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Browsing by Author "Elfizar, Elfizar"

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ANALISIS PENERIMAAN PENGGUNA SISTEM AKADEMIK ONLINE DI UNIVERSITAS RIAU MENGGUNAKAN METODE UTAUT
(2019-07-22) Rahmayuli, Ranni; Elfizar, Elfizar
Academic information systems is one of the emerging technologies in the field of education that is increasingly needed today. Academic information systems have various service features, one of them is study plan cards. The research aims to describe te acceptance and use of online KRS with several variables, such as Performance Expectancy, Effort Expectancy, Facilitating Conditions and Behavioral Intention. Data were colleted through questionnaire using Likert scale from 191 online KRS users. The research result obtained using multiple linier regression analysis. The results show that there is a correlation among the Performance Expectancy, Effort Expectancy and Facilitating Conditions of Behavioral Intention with strong tendency (0,758). Furthermore Performance Expectancy, Effort Expectancy and Facilitating Conditions have a significant effect on Behavioral Intention of online KRS accounting to 57,4%.
ANALISIS SENTIMEN PENGGUNA TWITER TERHADAP METODE PEMBELAJARAN JARAK JAUH MENGGUNAKAN ALGORITMA NAÏVE BAYES
(Elfitra, 2022-01) Fitriani, Diah; Elfizar, Elfizar
The Covid-19 pandemic has caused various impacts, one of which is on educational activities. The Indonesian government decided to implement learning by the Distance Learning method. This has become a hot topic of discussion on Twitter. The circulated tweets contain public opinions on the implementation of Distance Learning. This study aims to classify sentiments to see the public's view of the Distance Learning implementation. Data used in this study is obtained by using the keywords of online lecture, networked lecture, online school, and networked school from October to November 2020. The sentiment is classified into two classes: positive and negative. The classification process is carried out by the pre-processing data and word weighting using the TF/IDF technique. Data classification is done by using the Naïve Bayes Multinomial algorithm and evaluation of the algorithm is done by using the confusion matrix method. The final result of the classification process yields a good accuracy rate of 83%, precision of 33.33% and recall of 6.25%. The results show that netizens do not fully agree with the implementation of Distance Learning. It is showed by negative sentiments are 97% and positive sentiments are 3%.
DATA MINING DALAM MENENTUKAN TINGKAT KELAYAKAN PENERIMAAN BANTUAN BEDAH RUMAH PADA DESA SIALANG BUAH DENGAN MENGGUNAKAN ALGORITMA C4.5
(Elfitra, 2023-09) Situmorang, Alexandro Van Houven; Elfizar, Elfizar
Sialang Buah is a village located near the coastal area. Approximately 75% of the village's population consists of economically disadvantaged families, facing challenges in terms of income, education, and living conditions. The research problem of this study is how to predict the eligibility level for the recipients of a housing renovation assistance program. The objective of this study is to predict the eligibility level for the recipients of the housing renovation assistance program using the C4.5 algorithm. Direct interviews were conducted to gather information and data about the potential recipients of the housing renovation assistance program, as well as data from previous recipients. The results of the study showed that out of the 58 potential recipients used for testing, 30 were classified as "Eligible" and 28 as "Not Eligible". These prediction results can be used as a supporting tool in decision-making through discussions between the village government and the BPD (Badan Pemusyawarah Desa). The C4.5 algorithm, trained on 218 data points and implemented on the 58 potential recipients, achieved an accuracy rate of approximately 95%..
EVALUASI KEPUASAN PENGGUNA PORTAL KULIAH KERJA NYATA UNIVERSITAS RIAU MENGGUNAKAN METODE END-USER COMPUTING SATISFACTION (EUCS)
(Elfitra, 2022-01) Wahyuni, Ayu; Elfizar, Elfizar
Portal Kukerta is an academic portal provided by the University of Riau for managing data about the activities of students study service program (Kukerta). The purpose of this research is to know the level of user satisfaction in Portal Kukerta of Universitas Riau by using End-User Computing Satisfaction (EUCS) method. This method consists of five measuring values, there are: content, accuracy, format, ease of use, and timeliness. This study uses the approach of Importance Performance Analysis and User Satisfaction Index to analyze the data. These research subjects were 100 (one hundred) people, namely Riau University students who had participated in Kukerta activities in 2020. Stages in this study include questionnaires, validity test, reliability test, questionnaire distribution, EUCS method data analysis, mapping into science diagrams, and determine the User Satisfaction Index. Based on the overall calculation results, the user satisfaction index (IKP) is 64,99%.
