DSpace Repository :: Browsing by Author "Salambue, Roni"

Browsing by Author "Salambue, Roni"

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ANALISIS KUALITAS KUAT SINYAL JARINGAN INTERNET 4G DI PERAWANG DENGAN METODE DRIVE TEST DAN QOS
(2020-11) Syahri, Muhammad Desky; Salambue, Roni
4G LTE is successful in supporting the effectiveness and efficiency of everyone's work in carrying out work such as sending e-mails, sharing files, downloading, buying and selling online and others in Perawang, Tualang District. Drive Test and Quality of Service (QoS) are methods to measure how well the network is and to define the characteristics and properties of a service. Drive Test can be implemented more easily by using the GNet Track Pro software. This research used stages, starting from measuring signal strength (RSPR), signal quality (RSRP), average noise and interference (SINR) using GNet Track Pro software for downlink and uplink, delay and jitter, we used nPerf software on Telkomsel, Tri, XL Axiata and Smartfren providers. The results of the analysis show that 13 eNodeBs were detected on Telkomsel provider, 11 eNodeB on Tri provider, 11 eNodeB on XL Axiata provider and 12 eNodeB on Smartfren provider. Overall, in the Perawang area, Tualang District, Tri opearator was more stable than the other operators with RSRP values -87 dBm, RSRQ -14 dB, SINR 0.2 dB, Downlink 11.72 Mbps, Uplink 12.23 Mbps, 58 ms Delay and 25 ms Jitter.
ANALISIS PENENTUAN DOSEN PEMBIMBING SKRIPSI MAHASISWA MENGGUNAKAN NAIVE BAYES CLASSIFIER
(2020-09) Rahayu, Sri; Fatayat, Fatayat; Salambue, Roni; Aminuddin, Al
Determination of the mentor lecturer for students is very influential in completing the final task. Lecturers who are competent and in accordance with the field of student's final assignment able to direct of the student's final assignment. In this thesis, text mining is used to classify the appropriate guidance lecturers for students in completing the final assignment. Classification is applied to the title of the student's final assignment based on experience and field of mentor lecturers. The algorithm used naive bayes classifier algorithm. Before the data classification processed at the text preprocessing stage, which consist of case folding, stopcharacter removal, stopword, stemming, and weighted. Evaluation to measure the accuracy of this system using confussion matrix which resulted in 78% accuracy in mentor lecturers and generate acuration of 95% in field of expertise.
ANALISIS PENGUKURAN KUALITAS LAYANAN JARINGAN INTERNET JURUSAN ILMU KOMPUTER UNIVERSITAS RIAU MENGGUNAKAN METODE QoS DAN RMA
(wahyu sari yeni, 2019-04-30) Arianto, Yogi; Salambue, Roni
Internet networks are very important in this era of globalization. The University of Riau's Department of Computer Science is one of the departments that uses internet networks to support the effectiveness of work, access the information needed, and access social media applications to communicate. The internet network used by the University of Riau's Computer Science Department is internet service from Telkom. Quality measurement needs to be done in order to find out the level of quality of the internet that has been provided given the importance of the current role of the internet. The method used to measure the quality of the internet network is QoS and RMA. In this method, NetTools and PRTG software is needed. For Bandwidth the highest average value on staff accounts is 2.791.264 bit / s with an average Delay of 4 m / s with the category "Very Good" and the average Packet Loss of 3.29% with the category "Good". For the RMA method the value of the Availibility uptime and downtime method gets the highest value on the first day reaching 169.14%.
ANALISIS PERBANDINGAN KESUKSESAN APLIKASI GOJEK DAN GRAB DI KOTA PEKANBARU DENGAN MODEL DELONE DAN MCLEAN
(Elfitra, 2023-01) Deriska, Windi Heliana; Salambue, Roni
In this study, a comparative analysis of the success of the Gojek and Grab applications was carried out which aims to measure the success of the Gojek and Grab applications. Competition from the two companies makes potential consumers or the general public confused about having to choose one of these applications, so it is necessary to carry out a comparative success analysis to see what factors produce good benefits for users using the DeLone and McLean information system success models to measure the success of the Gojek and Grab applications. The results of this study indicate that user satisfaction is a factor influencing net benefits, meaning that satisfaction with the information and services provided by Gojek and Grab produces good benefits for users, namely increased productivity, experience, knowledge and communication effectiveness for users.
