D. Fadhilah, R. Purbaningtyas, Rifki Fahrial Zainal
{"title":"Disease Diagnosis System in Appel Plant Using Backward Chaining Method","authors":"D. Fadhilah, R. Purbaningtyas, Rifki Fahrial Zainal","doi":"10.54732/jeecs.v4i2.108","DOIUrl":"https://doi.org/10.54732/jeecs.v4i2.108","url":null,"abstract":"Apples are one type of food that contains nutrients, vitamins and minerals that are very good for consumption because it has antioxidants that are good for the body. However, in cultivating these apple plants there are many obstacles, especially when the plant is attacked by disease. Diseases that attack apple plants greatly affect fruit production, because it can produce bad fruit and can result in the death of apple trees. The disease attack can be resolved quickly if it is able to identify the type of disease that attacks it quickly and precisely based on the symptoms that appear. So that the impact can be minimized as early as possible. The purpose of this research is to build an expert system of diagnosing diseases in apple plants by using the backward chaining method that can facilitate in providing information about the causes of the emergence of diseases and how to deal with apple plants quickly and accurately. From the application trial results with the Expert Diagnosis System in Apple Plant Diseases Using the Backward Chaining Method, users can find out the symptoms of diseases experienced by apple plants and test results by making comparisons using the forward chaining method the results are the same as backward chaining accuracy level of 100 % input from backward chaining is the same as output from forward chaining.","PeriodicalId":273708,"journal":{"name":"JEECS (Journal of Electrical Engineering and Computer Sciences)","volume":"82 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114856010","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Online Based Academic Information System (case Study: SD. Hidayatur Rohman Asemrowo Surabaya)","authors":"Mustofa, R. Purbaningtyas, Rifki Fahrial Zainal","doi":"10.54732/jeecs.v4i2.110","DOIUrl":"https://doi.org/10.54732/jeecs.v4i2.110","url":null,"abstract":"The influence of technology is very large, especially in the development of information. Accurate, fast, and precise information is very important for life today because information becomes a necessity in conveying something. The use of computers is one of the developments in information that is very useful because it can perform data processing, making reports and sending information remotely and in determining the potential of students. Determination of the potential is absolutely necessary by the school agency, namely the school, the guidance teacher has an important role in granting status to students. Determination of student potential requires special professional handling, because it involves the success of students in facing the examinations that will be given. Mistakes in determining students' readiness to face national exams can negatively affect the process and results of student exams themselves. So we need a method that can help minimize the impact of mistakes when determining the potential of these students, namely by grouping data techniques from the results of data mining. The need for data mining becauseof the large amount of data that can be used to produce useful information and knowledge. Naïve Bayes is a machine learning method that uses probability calculations. The use of this algorithm is considered appropriate because Naive Bayesian Classifier is one classification algorithm that is simple but has high capability and accuracy.","PeriodicalId":273708,"journal":{"name":"JEECS (Journal of Electrical Engineering and Computer Sciences)","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122377485","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Reni Vivit Ayu Mawarti, Wiwiet Herulambang, R. Adityo
{"title":"Forecasting Omset Printing of Printing Sales in CV Sembilan Jaya with Neural Network Method","authors":"Reni Vivit Ayu Mawarti, Wiwiet Herulambang, R. Adityo","doi":"10.54732/jeecs.v4i2.111","DOIUrl":"https://doi.org/10.54732/jeecs.v4i2.111","url":null,"abstract":"Forecasting is a process for estimating several needs in the future which includes needs in order to meet thedemand for goods and services. Neural Network Backpropagation Method is a time series forecasting method. Thepurpose of this study is to predict the turnover results in the next period obtained by CV. Nine Jaya every week. Thisstudy uses sales data obtained from the printing of food boxes, shoe boxes, watch boxes from January 2014 toDecember 2018. The results of this forecasting are done using the Neural Network method, the smallest MSE valueobtained is 0.004211 with 1000 times iteration and learning rate 0.2. The MSE value obtained meets the condition orcondition value as a good forecasting method because it is able to meet the MSE value requirement <0.1.","PeriodicalId":273708,"journal":{"name":"JEECS (Journal of Electrical Engineering and Computer Sciences)","volume":"103 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115731399","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Decision Support System for The Feasibility of Giving Customer Credit Using Topsis and Saw Methods (case Study): Save Loan Cooperative CV. the Source of Prosperous Life","authors":"A. Nur, M. Hidayat, M. Hamidah","doi":"10.54732/jeecs.v4i2.115","DOIUrl":"https://doi.org/10.54732/jeecs.v4i2.115","url":null,"abstract":"Supporting System for Deciding the Feasibility of Providing Credit