Decision Support System For Developing Application For Pharmaceutical Supplies Using The MMSL And Pareto Law Methods

This study discusses the design and manufacture of a decision support system for pharmaceutical supply needs using the MMSL and Pareto Law methods. The development of this decision support system aims to assist the planning process for pharmaceutical supply needs including: drugs and consumables, as well as to reduce the cost of pharmaceutical supplies. Problem analysis is done by observing and conducting feasibility studies of ongoing information systems, and analyzing problem findings. The data used for the main support of this decision support system is dummy data. The decision support system is made using the PHP and MySQL programming languages as the database and will be implemented based on a web base. The results of this study produce a web-based decision support system that can support the management of pharmaceutical supplies and provide accurate and effective reports.

Prospect Prediction Model Of Indonesian Telematics Medium Large Size Enterprises Using Deep Learning Approach

Analysis of business prospects is an important part of predicting a country's economic conditions. Currently, the prediction of prospects for medium-big sized enterprises (MLE) in the telematics sector has not been widely researched and represented as a factor of economic development in Indonesia. In fact, in accordance with the development of the Industrial Revolution 4.0, the telematics sector business is one of the pillars that is a priority to be developed in Indonesia. The main purpose of this study is to construct the prediction model for prospects in the Indonesian telematics LME sector using a deep learning approach. We used data from the 2016 National Economic Census as many as 2500 preprocessed data. The deep learning approach in this study used a multilayer perceptrón (MLP) architecture, 17 attributes, 3 hidden layers and 5 target classes. The attributes in question include province, business owner education, legal entity status, length of operation, business network, total assets, business lava, number of workers, difficulties, partnerships, marketing innovations, comparison of profit with the previous year, and development plans. The target class of prospects are excellent, good, neutral, bad and very bad. The optimal results were achieved in epoch 50 conditions with a learning reate of 0.2 and an accuracy rate of 98.80%. Based on the prediction model, this business prospect can be used as a reference for the development of MLE in the telematics sector in Indonesia. This prospect model still lacks visualization and attribute analysis that affects the classification of prospects for Indonesian telematics MLE. Research development opportunities can be carried out through the integration of the whitebox model in the deep learning model and complementing a web-based graphical user interface (GUI) to make it easier for stakeholders to develop strategies based on the strength of attributes that affect the prospects for MLE Telematics Indonesia. This is expected to boost the competitiveness of the prospects for Indonesian telematics MLE.

Analytical & Experimental Analysis of Lightning Stokes Performance & Protection by MOV Based Simulation Model: A 33 KV Transmission Line Case Study

Researchers are working on techniques to mitigate failure rates as low as possible to avoid potential harm, sustain high power efficiency for this a considerable number of estimation studies were already performed and several designs of methodologies were being suggested. The transmission line performs the role of the arteries which maintain the process of transporting electricity in the transmission line. That is why it is important to maintain and manage the costs of these tracks. Surge arrestor and shield wire application are often techniques chosen for defensive strategy in a very technique. By pushing travelling waves towards the electrical equipment mounted on the transmission line, the effects of lightning stoke on the transmission line may cause severe damage to the electrical equipment. In this review, this research study provides a review-based overview of the mechanism of occurrence of lightning along with its impact on the transmission line and the defence methods used to prevent such effects. A MATLAB / SIMULINK 2020a simulation modeling-based analysis for the incidence of lightning on the 33 kV transmission line system is observed in this regard, and a Metal-Oxide surge arrestor-based lightning fault clearance safety scheme is also suggested and discussed.

Techno-Economic Feasibility Analysis of Concentrated Solar Thermal Power Plants as Dispatchable Renewable Energy Resource of Pakistan: A case study of Tharparkar

Pakistan is identified to be one of the next-11 the top emerging economies of the world after the BRICS. This emphasizes the establishment of a competitive electricity market that can fulfil the demand of the country considering the environmental concerns. In this scenario reliability of power is something that cannot be compromised. Dispatchable power stations play a major role in balancing supply and demand; this balance is essential for maintaining the power cuts free country. All dispatchable power stations incorporate some form of storage particularly thermal or chemical (i.e. a stored fuel). Earlier dispatchable power was regarded as the generation which can start quickly and meet the peak demand requirements but arrival of renewables in power system has increased worth of its presence since it has just not to supply peak demand but also to meet during the unavailability of other renewable energy sources because of their intermittent behavior meanly at times of dark hours and slow wind speed. This study considers the viability of Concentrated Solar Thermal Power in Pakistan and thoroughly analyses several characteristics i.e., Availability of fuel, water, road and communication network, flexibility and environmental impacts of the technology for the cite of Tharparkar.