ANALISIS POLA PEMBELIAN PRODUK TOSERBA MENGGUNAKAN ALGORITMA FP-GROWTH
(Elfitra, 2023-07) Nurhamijan, Nurhamijan; Salambue, Roni
Advances in technology make business people try to use it to facilitate and advance their business. In line with the development of consumer purchasing power, it requires business people to implement marketing strategies that are better than their competitors. To create a strategy, certain information is needed as material for consideration in making decisions, like determining sales strategies that can utilize information. from a collection of sales transaction data from the Senyum 5000 department store using data mining. Data mining is carried out to analyze the associations between products on the repeat transaction data, while the associations rule technique and the FP-Growth algorithm are part of the data mining used to determine the candidate combinations. The purpose of this study is to determine the result of applying the FP-Growth algorithm to analyze product purchase patterns, find product purchasing rules using the FP-Growth algorithm. This research was conducted on 3,165 transaction data in April-June 2022 with a support value 1% and a confidence value 50% using the Python programming language. The frequent itemset obtained is 17 and the association rules obtained were 21. The association rules obtained were then formed a selling strategy.
ANALISIS SENTIMEN MASYARAKAT TERHADAP ISU RANCANGAN UNDANG-UNDANG OMNIBUS LAW PADA DATA TWITTER MENGGUNAKAN METODE SVM
(Elfitra, 2022-07) Indrikh, Hafidz Wandrifo; Salambue, Roni
Omnibus Law is a law that is made to target one big issue that may be able to revoke or amend several laws at once so that it becomes simpler. The government's decision to combine several laws to be further simplified into an Omnibus Law has generated various responses from the public. Some of the community responses agreed or supported the results of the decision, and others did not agree. To find out the response from the public to government regulations regarding the omnibus law, Twitter is a good medium to see it through tweets from Twitter users, whether the comments given are positive, negative, or neutral comments. By classifying these comments into a data mining method, namely Support Vector Machine (SVM). The results of the application of the support vector machine method in classifying public sentiment data against the Omnibus Law Bill resulted in 5 combinations of data testing. The distribution of data of 90% : 10% produces the highest level of accuracy, which is 81%, while the distribution of data of 50% : 50% produces the lowest level of accuracy, which is 73%. Data sharing is very influential on the level of accuracy, where more and more test data can affect the results of a prediction so that it gets high accuracy
DETEKSI KOMENTAR SPAM PADA MEDIA SOSIAL INSTAGRAM MENGGUNAKAN METODE NAÏVE BAYES
(wahyu sari yeni, 2019-01-31) Andriani, Sela; Salambue, Roni
Text Mining is the process of finding new information or trends that were previously not revealed by processing and analyzing large amounts of data. In this thesis text mining is used to classify comments on Instagram social media. This technique aims to distinguish spam and not spam comments. One of the algorithms used in the classification is Naïve Bayes Classifier (NBC). In the NBC method, there are two stages, they are Training stage and the Testing Phase. Before the classification is done first the data will go through the Preprocessing stage, in which there are casefolding, stopcharacter removal, stopword, stemming and weighting. Evaluation to measure accuracy using Confussion Matrix which produces 93% Accuracy, 92% Precision, Recall 93.87% and Error Rate 7%.
DETEKSI PLAGIARISME PADA TUGAS MAHASISWA UNIVERSITAS RIAU BERDASARKAN KEMIRIPAN ISI TEKS MENGGUNAKAN ALGORITMA LEVENSHTEIN DISTANCE
(Elfitra, 2023-06) Wanda, Annisa Fitri; Salambue, Roni
There are many students and college students in Indonesia who commit plagiarism. In addition to online sources, students often plagiarize other students' assignments or writings. This is very worrying. Teachers and educators must take real measures to prevent plagiarism from taking root in the world of education. The purpose of this research is to apply the Levenshtein Distance Algorithm to a computer application that can calculate the percentage similarity of the textual content of student working documents to help faculty identify initial plagiarism allegations. The study was conducted at the Department of Information Systems, Faculty of Mathematics and Science, Riau University. This study creates a system that can detect the degree of similarity between text documents using the Levenshtein distance algorithm by adding a pre-processing process. The string matching process of this algorithm can produce a distance value that defines a weighted percentage of similarity. The system will display exam results with a percentage of at least 70% or serious plagiarism. The test results show that the Levenshtein distance algorithm can be implemented into the system after the pre-processing steps and is suitable for detecting initial word-for-word plagiarism claims.
