Konstruksi Realitas dalam Infotainment Silet

This paper aims to analyze the discourse of motto used by Silet, the most favorite infotainment programs of Panasonic Gobel Awards. The research found that Silet has used language that can transform reality. Using language, Silet has constructed meaning to audiences that information presented has changed from original form. Something that is taboo now can be worthy to discuss it after broadcasted by Silet. Silet gives suggestion and ‘false consciousness’ to audiences that everything presented by Silet is good and right. The use of words and motto is a tactic to make proper banality of news content presented by Silet

KINETIKA REAKSI PEMBUATAN PUPUK KALIUM FOSFAT DARI ABU PELEPAH PISANG DAN ASAM FOSFAT

Banyaknya limbah pelepah pisang di Indonesia yang tidak dimanfaatkan hanya akan menambah kuantitas limbah. Pelepah pisang memiliki kandungan kalium yang cukup besar dan dapat berfungsi sebagai bahan baku pupuk. Pembuatan pupuk kalium fosfat (K3PO4) dari abu pelepah pisang dan asam fosfat (H3PO4) adalah dengan cara ekstraksi. Abu dari hasil pembakaran pelepah pisang diekstraksi dengan asam fosfat. Penelitian ini bertujuan untuk menentukan kinetika reaksi yaitu konstanta kecepatan reaksi dan orde reaksi pembentukan kalium fosfat dari ekstrak abu pelepah pisang dan asam fosfat. Penelitian dilakukan dengan perbedaan suhu dan waktu. Suhu yang digunakan adalah 40, 50, 60, 70, dan 80 oC. Waktu ekstraksi berlangsung dalam variasi 10, 20, 30, 40, dan 50 menit. Berdasarkan penelitian yang telah dilakukan, pembentukan kalium fosfat dari abu pelepah pisang dan asam fosfat mengikuti orde satu dengan tetapan laju reaksi, k = 0,0151 menit-1 pada suhu 80oC. Energi aktivasi yang didapatkan adalah 170,8776 J/mol dengan nilai frekuensi tumbukan (k0) adalah 0,0163 persamaan tetapan laju reaksi k = 0,0163 e-20,533/T. Konversi terbaik yang didapatkan adalah 0,5698 atau 56,98 %

Radial basis function network based on time variant multi-objective particle swarm optimization for medical diseases diagnosis

This paper proposes an adaptive evolutionary radial basis function (RBF) network algorithm to evolve accuracy and connections (centers and weights) of RBF networks simultaneously. The problem of hybrid learning of RBF network is discussed with the multi-objective optimization methods to improve classification accuracy for medical disease diagnosis. In this paper, we introduce a time variant multi-objective particle swarm optimization (TVMOPSO) of radial basis function (RBF) network for diagnosing the medical diseases. This study applied RBF network training to determine whether RBF networks can be developed using TVMOPSO, and the performance is validated based on accuracy and complexity. Our approach is tested on three standard data sets from UCI machine learning repository. The results show that our approach is a viable alternative and provides an effective means to solve multi-objective RBF network for medical disease diagnosis. It is better than RBF network based on MOPSO and NSGA-II, and also competitive with other methods in the literature

Higher Order Centralised Scale-Invariants for Unconstrained Isolated Handwritten Digits

The works presented in this thesis are mainly involved in the study of global analysis of feature extractions. These include invariant moments for unequal scaling in x and y directions for handwritten digits, proposed method on scale-invariants and shearing invariants for unconstrained isolated handwritten digits. Classifications using Backpropagation model with its improved learning strategies are implemented in this study. Clustering technique with Self Organising Map (SOM) and dimension reduction with Principal Component Analysis (peA) on proposed invariant moments are also highlighted in this thesis. In feature extraction, a proposed improved formulation on scale-invariant moments is given mainly for unconstrained handwritten digits based on regular moments technique. Several types of features including algebraic and geometric invariants are also discussed. A computational comparison of these features found that the proposed method is superior than the existing feature techniques for unconstrained isolated handwritten digits. A proposed method on invariant moments with shearing parameters is also discussed. The formulation of this invariant shearing moments have been tested on unconstrained isolated handwritten digits. It is found that the proposed shearing moment invariants give good results for images which involved shearing parameters.peA is used in this study to reduce the dimension complexity of the proposed moments scale-invariants. The results show that the convergence rates of the proposed scaleinvariants are better after reduction process using peA. This implies that the peA is an alternative approach for dimension reduction of the moment invariants by using less variables for classification purposes. The results show that the memory storage can be saved by reducing the dimension of the moment invariants before sending them to the classifier. In addition, classifications of unconstrained isolated handwritten digits are extended using clustering technique with SOM methodology. The results of the study show that the clustering of the proposed moments scale-invariants is better visualised with SOM

