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Rifki Fahrial Zainal
Universitas Bhayangkara Surabaya
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering

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Disease Diagnosis System in Appel Plant Using Backward Chaining Method Rifki Fahrial Zainal; Rani Purbaningtyas; Dina Zahrotul Fadhilah
JEECS (Journal of Electrical Engineering and Computer Sciences) Vol. 4 No. 2 (2019): JEECS (Journal of Electrical Engineering and Computer Sciences)
Publisher : Fakultas Teknik Universitas Bhayangkara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54732/jeecs.v4i2.108

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.
Online Based Academic Information System (case Study: SD. Hidayatur Rohman Asemrowo Surabaya) Rifki Fahrial Zainal; Rani Purbaningtyas; Mustofa
JEECS (Journal of Electrical Engineering and Computer Sciences) Vol. 4 No. 2 (2019): JEECS (Journal of Electrical Engineering and Computer Sciences)
Publisher : Fakultas Teknik Universitas Bhayangkara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54732/jeecs.v4i2.110

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.
Honda Motorcycle Stock Forecasting System Using Double Exponential Smoothing Method (case Study of Honda Dealer PT Tommy Ferdiansyah; Rifki Fahrial Zainal; Arif Arizal
JEECS (Journal of Electrical Engineering and Computer Sciences) Vol. 4 No. 1 (2019): JEECS (Journal of Electrical Engineering and Computer Sciences)
Publisher : Fakultas Teknik Universitas Bhayangkara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54732/jeecs.v4i1.124

Abstract

Stock 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.
Design of Mental Disorder Consultation System with Decision Tree Method Ahmad Sarif Hikmawan; Eko Prasetyo; Rifki Fahrial Zainal
JEECS (Journal of Electrical Engineering and Computer Sciences) Vol. 4 No. 1 (2019): JEECS (Journal of Electrical Engineering and Computer Sciences)
Publisher : Fakultas Teknik Universitas Bhayangkara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54732/jeecs.v4i1.126

Abstract

level or category of disorders suffered by patients, so patients can be dealt with quickly according to the level of the disorder they suffer. Diagnosing the level of mental disorders using the expert system will record the symptoms of the patient and will diagnose the level of the disorder based on the knowledge obtained from an expert, the mental disorder expert system uses the Decision Tree method. in general is a system that seeks to adopt human knowledge to computers, so that computers can solve problems as they are usually done by experts or before consulting a psychologist without reducing the expert role of the psychologist or in other words expert systems are systems that are designed and implemented with help certain programming languages to be able to solve problems as experts do quickly and efficiently. It is hoped that with this system, lay people can be more sensitive in recognizing the level of psychiatry in person. As for the experts of this system can be used as an assistant or supporting the performance of psychologist officers. Based on the results of the system tests that have been done, the accuracy of 97.5% results and system error 2.5% and the percentage of each diagnosis, 32% psychosis, 27% Neurosis, 17% Learning Soldered, 12% Juvenile Delinquency and Growth Flower 10%.
Realtime Portable Music's Genre Classificator with The Kohonen (SOM) Methods Using Raspberry PI Wiwiet Herulambang; Rifki Fahrial Zainal
JEECS (Journal of Electrical Engineering and Computer Sciences) Vol. 3 No. 2 (2018): JEECS (Journal of Electrical Engineering and Computer Sciences)
Publisher : Fakultas Teknik Universitas Bhayangkara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54732/jeecs.v3i2.131