EVALUASI TATA KELOLA TI RSUD SELASIH KABUPATEN PELALAWAN PADA DOMAIN DSS MENGGUNAKAN FRAMEWORK COBIT 5
(Elfitra, 2022-04) Anggraini, Widya Putri; Salambue, Roni
In its activities, RSUD Selasih applies an information system to facilitate work in terms of administration and data management. However, there are issues surrounding operational activities related to the technology used, such as users who do not understand the use of the system so that sometimes they still rely on books. IT governance evaluation needs to be carried out to determine the current state of IT management from the level of capability in delivering IT support to users in order to provide excellent service to customers. Evaluation using the COBIT 5 framework in the DSS domain. The results showed that the assessment of IT governance capabilities in Selasih Hospital which was carried out in the DSS domain process was obtained at level 1, which means that the activity process in the DSS domain had been carried out to achieve the process objectives but had not been managed properly.
FORECASTING PERSEDIAAN SUKU CADANG ALAT BERAT MENGGUNAKAN METODE SINGLE EXPONENTIAL SMOOTHING
(Elfitra, 2022-12) Sitohang, Raka Giasta Mandani; Salambue, Roni
PT. Pandawa Perkasa Surya is a company engaged in the rental of heavy equipment and heavy equipment contractor services. One of the services provided by PT. Pandawa Perkasa Surya is in the form of heavy equipment maintenance. Forecasting stock of spare parts is important in a heavy equipment rental company because by using forecasting the company can predict the number of spare parts that must be in the warehouse. In this research, how to apply the Single Exponential Smoothing method to a web-based application so that it can be used to predict the required spare parts inventory each month. Based on the results of the experiments and evaluations carried out, it can be concluded that the supply of spare parts needed in Januari was Filter = 151,182 , Seal = 59.57 , Oring = 81,81 , Engine = 49,16, Fuel System = 42,15 , Undercarriage = 182,2 , Dinamo = 3.999, Bolt = 383,3 , and Hose = 346,3.
IMPLEMENTASI ALGORITMA MAXIMAL FREQUENT PATTERNS UNTUK MENGANALISIS POLA PEMBELIAN OBAT (STUDI KASUS: RSUD ARIFIN ACHMAD)
(perpustakaan UR, 2021-11) Candra, Yola Elliya; Salambue, Roni
Drug purchase transaction data are very valuable treasure in sales. Drug purchase transaction data are used to generate new knowledge in the transaction database. Drug purchase transaction data can be managed using the data mining association rules method. The aim of the study was to apply maximal frequent patterns algorithms to analyze a patient's drug purchase patterns, look for drug combinations purchased simultaneously by patients, apply the fp-max association rules algorithm to get rules by testing the minimum support and minimum confidence desired, and knowing what variables can affect the association. Drug purchase transaction data were processed by the data mining method association rule technique using the fp-max algorithm. Drug purchase transaction data were tested as much as 1909 data with a minimum support of 1% and minimum confidence of 20% which resulted in 8 rules with a lift ratio value of 1 as many as 2 rules. While testing using a minimum support of 2% and so on does not produce rules because no frequent itemset were produced. Testing lift ratio on 8 rules concluded no value is worth more than 1, meaning there were no rules that showed a strong dependence between antacedent and consequence so it can not be used as a recommendation or prediction of the emergence of a drug due to the emergence of other drugs. The amount of support count value affected the number of frequent items formed and the high minimum confidence limit affects the rules produced
IMPLEMENTASI DATA MINING PADA PEMBELIAN PRODUK KAFE DENGAN ALGORITMA ECLAT
(perpustakaan UR, 2021-11) Ridarto, Maisya Sabrina; Salambue, Roni
Seiring dengan perkembangan zaman, persaingan di dunia bisnis pun semakin ketat. Para pelaku bisnis berlomba-lomba untuk menarik pelanggan dan memenuhi tuntutan pasar. Salah satu cara untuk memenuhi keinginan pelanggan dan tuntutan pasar yaitu dengan menganalisis pola pembelian pelanggan. Pola pembelian tersebut dapat menjadi salah satu strategi bisnis yaitu dengan mengetahui kombinasi item apa saja yang sering dibeli oleh pelanggan secara bersamaan, lalu berdasarkan rules tersebut dibuat rekomendasi menu paket berdasarkan pola pembelian pelanggan sehingga sesuai dengan keinginan pelanggan. Pola pembelian pelanggan dapat diketahui dengan mengolah data transaksi penjualan. Pengolahan data transaksi penjualan dilakukan dengan metode data mining dengan teknik association rules dengan menggunakan algoritma Eclat. Hasil dari pengolahan data transaksi penjualan tersebut berupa rules yang dapat dijadikan rekomendasi menu paket sehingga dapat menarik minat dan keinginan pelanggan dalam membeli suatu produk.
