ANALISIS DAN PERANCANGAN SISTEM AKUNTANSI PERSEDIAAN PADA UD LI JAYA KUPANG

Inventory is a large asset owned by the company. Large investments invested in the form of inventory willcause problems related to the cost of organizing where the cost will increase the warehouse costs. Inventoryis very vulnerable to damage, theft, and misappropriation. The inventory accounting system plays animportant role in the arrangement of avoiding the repatriation of the company's wealth, especiallyinventory. Proper and correct accounting treatment of inventory is absolutely necessary. This is becausethe inventory post has a considerable influence in the financial statements, which is in the balance sheetand in determining the price of inventory in the income statement. The problem in the research is how todesign good documents, records, and procedures related to the inventory accounting system ofmerchandise at Usaha Dagang Li Jaya Kupang and how the internal control system prevent the multipositions, mis-recording, and possible misappropriation of inventory of at Usaha Dagang Li JayaKupang. The results showed that the inventory accounting information system at UD. Li Jaya hasweaknesses in terms of inventory recording undone because of the limited educational background of theexisting workforce and in terms of its internal controls that have not been effective. The obstacles faced byUD. Li Jaya Kupang is the absence of computerized administration in the recording system, so that isno recording at all in the warehouse section. The inventory accounting information system at UD LiJaya Kupang must have its own recording administration, so that employees do not record bythemshelves. Keywords : Inventory, Intenal Control, Inventory Accounting Information Syste

Age-related differences in features associated with polycystic ovary syndrome in normogonadotrophic oligo-amenorrhoeic infertile women of reproductive years

OBJECTIVE: To assess the effect of age on clinical, endocrine and sonographic features associated with polycystic ovary syndrome (PCOS) in normogonadotrophic anovulatory infertile women of reproductive years

Hubungan antara Motivasi dan Self-regulated Learning Siswa Selama Pembelajaran Jarak Jauh di Kota Kupang

Penerapan  pembelajaran  jarak  jauh  di  sekolah-sekolah  merupakan  hal  baru  bagi siswa dan guru, butuh waktu bagi siswa dan guru untuk beradaptasi. Keberhasilan pelaksanaan pembelajaran jarak jauh dipengaruhi oleh banyak faktor. Beberapa faktor yang mempengaruhi adalah motivasi dan self regulated learning. Penelitian ini bertujuan untuk mengetahui hubungan antara motivasi dengan self regulated learning siswa selama pembelajaran jarak jauh di kota kupang. Penelitian ini berjenis korelasional dengan pendekatan kuantitatif. Instrumen penelitian menggunakan kuesioner self regulated learning Jansen et al., (2017) dan kuesioner motivasi Garcia (1996). Responden dalam penelitian ini berjumlah 178 siswa di kota Kupang yang berasal dari jenjang pendidikan Sekolah Dasar, Sekolah Menengah Pertama, dan Sekolah Menengah Atas. Teknik analisis data menggunakan korelasi product moment. Hasil penelitian menunjukkan bahwa terdapat hubungan signifikan dan positif antara motivasi dengan self regulated learning dengan besar koefisien korelasi 0.780. Uji  koefisien  determinasi  menunjukkan  motivasi menjadi prediktor self regulated learning sebesar 0.608 atau 60,8%. Penelitian ini menyimpulkan bahwa terdapat hubungan antara motivasi dengan self regulated learning siswa selama pembelajaran jarak jauh di kota kupang

Classification of brain injury severity using a hybrid broadband NIRS and DCS instrument with a machine learning approach

Optical biomarkers of neonatal hypoxic ischemic (HI) brain injury can offer the advantage of continuous, cot-side assessment of the degree of injury; research thus far has focused on examining different optical measured brain physiological signals and feature combinations to achieve this. To maximize the breadth of physiological characteristics being taken into consideration, a multimodal optical platform has been developed, allowing unique physiological insights into brain injury. In this paper we present an assessment of severity of injury using a state-of-the-art hybrid broadband Near Infrared Spectrometer (bNIRS) and Diffusion Correlation Spectrometer (DCS) instrument called FLORENCE with a machine learning pipeline. We demonstrate in the preclinical neonatal model (the newborn piglet) that our approach can identify different HI insult severity (controls, mild, severe). We show that a machine learning pipeline based on k-means clustering can be used to differentiate between the controls and the HI piglets with an accuracy of 78%, the mild severity insult piglets from the severe insult piglets with an accuracy of 90% and can also differentiate the 3 piglet groups with an accuracy of 80%. So, this analytics pipeline demonstrates how optical data from multiple instruments can be processed towards markers of brain health

