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"Aljabar Lie adalah ruang vektor kompleks yang dilengkapi dengan operasi siku yang memenuhi aksioma bilinieritas, aksioma skew-symmetry, dan identitas Jacobi. Aljabar Lie linier adalah aljabar matriks dilengkapi operasi siku komutator. Salah satunya adalah aljabar Lie sl2, sebuah aljabar matriks 2x2 dengan trace nol. Modul Lie adalah ruang vektor yang dilengkapi dengan perkalian kiri anggota sebuah aljabar Lie, serta mempertahankan operasi siku aljabar. Perkalian dengan suatu anggota aljabar disebut sebagai aksi. Aksi yang merupakan transformasi linier dapat dipandang sebagai representasi anggota aljabar tersebut pada modul. Modul Lie diklasifikasikan berdasarkan kelas isomorfisma. Modul Lie tereduksi lengkap dapat didekomposisi sebagai hasil jumlah langsung submodul sederhana. Penelitian ini berpusat pada klasifikasi modul atas aljabar Lie sl2 berdasarkan nilai eigen aksinya.

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Lie algebras are complex vector spaces equipped with a bracket operation that satisfies bilinearity axiom, skew-symmetry axiom, and Jacobi identity. Linear Lie algebras are matrix algebras equipped with a commutator bracket. One such example is sl2 Lie algebra, a 2x2 matrix algebra with zero trace. Lie modules are complex vector spaces equipped with a left multiplication with a Lie algebra element that preserves its bracket operation. Left multiplication by a particular algebra element is called an action. This action can be viewed as Lie algebra's representation on its module as a linear mapping. Lie modules can be classified based on isomorphism class. Completely reducible Lie modules can be decomposed into direct sum of irreducible submodules. This research revolves around the classification of sl2 Lie modules using the eigenvalues of its actions."

"This self-contained text is an excellent introduction to Lie groups and their actions on manifolds. The authors start with an elementary discussion of matrix groups, followed by chapters devoted to the basic structure and representation theory of finite dimensinal Lie algebras. They then turn to global issues, demonstrating the key issue of the interplay between differential geometry and Lie theory. Special emphasis is placed on homogeneous spaces and invariant geometric structures. The last section of the book is dedicated to the structure theory of Lie groups. Particularly, they focus on maximal compact subgroups, dense subgroups, complex structures, and linearity."

"Telur ayam kampung atau telur ayam buras adalah telur ayam umum dikonsumsi masyarakat Indonesia sebagai makanan biasa atau juga sebagai obat. Pengklasifikasian kualitas telur ayam kampung. Dilakukan untuk dapat membedakan telur yang layak konsumsi dan tidak layak konsumsi. Beberapa penelitian serupa menggunakan Arduino dan sensor photodioda untuk melakukan klasifikasi, selain itu juga ada beberapa penelitian yang menggunakan machine learning untuk membedakan jenis telur. Dari penelitian yang telah di lakukan dilihat bahwa akurasi masih kecil, dan dirasa masih bisa di ditingkatkan. Dalam penelitian ini dibuat sistem klasifikasi kualitas telur ayam kampung dengan menggunakan algoritma you only look once (YOLO) versi 4. Data set yang digunakan pada penelitian ini berupa data set dari 4 kategori kondisi telur atau 4 class antara lain telur baik, busuk, fertil, dan telur retak. Data set diakuisisi dengan disinari dengan lampu led yang diberikan tegangan 12V pada kotak akuisisi, dan citra ditangkap dengan webcam Logitech c270. Dari pelatihan data set citra telur ayam kampung dihasilkan akurasi sebesar 96.76% di pengujian pada validation set dan sebesar 95.26% pada test set. Dari kasus pendeteksian kualitas telur ayam kampung dengan deep learning berbasis algoritma YOLOv4 ini memungkinkan adanya pengembangan lebih lanjut.

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Local breed chicken eggs or local breed chicken eggs are chicken eggs that are commonly consumed by Indonesian people as ordinary food or also as medicine. Classification of local breed chicken egg quality. This is done to be able to distinguish eggs that are suitable for consumption and not suitable for consumption. Several similar studies used Arduino and photodiode sensors to carry out classification, besides that there were also several studies using machine learning to distinguish types of eggs. From the research that has been done, the accuracy is still small, and it is felt that it can still be improved. In this research, local breed chicken egg quality classification system was created using you only look once (YOLO) version 4 algorithm. The dataset used in this study was a data set of 4 categories of egg conditions or 4 classes including good eggs, rotten, fertile, and cracked eggs. The dataset was acquired by irradiating it with a led lamp supplied with a 12V voltage on the acquisition box, and the image was captured with a Logitech c270 webcam. From the local breed chicken egg image dataset training, an accuracy of 96.76% was obtained in the validation set test and 95.26% in the test set. From the case of detecting local breed chicken egg quality with deep learning based on the YOLOv4 algorithm, it allows for further development."

