The application of artificial neural network for quality prediction of industrial standard water

Industrial Standard water is a source of water before being distributed in industry and household in a certain area. For the sake of health, quality water is a must to fulfill and control. Quality of water having several variables as indicators. One indicator, namely, Turbidity. It is defined as the level of cloudiness of water due to the presence of particles, mud or microorganisms. The highest of turbidity value meaning the index of water quality is low. In this study, we apply the Artificial neural network method for predicting the turbidity value. Three input variables are engaged, PH level, color spectrum, and electrical conductivity. As much of 827 data were collected during six months. Seventy percent are used for training and the rest thirty percent were used for testing. The ANN architecture consists of 3-6-1 configuration, 3 input variables, 6 hidden layers, and 1 output variable. The training was set into 1000 epoch and the MSE shows 0,0013, meaning that the ANN has the power of prediction. The prediction of turbidity level has a managerial implication as supporting information for purchasing decision of material in water processing

Condition of Hard Corals and Quality of The Turbid Waters in Spermonde Islands (Case Studies in Kayangan Island, Samalona Island and Kodingareng Keke Island)

Coral reefs in Spermonde waters have experienced degradation as a result of the increasing turbidity in these waters. This research was conducted on Kayangan Island, Samalona Island and Kodingareng Keke Island, Spermonde Islands, Makassar City. The purpose of this study was to determine the percentage of coral cover, types and the how much the turbidity of the waters influence the coral. The researcher measured the coral cover using Underwater Photo Transect and processed the data using CPCe software. The levels of turbidity were taken at three locations and examined in the laboratory and the other parameters were measured on site. The correlation between turbidity and coral cover was analysed by regression analysis method. Based on the regression results, the turbidity level has a negative effect on coral cover. The level of turbidity is higher on Kayangan Island with 0.89 NTU with a cover percentage of 4.95 %, Temperature of 30°C, Salinity of 30 ppm, DO of 5.44 mg/l, pH 7.8 and the species found were Porites and Faviidae. Samalona Island is 0.43 NTU with a percentage of coral cover of 14.08 %, Temperature of 30°C, Salinity of 30 ppm, DO of 5.44 mg/l, pH of 7.7 and the most common types are Acropora and Fungiidae. Kodingareng Keke Island has a turbidity value of 0.32 NTU, Temperature of 29°C, Salinity of 30 ppm, DO of 6.08 mg/l, pH 7.3 and the most common coral species, Fungiidae. Higher levels of turbidity in Kayangan Island will result in the death of certain coral species (unable to adapt) and will also have an impact on the percentage of hard coral cover.

SYSTEM PENDETEKSI KELAYAKAN KOLAM IKAN NILA MENGGUNAKAN METODE SAW (SIMPLE ADDITIVE WEIGHTING) BERBASIS IoT (INTERNET OF THINGS)

Tilapia (Oreochromis niloticus) is a type of freshwater fish consumption with elongated and flattened body shape laterally and blackish white color. Tilapia originated from the Nile River and surrounding lakes. Now this fish has spread to countries on five continents with tropical and subtropical climates. Whereas in cold climates, tilapia cannot live well. ideal water temperature in tilapia enlargement ponds ranges between 27.7-29.3 ° C, where fish will grow optimally at water temperatures around 25-32 ° C.for the pH of the tilapia enlargement ponds range between 6, 4-8.5 and turbidity range of 3-19 NTU, because this high turbidity level has an effect on the amount of tilapia mortality. With the system that the researchers created, it was easier to determine a suitable fish pond to maintain as a life of tilapia with the help of the Internet of Things network system and reduce the failure rate in breeding and implementation of Thingspeak as a platform to display the results of data obtained by sensors and calculated with method calculation. This system takes data with temperature sensors, pH and Turbidity, to find water temperature, acidity and alkalinity in water and turbidity of water. Then the data obtained is sent to the ESP8266 module network and sent to the thingspeak platform, the data that appears is inputted into the database to be processed using the SAW method, the results of the SAW method calculation are displayed by the system. Implementation of the SAW (Simple Additive Weighting) Method for Detecting the Feasibility of Iot-Based Fish Ponds (Internet of Things) has been successfully implemented. So that it can rank tilapia ponds based on parameters of temperature, pH, turbidity.

