Advance Sustainable Science, Engineering and Technology
Journal title Advance Sustainable Science, Engineering and Technology (ASSET) Initials ASSET Abbreviation ASSET Frequency 4 issues per year (April, July, October, January) DOI Prefix 10.26877 by ISSN 2715-4211 (online) Editor-in-chief Mega Novita, S.Si., M.Si., M.Nat.Sc., Ph.D Publisher Science and Technology Research Centre Universitas PGRI Semarang Citation Google Scholar | Garuda | Dimensions Advance Sustainable Science Engineering and Technology Now available at OJS 3
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Spatial Analysis of the Level of Accessibility of the Bobo Village Community in the Lore Lindu National park Area
This research aims to determine the level of community accessibility in the Lore Lindu National Park Conservation area and determine the level of community accessibility in reaching areas that have been selected based on the provisions of the Cooperation Agreement (PKS) between Lore Lindu National Park and the Bobo Village Government in 2021. This research uses spatial analysis with five variables: land use, slope, and distance from roads, rivers and settlements. Determining the weight of each variable uses the Analytical Hierarchy Process (AHP) method with sources from the Bobo Village community and the Bobo Village Conservation Management Institute. The research results show that with the AHP method, land use has a significant effect on the level of community accessibility with a weight of 52.3%, followed by other parameters, namely slope of 26.8%, distance from the main road of 11.3%, distance from the river is 3, 4%, and distance from settlements is 6.2%. Furthermore, three classes of accessibility levels for the Bobo Village community were obtained: low level covering an area of 390.94 ha (96%), medium level covering an area of 17.76 ha (4%) and high level surrounding an area of 0.11 ha. (0%).
Copyright (c) 2024 Advance Sustainable Science, Engineering and Technology (ASSET) https://creativecommons.org/licenses/by-sa/4.0
Optimization of Biogas Liquid Waste from Livestock Manure as a Source of Renewable Energy through Microbial Fuel Cell (MFC) Technology
This study examines the potential of biogas effluent as a source of electrical energy through microbial fuel cell (MFC) technology. The results showed that the one-room MFC produced a maximum voltage of 1302,2 mV, while the two-room MFC with KMnO4 electrolyte reached 1084,3 mV with an electric current of 0,1 mA. Simultaneously, the two-chamber MFC with K2Cr2O4 produced a maximum voltage of 1675,8 mV and an electric current of 0,99 mA. This potential, with electrical voltage values equivalent to commercial batteries, can improve the efficiency of electrical energy generation from organic waste and open up wider application opportunities in using renewable energy sources. Characterization of the MFC substrate showed a decrease in organic matter of biogas effluent with COD values of 500,96 mg/L and BOD of 300,23 mg/L. MFC bacteria from biogas waste were dominated by Gram-positive rod-shaped and Sarcina, except for one Gram-negative isolate of Spirillum.
Comparing Optimizer Strategies For Enhancing Emotion Classification In IndoBERT Models
Emotions are one of the reactions of human when they receive physical or verbal action. Every human action is based on emotion. Every opinion expressed in the comments column also contains the author's emotions. This research aims to classify five emotions, Marah, Takut, Senang, Cinta, and Sedih and evaluate the performance of three commonly used optimizer, Adam, RMSProp, and Nadam. The processed data used IndoBERT model for Indonesian text classification. The research purpose to search the best optimizer for text classification. The result shows classification used Adam Optimizer 90,21%, RMSProp Optimizer 82.11, and Nadam Optimizer 88.61%. The Adam optimizer applied to the IndoBERT model yielded the best results. This shows a significant improvement from previous studies, which had emotion classification.
Copyright (c) 2024 Advance Sustainable Science, Engineering and Technology https://creativecommons.org/licenses/by-sa/4.0
Implementation of Data Layer In Blockchain Network Using SHA256 Hashing Algorithm
The escalating demand for secure data management in blockchain systems has prompted the exploration of advanced cryptographic techniques. Leveraging the SHA256 hashing algorithm, this implementation aims to fortify data integrity, confidentiality, and authentication within the blockchain network. By meticulously examining the algorithm's application, the research demonstrates its efficacy in ensuring tamper-resistant data storage and retrieval, quantifying improvements in security percentages and specific metrics. The integration of SHA256 within the data layer is explored in technical detail, highlighting the concrete benefits of heightened security and immutability. The analysis discusses practical implications and delves into potential advancements in blockchain technology, offering valuable insights for researchers, developers, and practitioners seeking to bolster the robustness of data layers in blockchain networks.
