12 research outputs found
Multifunctional microsphere formulation of fluorescent magnetic properties for drug delivery system
No full text© 2017 Author(s). The microsphere formulations of Chit/TPP/Sm/Fe3O4/Rn were prepared by an ionic gelation technique, where Chit=chitosan, TPP=tripolyphosphate, Sm=samarium and Rn=ranitidine. Optimum of microsphere formulation exhibit magnetic and fluorescent properties with adsorption efficiency of ∼92% was obtained for Chit/TPP/Sm/Fe3O4/Rn with ratio 400:500:50:1:20. Fluorescence intensity of microsphere formulations increased with the cumulative amount release of ranitidine, so that the changing of fluorescence intensity at wavelength of 590 nm referring to the Sm3+ ion could be used as indicator in DDS. With the demonstration of sustained release from microsphere formulation, it allows to investigate the applications to other drugs
Optimasi Algoritma Naive Bayes Menggunakan Metode Cross Validation Untuk Meningkatkan Akurasi Prediksi Tingkat Kelulusan Tepat Waktu
No full textEducation at this time is an important requirement in facing the demands of an increasingly advanced era in technolo-gy. To compensate this, the existing educational standards in universities must also be improved, this is a bit much affect the pattern of teaching from universities that produce qualified graduates who can compete in the world of work later and indirectly give a positive impact on the university itself. Qualified graduates are of course not only depending on the role of a university but also majors and quality of education as long as students are still in high school / vocational school also plays an important role. Results of the on-time graduation rate prediction research can be used as an information to im-prove the quality and optimization of the education system but it requires a maximum degree of accuracy. This research predicts on time graduation rates by conducting analysis using data mining classification techniques. Naïve Bayes algo-rithm that are used for this research will be discussed as a reference in conducting research. The author performs a series of different experimental scenarios / cross validation to perform comparisons that can give a difference in the level of ac-curacy gained from this research. The results of this research indicate that with the addition of Cross Validation testing scenario there is an increase of 2% accuracy of the test
Enrichment process of biogas using simultaneous Absorption - Adsorption methods
No full text© 2017 Author(s). Removal of CO2 in biogas is an essential methods to the purification and upgrading of biogas. Natural Clinoptilolite zeolites were evaluated as sorbents for purification of biogas that produced from palm oil mill effluent (POME) by anerobic-digestion method. The absorption and adsorption experiments were conducted in a fixed-bed two column adsorption unit by simultaneous absorption-adsorption method. The Ca(OH)2 solution with concentration of 0.062 M was used as absorption method. Sorbent for removal of CO2 in biogas have been prepared by modifying of Clinoptilolite zeolites with an acid (HCl, 2M) and alkaline (NaOH, 2M), calcined at 450°C and then coated using chitosan (0.5 w/v%) in order to increase their adsorption capacity. The removal of CO2 in biogas was achieved about ∼83% using 2.5?g of sorbent zeolite (2M)/chitosan dosage for each column, breakthrough time of 30?min, and flow rate of 100?mL/min. Clinoptilolite zeolites with modifications of an acid-alkaline and chitosan (zeolite (2M)/chitosan) are promising sorbents due to the amine groups from chitosan and high surface-volume ratio are one of important factors in a simultaneous absorption-adsorption method
Community health nurse's role in public health centers (PUSKESMAS) in Makassar, South Sulawesi, Indonesia
No full textThis thesis was scanned from the print manuscript for digital preservation and is copyright the author.