Abstract

Music genre is one of the digital music data that is determined to classify music based on all the characterequations of each type. The characteristics in question are usually seen from the frequency of music, rhythmicstructure, instrumentation structure, and harmony content that the music has. Classification of music genres inrealtime (automatic / not manual), giving effect to the classification is no longer relative / subjective, because itis done based on predetermined parameters. In this study Raspberry Pi microcomputer is used, which is quiteconcisely used as a portable media and is quite powerful for realtime data processing. Raspberry Pi is used as asound processing unit, music genre identifier, and information on the results of the introduction of the musicgenre. This system input is in the form of music sound (realtime), while the system output is information (text)about the music genre. Whereas for the process of recognizing the music genre, the Self Organizing Maps (SOM)type Neural Neural Network (JOM) method is also used, or also known as the Kohonen ANN Network. Thefeature extraction stage uses the Music Genre Recognition by Analysis of Text (MUGRAT) method, with ninefeatures related to the spectral surface of music, and six features related to beat / rhythm of music. MelFrequency Cepstral Coefficients (MFCCs) feature extraction process was carried out as input from theclassification process using the Self Organizing Map (SOM) method. The classification results using the SOMmethod give an accuracy value of 74.75%. Accuracy of classification results using training data as many as 400pieces which are divided into 4 musical genres amounting to 74.75%.
Shoes Sales Forecasting Using Autoregressive Integrated Moving Average (arima) (case Study UD.Wardana Mojokerto) Achmad Kiki Qushayri Wahyu Kusuma; Eko Prasetyo; Rifki Fahrial Zainal
JEECS (Journal of Electrical Engineering and Computer Sciences) Vol. 3 No. 2 (2018): JEECS (Journal of Electrical Engineering and Computer Sciences)
Publisher : Fakultas Teknik Universitas Bhayangkara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54732/jeecs.v3i2.134

Abstract

Shoes sales is increase of day by day along with growing trend in the society. This makes shoemanufacturers demand to fulfill the customer needs. UD. Ward as one of the shoe manufacturers in Mojokertocity trying to fulfill the customer needs efficiently in order that the make sales fit with production. To predictsales of shoes used Autoregressive Integrated Moving Average (ARIMA) method. ARIMA forecasting method isone of methods that According to historical data. Before go into the forecasting stage, differentiated the salesdata per day during the year 2015-2016 ACF and PACF formula used Whose function is to Determine the valueof p and q coefficient of the which will later be used in forecasting models in every formula that is AR , MA andARMA. Result of this research shows that for the marching band category Obtained the best models that is MAwith forecasting the result at the last period of 95.6432 and MSE of 472.4514. Obtained fashion category for thebest models of forecasting that is AR with the result at the last period of 57.1872 and MSE of 304.8306. Obtainedcategory for the best wedding that is AR models with forecasting the result at the last period of 21.4206 and MSEof 118.0681.
Real Time Monitoring System Eggtray Production Process PT.Sinar Era Box Gresik Muhammad Rosyid Kurniawan; Rifki Fahrial Zainal; R Dimas Adityo
JEECS (Journal of Electrical Engineering and Computer Sciences) Vol. 3 No. 1 (2018): JEECS (Journal of Electrical Engineering and Computer Sciences)
Publisher : Fakultas Teknik Universitas Bhayangkara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54732/jeecs.v3i1.140

Abstract

PT. Sinar Era Box Gresik does not yet have a production process information system, so that all activities of production process process have not been well accommodated, for example production data file such as raw material mixing data, HPP (Cost of Production), production cost, raw material stock, production stock. Coordinator in data entry all aspects also not terakomodir well, and also data entry is still done manually and still have to meet with aspect concerned. System design is done by modeling language DFD (Data Flow Diagram) with system testing apply black-box testing with functional testing and error handling testing. While the programming language that is in use is PHP with framework CI (Codeigniter) and using database MySQL and the final result of the design is generating. RealTime Monitoring System Production Process Eggtray PT. Sinar Era Box Gresik is very helpful because it simplifies the employees and also the owner in monitoring the production process.
Forecasting for Book Classified on A Library by Using Single Exponential Smoothing (case Study : Library of Bhayangkara Surabaya University) Deddy Gita A.P; Rifki Fahrial Zainal; M Mahaputra Hidayat
JEECS (Journal of Electrical Engineering and Computer Sciences) Vol. 2 No. 2 (2017): JEECS (Journal of Electrical Engineering and Computer Sciences)
Publisher : Fakultas Teknik Universitas Bhayangkara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54732/jeecs.v2i2.152