Aspect-based Sentiment Analysis on Electric Motorcycles: Users' Perspective
Electric Vehicles (EVs) adoption is emerging especially electric motorcycles due to their lower price. Research has shown that the majority of people have positive sentiments towards EVs but most of the sentiments were from people who did not already own or use EVs, but rather from people who reacted / commented towards a product that is recently being launched/announced. This research aims to evaluate users' opinions regarding the positive and negative aspects of electric motorcycles they had purchased / used. This information will be beneficial for the manufacturers and marketers as an evaluation for their products; and it is also beneficial for prospective buyers as a buying consideration. This research uses Aspect-Based Sentiment Analysis applied on 844 electric motorcycles review data from www.bikewale.com website. Results showed that the notable positive sentiments are related to smooth riding experience and low maintenance. Whereas notable negative sentiments are related to poor build quality and product malfunctions. The other aspects of electric motorcycles received mixed sentiments such as related to vehicle speed and customer service. The research findings, limitations, and future research direction are discussed.
Identification Of Chatbot Usage In Online Store Services Using Natural Language Processing Methods
Chatbot is one of the implementations of artificial intelligence in helping human tasks. The way the chatbot itself works is to answer questions directly according to the database that has been created. Chatbot helps online store owners answer questions from the same customers so that there is efficiency in terms of employee salaries. 40 questions that are often asked by customers to the online store admin. In its use, chatbot is one of the implementations of machine learning, where the function of machine learning itself is to improve the ability of machines to learn new information from data and develop the ability of machines to solve problems. Machine learning requires instruction from training data or input to teach machines how to solve problems, answer questions, and draw conclusions from the results of data processing. Furthermore, it is processed using Natural Language Processing (NLP). Natural Language Processing (NLP) is a branch of artificial intelligence that is able to study communication between humans and computers through natural language. The processing stages are identifying the intent, processing the input and displaying the results according to the input. Followed by testing the accuracy level. Then conduct testing using 40 question and answer data. Then obtained 36 answers that are appropriate and 4 answers that are not appropriate with the percentage of accuracy of the answers generated from the chatbot is 90 percent. The results of this test can answer the questions asked by customers. This chatbot can make it easier for customers to get information with a very good level of accuracy.
Implementation of the Adaboost Method to Increase the Accuracy of Early Diabetes Predictions to Prevent Death Decision Tree-Based
This research discusses the importance of early diabetes prediction and efforts to increase prediction accuracy using a Decision Tree Learning Algorithm and integration of the Adaboost Method. This study uses a data set from Kaggle with 520 records, 16 attributes, and one positive or negative diabetes class. The evaluation method used is the Confusion Matrix. The research results showed that the Decision Tree algorithm achieved an accuracy of 94.23%, but after integrating the Adaboost Method, the accuracy increased to 97.31%. The implications of these findings emphasize the importance of predictive approaches in early disease detection and highlight the potential of the Adaboost method in improving the accuracy of diabetes prediction.
Identification of Landslide Prone Areas with Schlumberger Configuration Geoelectric Method, Kalongan Village, East Ungaran in 2023
Landslides are one of the natural disasters that occur in Semarang Regency. The landslide event in Kalongan Village, East Ungaran Subdistrict took place in 2022 to 2023. The dimension of the landslide is large and has the potential to cause damage to infrastructure and settlements, mitigation measures are needed. One of the mitigation measures is to identify the lithology of the landslide area and its surroundings. This study aims to determine the lithology of the landslide area and its surroundings using the Schlumberger configuration geoelectric method. Geoelectric acquisition using a set of naniura geoelectric, with a line variation of 120 to 300 meters. The number of measurement lines is 6 VES located in the landslide zone in the Kaligetas Formation. The results showed that the avalanche zone is composed of Tufan Sandstone with a resistivity of 0.17 Ωm to 334.9 Ωm, Tuff with a resistivity of 10.03 to 26.96 Ωm, and Lava Flow with a resistivity of 1161.91 Ωm to 3040.05 Ωm. Avalanche materials were identified to be associated with lithologies such as tufan sandstone and tuff with a thickness between 5 to 50 m.