IDENTIFICATION OF WATER TURBIDITY WITH TURBIDITY SENSOR BASED ON ARDUINO

Water is an important need for all living things, especially humans. Humans need water with quality that meets the physical, microbiological, chemical, and radiological requirements contained in the mandatory and additional parameters. The selection of these parameters is very important to meet the requirements of good water, namely tasteless, odorless, and colorless. Meanwhile, there are three parameters used for water identification, namely pH parameters, turbidity levels, and temperature parameters. From these problems, the authors examine the detection of water quality, especially water turbidity. The author tries to make a tool that can detect the level of turbidity of water with a turbidity sensor as a detector of the level of turbidity in the water, Arduino Uno as a processor for the data results that have been detected, and a 16x2 LCD as a display of turbidity level measurement results in the form of turbidity values ​​and descriptions of the water being tested. The measurement range that can be detected by this tool is from 0 – 3000 NTU. The research method used is direct observation of the selected object, namely the author's home environment, and conducting library research related to the Arduino microcontroller. The purpose of this study was to determine and detect the level of water quality in the community. As one of the tools or alternatives for the community to find out or detect the level of water quality early.

Analisis Kelayakan Air Berbasis Android

This research was conducted to identify the test of the water quality which good for consumption. It can be proved from temperature, turbidity level, and TDS (Total Dissolved Solids). By tempting the sensor, the turbidity and TDS meter controlled with the Arduino uno and the MCU node is forwarded to send data to the bylink application. The bylink application will help in monitoring water conditions by displaying the water condition which fit for consuming. The method used in this research was started with making a prototype then producing data to determine the feasibility of water through the TDS sensor, temperature sensor, and NTU (water clarity). This indicators were developed on an Android system whom the user could determine feasibility water easier.

Automatic Aquarium Cleaner and Fish Feeder Based on Microcontroller Atmega8535

The design of an aquarium cleaner and automatic fish feeder based on the Atmega8535 microcontroller has been successfully carried out. Testing is carried out after all components are integrated into one including the overall program that has been made. Testing is done by running the system according to the procedure and observing the system's performance, starting with measuring turbidity and checking the water replacement schedule. The work processes running on the system are analyzed after testing. When the water turbidity level is high, the drain pump will activate and pump water out of the aquarium. After the remaining water level is about 25%, the drain pump will stop, and the filling pump will be active. The fill pump runs until the water level reaches 100% and then shuts down. After 10 minutes of filling the water, the servo motor will move and drop the fish feed into the aquarium.

1. The Sensitivity Level Of Gentamicine, Cholramphenicol and Penicillin Inhibiting The Growth Of Pseudomonas Aeruginosa Bacteria Isolate From Aceh Bull Prepunce

This study aims to determine the sensitivity level of gentamicin, chloramphenicol and penicillin antibiotics to inhibit the bacterial growth of P. aeruginosa taken from preputium isolate of Aceh cattle. This Stock of Pseudomonas aeruginosa isolate from Microbiology Laboratory of FKH USK, re-identified its purity through: indole test, methyl red test, sugar test and as well as on Nutrient Broth (NB) media; incubated at 37ºC for 24 hours; observed the turbidity level of 0.5 Mc Farland solution. Then, the antibiotic sensitivity test was carried out using the method of Mueller Hinton Agar (MHA). The observations were made by measure the inhibition zone using the calipers in millimeters (mm) against antibiotics. The results of the observation of the inhibition zone on the gentamicin antibiotic was averaged of 25.5 mm, 23.7 mm chloramphenicol, and 12.1 mm penicillin. This study concluded that the gentamicin, chloramphenicol, and penicillin antibiotic were still effective against P. aeruginosa bacteria with the highest level of sensitivity seen in gentamicin antibiotic.