EVALUASI TINGKAT KEPUASAN PENGGUNA SISTEM INFORMASI PERMINTAAN PENGURUSAN SURAT (SIPPS) MENGGUNAKAN METODE END USER COMPUTING SATISFACTION
(Elfitra, 2023-01) Yanti, Damai; Elfizar, Elfizar
This study discusses the user satisfaction evaluation of document generation request information system at the Faculty of Mathematics and Natural Sciences, Riau University. Letter management at FMIPA University was previously carried out directly in the administrative department so that a system was formed that could help and facilitate the process of managing letters, namely SIPPS. SIPPS needs to be analyzed the level of user satisfaction with the aim of knowing the extent of the satisfaction level of SIPPS FMIPA users of Riau University. This study uses the End User Computing Satisfaction (EUCS) method which consists of 5 variables, namely content, accuracy, display, ease of use, timeliness. The sampling technique in this study used Taro Yamane with 96 samples from 2,608 active students of FMIPA Riau University as a population. The data obtained will be tested and analyzed using Importance Performance Analisys. Overall, the results of this study show that the satisfaction of SIPPS FMIPA users at Riau University is very satisfactory with the calculation of the IKP value of 80.39%.
IMPLEMENTASI ALGORITMA K-NEAREST NEIGHBOR UNTUK MENGANALISIS SENTIMEN USER TWITTER
(Elfitra, 2021-12) Ahmiyul, Aisyah Mutiah; Elfizar, Elfizar
Twitter is a frequently used social media that is used to state opinions whether it is positive or negative. The purpose of this research is to analyze the sentiment of Twitter users regarding an issue. The case study for this research is the incident of Tol Cikampek. The data that is proper to use for sentiment analysis are 618 data tweets which consists of 237 positive data tweets and 389 negative data tweets taken during December-January 2021 using Twint application in Python. Data tweets that are taken goes through pre-processing stage which consists of case folding, data cleansing, tokenization, normalization, stopword removal, and stemming. After pre-processing, data weighting is done using Term Frequency-Inverse Document Frequency (TF-IDF) and classification is done using the method of K-Nearest Neighbor with cosine similarity to calculate the distance between documents. Based on the evaluation results using confusion matrix, the highest accuracy is 83,1% when k=9, the highest precision 2 is 66,7% when k=5 and the highest recall is 87,5% when k=9.
IMPLEMENTASI JARINGAN SYARAF TIRUAN BACKPROPAGATION UNTUK PREDIKSI PENYEDIAAN ENERGI LISTRIK (STUDI KASUS PLN RAYON RUMBAI)
(2020-10) Rahmawati, Amelia Wahyu; Elfizar, Elfizar
This study applies the backpropagation algorithm to determine the supply of electrical energy with six variables, namely the amount of electricity for social users, the amount of electricity for household users, the amount of electricity for business users, the amount of electricity for industrial users, the amount of electricity for government users and the amount of electricity for special services. This study uses 12 data with the division of training data and test data that is 90%: 10%, 80%: 20% and 70%: 30% of 12 data. This study also uses several parameters namely learning rate (α) 0.1 to 0.9, maximum epoch 50 and six hidden neurons. The results of the test show the highest average prediction accuracy of 99,90% at 90%: 10% data sharing, six hidden neurons, learning rate (α) of 0.8 and the number of epoch 65 and testing of Mean Square Error (MSE) of 0.00009.
IMPLEMENTASI NAÏVE BAYES CLASSIFIER PADA TWITTER DALAM ANALISIS SENTIMEN TERHADAP VARIAN BARU CORONA VIRUS OMICRON
(Elfitra, 2023-06) Esmeralda, Irtha Bella; Elfizar, Elfizar
Omicron is a new variant of the Corona virus that was first reported to the World Health Organization (WHO) from South Africa on November 24, 2021. The amount of information related to the Omicron virus that is spread in the form of text on the internet and on social media sites like Twitter is of interest to researchers. This study aims to determine public sentiment from Twitter users about the omicron virus, then determine sentiment classification using the Nave Bayes Classifier and calculate the level of accuracy of the method in sentiment analysis. The data used is 1350 data points using two data testing scenarios, namely the first scenario, Split Validation, using a data ratio of 70%:30%, 80%:20%, and 90%:10%. The second scenario uses cross-validation, divided into 10 tests. Sentiment classifiers are divided into three classes: neutral, fearful, and fearless. The classification process is carried out by means of data pre-processing and weighting using the TF-IDF technique. The final results of the classification process get the highest accuracy values of 85%, 81% precision, and 86% recall in the split validation test with a 90:10 data division. Testing data with cross-validation resulted in the highest accuracy of 93,1% accuracy, 36,6% precision, and 98% recall, with a fold value of 1.
