Hasil Pencarian  ::  Simpan CSV :: Kembali

"Penelitian ini bertujuan untuk memahami proses preservasi pengetahuan mengenai sistem pengelolaan koleksi dan layanan pada Perpustakaan Gedong Kirtya, usaha-usaha preservasi yang dilakukan oleh Perpustakaan Gedong Kirtya baik yang menyangkut preservasi fisik maupun preservasi pengetahuan lontar sebagai bagian dari kebudayaan Bali, dan kendala-kendala yang dihadapi oleh Perpustakaan Gedong Kirtya dalam rangka melakukan presevasi terhadap berbagai koleksi yang dimilikinya. Penelitian ini dilakukan dengan metode kualitatif yang dititikberatkan pada deskripsi serta interpretasi perilaku manusia dalam melakukan preservasi pengetahuan mengenai pengelolaan perpustakaan Gedong Kirtya. Hasil penelitian menunjukkan bahwa Perpustakaan Gedong Kirtya memiliki sistem preservasi pengetahuan secara internal yaitu transfer pengetahuan yang dilakukan antar pegawai, serta preservasi pengetahuan secara eksternal yang dilakukan dengan pihak luar Gedong Kirtya.

---

This study aims to understand the process of knowledge preservation on collection management systems and library services in Gedong Kirtya, preservation efforts undertaken by the Gedong Kirtya Library both concerning on physical and knowledge of lontar as part of Balinese culture, and the constraints faced by this library in order to perform preservation to its various collections.

This research was conducted by using qualitative methods that focused on the description and interpretation of human behavior in conducting knowledge preservation concerning to Gedong Kirtya libarary management. The results show that Gedong Kirtya Library has knowledge preservation system that is internally performed by knowledge transfer among employees, as well as the preservation that is done externally with outside parties of Gedong Kirtya."

"Penelitian ini bertujuan untuk (1) memetakan ilmu pengetahuan bidang ekonomi berdasarkan laporan penelitian dosen Universitas Jambi, dengan co-words dan co-classification, (2) mengetahui dan menjelaskan peta ilmu pengetahuan dari laporan penelitian dosen Fakultas Ekonomi Universitas Jambi berdasarkan co-classification dan co-words, dan (3) mengelompokan dokumen berdasarkan descriptor/kata kunci. Dalam penelitian ini Simple matching digunakan untuk mengukur similarity antar dokumen dan koefisien Jaccad digunakan untuk pemetaan dan pengelompokan dengan menggunakan metode complete linkage (furthes neighbor). Pemetaan dilakukan berdasarkan co-word dan co-classification.Dari 406 judul laporan penelitian dosen Fakultas Ekonomi Universitas Jambi yang diterbitkan tahun 1991 - 2000, ditarik sampel sebanyak 197 dokumen. Berdasarkan analisis co-words diperoleh 671 kata kunci atau dengan rata-rates. 3,39 kata kunci perlaporan penelitian. Kemudian dilakukan pengelompokan pada tahun 1991-1995, 1996-1998 dan 1999-2000 masing-masing 6 (enam) kelompok. Sedangkan berdasarkan co-classification dengan kriteria yang sama, dilakukan pengelompokan terhadap laporan penelitian dosen Fakultas Ekonomi Universitas Jambi tahun 1991-1995, 1996-1998 dan 1999-2000 masing-masing terbagi 5 (lima) kelompok.Berdasarkan analisis co-words, hasil pengelompokan laporan penelitian dosen Fakultas Ekonomi Universitas Jambi tahun 1991-1995 terdiri dari: Koperasi, Demografi, Tenaga Kerja, Keuangan, Ekonomi-Keadaan, dan Perdagangan. Pada tahun 1996-1998 terdiri dari: Koperasi, Tenaga Kerja, Industri, Ekonomi-Keadaan, Keuangan, dan Pendapatan. Kemudian tahun 1999-2000 terdiri dari: Ekonomi-Keadaan, Wanita Pekerja, Perdagangan, Tenaga Kerja, Pendapatan, dan Investasi.Berdasarkan analisis co-classification, hasil pengelompokan laporan penelitian dosen Fakultas Ekonomi Universitas Jambi tahun 1991-1995 terdiri dari: Keuangan, industri, Tenaga Kerja, Koperasi, Ekonomi-Keadaan. Pada tahun 1996-1998 terdiri dari: Industri, Tenaga Kerja (Pekerja Wanita), Koperasi, Investasi dan Ekonomi-Keadaan. Kemudian tahun 1999-2000 terdiri dari: Investasi, Produksi, keuangan dan perkembangan ekonomi.Visualization of Knowledge for Report of the Research Lecture of Economic Faculty of the Jambi University, 1991-2000Goal of this research is (1) To visualization of knowledge of economics be bases on report of research lecture of the Jambi University, with co-words and co-classification, (2) To know and explained map of knowledge for report research lecture of Economic Faculty of the Jambi University be based on co-classification and co-words, and (3) to cluster document be based on descriptor/co-words. For this research simple matching is measuring to similarity for documents and Jaccad coefficients is measuring to mapping and to clustering by method complete linkage (furthers neighbor). To mapping this document by co-words analysis and co-classification analysis.