Enhancing Web Server Security against Layered Cyber Threats in Healthcare
Information technology plays an important role in improving operational efficiency at Torabelo Hospital. The server system in use today faces security and optimization challenges. This research analyzes the impact and recommends solutions to improve server security and optimization. The findings show that the server system is vulnerable to various types of attacks and performance degradation. This can negatively impact hospital operations and put patients at risk. The recommended solution is to implement Squid as reverse proxy, WAF (Web Application Firewall), and Snort as IDS (Intrusion Detection System). System testing showed that this solution successfully detected and prevented various common attacks. This research provides insights to health IT professionals to improve the security and performance of their server systems and improve healthcare services to patients at Torabelo Hospital.
Implementing Blockchain For Publishing and Verifying Digital Certificates On EduTech
This study investigates the application of blockchain technology in enhancing the security and authenticity of digital certificates. Addressing key challenges such as fraud and the lack of a standardized verification process, the paper proposes a comprehensive framework aimed at fortifying the integrity of digital credentials. This framework is the utilization of blockchain as a distributed ledger, serving as a tamper-proof repository for recording certification transactions. Through this decentralized ledger, each certification issuance and verification action is securely recorded, enhancing trust and transparency in the certification process. The methodology includes the integration of a decentralized ledger for immutable record-keeping and implementation of smart contracts for automated authenticity checks, and the use of cryptographic measures to ensure data security. This approach promises significant implications for various sectors reliant on credential verification, advocating for a broader adoption of blockchain in digital certificates systems.
Wina Sentosa Bottled Water Distribution System Using Web-Based Distribution Requirement Planning and Trend Moment Algorithms
This research focuses on the problem of PT Anugrah Wina Sentosa, which is a producer of bottled drinking water in Central Sulawesi. The company faces challenges in organizing and improving the efficiency of the distribution of bottled drinking water products. Problems include distribution management that has not been optimized and distribution arrangements at various outlets that have not been mapped. Based on this problem, researcher develop a web-based distribution system with the Distribution Requirement Planning (DRP) algorithm and Trend Moment Algorithm to see the results of sales and distribution predictions. The designed application can carry out data processing, Distribution Requirement Planning processes, Trend moment processes, MAPE calculations, and sales predictions. The application development method uses the Waterfall method. The test results show that the system can manage input, edit, and delete data and run DRP calculations as a whole or per outlet. With an error value of 1.71%, the trend moment forecasting system proved to be very accurate in forecasting sales of drinking water products. Thus, the implementation of a web-based distribution system can improve production efficiency and facilitate stock management and distribution management at PT Anugrah Wina Sentosa. This research has several limitations that need to be considered, namely limited scope, limited data, limited generalization, limited affordability, and limited time.
Supplier Selection Modeling and Analysis in the Metal Casting Industry Using Analytical Hierarchy Process
This study presents a supplier selection problem of a raw material using an analytical hierarchy process. In the existing process, the delivery of raw materials experienced delays and impacted the production process. Therefore, this paper aims to determine the criteria for supplier selection and provide recommendations for the best vendor to be selected from the last request for quotation document. Analytical Hierarchy Process (AHP), as a multi-criteria approach, was utilized in this research, starting from determining criteria, the weight of criteria, and the final score for each supplier. Through discussions with the company's expert, procurement department, and users, as well as a review of the previous studies, this research defined three criteria, each consisting of three sub-criteria. The AHP approach was utilized to evaluate and determine the weights for the three criteria, yielding the following results: quality (62%), price (28%), and delivery (10%). The identified criteria, sub-criteria, and respective weights are subsequently utilized in a supplier selection scenario. Three suppliers of mild steel raw materials were evaluated using the weights of the criteria and sub-criteria obtained. Supplier 1 was selected because of having the higher alternative value of 0.602. The use of AHP in supplier selection is often impractical and contains subjectivity. Therefore, further research can be performed by integrating AHP with other methods, such as weighted scoring, to facilitate further the vendor selection process and integration with other methods, such as fuzzy logic, to reduce subjectivity.
