Book Review of Cewek Paling Badung Di Sekolah by Enid Blyton

BOOK REVIEW OF CEWEK PALING BADUNG DI SEKOLAH by Enid Blyto

An Early Detection Method of Type-2 Diabetes Mellitus in Public Hospital

Diabetes is a chronic disease and major problem of morbidity and mortality in developing countries. The International Diabetes Federation estimates that 285 million people around the world have diabetes. This total is expected to rise to 438 million within 20 years. Type-2 diabetes mellitus (T2DM) is the most common type of diabetes and accounts for 90-95% of all diabetes. Detection of T2DM from various factors or symptoms became an issue which was not free from false presumptions accompanied by unpredictable effects. According to this context, data mining and machine learning could be used as an alternative way help us in knowledge discovery from data. We applied several learning methods, such as instance based learners, naive bayes, decision tree, support vector machines, and boosted algorithm acquire information from historical data of patient’s medical records of Mohammad Hoesin public hospital in Southern Sumatera. Rules are extracted from Decision tree to offer decision-making support through early detection of T2DM for clinicians.

Penjadwalan Produksi Pada Lingkungan Flexible Job Shop Problem (Fjsp) Untuk Meminimasi Total Tardiness (Studi Kasus Di Divisi Ppip PT. Barata Indonesia (Persero), Gresik)

PT. Barata Indonesia (Persero) Gresik merupakan Badan Usaha Milik Negara (BUMN) yang bergerak dibidang Engineering, Procurement, dan Construction. Divisi Produksi Peralatan Industri Proses (PPIP) sering mengalami keterlambatan dalam memenuhi order atau pesanan dari konsumen dikarenakan oleh metode penjadwalan yang kurang disesuaikan dengan waktu datang kontrak dan waktu pemenuhan due date dari tiap order-nya,. Berdasarkan hal tersebut, Perusahaan menginginkan solusi usulan agar kondisi buruk ini dapat diperbaiki sehingga keterlambatan pengerjaan order dapat diatasi. Penelitian ini mengusulkan metode Earliest Due Date (EDD), First Come First Serve (FCFS), dan integrasi antara Algoritma Tabu Search dengan Pairwise Interchange Heuristic sebagai keputusan untuk memprioritaskan urutan job sebelum dijadwalkan, kemudian dalam tahapan pengerjaannya menggunakan algoritma Sequencing yang dirancang untuk mendapatkan hasil jadwal usulan yang mendekati optimal, yaitu dengan nilai tardiness dan penalti yang paling minimal. Hasil penelitian menunjukkan bahwa prioritas urutan job yang optimal adalah 1-2-3; 2-3-1; 3-2-1; dan 1-3-2. Seluruh job yang dijadwalkan, yaitu job 1, job 2 dan job 3, secara berurutan membutuhkan waktu produksi selama 87,3 jam; 156 jam; dan 218,6 jam. Nilai ini setara dengan 11 hari, 20 hari dan 28 hari dan seluruh job dapat selesai 9 hari, 12 hari, dan 14 hari sebelum due date-nya. Selanjutnya, penalti diperhitungkan berdasarkan nilai tardiness. Dengan menggunakan metode usulan menghasilkan jadwal yang tidak menghasilkan tardiness, maka penalti juga tidak terjadi sehingga Perusahaan dapat menghemat biaya produksi

Nonlinearity of Mechanochemical Motions in Motor Proteins

The assumption of linear response of protein molecules to thermal noise or structural perturbations, such as ligand binding or detachment, is broadly used in the studies of protein dynamics. Conformational motions in proteins are traditionally analyzed in terms of normal modes and experimental data on thermal fluctuations in such macromolecules is also usually interpreted in terms of the excitation of normal modes. We have chosen two important protein motors - myosin V and kinesin KIF1A - and performed numerical investigations of their conformational relaxation properties within the coarse-grained elastic network approximation. We have found that the linearity assumption is deficient for ligand-induced conformational motions and can even be violated for characteristic thermal fluctuations. The deficiency is particularly pronounced in KIF1A where the normal mode description fails completely in describing functional mechanochemical motions. These results indicate that important assumptions of the theory of protein dynamics may need to be reconsidered. Neither a single normal mode, nor a superposition of such modes yield an approximation of strongly nonlinear dynamics.Comment: 10 pages, 6 figure

Status of the joint LIGO--TAMA300 inspiral analysis

We present the status of the joint search for gravitational waves from inspiraling neutron star binaries in the LIGO Science Run 2 and TAMA300 Data Taking Run 8 data, which was taken from February 14 to April 14, 2003, by the LIGO and TAMA collaborations. In this paper we discuss what has been learned from an analysis of a subset of the data sample reserved as a ``playground''. We determine the coincidence conditions for parameters such as the coalescence time and chirp mass by injecting simulated Galactic binary neutron star signals into the data stream. We select coincidence conditions so as to maximize our efficiency of detecting simulated signals. We obtain an efficiency for our coincident search of 78 %, and show that we are missing primarily very distant signals for TAMA300. We perform a time slide analysis to estimate the background due to accidental coincidence of noise triggers. We find that the background triggers have a very different character from the triggers of simulated signals.Comment: 10 page, 8 figures, accepted for publication in Classical and Quantum Gravity for the special issue of the GWDAW9 Proceedings ; Corrected typos, minor change