Browsing by Author "Alfirman, Alfirman"

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    ANALISA SENTIMEN PENGGUNA TERHADAP KEBIJAKAN BARU WHATSAPP MENGGUNAKAN NAIVE BAYES CLASSIFIER DAN SUPPORT VECTOR MACHINE
    (Elfitra, 2021-12) Alawiyah, Nur’aini; Alfirman, Alfirman
    This study applies the Naïve Bayes Classifier (NBC) and Support Vector Machine (SVM) algorithms in classifying WhatsApp user review data to determine the percentage of user sentiment towards the whatsapp’s new privacy policy and to compare the performance of the two algorithms. This study uses 760 data with the distribution of training and testing data, namely 90%:10%, 70%:30%, 50%:50%, 30%:70%, and 10%:90%. The results showed that there were 338 positive reviews and 422 negative reviews, so it can be concluded that the trend of user sentiment towards the whatsapp’s new privacy policy was negative with a percentage of 56%. The results of the confusion matrix test show that the highest accuracy value is obtained in the first test with a data ratio of 90%:10%. The NBC method has an accuracy of 92.11% while the SVM method has an accuracy of 96.05%, it can be said that the SVM method has a better performance than the NBC method in classifying whatsapp user review data.
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    ANALISIS KEPUASAN PENGGUNA LAYANAN SHOPEE MENGGUNAKAN METODE E-SERVQUAL (STUDI KASUS: MAHASISWA UNIVERSITAS RIAU)
    (Elfitra, 2023-02) Rasmani, Rasmani; Alfirman, Alfirman
    Shopee is an online marketplace application that can be accessed via a smartphone, with this application making shopping and selling activities easier. Behind this convenience, of course there are more or less shortcomings that are felt by users, such as slow application responses which can affect service quality, therefore an analysis is needed to measure the extent to which the system provides services to users. The number of respondents to this study was 100 (one hundred) active students at the University of Riau in 2021. This research used the E-Servqual method, which consisted of 7 (seven) dimensions and the analysis used in this research was the Importance Performance Analysis (IPA) Matrix. Based on the results of the overall calculation, the User Satisfaction Index (IKP) was obtained at 72.79%, which means that users are quite satisfied with the services provided by the Shopee application.
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    ANALISIS PERSEPSI MASYARAKAT TERHADAP PENGESAHAN UU CIPTA KERJA TAHUN 2020 MENGGUNAKANMETODE SVM DAN NBC
    (Elfitra, 2022-07) Imannurin, Alparondi; Alfirman, Alfirman
    Twitter is one of the social media that people choosen to express their opinion. Opinion is a statement from the public based on their problem which distribute through social media. The government has legitimate the Job Creation Law No. 11 2020 which reap the criticism from society elements. The aims of this study are to find out the public perception to validation of the Job Creation also, to determine the performance of the Support Vector Machine to obtaining the optimal hyperplane that gives distance or separator between the two classes and classifying Naïve Bayes in determining to classify simple probabilities. Data used in this study was collected using twitter scraper, in the form of data tweets with the keywords #omnibuslawand #UUCiptaKerja in the month of October 2020. The result of the evaluation that used confusion matrix showed that Support Vector Machine method produced 82% accuracy level which is better than the Naive Bayes Classifier which produced 80% accuracy. Society was not completely against the legalization of the Job Creation Law, as there were a few perspective of the society that agreed towards the clauses that was considered profitable for the society such as lay off policy, economic growth and investation, work field creation and simplifying the process of business licensing.