Nonlinear evolution of dark matter and dark energy in the Chaplygin-gas cosmology

The hypothesis that dark matter and dark energy are unified through the Chaplygin gas is reexamined. Using generalizations of the spherical model which incorporate effects of the acoustic horizon we show that an initially perturbative Chaplygin gas evolves into a mixed system containing cold dark matter-like gravitational condensate.Comment: 11 pages, 3 figures, substantial revision, title changed, content changed, added references, to appear in JCA

Identifying structure-absorption relationships and predicting absorption strength of non-fullerene acceptors for organic photovoltaics

Non-fullerene acceptors (NFAs) are excellent light harvesters, yet the origin of their high optical extinction is not well understood. In this work, we investigate the absorption strength of NFAs by building a database of time-dependent density functional theory (TDDFT) calculations of ∼500 π-conjugated molecules. The calculations are first validated by comparison with experimental measurements in solution and solid state using common fullerene and non-fullerene acceptors. We find that the molar extinction coefficient (εd,max) shows reasonable agreement between calculation in vacuum and experiment for molecules in solution, highlighting the effectiveness of TDDFT for predicting optical properties of organic π-conjugated molecules. We then perform a statistical analysis based on molecular descriptors to identify which features are important in defining the absorption strength. This allows us to identify structural features that are correlated with high absorption strength in NFAs and could be used to guide molecular design: highly absorbing NFAs should possess a planar, linear, and fully conjugated molecular backbone with highly polarisable heteroatoms. We then exploit a random decision forest algorithm to draw predictions for εd,max using a computational framework based on extended tight-binding Hamiltonians, which shows reasonable predicting accuracy with lower computational cost than TDDFT. This work provides a general understanding of the relationship between molecular structure and absorption strength in π-conjugated organic molecules, including NFAs, while introducing predictive machine-learning models of low computational cost

Antiphospholipid syndrome; its implication in cardiovascular diseases: a review

Antiphospholipid syndrome (APLS) is a rare syndrome mainly characterized by several hyper-coagulable complications and therefore, implicated in the operated cardiac surgery patient. APLS comprises clinical features such as arterial or venous thromboses, valve disease, coronary artery disease, intracardiac thrombus formation, pulmonary hypertension and dilated cardiomyopathy. The most commonly affected valve is the mitral, followed by the aortic and tricuspid valve. For APLS diagnosis essential is the detection of so-called antiphospholipid antibodies (aPL) as anticardiolipin antibodies (aCL) or lupus anticoagulant (LA). Minor alterations in the anticoagulation, infection, and surgical stress may trigger widespread thrombosis. The incidence of thrombosis is highest during the following perioperative periods: preoperatively during the withdrawal of warfarin, postoperatively during the period of hypercoagulability despite warfarin or heparin therapy, or postoperatively before adequate anticoagulation achievement. Cardiac valvular pathology includes irregular thickening of the valve leaflets due to deposition of immune complexes that may lead to vegetations and valve dysfunction; a significant risk factor for stroke. Patients with APLS are at increased risk for thrombosis and adequate anticoagulation is of vital importance during cardiopulmonary bypass (CPB). A successful outcome requires multidisciplinary management in order to prevent thrombotic or bleeding complications and to manage perioperative anticoagulation. More work and reporting on anticoagulation management and adjuvant therapy in patients with APLS during extracorporeal circulation are necessary

Follicular fluid content and oocyte quality: from single biochemical markers to metabolomics

The assessment of oocyte quality in human in vitro fertilization (IVF) is getting increasing attention from embryologists. Oocyte selection and the identification of the best oocytes, in fact, would help to limit embryo overproduction and to improve the results of oocyte cryostorage programs. Follicular fluid (FF) is easily available during oocyte pick-up and theorically represents an optimal source on non-invasive biochemical predictors of oocyte quality. Unfortunately, however, the studies aiming to find a good molecular predictor of oocyte quality in FF were not able to identify substances that could be used as reliable markers of oocyte competence to fertilization, embryo development and pregnancy. In the last years, a well definite trend toward passing from the research of single molecular markers to more complex techniques that study all metabolites of FF has been observed. The metabolomic approach is a powerful tool to study biochemical predictors of oocyte quality in FF, but its application in this area is still at the beginning. This review provides an overview of the current knowledge about the biochemical predictors of oocyte quality in FF, describing both the results coming from studies on single biochemical markers and those deriving from the most recent studies of metabolomic