Researchers can access this thesis by asking their local university, institution or public library to
make a request on their behalf. Monash staff and postgraduate students can use the link in the References field
Expert System to Diagnose Appendicitis with the Certainty Factor Method
No full textHealth is the main key to human life, for that the author also needs health in writing a thesis entitled appendicitis so that readers can understand and recognize appendicitis more quickly. According to Kusrini, S.Kom (2006:11). An expert system is a computer-based system that uses knowledge, facts and reasoning techniques in solving problems that can usually only be solved by an expert in the field. Basically expert systems are applied to support problem solving activities. According to (T. Sujoto, Edy Mulyanto, Dr. Vincen Suhartono, 2011: 125) the Certainty Factor (CF) theory is to accommodate the inexact reasoning of an expert proposed by Shortliffe and Buchanan in 1975. Here the author will discuss on the Expert System for Diagnosing Appendicitis, Certainty Factor Method is one of the Expert System Methods for diagnosing appendicitis. To make the application the author uses Microsoft Visual Studio 2010
Kombinasi Metode ABC dan MMSL dalam Pengendalian Stok Obat
No full textAbstract - In hospitals, problems often occur in the management of drug supplies with the condition that the drug runs out due to spending in one year 30% for the investment cost of drugs. In overcoming this problem, the hospital should have good drug data processing, processing can be done by doing good management. The author will use the ABC method combined with MMSL. ABC functions in grouping A, B, and C and is combined with MMSL in calculating Maximum Stock and Minimum stock. From this study, it was found that using the ABC method of drug analysis was grouped based on drug use into three groups, namely group A with a percentage of 21.90%, group B with a percentage of 32.25%, and group C with a percentage of 45.85%. For the results of MMSL, namely combining several variables in the ABC to MMSL algorithm. The results of the MMSL entered into the drug stock control process that the optimal prediction was 17.15% MAPE compared to the MAPE investment value of 19.05% and the MAPE lead time 18.14%.Keywords  - MMSL, Classification, Prediction, ABC Analysis Abstrak - Pada rumah sakit sering terjadi permasalahan pada pengelolaan persedian obat dengan kondisi obat habis disebabkan oleh pengeluaran dalam satu tahun 30 % untuk biaya investasi obat. Dalam mengatasi permasalahan ini rumah sakit seharunya mempunyai pengolahan data obat yang baik, cara pengolahan bisa dengan melakukan management yang baik. Penelitian ini menggunakan metode ABC dikombinasikan dengan MMSL. ABC berfungsi dalam pengelompokan A,B dan C serta dikombinasikan dengan  MMSL dalam menghitung Maximum Stock dan Minimum stock.  Dari penelitian ini mandapatkan hasil bahwa dengan menggunakan metode ABC analisis obat dikelompokan berdasarkan pemakaian obat menjadi tiga kelompok yaitu kelompok A dengan persentase 21.90%, kelompok B dengan persentase 32.25% dan kelompok C dengan persentase 45.85%. Untuk hasil dari MMSL yakni mengkombinasikan beberapa variabel pada algoritma ABC ke MMSL. Hasil dari MMSL masuk kedalam proses pengendalian stock obat bahwa prediksi yang optimal yakni MAPE 17.15% dibandingkan dengan nilai investasi MAPE 19.05% dan Lead time MAPE 18.14%.Kata Kunci - MMSL, Klasifikasi, Prediksi , ABC Analisis.