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    DIAGNOSA AUTISME PADA ANAK MENGGUNAKAN METODE BACKWARD CHAINING BERBASIS WEB
    (wahyu sari yeni, 2019-04-30) Sucitawarni, Sucitawarni; Alfirman, Alfirman
    Autism is defined as a complex developmental disorder involving communication, social interaction and imagination activity. With expert system can be created that can help diagnose autism spectrum for children. The reasoning process in this expert system use a backward chaining method that will prove the assumption of the disease suffered by tracing back to the symptoms experienced to obtain a treatment solution. This expert system design use UML (Unified Modeling Language). This research produced an expert system diagnosis autism for children use web-based OOP (Oriented Object Programming). The testing in this research are Black Box Testing and User Acceptance Testing. The results of the Black Box Testing are valid which indicates that the system functionality is running well. Whereas from User Acceptance Testing, users feel helped which this expert system
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    IMPLEMENTASI METODE SINGLE MOVING AVERAGE DALAM PERAMALAN PENJUALAN ACCESSORIES HANDPHONE DI RETRO CELLULER BANGKINANG
    (Elfitra, 2023-10) Aulia, Nurul; Alfirman, Alfirman
    Mobile accessories have many different types and functions to be able to help perfect the performance of the phone. Retro cellular Bangkinang is one of the places to provide sales of cellphone accessories. The store sells many types of cellphone accessories that make it difficult to control old inventory that is not sold. With so many types of cellphone accessories, the stock of goods is out of control. This is caused by an error in increasing the number of goods to the accumulation of stock of goods. Product forecasting is a form of inventory control so that the amount of inventory can be controlled. The method used to forecast sales of HP accessories using the single moving average method. The calculation data used is sales data for the last 12 months. The calculation is carried out using periods 5, 7, and 9. Then to measure the error rate that occurs after calculations using equations from MAD, MSE, and MAPE. The forecasting results can be in the form of the number of sales of goods that will be sold in June 2023. The smallest measuring value of the forecasting error rate is forecasting on PowerBank goods with MAD values of 0.99, MSE 1.42, and MAPE 4.24. The measurement value of the largest forecasting error rate is in the type of Case Motive goods with a value of MAD 218.51, MSE 59979.48, and MAPE 74.20.
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    KLASIFIKASI KEMATANGAN BUAH SEMANGKA DENGAN METODE PERCEPTRON
    (Elfitra, 2022-12) Zanuroini, Melfin; Alfirman, Alfirman
    Watermelon is a fruit that is widely consumed by humans, watermelons that are consumed are ripe, ripe watermelons and raw watermelons tend to have the same skin color, which is green, so that visually distinguishing the human eye is very difficult to distinguish. common people. Along with the development of technology, it is possible to regret this problem, namely the technique of image processing, with the help of digital image processing. This study aims to build a system that can classify raw and ripe watermelons using the perceptron method. The perceptron method is a method that is able to perform calculations by recognizing variables in pattern matching. In this method there are several variables that must be initialized, namely the input value, weight value, bias value and learning rate. The application of the perceptron model in this study uses an initial weight value of 0, an initial bias value of 0 and a learning rate of 1. The data used is a digital image of the watermelon in JPG format, totaling 100 images, 50 raw and 50 ripe. 50 images are used as training data and 50 images are used as testing data. In a digital image composed of RGB colors, the warrant value is converted to the HSV color space and only the hue value is taken. Before taking the hue value, the digital image object is processed, namely by giving a filter to remove the background so that the color object is not influenced by other colors. The hue value obtained is then processed using a single layer perceptron and a bipolar sigmoid activation function. We found a convergent weight at the 102 epoch with a bias value of -142 and a weight value of 0,586354073. From this value, testing is carried out and results in 92% accuracy from 50 testing data.
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    KLASTERISASI LOKASI TINGKAT PENYEBARAN COVID-19 MENGGUNAKAN ALGORITMA K-MEANS
    (Elfitra, 2022-07) Sabrillian, Nickhallen; Alfirman, Alfirman
    Disease is a bad condition in specific organs or body parts caused by harmful microorganisms such as bacteria, viruses, wounds, chemical imbalances in the body, exposure to toxins, and the appearance of imperfect cells. From 2020 until now, Indonesia has been shocked about the spread of a fairly serious disease. The case was caused by the coronavirus, known as covid-19 (Corona Virus Disease-2019). The spread of the Covid-19 virus is swift. Human-to-human transmission occurs near an infected person. The main transmission is an infected person sneezing and respiratory droplets such as influenza, the oral or nasal mucosa, and the lungs of people who breathe infected air. The government has issued various policies to minimize the spread of COVID-19 by imposing social distancing, physical distancing, large-scale social restrictions (PSBB), and restrictions on community activities (PPKM) in several areas. Problems arise that make it difficult for the Health Office to group areas that will produce the central points for the spread of COVID-19 sufferers, so data is grouped based on the number of sufferers. This study aimed to determine the regional grouping of the spread of COVID-19 in Pekanbaru City. The data used is data on positive cases of COVID-19 obtained from the Pekanbaru City Health Office and data on the number of residents in Pekanbaru City based on 83 villages. The method used in this research is K-Means Clustering. K-Means Clustering is a method that can group areas with the potential for COVID-19. Based on the research results, there are 46 villages in cluster 1, 7 villages in cluster 2 and 30 villages in cluster 3.