Prediction of the Birth Rate of Babies at Regional Hospitals in Salatiga City Using the Naive Bayes Algorithm
Birth rates have a significant impact on population growth and large populations can be a burden on development. In the Salatiga City Regional Hospital, the numbers tend to change every year, with the current population density making it a special concern for the City of Salatiga. Therefore, it is hoped that the application of Data Mining Techniques with the Naive Bayes algorithm can help predict the number of births in the future using the RapidMiner Application. In this research, the population used was Population Data from Salatiga City with a total of 989,674 residents. Then the sample used was 4699 babies from the Salatiga City Regional Hospital. All data was taken from 2019 - 2023 by conducting observations, literature studies and documentation. By analyzing the pattern of each variable and testing the training data against the testing data, a calculation was produced which shows the Testing Data Prediction, namely the "High" label with the number 4.77192E-06, with this the predicted result of the Baby Birth Rate in the Salatiga City Regional Hospital which is influenced by Population Density in 2024 it will be even higher.
Development of Website-Based Stunting Prevention Educational Media Services (Case Study: UPT Puskemas Tirto Pekalongan)
UPT Puskesmas Tirto is a public health center located in the West Pekalongan sub-district that provides maternal and child health poly services. This poly provides educational services related to the problem of stunting in children through Posyandu activities. However, providing educational services is less effective and efficient because some parents do not have much time to attend counseling so information is not conveyed properly. This research aims to optimize the provision of educational services to parents, prospective mothers, and young women through the use of information technology by developing a website-based stunting prevention educational media service using the ReactJs framework. The development process of this research is carried out by prototyping method. Based on the results of testing using the Blackbox method, it shows that the main features such as nutrition check services, consultation services with Puskesmas nutritionists, and literacy services in the form of articles in the application can run well according to their functions in providing stunting prevention information with 100% results.
Utilizing Data Mining Techniques to Analysis Changes in Purchase Behavior of Batik's Customers
Sales transaction data contains rich information potentially used to support company competitiveness. However, interpreting and utilizing transaction data in developing marketing strategies remains a challenge, even for big companies. Therefore, this research aims to develop marketing strategies using data mining techniques. A medium-sized company focusing on producing and selling traditional motif clothes (batik) will be used as a case study. The negative sales trend is the biggest issue currently faced by the company. Hypothetically, this problem is caused by imported products sold at lower prices or changing consumer behavior after pandemic covid. Currently, the company only implements simple analysis of its transaction data. The analysis of transaction data, conducted through five data mining stages, yielded a shift from purchasing small quantities to larger quantities, increased purchases during the final week of each month, and increased purchases on religious occasions. Furthermore, the analysis revealed that 31.29% of all transactions were attributed to loyal consumers, and 192 customers exhibited in Cluster 1 (high transaction quantities and high transaction values). Further investigation also revealed that customers categorized as loyal customers and Cluster 1 have different behaviors that can be used to develop further customer relationship programs. Future research can be conducted by employing data mining techniques to study the organization's assortment of products. Management discussions reveal that changes in consumer buying behavior extend to the selection of items and batik themes.
Meta Insights: Analyzing Hero Performance in Mobile Legends with K-Nearest Neighbors
This research presents a thorough statistical analysis of hero performance in the latest Mobile Legends meta, employing the K-Nearest Neighbor (KNN) algorithm. Utilizing diverse data sources, the study explores factors influencing hero success, leveraging KNN's ability to identify intricate patterns in complex datasets. Through meticulous data collection, preprocessing, and application of the KNN algorithm, the research classifies and predicts hero performance based on similarities with neighboring heroes. Critical determinants such as win rates, popularity, and hero ban rates emerge, providing profound insights into gameplay strategies. The study emphasizes the importance of understanding meta dynamics, hero attributes, and player expertise for informed decision-making in hero selection within the dynamic landscape of Mobile Legends.
Project Delay Factor Analysis Using Fault Tree Analysis (FTA) Method and Rescheduling with Critical Path Method (CPM) in Ducting Manufacturing Projects at PT. FRA
Ducting manufacturing project at PT. The FRA was planned to be completed in 14 days, but was implemented in 19 days and 5 days late. The method to find the cause of project delays is Fault Tree Analysis (FTA), then analyze rescheduling with the Critical Path Method (CPM). The purpose of this study is to identify factors of work delay, determine new steps for project contractors and reschedule with alternative working hours and labor additions. The results of the analysis using the FTA method obtained the main cause of delay in drawing engineering work of 0.0002592 and obtained 4 new steps for project contractors. The results of rescheduling using the CPM method obtained a percentage increase in productivity with the alternative of adding working for 4 hours with a duration of 25% or 6 days faster than the normal duration of 19 days to 13 days and an additional cost of 91.96%, which is Rp. 21,500,000. While the percentage of productivity increase with alternative labor additions with a duration of 38.75% or 5 days faster than the normal duration of 19 days to 14 days and additional costs of 178.57%, namely Rp. 31,200,000. So it can be concluded by using the FTA method the main cause is drawing engineering work and 4 new steps are obtained and using the CPM method alternative scheduling is obtained to increase overtime work hours more effectively and additional costs are not too large, so that the company does not experience delays for future ducting projects.