For the 406 report of the lecture of the Jambi University for 1991-2000 have 197 documents for sample. Be based co-words analysis has 671 co-words or average 3,39 words for report. And than divisible 6 clusters all of periods: 1991-1995, 1996-1998 and 1999-2000 and for co-classification analysis and the same criteria, at 1991-1996, 1996-1998, and 1999-2000 has all 5 clusters.

Be based on co-words analysis, result of clustering reports of research lecture of Economic Faculty of the Jambi University at 1991-1999 consists of: corporation, demography, labor's, financial, economic, and trade. At the 1996-1998 consists: corporation, labors, industry, economics, financial, and income. And at the 1999-2000'' consists: economics, laborer of women, trade, and labor?s, income, and invests.

Be based on co-classification analysis, clustering of the report of research of lecture economy faculty of the Jambi University at 1991-1995, consists of: corporation, labor's, economy, industry and financial. At the 1996-1998 consists of: corporation, labors, small industry, economy, and income. And so on at 1999-2000t consists of: economy, labor's, invests, industry and taxation.

By co-words analysis, reports of research of Lecture of Economy Faculty of the Jambi University have 6 clusters, and co-classification analysis only 5 clusters. So, co-classification analysis more simple than co-words analysis."

"In this book, the capability map, a novel general representation of the kinematic capabilities of a robot arm, is introduced. The capability map allows to determine how well regions of the workspace are reachable for the end effector in different orientations. It is a representation that can be machine processed as well as intuitively visualized for the human. The capability map and the derived algorithms are a valuable source of information for high- and low-level planning processes. The versatile applicability of the capability map is shown by examples from several distinct application domains. In human-robot interaction, a bi-manual interface for tele-operation is objectively evaluated. In low-level geometric planning, more human-like motion is planned for a humanoid robot while also reducing the computation time. And in high-level task reasoning, the suitability of a robot for a task is evaluated. "

"This book constitutes the thoroughly refereed post-conference proceedings of the Second International Workshop on Graph Structures for Knowledge Representation and Reasoning, GKR 2011, held in Barcelona, Spain, in July 2011 as satellite event of IJCAI 2011, the 22nd International Joint Conference on Artificial Intelligence. The 7 revised full papers presented together with 1 invited paper were carefully reviewed and selected from 12 submissions. The papers feature current research involved in the development and application of graph-based knowledge representation formalisms and reasoning techniques and investigate further developments of knowledge representation and reasoning graph based techniques. Topics addressed are such as: bayesian networks, semantic networks, conceptual graphs, formal concept analysis, cp-nets, gai-nets, euler diagrams, existential graphs all of which have been successfully used in a number of applications (semantic Web, recommender systems, bioinformatics etc.)."