to Customers with Topsis Method andSimple Additive Weighting Method in CV. Sumber Hidup Prosperous, this research is motivated by the results of acustomer who must meet the criteria determined by the cooperative to be able to get credit. In this case cooperativesare required to be able to make decisions quickly and carefully. To realize this it is necessary to have a decisionsupport system (SPK) with the Topsis method and the Simple Additive Weighting method that can solve the problemof decision making with many criteria. The results obtained from this study are the application program of the DecisionSupport System for Providing Credit to the Customer with the Topsis Method and the Simple Additive WeightingMethod in CV. The Source of Prosperous Life. The conclusions of the results of this study have shown a value that isaccurate enough to help simplify the process of creditworthiness and report generation.","PeriodicalId":273708,"journal":{"name":"JEECS (Journal of Electrical Engineering and Computer Sciences)","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123563618","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Mobile-Based Nearby Mosque Determination System Application Using Particle Swarm Optimization (PSO) Algorithm In the Gayungan District","authors":"B. Santoso, Wiwiet Herulambang, M. Hidayat","doi":"10.54732/jeecs.v4i2.117","DOIUrl":"https://doi.org/10.54732/jeecs.v4i2.117","url":null,"abstract":"Public facilities related to religion one of which is the mosque. Mosque Is a place of worship for Muslimsworldwide. The city of Surabaya which incidentally is a tourist city that is often visited by foreign and local tourists,and especially the Muslims who want to establish prayer and need access to the location of the nearest mosque. Thereal condition that often happens is that tourists do not know the position of the closest mosque around them, so spendtime searching for the existence of the mosque. Particle Swarm Optimization Method is an algorithm that is inspiredby the behavior of a group of birds in a group to look for food. This method is one of the methods for searching theshortest distance. With this method, it can provide solutions to produce the closest location. From the tests carriedout, the Particle Swarm Optimization algorithm has been successfully applied to the search for the nearest Mosquelocation point and has successfully designed and built a nearby Mosque location search application based on AndroidMobile. By comparing with the euclidean distance algorithm the results of Particle Swarm Optimization show that70% accurately show the same results.","PeriodicalId":273708,"journal":{"name":"JEECS (Journal of Electrical Engineering and Computer Sciences)","volume":"65 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126758180","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Sound Calculation Simulation System for Distribution of Chair Parliament Using Hare Quota and Sainte Lague Methods","authors":"A. Pratama, A. Arizal, Syariful Alim","doi":"10.54732/jeecs.v4i2.114","DOIUrl":"https://doi.org/10.54732/jeecs.v4i2.114","url":null,"abstract":"The conversion of the ballot for the division of parliamentary seats has become one of the historical points inthe development of the democratic order in Indonesia. How not, through a plenary session, the DPR RI finally finalizesthe discussion and decision making on the Election Bill proposed by the government. Conversion of votes is one of thecrucial issues to get the word consensus in the House of Representatives, because the method of voting conversionused will greatly determine the acquisition of seats for a political party. For example, if using the quota method, aparty can get 5 seats, but it is not certain if the calculation method uses the Sainte Lague method, it could be that oneparty will get 4 to 6 seats. That is why the voting conversion method is one of the main variables of an electoral system.The method of converting votes is the procedure for calculating the results of elections to determine theacquisition of seats for political parties in representative institutions based on the results of the acquisition of validvotes of each political party participating in the election. The Hare Quota method is characterized by a calculationmethod using the Number of Voters Dividers (BPP) which divides the total number of valid voting votes by the numberof seats allocated to one particular constituency, and always has the remaining choice of votes that requirescalculation at the next stage for the remaining votes of choice / residual the chair is the Sainte Lague method (theremaining votes are voted on).","PeriodicalId":273708,"journal":{"name":"JEECS (Journal of Electrical Engineering and Computer Sciences)","volume":"50 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123079699","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Clustering for Searching Type of House Suitable for New Consumer Candidates Using K-Means Clustering Method (case Study of PT. Maxima Jaya Perkasa)","authors":"Azziyati, Eko Prasetyo, Wiwiet Herulambang","doi":"10.54732/jeecs.v4i2.116","DOIUrl":"https://doi.org/10.54732/jeecs.v4i2.116","url":null,"abstract":"For some Indonesian people, housing is one of the secondary needs, so that in choosing the right housingmust be in accordance with the wishes of consumers. With the existence of PT. Maxima Jaya Perkasa, which waspioneered since 2012, in which the data on housing sales in the company has increased rapidly each year. Then datamining analysis can be done using