Family as the First and Main Review Child Character Education

Keluarga merupakan tempat yang paling awal dan efektif untuk menjalankan fungsi Departemen Kesehatan, Pendidikan, dan Kesejahteraan. Apabila keluarga gagal untuk mengajarkan kejujuran, semangat, keinginan untuk menjadi yang terbaik, dan kemampuan-kemampuan dasar, maka akan sulit sekali bagi institusi-institusi lain untuk memperbaiki kegagalan-kegagalannya. Kegagalan keluarga dalam membentuk karakter anak akan berakibat pada timbulnya masyarakat yang tidak berkarakter. Oleh karena itu, penelitian ini bertujuan untuk mengetahui setiap keluarga harus memiliki kesadaran bahwa karakter bangsa sangat tergantung pada pendidikan karakter anak di dalam keluarga. Penelitian ini menggunakan metode deskriptif kualitatif dimana penulis menggambarkan fenomena dan keadaan sedalam-dalamnya tentang keluarga sebagai wahana pertama dan utama pendidikan karakter anak. Hasil penelitian menunjukkan bahwa pendidikan dalam keluarga merupakan pendidikan awal atau pertama bagi anak karena pertama kalinya mereka mengenal dunia terlahir dalam lingkungan keluarga dan dididik oleh orang tua. Sehingga pengalaman masa anak-anak merupakan faktor yang sangat penting bagi perkembangan selanjutnya, keteladanan orang tua dalam tindakan sehari-hari akan menjadi wahana pendidikan moral bagi anak, membentuk anak sebagai makhluk sosial, religius, untuk menciptakan kondisi yang dapat menumbuh kembangkan inisiatif dan kreativitas anak

Spectral properties from Matsubara Green's function approach - application to molecules

We present results for many-body perturbation theory for the one-body Green's function at finite temperatures using the Matsubara formalism. Our method relies on the accurate representation of the single-particle states in standard Gaussian basis sets, allowing to efficiently compute, among other observables, quasiparticle energies and Dyson orbitals of atoms and molecules. In particular, we challenge the second-order treatment of the Coulomb interaction by benchmarking its accuracy for a well-established test set of small molecules, which includes also systems where the usual Hartree-Fock treatment encounters difficulties. We discuss different schemes how to extract quasiparticle properties and assess their range of applicability. With an accurate solution and compact representation, our method is an ideal starting point to study electron dynamics in time-resolved experiments by the propagation of the Kadanoff-Baym equations.Comment: 12 pages, 8 figure

Improvement of authorship invarianceness for individuality representation in writer identification

Writer Identification (WI) is one of the areas in pattern recognition that have created a center of attention for many researchers to work in. Recently, its main focus is in forensics and biometric application, e.g. writing style can be used as biometric features for authenticating individuality uniqueness. Existing works in WI concentrate on feature extraction and classi?cation task in order to identify the handwritten authorship. However, additional steps need to be per- formed in order to have a better representation of input prior to the classi?cation task. Features extracted from the feature extraction task for a writer are in vari- ous representations, which degrades the classi?cation performance. This paper will discuss this additional process that can transform the various representations into a better representation of individual features for Individuality of Handwriting, in order to improve the performance of identification in WI

Multilevel kohonen network learning for clustering problems

Clustering is the procedure of recognising classes of patterns that occur in the environment and assigning each pattern to its relevant class. Unlike classical statistical methods, self-organising map (SOM) does not require any prior knowledge about the statistical distribution of the patterns in the environment. In this study, an alternative classification of self-organising neural networks, known as multilevel learning, was proposed to solve the task of pattern separation. The performance of standard SOM and multilevel SOM were evaluated with different distance or dissimilarity measures in retrieving similarity between patterns. The purpose of this analysis was to evaluate the quality of map produced by SOM learning using different distance measures in representing a given dataset. Based on the results obtained from both SOM methods, predictions can be made for the unknown samples. The results showed that multilevel SOM learning gives better classification rate for small and medium scale datasets, but not for large scale dataset

PENGEMBANGAN KREATIVITAS KETERAMPILAN PROSES SAINS DALAM ASPEK KEHIDUPAN ORGANISME PADA MATA PELAJARAN IPA SD

Abstrak: Penelitian ini bertujuan mengetahui seberapa jauh pengembangan kreativitas keterampilan proses sains dalam aspek kehidupan organisme melalui IPA di SD di DIY. Penelitian ini merupakan hasil need assessment yang dilaksanakan pada tahun pertama dari penelitian dengan judul kreativitas keterampilan proses sains dalam aspek kehidupan organisme pada mata pelajaran IPA SD yang akan dilaksanakan selama tiga tahun. Pengumpulan data melalui survei dengan teknik sampel gugus setelah ditetapkan Unit Pelaksana Tenis (UPT) Dinas Pendidikan yang mewakili wilayah perkotaan dan pinggiran. Hasil survei terhadap 400 guru kelas IV dan V serta 1200 grup peserta didik dari 10 UPT di lima kabupaten/kota di DIY menunjukkan hampir semua guru menyatakan pentingnya pembelajaran untuk mengembangkan kreativitas keterampilan proses sains dalam aspek kehidupan kepada peserta didik. Mereka hampir tidak pernah atau jarang membelajarkannya tanpa disertai pemberian contoh. Umumnya mereka sering melakukannya dengan disertai pemberian contoh. Tidak ada guru yang melaporkan pernah mengikuti diklat pengembangan kreativitas