Protein Concentrate From Tuna Head Waste Using Methanol-Acetone Solvent Extraction
The frigate tuna (Euthynnus affinis) is known for its high protein content in the head, making it suitable for the production of protein concentrate used in animal feed. This research aims to investigate the influence of adding a methanol-acetone mixture solvent, the duration of the extraction process, and the protein content in the resulting concentrate using the Kjeldahl method. The protein concentrate is produced through the maceration extraction method, where 30 grams of the frigate tuna head sample is mixed with a methanol-acetone solvent in various ratios (1:9; 3:7; 5:5; 7:3; 9:1) at a temperature of 50 °C and a stirring speed of 500 rpm, with extraction times ranging from 2 to 6 hours. Subsequently, filtration is performed, and the precipitate is dried using an oven at 100 °C for 30 minutes. The dried sample is then subjected to protein content testing using the Kjeldahl method. Research results indicate that both protein content and extraction yield values increase with the duration of the extraction process, while the water content decreases. The optimal result in maceration extraction is achieved with the methanol-acetone mixture (9:1) treatment and a 6-hour extraction time, yielding a protein content of 89.15 %, water content of 5.57 %, and an extraction yield of 23.86 %.Protein concentrate can be used as animal feed to increase protein needs. Animals that are given sufficient protein will fatten and make the animal healthy
MERN Implementation in Online Quiz Applications to Recognize and Avoid Social Media Hoaxes
Social media makes it easier for people to get information on the internet by allowing them to do more than just consume it. They can also create, comment on, and share content in different formats. False information that has permeated society can be readily ingested and used as a source of reference. A JavaScript application developed with the MERN stack technology, which combines several technologies—MongoDB, ExpressJS, ReactJS, and NodeJS—all functioning with one programming language. Data from numerous relevant research sources is gathered using qualitative approaches, and the Scrum method is employed to construct the application system. In addition to fostering creativity and innovation, this approach can resolve challenging and adaptive challenges. There is a maximum duration for every Scrum event. Once a sprint has begun, it cannot be stopped or shortened. Another event may be called off if its objectives have been fulfilled. The purpose of this study is to develop a website that offers pertinent tools and data to social media users in an attempt to stop the spread of hoaxes and fake news. The achieved result is that this application provides various quizzes designed to test users' knowledge of hoaxes and online scams.
Analysis of Improving the Quality of Fatty Acid Methyl Ester (FAME) Products Against Acid Value (AV) Levels Using the Six Sigma and Kaizen Methods
. PT XYZ is a palm oil derivative processing company that produces biodiesel / FAME (Fatty Acid Methyl Ester) products. However, there are several obstacles that still occur during the company's production process which causes the acid value (AV) level of FAME products to not meet specifications and there are 3% defective products. Therefore, this study aims to determine the improvement plan by applying kaizen to the Six Sigma improvement stage and reducing outspec products in the FAME production process. The results of the research conducted using the six sigma method show that the company has a DPMO value of 71,459 and a sigma value of 2.96 which is in the average position of the industry in Indonesia based on the results of data processing. While recommendations for improvement by implementing kaizen include training machine operators, making standard operating procedures (SOPs) for machine inspections on each shift, reducing the amount of strearin added to AV raw materials before pre-treatment, maintenance and machine calibration. This step are expected to overcome the main problems identified in the study.
Optimizing Sample Warehouse Layout At PT BIJ: Comparative Study Of Dedicated And Class-Based Storage
PT. BIJ is an analytical laboratory services company, therefore PT. BIJ needs a good warehouse to be able to accommodate the samples it has PT. BIJ experienced problems with sample storage. Therefore, it is necessary to improve the sample storage system to make it easier to find samples to be analyzed. Using the Dedicated Storege and Class Base Storage methods will help provide grouping for each type of sample and place the samples in the right place so that the sample travel distance is shorter. The results of the research carried out can be obtained that the initial travel distance is 262.98 meters, while the proposed dedicated storage distance is 163.19 meters and the proposed basic class storage distance is 149.95 meters, so there is the largest percentage difference of 42.89%. So it can be concluded that using the class base storage method is better than the dedicated storage method.