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    PENENTUAN CALON PENERIMA BEASISWA PENINGKATAN PRESTASI AKADEMIK (PPA) MENGGUNAKAN ALGORITMA C4.5 BERBASIS WEB
    (wahyu sari yeni, 2019-01-31) Hariyati, Sarmira; Alfirman, Alfirman
    Faculty of Mathematics and Natural Sciences (FMIPA) University of Riau provides PPA scholarship to help the students who are incapable economically and have good academic potential. The problem of scholarship funds distribution is selection process still done manually and need a long time, So that is a needs to create a system for determining Scholarship candidates using web-based C4.5 algorithm. System developed using UML modeling language, PHP programming language and MySQL database. The result testing of 20 students obtained accuration level value is 82,19
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    PENERAPAN ALGORITMA K-MEANS CLUSTERING DALAM PENGELOMPOKAN POTENSI PRODUKSI PERTANIAN DAN PERKEBUNAN DI PROVINSI RIAU
    (Elfitra, 2023-05) Atmoko, Gesit Widi Atmoko; Alfirman, Alfirman
    The agricultural sector is very important for Riau province, as the province is still heavily dependent on the agricultural sector for economic growth. Riau province has the potential for plantation development in order to accelerate access to encourage the development of economic potential and create economic growth and equity in Riau province. The development of plantation and agricultural commodities in Riau province is still not optimal. One of the problems and obstacles faced in its development is the low productivity of plantation and agricultural crops. Therefore, the Riau provincial government needs to know the description of plantations and agriculture in the form of characteristics found in each district or city in Riau province. This research aims to cluster the potential of agricultural and plantation production in Riau province using the k-means method. The k-means method is a clustering technique that is useful for dividing data into several groups where data is grouped based on the same characteristics. In the process of collecting data on agricultural and plantation harvest areas, 528 data were generated. After going through the cleaning step the resulting data becomes 408 data. The results of calculations with the k-means method carried out 3 times the experiment obtained the formation of 3 clustering stops in iteration 7, the formation of 4 clustering stops in iteration 11, and the formation of 5 clustering stops in iteration 12. The highest silhouette coefficient value is in the formation of 3 clusters of 0.804 which is classified as a strong structure. Cluster 1 consists of 21 members which is a cluster with high production, cluster 2 consists of 35 members which is a cluster with medium production, and cluster 3 consists of 352 members which is a cluster with low production.
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    PENERAPAN ASSOCIATION RULE UNTUK MENGANALISA DATA KONSUMEN KEPEMILIKAN RUMAH SUBSIDI
    (Elfitra, 2023-01) Sinaga, Jordiansyah Simto; Alfirman, Alfirman
    Increasing population growth and increasingly limited land for housing needs has led to high public interest in housing loans so that they can pay installments every month. But problems that often occur are errors in determining the credit period and the number of installments paid each month causing credit arrears. This causes difficulties for developers in recommending services that are in accordance with the consumer's economy at PT. Semangat Jaya Sentosa enthusiasm for processing data manually. So to overcome this problem, companies need recommendations in the form of strategies obtained from consumer data at PT. Semangat Jaya Sentosa. This study aims to obtain Association Rules from consumer data and information on housing loans. The results of the Association Rules will form strategic recommendations for the developer. The attributes used are gender, status, occupation, district/city, credit period, and income. This study carried out 6 stages in obtaining Association Rules namely literature study, data collection, data selection, data cleaning, implementation of a priori algorithms, and interpretation. This study uses the Python programming language to find Association Rules from consumer housing loan data sets and through join and prune processes. This study uses consumer data for the period from January to December 2021 as many as 1,514 data with a minimum Support value of 30% and a minimum Confidance of 83% so as to produce a pattern of 18 rules so that the highest value for the combination of 3 itemset is Pekanbaru, Lowerclient, 20 has a Support value of 0.4557 = 45.57 % and Confidance value 1 = 100%. The results of the interpretation of the rules concluded, the developer can provide recommendations regarding the appropriate credit period for consumers with income below 3 million rupiah from the Pekanbaru city area, which is 20 years. The results of the Association Rules are then formed to recommend the best strategy for the developer and are expected to be able to overcome the problem of housing loans at PT. Semangat Jaya Sentosa.