IMPLEMENTASI RATIONAL UNIFIED PROCESS DALAM PERANCANGAN SISTEM INFORMASI PRESTASI MAHASISWA FMIPA UNIVERSITAS RIAU
(wahyu sari yeni, 2019-01-14) Wibowo, Herry; Elfizar, Elfizar
The information system of students' achievements of the Faculty of Mathematics and Natural Sciences of the University of Riau is a web-based information system that was built to provide information about the achievements that have been achieved by the students of Mathematics and Natural Sciences, University of Riau. The achievement information system is built using the PHP and MySQL programming languages. The system buildment method used is the Rational Unified Process (RUP) which is divided into three phases, namely inception, elaboration and construction. Each stage has several processes carried out starting from business modeling, requirements, design, implementation, and testing. The process carried out in the inception phase are the stages of business modeling and requirements, then in the elaboration phase the design and construction phases are carried out in the implementation and testing phases. Software product testing is done using black box testing
IMPLEMENTASI TEXT MINING DENGAN RANDOM FOREST UNTUK ANALISIS SENTIMEN ULASAN PENGGUNA APLIKASI ALODOKTER
(Elfitra, 2022-12) Norman, Nadia Fadhilah; Elfizar, Elfizar
During the COVID-19 pandemic, most people relied on the internet to find information, including health information. The process of digitizing the world of health, especially during a pandemic, was actually enough to help people get their right to health. The existence of digital health applications certainly will not replace the function of doctors and medical personnel in the world of health. Alodokter is a health platform in Indonesia. Alodokter application users can provide reviews of these application services through the review feature on the Google Play Store. The existence of this feature is one of the considerations for prospective users to download applications and can be used as an evaluation to improve application performance. Therefore, it is necessary to carry out a sentiment analysis to see an overview of the perceptions of Alodokter application users on the Google Play Store. In this study, data collection was carried out using web scraping techniques using Google Colab. The data used is user review data after it was determined that COVID-19 entered Indonesia, namely from March 2020 to May 2020 with a total of 13,225 review data. The method used in this study is Random Forest, this method produces classification accuracy performance with an accuracy rate of 96.1% as measured using the Confusion Matrix. Based on the accuracy value, it can be seen that Random Forest has good performance in processing big data.
PENERAPAN DATA MINING UNTUK MENENTUKAN POLA PEMBELIAN PRODUK PADA TOKO LS MART MENGGUNAKAN ALGORITMA ECLAT
(Elfitra, 2023-10) Mukthy, M. Luthfi; Elfizar, Elfizar
At this time, the retail sector in Indonesia continues to experience significant growth, with an increase in the number of outlets built in various locations. In sales places such as shops, sales transactions are carried out every day, and the number is increasing. The LS Mart shop is a sales place that provides household necessities, food, and people's daily necessities, which are generally sold. An effective and efficient sales strategy is needed to attract customer interest and comfort when shopping, but the sales transaction data that we have has not been used to dig up this information. It is very important to have knowledge of the required strategy. Existing sales transaction data is used to find purchasing patterns and determine sales strategy recommendations using the association rule method using the ECLAT algorithm. ECLAT is an association algorithm that identifies the most frequently repeated itemsets and is one of the association algorithms with the most effective search for frequently repeated itemsets when compared to other algorithms. The results of data processing showed that the ECLAT algorithm was successfully applied to determine product purchasing patterns. Sales transaction data processing resulted in 12 rules for 2-itemset combinations and also nine rules for 3- itemset combinations, as well as recommendations for sales strategies that can be implemented in the form of bidding strategies, packages, and product placement strategies.
PREDIKSI CALON PENERIMA BANTUAN PROGRAM KELUARGA HARAPAN (PKH) MENGGUNAKAN ALGORITMA C4.5 (STUDI KASUS: KECAMATAN BANGKO KABUPATEN ROKAN HILIR)
(2021-04) Sari, Refna Afrita; Elfizar, Elfizar
Bangko Sub-district is one of sub-districts in Rokan Hilir Regency that has distributed assistance of Keluarga Harapan (Family Hope) Program since 2007. The program is a conditional social protection program from the central government through distribution of cash assistance to very poor families. In the process of validating prospective recipient data of the program assistance, it is still performed manually which takes a long time. In addition, there are often problems regarding the recipient assistance that do not match criteria for participating in the program. This study aims to build a system that is able to predict potential beneficiaries of the expected family program assistance using the C4.5 algorithm. The attributes used were place of residence, occupation, pregnancy status, dependents of school age children and family members with disabilities. The category of decisions produced was recipients who were predicted to receive and not receive assistance from the program. This system was designed using Unified Modeling Language and developed with the PHP programming language and MySQL DBMS. The results of system testing calculated using confusion matrix against 300 recipient data and not the recipient of the program produced an accuracy rate of 87%.