Kombinasi Metode ABC dan MMSL dalam Pengendalian Stok Obat
No full text- In hospitals, problems often occur in the management of drug supplies with the condition that the drug runs out due to spending in one year 30% for the investment cost of drugs. In overcoming this problem, the hospital should have good drug data processing, processing can be done by doing good management. The author will use the ABC method combined with MMSL. ABC functions in grouping A, B, and C and is combined with MMSL in calculating Maximum Stock and Minimum stock. From this study, it was found that using the ABC method of drug analysis was grouped based on drug use into three groups, namely group A with a percentage of 21.90%, group B with a percentage of 32.25%, and group C with a percentage of 45.85%. For the results of MMSL, namely combining several variables in the ABC to MMSL algorithm. The results of the MMSL entered into the drug stock control process that the optimal prediction was 17.15% MAPE compared to the MAPE investment value of 19.05% and the MAPE lead time 18.14%.Keywords - MMSL, Classification, Prediction, ABC Analysi
Sesame Plant Disease Classification Using Deep Convolution Neural Networks
No full textMonitoring sesame plant health and detecting disease early are essential to reducing disease spread and facilitate effective management practices. In this research, we developed an image classification model to detect bacterial blight-infected, phyllody-infected, and healthy sesame crops. Since images were necessary to carry out this study, we collected 2300 images at the Gondar and Humera Agriculture Research Centers and directly from the field in Metema. Since the collected images were limited, to increase the number of images in the dataset, we used image augmentation with different variations. In the image preprocessing step, we used a median filter for noise filtering, and contrast stretching techniques were used for image contrast and brightness enhancement. SegNet semantic segmentation, which is deep convolution neural network-based architecture, was used to segment the leaf part of the image from the background. In the feature extraction and classification steps, a deep convolutional neural network was used. Finally, we evaluated the proposed model and compared it with two recent deep convolution neural network models, namely, Xception and InceptionV3. The proposed model for the classification of sesame diseases achieved better accuracy, with 96.67% testing accuracy, 97.78% validation accuracy, and 98% training accuracy
Analisa ekonomis peralatan pulverizer untuk optimalisasi keandalan PLTU dengan simulasi Monte Carlo dan pendekatan analisa biaya siklus hidup (Studi kasus: PLTU X)
No full textTo improve and maintain the reliability of PLTU X (FTP-1) power supply using coal fuel it is necessary to improve the reliability of the equipment especially on the crucial equipment which one of the pulverizer equipment for it is necessary to process the procurement of equipment components (stock warehouse) to maintain if possible a malfunction or malfunction occurs. The author intends to make three alternative procurement process that is through OEM procurement process, Non OEM / reverse engineering and recondition.This journal will analyze a financial feasibility study to ascertain whether the procurement has economic value and the asset will be used effectively and efficiently over the life of the benefit using the LCCA cost analysis approach. In this paper, historical data on pulverizer damage is obtained from the HDKP Rapsodi Settlement application to be verified and processed using minitab 17 applications to obtain the weibull shape factor (β) and scale factor / characteristic life () and the data as monte carlo simulation input. So we get mean time to failure (MTTF) / age of pulverizer component. To analyze the threealternatives and determine which alternatives are most profitable for 10 years with a life cycle cost analysis approach.Based on the analysis of quantitative calculation data, the life of pulverizer mills (MTTF) procurement process OEM for 10,108 hours / 1.2 years, non-OEM / reverse engineering for 16,899 hours / 2 years and recondition for 5,323 hours / 0.7 years and the results of approach life cycle cost analysis was obtained cost savings of 35.22 billion per unit pulverizer mills for 10 years with reverse engineering procurement process compared to OEM
Thermal properties of sonicated graphene in coconut oil as a phase change material for energy storage in building applications
No full text© 2020 The Author(s). Published by Oxford University Press. This study aims to investigate the thermal properties of a phase change material (PCM) based on coconut oil for building energy storage applications. Coconut oil is classified as an organic PCM composed of fatty acids made from renewable feedstock. However, low thermal conductivity is one of the major drawbacks of organic PCMs that must be improved. Graphene could be an effective material to enhance the thermal performance of organic PCMs. In this study, coconut oil with a latent heat capacity of 114.6 J/g and a melting point of 17.38°C was used. PCMs were prepared by sonicating graphene into coconut oil, as a supporting material. The mass fractions of the prepared PCMs were 0, 0.1, 0.2, 0.3, 0.4 and 0.5. Thermal conductivity tests were performed using a KD2 thermal property analyser under different ambient temperatures of 5, 10, 15, 20 and 25°C simulated with a circulating thermostatic bath. The latent heat, melting point and freezing point were determined through differential scanning calorimetry, the thermal stability was determined using thermogravimetric analysis (TGA) and the morphology and chemical structure were examined using transmission electron microscopy and Fourier-transform infrared spectroscopy, respectively. The results of this study showed that graphene addition to coconut oil improved the thermal performance, with the highest improvement seen in a 0.3 wt% sample at 20°C. The latent heat decreased by 11% owing to molecular movements within the PCM. However, TGA revealed that the composite PCMs showed good thermal stability in ambient building temperature ranges