KLASIFIKASI KEMATANGAN BUAH SAWIT DENGAN JARINGAN SYARAF TIRUAN METODE PERCEPTRON
(2020-12) Ningsih, Isma Fitria; Salambue, Roni
The development of digital image processing science makes it possible to sort and sort the maturity level of oil palm fruit with the help of image processing applications. Image processing techniques are another form of visual observation. Currently, the process of determining mortality is still using traditional methods, namely looking at the number of loose fruit and falling from the fruit bunches and the color of the fruit on the bunches. This study aims to design a system using the perceptron method, measure the accuracy of the system and measure the correlation between the color of the oil palm fruit and the level of maturity. The data used is a digital image in JPG format by extracting the RGB and HSV values. The sample used was palm fruit which presented 2 levels of maturity which were grouped into 5 fractions, namely F00, F0 categorized as raw fruit, F1, F2 and F3 categorized as ripe fruit. The amount of input data used amounted to 50 palms then processed using the single layer perceptron method and using the sigmoid bipolar and maximal epoh activation functions used were 30 where 10 data were for the training process and 30 data were for the testing process. The output produced is raw and ripe palm fruit. The success rate in experiment 1 using flash was 55% and the success rate in experiment 2 without flash resulted in an accuracy of 80%
KLASIFIKASI KEMATANGAN TANDAN BUAH SEGAR (TBS) KELAPA SAWIT DENGAN BIO SPECKLE IMAGING MENGGUNAKAN METODE K-MEANS CLUSTERING
(wahyu sari yeni, 2019-04-30) Fahlawi, Ahmad Reza; Salambue, Roni
This study was focused to identify the ripeness level of oil palm Fresh Fruit Bunch (FFB) using image processing. Laser Speckle imaging (LSI) is used as an optical method to find out bio-speckle activity. Image acquisition was obtained by laser illuminating the fruit and the light beam of the fruit would be recorded. Digital image feature extraction produced an average value, standard deviation and contrast from image pixel. The contrast value was obtained from the comparison between the standard deviation and the mean value. Data would be classified using the k-means algorithm based on contrast value into 3 clusters that is unripe, ripe, and overripe. The results of the research had shown that in the second experiment with 90 sample data with various levels of ripeness it produces 71% accuracy, with 64 sample data identified correctly. In the third experiment with 64 sample data with relevant contrast values resulting 100% accuracy which means all data was identified correctly
KLASIFIKASI PEKERJAAN SUMUR MINYAK DI PT PERTAMINA HULU ROKAN MENGGUNAKAN METODE RANDOM FOREST
(Elfitra, 2023-08) Noviani, Puti Melani; Salambue, Roni; Wilantara, Dedi
The oil well anomaly detection system has been running for 7 years, generating a large and complex dataset consisting of indications of oil well issues along with recommendations for oil well operations by petroleum engineers, commonly referred to as big data. However, the system has limitations as it can only display indications of well issues, requiring manual review by petroleum engineers to determine suitable well operation recommendations based on the data. Additionally, the number of petroleum engineers at PT Pertamina Hulu Rokan is limited, making it challenging to review all well issue indications, making it difficult to review all well indications. The objective of this research is to classify oil well operation data using the Random Forest method. The random forest model works by constructing multiple decision trees, combining them, and producing several classes, which are then aggregated to determine the final class. Performance of the model in classifying oil well operation data using the Random Forest method with 5 target data labels resulted in an accuracy of 0.66%. The model was processed by filling missing values with the median, not removing outliers, applying Oversampling techniques, normalizing the data using MinMax Scaler, and dividing the data using K-Fold Cross Validation with k=10.