Abstract

To facilitate the addition of library collections of UBHARA libraries, in this study will provide a solution to fieldmanuals based on forecasting using MSE single exponential smoothing formula errors and RMSE errors. Data isforecast from 2012 to 2016, with the value of each field of economics, law, socio-political, and engineering. The datawill be processed through the pre-processing process before preparing the data to be forecast. In the calculationexample, the program uses data in 2012 and 2015, alpha value = 0.1 and is calculated from month 1 to month to 3months so it is estimated to 4. The result of the data obtained is borrowed book which has the highest data isEconomy. Because in every data the number of loan books looks more dominant economic data. In 2015 thecalculation shows the value of MSE error and RMSE error. The error value to determine whether the errorforecasting results is better or not. For 2015 forecast data to be displayed at the value of the error.
Classification of Scout Skills Using Naive Bayes Algorithm Rizky Yudha Pramudhika; Rifki Fahrial Zainal; Rani Purbaningtyas
JEECS (Journal of Electrical Engineering and Computer Sciences) Vol. 2 No. 2 (2017): JEECS (Journal of Electrical Engineering and Computer Sciences)
Publisher : Fakultas Teknik Universitas Bhayangkara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54732/jeecs.v2i2.156

Abstract

In the development of skills and skills of students Scout often finds the problem is the difficulty of developing theskills of learners caused by mistakes in determining the skills dominated by learners. How you can do it to solve thatproblem is by making a class determination or classification of areas of expertise controlled by the learner. Thisstudy aims to build a system to determine the inner class Scout skills area using Naïve Bayes algorithm for ScoutCoach to determine the area of expertise of learners. So Scout Coach can develop the skills of learners inaccordance with the areas of expertise that are owned optimally. Assessment criteria used are the values of GeneralKnowledge, Scout Knowledge, Sign Language (Password, Morse, Semaphore), Node Bond, Pioneering, and HastaKarya. All assessment criteria are used numerically. The resulting classification is the students who are included inthe class Intelligence (Intelligence), Physical (Strength), or Creativity. The results of this study is a program that canperform calculations to determine skill class scout field. The Scouting Skill Classification Program using the NaïveBayes Algorithm has been tested and its accuracy or accuracy is 100%.
Decision Support System for New Employee Placement on An Office Department by Using Saw Fuzzy (case Study: CV.Kencana Abadi) Indah Sri Rahayu; Syariful Alim; Rifki Fahrial Zainal
JEECS (Journal of Electrical Engineering and Computer Sciences) Vol. 2 No. 2 (2017): JEECS (Journal of Electrical Engineering and Computer Sciences)
Publisher : Fakultas Teknik Universitas Bhayangkara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54732/jeecs.v2i2.157

Abstract

CV. KENCANA ABADI is a company engage for sale Castrol Oil in which there are several departments of HRD,accounting, finance & tax (tax), lubricant general manager and IT. During this time to determine the placement ofnew employees to the appropriate department still using the manual system. So needed a system needs that can be adecision support system for placement of new employees to appropriate departments that help the HRD and GA inorder to decide the right position placement for new employees. The model used in this decision support system isFuzzy Multiple Attribute Decision Making (FMADM). This SAW method is chosen because it determines the weightvalue for each attribute, followed by a ranking process that will select the best alternative from a number ofalternatives. Based on the results of testing HRD departments are eligible received Fajar Ferdhina, the test resultsof the Finance department, Accounting, Tax Budi Setyawan eligible, the results of testing IT departments eligibleGatot Nugroho, and the results of testing department Lubrican General Manager eligible Imelda Oktavia F.
Co-Authors Achmad Irfan Ferdiansyah Achmad Kiki Qushayri Wahyu Kusuma Adam Ridwan Afif Nuzia Al-Asadi Ahmad Sarif Hikmawan Akhmad Najmul Irfani Allexandro Billy Sukarta Andi Alfian Efendi Andriano Lukas Ani Dijah Rahajoe Arif Arizal Bachtiar Azhari Deddy Gita A.P Dina Zahrotul Fadhilah Eko Prasetyo Erwin Dwi Riyanto Fajrul Islam Fardanto Setyatama Febriardi Mahendra Ida Lailatul Qurnia Indah Sri Rahayu M Mahaputra Hidayat M. Mahaputra Hidayat Mas Nurul Hamidah Muhammad Rosyid Kurniawan Muhammad Saiful Irawan Mustofa Noer Firda Yuana Ridhawaty R Dimas Adityo Rahmawati Febrifyaning Tias Rahmawati Febriyaning Tias Rangsang Purnama Rani Pubaningtyas Rani Purbaningtyas Rizky Yudha Pramudhika Shagi Hisyam Al Fathony Syariful Alim Tio Kukuh Ardiansyah Tommy Ferdiansyah Wiwiet Herulambang