PREDIKSI PENJUALAN SEPEDA MOTOR MENGGUNAKAN METODE DOUBLE EXPONENTIAL SMOOTHING
(2020-08) Astuti, Wari; Elfizar, Elfizar
The uncertainty of motorcycle sales, which sometimes increases and decreases in sales, makes it difficult for dealer to determine motorcycle inventory. From this problem the dealere needs a system that can provide information about motorcycle sales predictions to assist dealer in determining motorcycle inventory. This study describes the process of developing a motorcycle sales forecast information system using the Double Exponential Smoothing method and Unified Language Modeling (UML) as a system design. The outputs of this system are table and graph which exhibit motorcycle sales predictions.
SISTEM PAKAR DIAGNOSA PENYAKIT TANAMAN PINANG MENGGUNAKAN METODE CERTAINTY FACTOR BERBASIS WEB
(2020-10) Riaui, Muhammad Amin NL; Elfizar, Elfizar
The number of diseases in areca plants makes betel nut farmers confused in determining or choosing the right and suitable type of treatment for the areca plant. This is what makes it difficult for farmers to get good and maximum betel nut fruit because they cannot make a proper diagnosis of the betel nut plant, which causes the quality and productivity of the betel nut to decline and it can cause the incomes of betel nut farmers to drop. A web-based expert system can be used to help solve problems in terms of assisting each farmer in making diagnoses for handling betel nut diseases appropriately and effectively. The method used in diagnosing diseases in areca plants is the Certainty Factor Method, where this method will analyze based on the symptom data entered by the user so that a result of disease identification in the betel nut plant is obtained in the form of disease name, level of certainty and how to handle it. The system that is built is expected to be able to help farmers solve medical problems in areca plants so that they can get high-quality and high-quality betel nuts.
SISTEM PAKAR PENENTUAN KUALITAS TIDUR MENGGUNAKAN METODE SISTEM INFERENSI FUZZY TSUKAMOTO
(Elfitra, 2021-12) Subaktianto, Dimas; Elfizar, Elfizar
Sleep quality is the level of satisfaction of an individual with a condition experienced while sleeping, so that the individual feels fresh or not when he wakes up. This study aims to develop an expert system that can determine the quality of an individual's sleep. The reasoning process to determine the sleep quality of an individual in this expert system uses the Tsukamoto fuzzy inference system method. This method has three important stages, namely fuzzification, inference, and defuzzification. In this study, reasoning was carried out on an individual's sleep condition data consisting of data on the condition of body temperature, heart rate, anxiety level, room temperature, room humidity, and light intensity. These data are obtained with the help of Internet of Things-based sleep monitoring devices so that they can record data in real time and periodically. The process of designing the system using Unified Modeling Language (UML) diagrams. The system was developed using the PHP programming language, Codeigniter 3 framework, MySQL database, and run on the Apache web server. This study involved ten subjects. Data retrieval is done by pairing a monitoring device on the subject while the subject is sleeping. The results of this study are the Tsukamoto fuzzy inference system method can be used to determine the quality of sleep of an individual in the developed expert system.