"Pendidikan vokasi memiliki beberapa karakteristik utama, yaitu (1) berfokus pada perolehan kompetensi dan keterampilan tertentu, dan (2) mengutamakan pengajaran praktis. Dengan karakteristik tersebut, mahasiswa dituntut untuk memenuhi target kompetensi dan keterampilan yang sama yang telah ditetapkan. Disisi lain, adanya keragaman karakteristik mahasiswa dapat menyebabkan perbedaan dalam hal proses belajar. Untuk mencapai target kompetensi yang diharapkan dan mengakomodir keragaman mahasiswa, penggunaan konsep personalized e-learning dapat menjadi pilihan. Sementara itu, dengan karakteristik kurikulum vokasi yang mengutamakan pengajaran praktikum, penggunaan model pembelajaran bauran dapat menjawab tantangan ketika pembelajaran daring tidak dapat sepenuhnya diterapkan pada pendidikan vokasi. Oleh karena itu, penggunaan konsep personalized learning pada pembelajaran bauran dapat menjadi solusi. Dengan demikian penelitian ini bertujuan untuk (1) membangun model personalisasi pembelajaran bauran (p-PB) yakni model yang menggunakan konsep personalized learning dalam konteks kurikulum vokasi yang bersifat serial dan diintegrasikan dengan model pembelajaran bauran; (2) membangun purwarupa sistem berdasarkan model; dan (3) mengukur dampak implementasi sistem terhadap pembelajaran pada pendidikan tinggi vokasi.Metodologi yang digunakan dalam penelitian ini adalah exploratory sequential mixed method. Metode kualitatif digunakan dalam studi literatur dan evaluasi model, sementara metode kuantitatif digunakan dalam survei mengenai pembelajaran praktikum pada pendidikan tinggi vokasi dan eksperimen dalam melakukan evaluasi pada implementasi sistem p-PB.Model p-PB yang dikembangkan dalam penelitian ini terdiri dari tiga komponen yakni model mahasiswa, model knowledge, dan model personalisasi. Model mahasiswa mengklasifikasikan mahasiswa berdasarkan tingkat pengetahuan (dasar, menengah, lanjut) dan gaya belajar sesuai teori Felder Silverman Learning Style Model (FSLSM) dengan fokus pada dua gaya dominan. Model knowledge memberikan anotasi pada learning object dengan tingkat kesulitan (mudah, sedang, sulit) dan disesuaikan dengan dimensi dalam teori FSLSM. Pada model personalisasi, strategi personalisasi yang diusulkan mencakup rekomendasi learning object dan sistem umpan balik yang sesuai dengan model mahasiswa. Sistem umpan balik memberikan rekomendasi berdasarkan hasil asesmen dan jika dibutuhkan akan berulang untuk memastikan mahasiswa menguasai kompetensi sebelum melanjutkan modul. Hal ini untuk mengakomodir kurikulum pendidikan tinggi vokasi yang berfokus pada penguasaan kompetensi secara berurutan. Model p-PB diintegrasikan dengan pembelajaran bauran yang mengkombinasikan model station rotation dan flipped classroom, di mana tingkat pengetahuan dijadikan station dalam pengajaran sinkronus dan asinkronus.Purwarupa sistem p-PB dikembangkan dengan metodologi SDLC. Rekomendasi dan umpan balik yang diberikan menggunakan pendekatan knowledge-based. Knowledge direpresentasikan dengan menggunakan ontologi dan diimplementasikan dengan knowledge graph. Knowledge graph tidak hanya menghubungkan learning object, tingkat kesulitan, gaya belajar, dan hasil asesmen mahasiswa dalam jaringan yang terstruktur, tetapi juga berfungsi sebagai sistem penyimpanan dan pengelolaan data knowledge. Dengan menggunakan knowledge graph, sistem dapat menelusuri jalur yang paling relevan dan efisien untuk memberikan rekomendasi learning object dan umpan balik yang dipersonalisasi.Evaluasi terhadap purwarupa sistem p-PB dilakukan dengan metode eksperimen berupa implementasi sistem dengan menggunakan kelas eksperimen dan kelas kontrol. Eksperimen dilakukan pada dua mata kuliah di salah satu perguruan tinggi vokasi di Jakarta yakni mata kuliah Pemrograman 1 dan Perancangan Proses Manufaktur. Kelas eksperimen menggunakan sistem p-PB dalam pembelajaran, sementara kelas kontrol menggunakan LMS institusi dan tidak menggunakan sistem p-PB. Hasil implementasi menunjukkan kelas eksperimen mencapai tingkat pencapaian hasil belajar yang lebih tinggi secara signifikan dibandingkan dengan kelas kontrol pada kedua mata kuliah yang diuji. Persepsi dan kepuasan mahasiwa mengenai tingkat kegunaan sistem p-PB cukup baik dengan skor SUS 74,36. Dari wawancara mahasiswa didapat sistem dapat meningkatkan pemahaman, kepercayaan diri, dan antusiasme mahasiswa. Dapat dikatakan terdapat pengaruh positif sistem p-PB terhadap hasil belajar dan pengalaman belajar mahasiswa. Hasil penelitian ini dapat dijadikan dasar bagi implementasi pada perkuliahan dan institusi sejenis lainnya.