The Analysis of Habitat Suitability for Macaca Tonkeana in the Pangi Binangga Natural Reserve of West Toboli Village Using SIG and PCA Approach
The boti monkey, also known by its scientific name Macaca tonkeana, is a type of endemic primate found on Sulawesi Island. This study aims to determine the suitability of Macaca tonkeana habitat by using spatial analysis methods to determine the most suitable areas for survival. The study used a sample of locations conducted by observation method. The data collected was then spatially analysed by overlaying, classing, weighting, and scoring. PCA analysis was used to classify variables and assign weights to each parameter. Based on the habitat suitability model developed, the study sites were classified into three suitability levels: low, medium and high. Low suitability with an area of 9.475621 ha (0.374%). Medium suitability with an area of 461.777729 ha (18.184 %). High suitability with an area of 2065.896076 ha (81.442%). The model validation showed that most of the validation points were located within the high suitability class, with 92.59% of the total validation points. This indicates that the study site is likely to be a highly suitable habitat for Boti Monkeys.
Sustainability Strategies of Traditional Vannamei Shrimp Cultivation in East Java: A Case Study in Kudu Hamlet, Lamongan District
The research investigates small-scale farming practices, particularly vannamei shrimp cultivation, in Kudu Hamlet, focusing on how traditional farmers have adopted technology over two decades. Conducted over two years, the study sampled 17 farmers out of 38, analyzing various variables such as age, education, and economic factors. Farmers, predominantly older, have engaged in shrimp farming for nearly two decades, despite fluctuating incomes. Education levels vary, impacting farmers' understanding of new technologies and market trends. Most farmers own their pond land, managing it carefully for shrimp cultivation. Polyculture systems, combining vannamei shrimp with other species, enhance productivity but face challenges like disease outbreaks and market price fluctuations. The choice of feed, predominantly artificial, significantly affects shrimp yields. Farmers also engage in side jobs to supplement income. Overall, enhancing farmers' capacity through education and sustainable practices is crucial for the long-term viability of shrimp farming.
Design of a Mobile-Based Wedding Information and Booking System using Backend as a Services (BaaS) on android platform
Nowadays, wedding organizer services have become a necessity in wedding events. However, it is often found that bookings are made manually to the vendor's location which results in impracticality. This research aims to build an application that brings practicality in the field of wedding organizers. Later this application has an online booking function carried out by wedding bookers and can establish communication with vendors in making wedding bookings. The focus of the research is to provide practicality to bookers and vendors. This research uses the Case Study method, interviews and observations conducted at Omah Kebon Resto as a case study. The application was built based on Android with Cloud Baas services on the Firebase platform for database management. The final evaluation was carried out by distributing questionnaires to respondents for the level of satisfaction of using the application built. The results stated that 37.12% of respondents were very positive, 45.41% stated positive, 13.54% stated neutral, and 3.93% stated negative. So, it can be concluded that respondents feel positive if this application can help practicality in getting information and booking wedding organizer vendors.
Portable Low-Cost Home Sleep Monitor using Wemos D1 Mini
Sleeps disorders are a common disease overlooked by many people. Sleep disorder have many types and kinds and often associated with other severe illness such as diabetes, stroke, obesity and many others. Sleep monitors are one of many ways to read all parameters related to sleep and detect sleep disorders the subject has, however access to sleep monitor still expensive and tough to come by. Because of that accessibility, countless development of home sleep monitor occured around the world. However, most of that device still hard to operate and some of them gives error readings of parameters. Based on this, a portable low-cost home sleep monitor was developed using Wemos D1 mini as a microcontroller, MAX30102 as an oxygen level sensor, MPU6050 as an accelerometer, DS18B20 as a breathing flow sensor, and MAX9814 as a microphone. Each of the sensors read and give value to microcontroller and store the data to cloud and display the result in user's gadget. The aim of this development is to detect sleep disorders associated with each reading of sensors used and determine sleep quality as an early detection of symptoms before referring to professional relaled to sleep disorders or doctors.