SISTEM PENDUKUNG KEPUTUSAN PEMILIHAN GURU BERPRESTASI TINGKAT SEKOLAH MENENGAH ATAS MENGGUNAKAN METODE PROFILE MATCHING (STUDI KASUS: DINAS PENDIDIKAN PROVINSI RIAU)
(Elfitra, 2023-01) Aisyah, Siti; Elfizar, Elfizar
Teachers are a major milestone in the world of education and as a central figure in the improvement of national education. The title of outstanding teacher is one way to improve the quality of education and to increase teacher motivation, dedication, loyalty, and professionalism. This decision support system for the selection of outstanding teachers aims to assist decision-making in the selection of outstanding teachers at the high school level using the Profile Matching method quickly and easily. The criteria that are taken into consideration in determining outstanding teachers are Portopolio documents, teacher performance reports, best practice presentations, interviews, and written tests. In the process of the Profile Matching method, it is broadly a process of comparing the value of the attribute data of the profile to be assessed with the expected or ideal profile value. So that it can be known the difference in GAP competence. The final result of the system is in the form of a report on the results of outstanding teachers in the order of the highest to lowest ranking scores. The testing system uses black-box testing
SISTEM PENDUKUNG KEPUTUSAN PENERIMA BANTUAN PROGRAM KELUARGA HARAPAN MENGGUNAKAN METODE MOORA DI KECAMATAN KELAYANG INDRAGIRI HULU
(Elfitra, 2023-02) Susilawati, Yeti; Elfizar, Elfizar
PKH is one of the programs to accelerate poverty alleviation and develop a social security system through the provision of conditional cash assistance to Very Poor Households (RTSM) in an effort to improve the quality of Human Resources (HR), especially in the health and education sectors. Therefore assistance must be given to recipients who are worthy and deserve it. However, there are still problems in the data processing because of the large amount of data and criteria that must be considered for the selection of PKH beneficiaries, so the process takes a long time. For this reason, a decision support system is needed to make it easier to make recommendations on PKH assistance recipients. This study aims to create a decision support system using the Multi Objective Optimization on the Basis of Ratio Analysis method for PKH beneficiaries. The system that was created was designed using UML Diagrams, the system was built using the CodeIgniter Framework with the PHP programming language and MysQL as the database. This study used sample data of 170 poor population data, it was concluded that as many as 109 people were declared eligible, and 61 people were declared unfit.
SISTEM PENDUKUNG KEPUTUSAN PROMOSI JABATAN PEGAWAI MENGGUNAKAN METODE SIMPLE ADDITIVE WEIGHTING (SAW)
(2020-08) Syahminati, Dita Arifa; Elfizar, Elfizar
The promotion of government officials, also known as civil sevants is implemented based on several regulations, such as Government Regulation No. 11 of 2017 concerning the civil servants management and Act No. 5 of 2014 concerning civil servants. One of the policies from both of regulations is the implementation of merit system. The SAW method used in this decision support system contributes to obtain the employees scores in accordance with the required criterias. Each score obtained by the employee will be multiplied by the preference weight of each criteria. The preference weight and rating scores are determined by the fuzzification process and the results are between 0 to 1. The final scores are obtained by adding up all of the multiplication results between scores and preference weights of all the criterias
SISTEM PENDUKUNG KEPUTUSAN SPASIAL PEMILIHAN SEKOLAH MENENGAH KEJURUAN TEKNIK KOMPUTER DAN JARINGAN MENGGUNAKAN METODE PROFILE MATCHING
(wahyu sari yeni, 2019-01-31) Setiawati, Yolanda; Elfizar, Elfizar
The purpose of Spatial DSS (Decision Support Systems) in this research is to give school recommendation for user in choosing school according to the criteria that desired by user. Criteria that used for decision process are education development donation, accreditation, number of computer laboratories, school facilities / school infrastructures, and the distance from student house to school location that calculated using Google map. System developed using UML modeling language, PHP programming language, and MariaDB database. The system results school recommendation rank, and spatial information such as distance and travel route from student house to school location using Google map. The result testing of 26 schools was SMK Taruna Satria Pekanbaru have the highest profile matching total, that is 4,85
SISTEM PREDIKSI KELULUSAN MAHASISWA TEPAT WAKTU MENGGUNAKAN ALGORITMA SVM (STUDI KASUS: MAHASISWA FMIPA UNRI)
(Elfitra, 2023-08) Mahendra, Yusril; Elfizar, Elfizar
The quality of education is the main focus in providing higher education. However, the quality of education cannot be measured solely by looking at the results of the final exam, therefore, a timely graduation prediction system is needed that can assist lecturers and faculty staff in providing supervision and support to students in achieving their goals. Student graduation on time is one of the assessments or benchmarks in the higher education accreditation process. Higher education accreditation assessment is carried out by the National Accreditation Board for Higher Education. The higher the accreditation value, the higher the level of quality of higher education. In this case, technology can be used as a solution to develop an effective and efficient prediction system. This study focuses on predicting student graduation by Data Mining using the Support Vector Machine algorithm and the level of accuracy of the algorithm is measured using the Confusion Matrix. This study used data from students of the Information Systems Study Program, Mathematics, Statistics, Chemistry, Biology, and Physics of the Faculty of Mathematics and Natural Sciences, University of Riau who had graduated from 2014-2017 as many as 1045 data. Ability to classify student graduation predictions with an accurate 99,04% data accuracy rate.

Browsing by Author "Elfizar, Elfizar"

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