---

Vocational education has several main characteristics, namely (1) focusing on the acquisition of specific competencies and skills, and (2) prioritizing practical teaching. With these characteristics, students are required to meet the same competency and skill targets that have been set. On the other hand, the diversity of students’ characterisitcs can lead to differences in the learning process. To achieve the expected competency targets and accommodate student diversity, the use of personalized e-learning concepts can be an option. Meanwhile, given the vocational curriculum's emphasis on practical teaching, the use of blended learning models can address the challenges when online learning cannot be fully applied to vocational education. Therefore, the use of personalized learning concepts in blended learning can be a solution. Thus, this research aims to (1) develop a personalized blended learning (p-BL) model, which uses the personalized learning concept in the context of a vocational curriculum that is sequential and integrated with the blended learning model; (2) develop a system prototype based on the model; and (3) measure the impact of system implementation on learning in vocational higher education.

The methodology used in this research is exploratory sequential mixed method. Qualitative methods are used in literature studies and model evaluation, while quantitative methods are used in surveys on practical learning in vocational higher education and experiments to evaluate the implementation of the p-BL system.

The p-BL model developed in this research consists of three components: the student model, the knowledge model, and the personalization model. The student model classifies students based on knowledge level (basic, intermediate, advanced) and learning style according to the Felder Silverman Learning Style Model (FSLSM) theory with a focus on two dominant styles. The knowledge model annotates learning objects with difficulty levels (easy, medium, hard) and aligns them with dimensions in the FSLSM theory. In the personalization model, the proposed personalization strategies include recommending learning objects and a feedback system tailored to the student model. The feedback system provides recommendations based on assessment results and, if necessary, repeats to ensure students master the competencies before proceeding to the next module. This accommodates the sequential competency mastery focus of vocational higher education curricula. The p-BL model is integrated with blended learning that combines the station rotation model and flipped classroom, where knowledge levels are used as stations in synchronous and asynchronous teaching.

The p-BL system prototype is developed using the SDLC methodology. Recommendations and feedback are provided using a knowledge-based approach. Knowledge is represented using ontology and implemented with a knowledge graph. The knowledge graph connects learning objects, difficulty levels, learning styles, and student assessment results in a structured network and serves as a data storage and management system. Using the knowledge graph, the system can trace the most relevant and efficient paths to provide personalized learning object recommendations and feedback.

The p-BL system prototype evaluation was conducted using experimental methods involving system implementation with an experimental class and a control class. The experiment was carried out in two courses at a vocational higher education institution in Jakarta, namely Programming 1 and Manufacturing & Process Design. The experimental class used the p-BL system in learning, while the control class used the institution's LMS and did not use the p-BL system. The implementation results showed that the experimental class achieved significantly higher learning outcome levels compared to the control class in both tested courses. From 51 students in the experimental class, the student perceptions and satisfaction with the usability of the p-BL system were quite good with a SUS score of 74.36. Interviews with 12 students revealed that the system could enhance students' understanding, confidence, and enthusiasm. It can be said that there is a positive impact of the p-BL system on student learning outcomes and learning experiences. The results of this study can serve as a basis for implementation in similar courses and institutions."

"This book discusses knowledge representation in semantic web. It introduces the relevant background knowledge, models of fuzzy ontologies, importance and priority of properties in concepts, and object typicality in fuzzy ontologies and context-aware ontologies."

"This book constitutes the proceedings of the 8th International Conference on Spatial Cognition, SC 2012, held in Kloster Seeon, Germany, in August/September 2012. The 31 papers presented in this volume were carefully reviewed and selected from 59 submissions. The conference deals with spatial cognition, biological inspired systems, spatial learning, communication, robotics, and perception."