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    PENERAPAN METODE DOUBLE EXPONENTIAL SMOOTHING DALAM MERAMALKAN HASIL PANEN PADI DI KABUPATEN KAMPAR
    (Elfitra, 2023-01) Firdaus, M.Riski; Alfirman, Alfirman
    Indonesia merupakan negara yang memiliki tanah subur. Hal ini dapat dibuktikan dengan mudahnya ditemukan lahan pertanian dan perkebunan. Aktivitas pertanian yang terdapat di Indonesia ada dua macam, yaitu pertanian lahan kering dan lahan basah. Jenis tanaman yang tumbuh di sawah cukup beragam, tapi pada umumnya tanaman yang ditanam di sawah oleh petani yaitu padi, jagung, kacang, dan palawija lainnya. Diantara tanaman tersebut yang memiliki produktivitas tinggi adalah padi. Padi merupakan salah satu tanaman yang penting di Indonesia. Tanaman padi menghasilkan beras yang merupakan bahan makanan pokok bagi rakyat Indonesia. Objek pada penelitian ini yaitu di Kabupaten Kampar. Kabupaten Kampar merupakan salah satu penghasil padi, yang mana hasil panen padi di Kabupaten Kampar belum memenuhi kebutuhan dikarenakan setiap tahun panen padi mengalami perubahan yang disebabkan oleh faktor-faktor yang mempengaruhi hasil panen. Sehingga pemerintah harus dapat merencanakan perencanaan yang tepat dalam melakukan tindakan selanjutnya salah satunya dengan melakukan peramalan agar tidak terjadi penurunan tingkat produksi padi yang akan mempengaruhi ketersediaan beras. Oleh karena itu, peneliti merancang sistem peramalan hasil produksi padi menggunakan Metode Double Exponential Smoothing untuk menentukan nilai estimasi produksi padi dalam satu tahun yang akan datang. Metode ini dipilih karena dapat digunakan untuk meramalkan data timeseries dan memiliki kemampuan peramalan yang baik. Pada penelitian ini dilakukan pengujian tingkat error. Penerapan Metode ini menghasilkan peramalan panen padi di Kabupaten Kampar tahun 2022 sebesar 26.271,81 ton dengan nilai MAPE sebesar 28,21%. Berdasarkan rata-rata tersebut, kesalahan peramalan termasuk kategori cukup karena kesalahan presentase =< dari 50%.
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    PENGELOMPOKAN EVALUASI AKADEMIK MAHASISWA JURUSAN ILMU KOMPUTER UNIVERSITAS RIAU MENGGUNAKAN METODE K-MEDOIDS CLUSTERING
    (Elfitra, 2022-12) Saputra, Nur Ihsan; Alfirman, Alfirman
    One of the successes of higher education is the success of students in pursuing their studies. The success of students can be seen from the achievement index they have achieved. The high average number of student achievement index has a big influence on the image and accreditation of universities. Therefore, a research was conducted on the grouping of the Academic Evaluation of Students of the Department of Computer Science, University of Riau using the K-Medoids Clustering Method. Clustering is the process of dividing data in a set into several groups whose data similarity in one group is greater than the similarity of the data with data in other groups. K-Medoids Clustering is one method of partitioning because it uses the most centralized objects in the cluster to be the center cluster of the average values of objects in a cluster. The stages in this research are processing data with K-Medoids Clustering, Evaluation Processing and analysis of results. From the research conducted, the results of the analysis of each cluster are obtained, the first cluster is normal students with a total of 40 students, the second cluster of problematic students with a total of 5 students. While the third cluster is a cluster of excellent students with a total of 68 students. From the research conducted, it was found that students dominated the entire cluster.