"Sistem Klasifikasi Dewey Decimal Classification ini merupakan salah satu sistem yang dikenal di kalangan pustakawan.Saking dikenalnya,hampir setiap pustakawan mengenal sistem ini minimal namanya dan bahkan mengetahui urutan kelasnya...."

"There are many information which can be processed in many emails. Clasisification is a way to organize the informations which are be in the emails....."

"Land cover information is vital for supporting decision concerning the management of the environment and for understanding the causes and trnds of human and natural processess on the earth surface...."

"The NTIS classification system has simpler notation than DDC. It does not recognize supporting table so that it can determine the notation faster. The number of the main class in NTIS classification system is 39 while DDC is 10. NTIS is most suitable for special libraries in the field of technology such as the Agency for the Assesment and Application of Technology (BPPT) since the system has a more specific technology subject. DDC is also effective for collection data exchange since 2010, referring that generally libraries in Indonesia has not recognized NTIS. Both systems actually have its advantages and disadvantages. In determining notations, both NTIS and DDC use the same initial step that is to determine the collection subject. NTIS is faster especially in handling technology subject. It is also more specific in referring technology subject. The number of the main class in NTIS is 39 while DDC is 10. Both systems have index. NTIS does not have supporting table while DDC has. NTIS uses a simpler notation because it uses only 2 digits. According to a key informant, the NTIS classification system does not recognize supporting table. In terms of notation search, NTIS's scheme is faster because it uses limited classification numbers. Index is mostly used for determining classification notation. Index in both systems is a clue represented in a systematically arranged letters. In NTIS, it can be figured out that subjects on technology is more specific yet in some certain categories is not as detail as DDC."

"Epilepsi merupakan penyakit kronik dengan gejala yang cukup khas yaitu adanya bangkitan kejang tanpa pemicu. Angka prevalensi epilepsi tergolong tinggi di Indonesia dan hal ini merupakan masalah yang harus segera diatasi. Selain itu, epilepsi pada anak dapat menyebabkan berbagai gangguan perkembangan. Salah satu pemeriksaan penunjang untuk mendiagnosis klasifikasi epilepsi yang tersedia saat ini adalah EEG yang memberikan gambaran pola gelombang spesifik tertentu. Oleh karena itu, dalam penelitian ini akan dianalisis hubungan antara epilepsi pada anak dengan gambaran EEG serta perkembangan anak. Desain penelitian ini adalah potong lintang dengan menggunakan data sekunder rekam medik dari Departemen Ilmu Kesehatan Anak RSUPN Cipto Mangunkusumo tahun 1995-2010. Hasil penelitian ini menunjukkan bahwa terdapat 115 anak (61,5%) dengan klasifikasi epilepsi simtomatik, 105 anak (56,1%) dengan gambaran EEG abnormal, dan 96 anak (51,3%) dengan perkembangan terlambat. Dari hasil analisis hubungan antar variabel menggunakan Chi-Square, terdapat hubungan bermakna antara perkembangan anak dengan klasifikasi epilepsi (p<0,001) disertai dengan hubungan bermakna antara aspek perkembangan yaitu motorik kasar (p<0,001), sosial personal (p=0,024), dan bahasa (p<0,001) tetapi tidak ada hubungan bermakna antara aspek motorik halus terhadap klasifikasi epilepsi.Tidak ada hubungan bermakna antara gambaran EEG secara umum dengan klasifikasi epilepsi tetapi terdapat hubungan bermakna antara adanya gambaran epileptiform multifokal (p=0,018) dan nonspesifik (p=0,015) terhadap klasifikasi epilepsi.

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Epilepsy is a chronic disease with typical symptom, seizure without provocation. The prevalence of epilepsy in Indonesia can be classified as high which creates another health problem to overcome. Furthermore, epilepsy in children may cause variety of development impairment. EEG is one of the current available examination to diagnose the classification of epilepsy through specific wave pattern findings. Therefore, this study is determined to analyze the association between epilepsy in children with EEG recording and child development. This study is a cross-sectional study using secondary data from Child Health Department of RSUPN Cipto Mangunkusumo medical records from 1995-2010.The result of the study shows that 115 subjects (61,5%) has symptomatic epilepsy, 105 subjects (56,1%) with abnormal EEG finding, and 96 subjects (51,3%) with delayed development. After performing Chi-Square test, there is a significant association between child development and epilepsy classification (p<0,001)followed by significant association between gross motoric (p<0,001), social personal (p=0,024), and language (p<0,001), however there were no association between gross motoric and epilepsy classification.There were no association between EEG recording with epilepsy classification,however there were a significant association between multifocal epileptiform finding (p=0,018) and nonspecific wave finding (p=0,015) to classify epilepsy"