Early Detection of Diseases And Abnormalities In The Respiratory System Using Certainty Factor Method

Health is a very important factor in the human body. If the health of ourselves is interrupted, it is also interrupted by someone to do the activity. There are several diseases that have a lot of sufferers. One of them is the disease of the respiratory system. Respiratory system is defined generally as a matter that disrupts the process of breathing in our body. Diseases of the respiratory system is one of the main problems of public health in Indonesia, because the disease is a human breathing. The expert system is a library of specialists or an expert in diseases of the respiratory system and the conditions used to take the conclusion of the symptoms. In the calculation process used the certanity factor method to find a percentage level of confidence. The Parameter used in the diagnosis is the symptom chosen by the sufferer. The conclusion of this application results in the diagnosis of the disease suffered and the percentage result of confidence through the selected symptoms. Keywords: Respiratory disease, expert system, Certainty Factor

An Automatic System to Detect Presence of Water in Supply Lines and Maintain Water level of Underground and Overhead Tanks

Commonly most of the houses rely upon the overhead and underground tanks as the main source of water. People usually turn on the motor when their taps go dry and switch off the motor when the tank starts overflowing. This results in needless wasting of water and the lack of water in emergencies. This water is mostly coming through supply line pipes installed by the government through different schemes. The timing of this water coming is mostly irregular because it varies time to time, and in areas where it is fixed, the time is inconvenient for domestic residents to switch ON their motors and fill their tanks. Either the water comes late at night or in the daytime when the people are mostly at their jobs, so they are unable to turn ON their motors. This paper presents a solution to both these problems, a hardware model has been developed using Arduino as the main microcontroller, ultrasonic sensors to detect the level of water in tanks two pumping motors one for underground and one for an overhead tank. And one a water flow sensor is used to automatically detect the water coming in supply lines and switch on the motor. The proposed system saves water, electrical power and human efforts as the whole system is automatic.

GIS implementation and classterization of potential blood donors using the agglomerative hierarchical clustering method

The blood needs of PMI (Indonesian Red Cross) in the Surabaya City area are sometimes erratic, the problem occurs because the amount of blood demand continues to increase while the blood supply is running low. As the main objective of this research, data mining was applied to able to cluster the blood donor data in UTD-PMI Surabaya City Center which was to determine both potential and no potential donors and also visualize the pattern of donor distribution in Geographic Information System (GIS). Agglomerative Hierarchical Clustering was applied to obtain the clustering result from the existing of 8757 donors. The experiment result shown that the cluster quality was quite good which reached 0.6065410 using Silhouette Coefficient. We concluded the one interesting analysis that private male employees with blood type O, and live in the eastern part of Surabaya City are the most potential donors.

PLC Based Load Sharing of Transformers

The transformer is very expensive and bulky power system equipment. It runs and feed the load for 24 hours a day. Sometimes the load on the transformer unexpectedly rises above its rated capacity in that situation the load on the transformer increases and it will be overloaded and current will increase and cause overheating which in results damage the insulation of transformer. That insulation failure resulting in interruption of power supply. The common problems which transformer face is overloading voltage fluctuations and heating effect. It takes lot of time to fix the transformer so that a device need to be introduced a device which would help in automatically sharing of these over voltages. We will try to build an automated transformer sharing system in this project where the transformer current is confined to auxiliary transformer and automatically enters system. There are three transformers working as sources in this project, initially when the main switched ON the load that time load will be shared through the first transformer but when the load on first transformer suddenly increase above its reference value then immediately second transformer connected parallel with first transformer automatically through PLC by busing relay circuit.

Prediction Of Tiger Shrimp Supply Using Time Series Anlysis Method Case Study CV.Surya Perdana Benur

Prediction of demand for tiger shrimp buyers using data from the company CV. Surya Perdana Benur. The process is carried out with the models in the Autoregressive Integrated Moving Average method. Tiger shrimp is a marine animal that is now widely cultivated by big company in Indonesia. Tiger shrimp has important economic value, so its existence must be maintained as part of Indonesian germplasm. The problem now faced by many tiger shrimp companies is the inadequate availability of goods for consumers. This time series data method is useful for predicting the availability of goods for consumers who want to buy goods at the company CV. Surya Perdana Benur. This time series data method is useful for predicting the availability of goods for consumers who want to buy goods at the company CV. Surya Perdana Benur. Autoregressive (AR), MovingAverage (MA), and Autoregressive Integrated Moving Average (ARIMA) model and will be evaluated through Mean Absolute Percent Error (MAPE). The initial process that will be carried out after the data is processed is model identification, estimation of model parameters, residual inspection, using forecasting models if the model has been fulfilled will be evaluated using MAPE until the results come out 14875.593875 to be able to predict the next buyer demand.