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    PENGELOMPOKAN KEMISKINAN DI PROVINSI RIAU DENGAN MENGGUNAKAN METODE K-MEDOIDS
    (Elfitra, 2023-10) Wijoanda, Putra Heru; Alfirman, Alfirman
    Poverty is a long-standing problem in Indonesia, and it has been an issue during almost all periods of government. Poverty can cause serious problems in the future when the government does not pay special attention to it. The inability of people to meet their standard of living, lack of access to education and employment will lead to recession. The quality of human resources affects low income productivity. Efforts to fight poverty must be carried out comprehensively, covering all areas of people's lives and coordinating their implementation. Poverty has always been a problem for Indonesia, until now there is no sign that it will stop. Therefore, research was conducted on poverty grouping in Riau province using the K-medoids method. It is expected that the results can provide additional information in optimizing poverty reduction in Riau Province. The research was conducted by forming 2 to 4 clusters, then the best results were obtained where the value close to 1 is the best value, namely in the formation of 2 clusters with 0.314477 in cluster 1 consisting of 3 districts Kuantan singingi, Indragiri Hulu, and Indragiri Hilir with high poverty rates while in cluster 2 consisting of Pelalawan, Siak, Kampar, Rokan Hulu, Bengkalis, Rokan Hilir, Kepulaun meranti, Pekanbaru city, and Dumai city with poverty rates.
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    PENILAIAN RISIKO KEAMANAN WEBSITE PERPUSTAKAAN UNIVERSITAS RIAU MENGGUNAKAN METODE FAILURE MODE AND EFFECT ANALYSIS
    (Elfitra, 2022-03) Tania, Nabila; Alfirman, Alfirman
    University of Riau has implemented a website-based library information system to facilitate library management activities. In addition to providing benefits in the form of speed and ease of access, this information system is vulnerable to the risk of crime so that high level of security is required. Therefore, it is necessary to carry out an assessment of information system security risks to find out the risks that may occur and the carry out risk mitigation to reduce these risks. This study used The Failure Mode and Effect Analysis method to identify the risks that may occur. Based on the results of the analysis, obtained 18 risks along with 30 potential causes. There were four potential causes with a high level, four potential causes with a medium level, 21 potential causes with a low level, and one potential cause with a very low level. Then risk mitigation is carried out based in ISO/IEC 27001:2013 as a control used in risk management.
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    PREDIKSI HARGA EMAS DENGAN METODE LONG SHORT-TERM MEMORY
    (Elfitra, 2023-11) Sholeh, Muhammad; Alfirman, Alfirman
    Predicting gold prices holds significant importance in the realms of finance and investment, enabling market participants to make wiser decisions amidst gold price fluctuations. The training results of the Long Short-Term Memory (LSTM) model displayed remarkable performance, with a Mean Squared Error (MSE) value of 0.0034 and a Mean Absolute Percentage Error (MAPE) value of 7.13%. According to the MAPE criterion, this LSTM model's predictive capabilities can be categorized as highly accurate. These outcomes affirm the potential of the LSTM model in providing precise gold price predictions, aiding market participants in more informed decision-making. The forecasted gold prices using LSTM from January 1, 2023, to March 1, 2023, indicate a daily decrease in gold prices. Consequently, a prudent approach for market participants would be to engage in future gold purchases during the predicted gold price decrease in 2023.