Rancang Bangun Alat Ukur Kekeruhan Air Menggunakan Fototransistor dan LED Inframerah Berbasis Arduino Uno

In this research, the water turbidity measurement tool based on Arduino Uno has been designed and built using phototransistors and infrared LEDs. This measuring instrument consists of a series of infrared sensors, Arduino as a process, LCD I2C as a value viewer, Micro SD as a data storage, and RTC as a timer. This study used two water samples with various concentrations. The sample used, namely distilled water plus impurities in the form of soil and ash. The distilled water used is still 100 ml with variations in the concentration of impurities ranging from 0,1-0,9 gr. Sensor test results show that the greater the turbidity level, the greater the voltage obtained. Sensor scanning ranges from 2,02 V-4,00 V for groundwater and 2,02 V-4,31 V for ash water. The reading uses a standard measuring instrument for groundwater ranging from 0 NTU to 331,4 NTU, while for ash water ranging from 0 NTU to 284,4 NTU. Data from the sensor test results in an equation used to convert the artificial measuring instrument's voltage value into a turbidity value. Then, data is taken using the same sample, so groundwater's turbidity value was obtained from 0 NTU to 318,94 NTU while for ash water from 0 NTU to 285,13 NTU. Based on the results, average accuracy for water was obtained. Soil amounted to 94,66%, while for ash water was 96,63%.

Efektivitas Berbagai Media Pasir Lokal Sebagai Media Filtrasi Air Baku Menjadi Air Untuk Kebutuhan Higiene Sanitasi

Meeting the needs of clean water services in the community requires innovation with appropriate technology by developing groundwater or well water treatment (filtering) which has a high turbidity level so that clean water is obtained with quality that meets health requirements The water processing (filtering) is the Water Well Submerged Filter by using filter media, namely sand, gravel, activated carbon, and fibers. The purpose of this study was to determine the ability of the immersed water filter to reduce water turbidity, Fe, Mn content and total coliform. This type of research is experimental with the design of One Group Pretest-Posttest Design. The results showed that the immersed water filter was effective in reducing turbidity and Fe content in the water, while the immersion filter's ability to reduce the Mn content and total coliform was not effective. It was concluded that the Up Flow Sand Filter in which A filter with sea sand media, B filter with land sand medium and C filter with sea sand media effectively reduced the turbidity and manganese levels, while the total coliform for and E. coli still exceeded the required quality standards. Further research needs to be done on the effect of varying media thickness and finer diameter in order to reduce colform and E. coli effectively

The Virtual Lock-in Amplifiers - Accuracy of Measurement Results in Light Transmission Experiments

This research focuses on the analysis of the measurement result of the virtual lock-in amplifier (virtual-LIA) in the light transmission experiment as the trial step of developing the virtual-LIA. The virtual-LIA used in this research is designed by using the Vernier sensor DAQ as the data acquisition and the LabVIEW as the programming media. The design of virtual-LIA is based on the mathematical operations of LIA. The type of virtual-LIA is a single phase with the capabilities to process the external reference signal. Light transmission experiments are carried out using formazin polymer suspension with turbidity level of 3000 NTU, 3500 NTU, and 4000 NTU as the medium in which light is passed. The accuracy of the measurement results is known by comparing the results of virtual-LIA with real-LIA SR510. The experiments are also carried out in bright and darkroom conditions to determine the ability of virtual-LIA in reducing noise signals. Based on the experiment, the results obtained that the measurement accuracy of the virtual-LIA developed is above 94% compared to the LIA SR510. Virtual-LIA could measure small signals with and without noise with the average percentage of differences measured between dark and bright conditions is 0.54%.