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"Ekstraksi informasi merupakan sebuah tahap awal dari proses analisis data tekstual. Ekstraksi informasi diperlukan untuk mendapatkan informasi dari data tekstual sehingga dapat digunakan untuk proses analisis seperti misalnya klasifikasi dan kategorisasi. Data tekstualsangat dipengaruhi oleh bahasa, jika sebuah data tekstual berbahasa Arab maka karakter yang digunakan adalah karakter arab.Knowledge dictionary merupakan sebuah kamus yang dapat digunakan untuk mengekstraksi informasi dari data tekstual. Informasi yang diekstraksi menggunakan knowledge dictionary adalah konsep.Knowledge dictionary biasanya dibangun secara manual oleh seorang pakar yang tentunya membutuhkan waktu yang lama dan spesifik untuksetiap masalah. Pada penelitian ini diusulkan sebuah metode untuk membangun knowledge dictionary secara otomatis. Pembentukanknowledge dictionary dilakukan dengan cara mengelompokkan kalimat yang memiliki konsep yang sama, dengan asumsi kalimat yang memiliki konsep yang sama akan memiliki nilai simi laritas yang tinggi. Konsep yang telah diekstraksi dapat digunakan sebagai fitur untuk proses komputasi berikutnya misalnya klasifikasi ataupun kategorisasi.Dataset yang digunakan dalam penelitian ini adalah dataset teks Arab. Hasil ekstraksi diuji dengan menggunakan mesin klasifikasidecision tree dan didapatkan nilai presisi tertinggi 71,0% dan nilai recall tertinggi 75,0%.

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AbstractInformation extraction is an early stage of a process of textual data analysis. Information extraction is required to get information from textual data that can be used for process analysis, such as classification and categorization. A textual data is strongly influenced by the language. Arabic is gaining a significant attention inmany studies because Arabic language is very different from others, and in contrast to other languages, tools and research on the Arabic language is still lacking. The information extracted using the knowledgedictionary is a concept of expression. A knowledge dictionary is usually constructed manually by an expert and this would take a long time and is specific to a problem only. This paper proposed a method for automatically building a knowledge dictionary. Dictionary knowledge is formed by classifying sentences having the same concept, assuming that they will have a high similarity value. The concept that has been extracted can be used as features for subsequent computational process such as classification or categorization. Dataset used in this paper was the Arabic text dataset. Extraction result was tested by using a decision tree classification engine and the highest precision value obtained was 71.0% while the highest recall value was 75.0%. "

"ABSTRAKThe paper investigates both the causes and effects of the rapid increase in the data volume Big Data and their impact on human cognition. The role of the Internet in distributing and exchanging of such data, and their impact on the growth of the Information Society are emphasized. As a result, Wisdom Science a new kind of research emerges which has the potential to facilitate more advanced solutions in the digital world. In consequence, new kinds of info driven devices, services and systems called smart are developed and applied in almost every aspect of human activities around the world. However, this is not enough for humans to use all those well informed smart devices and systems because, first of all, their decisions should be wise. Therefore, the paper, coming from a cognitive informatics approach defines wisdom and its applications, illustrated by some practical cases. Based on this, relations between knowledgeand wisdom are shown, and human abilities corresponding to them are defined. They can decide about a transformation of a knowledge society to a wisdom society."

"Penyediaan layanan publik digital sangat penting. Standar pengalaman pelanggan telah meningkat di sektor swasta, dan masyarakat mengharapkan pemerintah untuk mengikutinya. Pemerintah menghadapi berbagai tantangan ketika mencoba menumbuhkan solusi digital, banyak di antaranya yang terbesar bukan teknologi. Keberhasilan implementasi transformasi digital di pemerintahan bergantung pada pengambilan tindakan tegas atas masalah ini, yang dapat mencakup segala hal mulai dari menghilangkan silo organisasi hingga mengatasi kesenjangan keterampilan digital dan kurangnya pendanaan. Jika tantangan ini dibiarkan tidak teratasi, program pemerintah digital berisiko kehilangan pendanaan berkelanjutan dan, tentu saja, kemampuan organisasi untuk memanfaatkan manfaat yang dijanjikan dari solusi digital. Penelitian ini mengambil studi kasus implementasi transformasi digital di Kementerian Pekerjaan Umum dan Perumahan Rakyat khususnya pada Pusat Data dan Teknologi Informasi. Permasalahan yang menjadi fokus utama penelitian yaitu belum dilakukannya monitoring evaluasi transformasi digital di Kementerian Pekerjaan Umum dan Perumahan Rakyat. Urgensi melakukan evaluasi transformasi digital adalah dari hasil evaluasi yang dihasilkan dapat digali rekomendasi dan dilakukan perbaikan agar pelaksanaan transformasi digital Kementerian PUPR menjadi lebih baik dan meningkat. Penelitian ini menggunakan GovTech Maturity Index sebagai kerangka kerja evaluasi dan metode campuran yaitu pendekatan kualitatif dengan wawancara, observasi, dan studi dokumen dan pendekatan kuantitatif dengan survei menggunakan kuesioner. Berdasarkan hasil evaluasi, tingkat kematangan transformasi digital Pusdatin Kementerian PUPR berdasarkan kerangka kerja GTMI memperoleh nilai 0,87 (nol koma delapan tujuh) berarti sangat tinggi yang dikategorikan masuk ke dalam grup A. Kementerian PUPR telah mendemonstrasikan solusi canggih atau inovatif dan praktik yang baik di area fokus GovTech.

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The provision of digital public services is very important. Customer experience standards have risen in the private sector, and society expects governments to follow it. Governments face a variety of challenges when trying to grow digital solutions, many of the biggest of which are non-technological. The successful implementation of digital transformation in government depends on taking decisive action on this issue, which can include everything from eliminating organizational silos to addressing digital skills weaknesses and capital shortages. If these challenges are left unaddressed, digital government programs risk losing ongoing funding and, of course, the ability of organizations to take advantage of the benefits that digital solutions offer. This research takes a case study of the implementation of digital transformation in the Ministry of Public Works and Public Housing especially in Data and Information Technology Center. The main problem of this research is that an evaluation of digital transformation has not been carried out at the Ministry of Public Works and Public Housing. The urgency of evaluating digital transformation is based on evaluation result, recommendations can be explored and made improvements so that the implementation of the Ministry of Public Works and Public Housing's digital transformation is better and improved. This study uses the GovTech Maturity Index as an evaluation framework and mixed methods, qualitative approach with interviews, observations, and document studies and quantitative approach with survey using questionnaire. Based on the evaluation result, the maturity level of the digital transformation of the Data and Information Technology Center in Ministry of Public Works and Public Housing based on the GTMI framework is 0.87 (zero point eight seven) which means it is very high which is included in group A. The Ministry of of Public Works and Public Housing has demonstrated advanced or innovative solutions and good practices in focus areas GovTech."

"Data fusion in information retrieval This book offers a theoretical and empirical approach to data fusion, used in information retrieval in complex, diverse settings such as web and social networks, legal, enterprise and others. Discusses, analyzes and ealuates typical data fusion algorithms."