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    PREDIKSI PEMAKAIAN CITY GAS RUMAH TANGGA MENGGUNAKAN METODE KLASIFIKASI NAIVE BAYES (STUDI KASUS: PT. SARANA PEMBANGUNAN ENERGI MADANI)
    (2020-09) Amalianty, Rani; Alfirman, Alfirman
    In 2016 natural gas was distributed in 3,713 houses in Limapuluh District, Pekanbaru. This number is spread in 4 villages in Limapuluh District Pekanbaru, namely Rintis, Sekip, Tanjung Rhu, and Pesisir. The unwise usage city gas will have impact on the size of the use of city gas, this will also affect the depletion of the supply of natural gas due to the bigger demand for city gas than its supply. The purpose of this study is to build a system that can predict household city gas usage by using the Naive Bayes Classification method. The working principle of the Naive Bayes method is to calculate a set of probabilities by adding up the frequencies and combinations of datasets that have been made. This system was built with the PHP programming language, MySQL as a database server, and UML as a system design. Data was collected by distributing questionnaires to 97 houses with a span of 2 months, September and Oktober 2019. Total data used are 194 data. Then the results obtained percentage of 70,1030% for accuracy of predictions with good feasibility, where from 194 data tested there were 136 data that were successfully predicted correctly. The manual calculation test is performed and the system calculation produces a similar usage level
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    PREDIKSI PENDAPATAN PAJAK KENDARAAN BERMOTOR MENGGUNAKAN ALGORITMA MARKOV CHAINS (STUDI KASUS : UPT SAMSAT PEKANBARU KOTA)
    (Elfitra, 2023-10) Simbolon, Adriano Megumi; Alfirman, Alfirman
    Motor Vehicle Tax is direct regional income to pay for services or to issue certain permits that are specifically granted by the regional government for the benefit of individuals or organizations. Considering the large contribution of motor vehicle tax as a source of Regional Original Income income, the government has made many efforts to increase the amount of motor vehicle tax revenue. UPT SAMSAT Pekanbaru Kota as one of the community service units in fulfilling motor vehicle tax does not yet have accurate calculations in calculating the potential increase in PKB income, resulting in the motor vehicle tax revenue target not being achieved optimally. The aim of this research is to create a web-based system that can predict the income of motor vehicle tax UPT SAMSAT Pekanbaru Kota in the future. The data used in this research is data from 2010-2023. Based on the research results, it is obtained that PKB income in 2023 is 6.27% in January, 5.76% in February, 6.81% in March, 6 .92% in April, 7.34% in May, 7.69% in June, 8.32% in July, 8.84% in August, 9.79% in September, 10.24% in October, 10.43% in November, 11.58% in December with a MAPE error value of 13% and RMSE of 0.12666.
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    SISTEM PAKAR PENDETEKSI KERUSAKAN PADA SEPEDA MOTOR MATIC INJEKSI MENGGUNAKAN METODE FORWARD CHAINING BERBASIS WEB
    (wahyu sari yeni, 2019-08-15) Sitanggang, Dikha Friasi; Alfirman, Alfirman
    The development of the automatic injection motorcycle industry in Indonesia has experienced significant development. With the many users of automatic injection motorcycles make problems that is not all users of automatic injection motorcycles have the ability to know the damage and solutions to repair the damage. So that is needs to create a expert system to detect the damage to automatic injection motorcycle using forward chaining method based on web. The system created, designed using UML diagrams, makes the system using the PHP programming language and MariaDB database. The results of this research are expert systems for detecting damage to automatic injection motorcycles using forward chaining method based on web, which can be used to help people determine the damage and solutions to motorcycle injection
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    SISTEM PAKAR UNTUK DIAGNOSA HAMA DAN PENYAKIT PADA TANAMAN ALLIUM ASCALONICUM L (BAWANG MERAH) MENGGUNAKAN METODE CERTAINTY FACTOR
    (perpustakaan UR, 2021-07) Hanif, Alex Chandra; Alfirman, Alfirman
    Shallots are one of the main cooking seasonings originating from Iran, Pakistan, and the mountains to the north. Shallots contain vitamin C, potassium, fiber, folic acid \ calcium and iron. Shallots also contain natural growth regulators in the form of auksin and giberelin hormones. The handling of shallot plants always encounters obstacles, one of which is pest and disease attacks. Pest and disease attacks require quick and correct handling, because this can harm farmers of shallot crops and can have an influence on production of shallots. Therefore, an expert system was created to solve the problem using the web-based certainty Factor method. The results of certainty factor method was calculated in a form of the diagnosis of pests and diseases in onion plants, as well as the first solution to overcome the attacks. This expert system could help users to conduct early detection and know the temporary diagnosis of pests and diseases in onion plants
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    SISTEM PENDUKUNG KEPUTUSAN PEMILIHAN SISWA TERBAIK MENGGUNAKAN METODE SIMPLE MULTI ATTRIBUTE RATING TECHNIQUE (SMART)
    (2020-09) Anggraini, Mulia; Alfirman, Alfirman
    This researche discusses the best student selection program at SMKN 1 Bangkinang. The purpose of this research is to create a Decision Support System (SPK) for selecting the best student using the Simple Multi Attribute Rating Technique (SMART) method so that the selection of the best student is computerized. This system is built with the PHP programming language, MySQL as the database server, and UML as the system design. The results obtained in this study are the best student ranking seen based on the total value of all the criteria value from the results of manual calculations and according to the system generated.