the K-means Clustering method. K-means Clustering is a method of clustering nonhierarchicaldata which seeks to partition existing data into two or more groups. This method partitioned the data intogroups so that the data with the same characteristics were entered into the same group and the data with differentcharacteristics were grouped into other groups. This study uses data such as salary income, age, status, house pricesand mortgage payments. The results of this study were conducted twice using 12 training data training data and 100training data plus 1 as test data and obtained an accuracy value of 83% and error of 17%.","PeriodicalId":273708,"journal":{"name":"JEECS (Journal of Electrical Engineering and Computer Sciences)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122514365","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Forecasting the Total Sales and Benefits of Drug Using the Single Exponential Smoothing Method (case Study: Bentar Pharmacy)","authors":"Sundariyah, R. Adityo, A. Arizal","doi":"10.54732/jeecs.v4i2.112","DOIUrl":"https://doi.org/10.54732/jeecs.v4i2.112","url":null,"abstract":"Forecasting is an important thing in corporate strategy planning. The Single Exponential smoothing methodis a time series forecasting method. The purpose of the research is to predict the number of sales of Enervon C drugsand the value of profits at the Bentar Pharmacies each month. The study used sales data for 3 years from January2015 to December 2017. The chosen alpha value was 0.5 by having a MAD value of 5.029360202. Forecasting resultsare carried out by the Single Exponential Smoothing method with the smallest error calculation results. MAD valueon the number of sales of Enervon Aktive 30s with α = 0.1 forecasting results 6.9118 with MAD of 7.363601841, α =0.2 forecasting results of 6.0622 with MAD of 5.375139148, α = 0.3 forecasting results of 5.7198 with MAD of5,375139148, α = 0.4 forecasting results 5,3421 with MAD of 5,121971763, α = 0.5 forecasting results 4,9617 withMAD of 5,029360202, α = 0.6 forecasting results 4,5888 with MAD of 5,04912007 , α = 0.7 forecasting results 4.2229with MAD of 5.206054971, α = 0.8 forecasting results of 3.8533 with MAD of 5.385531046, and α = 0.9 forecastingresults of 3.456869004 with MAD of 5.599237215. And the value of drug benefits obtained from forecasting results in2017 by comparing the actual benefits and the benefits of forecasting.","PeriodicalId":273708,"journal":{"name":"JEECS (Journal of Electrical Engineering and Computer Sciences)","volume":"153 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121309456","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Calculation of Android Based Eggtray Production Based Prices Using Moving Average Method (case Study of PT. Sinar Era Box Gresik)","authors":"Dani Marido, R. Purbaningtyas, M. Hamidah","doi":"10.54732/jeecs.v4i1.127","DOIUrl":"https://doi.org/10.54732/jeecs.v4i1.127","url":null,"abstract":"\u0000The price of the staple production based on activities is how to determine a fee by way of tracing the activities of an organization the company in generating an item. This is intended so that the largest cost breakfast buffet in producing goods itself. In addition the existence of a desire of the company to produce goods and costs as effectively as possible. Tracking the cost of these activities through automatic menegement parties can manage cost effectiveness. To find out the price of a staple production of PT.Sinar Era Box Gresik, then on the basis of the research that's going on. Research carried out using moving average algorithm (moving average), while the data is the data that comes from the PT.Sinar Era Box Gresik. This research resulted in the value of the production cost of goods based on the average price moves in can be of any purchase of goods. \u0000","PeriodicalId":273708,"journal":{"name":"JEECS (Journal of Electrical Engineering and Computer Sciences)","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127489279","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Tommy Ferdiansyah, Rifki Fahrial Zainal, A. Arizal
{"title":"Honda Motorcycle Stock Forecasting System Using Double Exponential Smoothing Method (case Study of Honda Dealer PT","authors":"Tommy Ferdiansyah, Rifki Fahrial Zainal, A. Arizal","doi":"10.54732/jeecs.v4i1.124","DOIUrl":"https://doi.org/10.54732/jeecs.v4i1.124","url":null,"abstract":"\u0000Stock in the warehouse of PT. Delta Sari Agung Sidoarjo is currently unstable, therefore between in and out stock is still out of control. Forecasting is estimating the state of the future through testing the state of the past. In social life, everything is uncertain and difficult to predict accurately, so forecasting is needed. In other words forecasting aims to get forecasting that can minimize forecasting errors (forecast error) which is usually measured by mean square error, mean absolute error, and so on. The Double Exponential Smoothing method is used for forecasting by determining the amount of α (alpha), as well as the smoothing process twice and this study is compared with ANNMatlab. From the results of the comparison of the trial system forecasting and JST-Matlab there is a difference of 16 motorbikes from the remaining stock, which is for the results of forecasting 622 and JST-Matlab 638 results. \u0000","PeriodicalId":273708,"journal":{"name":"JEECS (Journal of Electrical Engineering and Computer Sciences)","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116281274","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}