process was solely based on the ‘natural personal' computer provided by Mother Nature. Fortunately, in recent decades the problem has begun to be solved based on the development of the Data mining technology, aided by the huge computational power of the 'artificial' computers. Digging intelligently in different large databases, data mining aims to extract implicit, previously unknown and potentially useful information from data, since “knowledge is power”. The goal of this book is to provide, in a friendly way, both theoretical concepts and, especially, practical techniques of this exciting field, ready to be applied in real-world situations. Accordingly, it is meant for all those who wish to learn how to explore and analysis of large quantities of data in order to discover the hidden nugget of information.

Buku Ajar Machine Learning
  • Language: id
  • Pages: 214

Buku Ajar Machine Learning

Buku Ajar Machine Learning ini disusun sebagai buku panduan komprehensif yang menjelajahi kompleksitas dan mendalamnya tentang ilmu teknologi sistem informasi. Buku ini dapat digunakan oleh pendidik dalam melaksanakan kegiatan pembelajaran di bidang ilmu machine learning dan diberbagai bidang Ilmu terkait lainnya. Buku ini dapat digunakan sebagai panduan dan referensi mengajar mata kuliah Medikal mechine learning dan menyesuaikan dengan Rencana Pembelajaran Semester tingkat Perguruan Tinggi masing-masing. Secara garis besar, buku ajar ini pembahasannya mulai dari pengenalan machine learning, data dalam machine learning, tipe-tipe machine learning, tahapan machine learning, supervised learning : linear regression, K-NN, naïve bayes dan decision tree (pyhton), unsupervised learning : k-means, association rule : apriori algorithm. Selain itu materi mengenai supervised learning: backpropagation neural network (python) juga di bahas secara mendalam. Buku ajar ini disusun secara sistematis, ditulis dengan bahasa yang jelas dan mudah dipahami, dan dapat digunakan dalam kegiatan pembelajaran.

Machine Learning
  • Language: id
  • Pages: 115

Machine Learning

Buku ini mengulas berbagai algoritma penting seperti K-NN, Naïve Bayes, Support Vector Machine (SVM), Logistic Regression, Linear Regression, K-Means Clustering, K-Medoid, Fuzzy C-Means, Apriori, FP-Growth, hingga konsep Feature Extraction dan Feature Selection. Kami menyajikan penjelasan yang ringkas namun komprehensif untuk memudahkan pembaca memahami setiap algoritma. Harapannya, buku ini akan menjadi panduan yang bermanfaat bagi mereka yang ingin mendalami Machine Learning