"Description logics are knowledge representation formalisms that are highly relevant in computer science, knowledge representation and the semantic web. This is the first introductory textbook published on the subject, suitable for self-study by graduate students and as teaching material for university courses"

"Seringkali kita mengelompokkan dokumen berdasarkan hasil identifikasi topik. Identifikasi topik terhadap sejumlah dokumen tidak terstruktur, contohnya abstrak, dapat dibantu dengan algoritma pemodelan topik. Namun, pelatihan model topik membutuhkan dokumen dengan jumlah yang memadai. Dengan pembelajaran zero shot, kita dapat melakukan prediksi topik terhadap dokumen dengan jumlah yang kurang memadai dengan mentransfer hasil pembelajaran dari dokumen dalam bahasa lain, contohnya Bahasa Inggris, walaupun tidak ada contoh dari bahasa yang diuji (Bahasa Indonesia). Pemanfaatan zero-shot learning sudah dilakukan oleh Bianchi et al. (2021) dengan Contextual Topic Model (CTM). Koherensi topik yang diprediksi CTM dapat ditingkatkan contohnya jika dokumen terkait dengan knowledge graph (KG). Dengan penambahan informasi dari KG, frekuensi kemunculan kata penting menjadi lebih tinggi. Adapun kualitas topik juga dapat ditingkatkan dengan memodifikasi bag-of-word (BoW) kata tunggal menjadi n-gram. Namun, CTM terbatas pada 1-gram. Penelitian ini bertujuan untuk memperkaya topik serta meningkatkan koherensi prediksi topik untuk dokumen unseen dengan memanfaatkan KG dan kualitas topik dengan memodifikasi BoW pada CTM menjadi n-gram. Hasil eksperimen menunjukkan koherensi topik (dalam ukuran NPMI) tertinggi terhadap dokumen Bahasa Inggris yaitu dengan abstrak singkat dan BoW n-gram sebesar 0,24 dengan margin 0.1019 terhadap Bianchi et al.. Namun, prediksi topik terhadap dokumen Bahasa Indonesia memiliki tingkat similaritas yang lebih baik dengan penambahan KG dilihat dari peningkatan nilai Match sebesar 6% untuk 1-gram dan 4.34% untuk n-gram, centroid similarity sebesar 0.02 untuk 1-gram, dan Kullback-Leibler Divergence 0.1 untuk 1-gram dan 0.04 untuk n-gram. Peningkatan kualitas topik juga terjadi dengan modifikasi BoW menjadi n-gram yang ditunjukkan oleh kemunculan topik yang tidak didapatkan sebelum modifikasi BoW. Adapun, model juga dapat memprediksi dokumen dari sumber lain, contohnya berita. Namun, jika topik dokumen tidak tampak pada pelatihan, topik yang diprediksi kurang koheren terhadap dokumen.

---

Often we group documents based on the results of topic identification. Topic identification against a number of unstructured documents, for example abstracts, can be assisted by topic modeling algorithms. However, topic model training requires a sufficient number of documents. With zero shot learning, we can predict the topic of an inadequate number of documents by transferring learning outcomes from documents in other languages, for example English, even though there are no examples from the tested language (Indonesian). The use of zero-shot learning has been carried out by Bianchi et al. (2021) with the Contextual Topic Model (CTM). The coherence of topics predicted by CTM can be improved, for example if the document is related to a knowledge graph (KG). With the addition of information from KG, the frequency of occurrence of important words becomes higher. The topic quality can also be improved by modifying the single word bag-of-word (BoW) into n-grams. However, CTM is limited to 1-gram. This study aims to enrich the topic and improve the coherence of topic prediction for unseen documents by utilizing KG and topic quality by modifying BoW on CTM to n-grams. The experimental results show the highest topic coherence (in terms of NPMI) to English documents with a short abstract and a BoW n-gram of 0.24 with a margin of 0.1019 to Bianchi et al.. However, topic predictions for Indonesian documents have a better level of similarity with the addition of KG seen from the increase in the Match value by 6% for 1-gram and 4.34% for n-gram, centroid similarity of 0.02 for 1-gram, and Kullback-Leibler Divergence 0.1 for 1-gram and 0.04 for n-gram. An increase in the quality of the topic also occurs with the modification of BoW to n-grams which is indicated by the appearance of topics that are not obtained before the BoW modification. Meanwhile, the model can also predict documents from other sources, for example news. However, if the topic of the document does not appear in the training, the predicted topic is less coherent with the document."