PENERAPAN FORECASTING TERHADAP JUMLAH PENGUNJUNG KLINIK PRATAMA TIGA PERMATA MENGGUNAKAN METODE DOUBLE EXPONENTIAL
(2020-10) Puspaningrum, Tyas Endah; Salambue, Roni
Predicting clinic visitors within one year is an important role so that clinic owners can find out the number of visitors who will seek treatment at the clinic. From this problem, it seems that the Pratama Tiga Permata clinic needs a system that can provide information about predictions of visitors to the clinic. This journal explains the process of making "The application of forecasting on the number of visitors to the Pratama Tiga Permata clinic using the double exponential smoothing method. In the calculation phase, two stages are carried out, namely the calculation and testing phase, as well as the manual calculation results and system testing to produce the same output, so that the resulting prediction is to determine the prediction of the number of visitors in the following year, namely 2019. The number of predictions uses the alpha value 0.1 General patient is 1002 by measuring the error rate using MAD 8.8, MSE 118, and MAPE 0.87%
PENGGUNAAN ALGORITMA APRIORI UNTUK MENEMUKAN POLA PEMINJAMAN BUKU DI PERPUSTAKAAN UNIVERSITAS RIAU
(2021-01) Nafiah, Nuri Ilma; Salambue, Roni
The Library of University of Riau provides various kinds of reading material such as journals, literature lecture modules, final project reports, and others. It provides a book search catalog feature to make it easier for visitors to borrow books based on book numbers and locker numbers without having to search it manually. Library visitors can borrow more than one book at a time. However, sometimes the borrowed book lockers are located far from another books. By because it is, the library must develop a variety of strategies in order to facilitate visitors to borrow books it simultaneously. One of the strategies that can be done is to analyze the pattern of borrowing books and give a recommendation of borrowing as well as the placement of books most many borrowed. The pattern of borrowing books is processed using the method of data mining association rule and algorithm priori to analyze the association between books were borrowed and determine the candidate combinations of the book are often borrowed. Research is conducted on 8237 the data transactions in a month from January to June 2019 with the value of minimum support 0,3% and minimum confidence of 30%. This research results in a combination of 5 rules of books, where the book with code B091371529 entitled Banking Law: Textbook will borrow a book with code B091361590 entitled Banking Law: an overview of money laundering, mergers, liquidations and bankruptcy with a support value of 0,004 = 0,4% and a value confidence 0,41 = 41%. The results of the interpretation of these rules can be used as a reference for placing recommendations and recommendations for borrowing books, namely books with code B091371529 and B091361590 placed on a bookshelf close together to make it easier for visitors to find and borrow the book simultaneously.
PREDIKSI DIAGNOSIS PENYAKIT JANTUNG MENGGUNAKAN METODE RANDOM FOREST
(Elfitra, 2022-11) Ferdian, Ferdian; Salambue, Roni
throughout the body. Heart health must be maintained because the mortality rate caused by heart disease is among the highest in the world. So early action is needed to predict the diagnosis of heart disease as a form of prevention or treatment efforts so that there is no increase in cases of heart disease. Therefore, a system is needed that can help predict the diagnosis precisely and accurately and on time based on a computer. This study aims to build a prediction model for the diagnosis of heart disease using the Random Forest method. This prediction model uses the RSI Ibnu Sina medical record dataset of 336 data, including 268 used as training data and 68 testing data. The data attributes used were 11 attributes, namely gender, age, chest pain, systolic blood pressure, diastolic blood pressure, cholesterol, current blood sugar (GDS), RestingECG, heart rate, ST Slope, and diagnosis. This study produced a prediction model with an accuracy of 85.29% measured using the Confusion Matrix.
SISTEM INFORMASI GEOGRAFIS ANALISIS DAERAH RAWAN BANJIR MENGGUNAKAN METODE ANALYTICAL HIERARCHY PROCESS
(Elfitra, 2022-07) Desrian, Muhammad Anugrah; Salambue, Roni
Pekanbaru City is one of the areas in Indonesia that is included in a flood-prone area. It is even said that Pekanbaru City is included in the red zone related to flooding, judging from the majority of areas which are swamp areas and river banks. This study aims to determine the level of flood vulnerability in Pekanbaru City by using the Analytical Hierarchy Process (AHP) method, which is an analytical method that can calculate the relative level of a problem based on the weight of importance given to the criteria that affect the problem. The criteria used as variables in this study to determine the level of flood vulnerability in Pekanbaru City are rainfall, land use, and land height. The calculation of the flood vulnerability value by multiplying the weights of each criterion, results in the value of flood vulnerability at several points in Pekanbaru City. The final results of the analysis are displayed using a Geographic Information System (GIS) in the form of a map display of the level of flood vulnerability, which are Vulnerable, Moderately Vulnerable, and Not Vulnerable with different colors at each level.
SISTEM INFORMASI PEMBELIAN BUAH SAWIT
(Elfitra, 2022-07) Yuhendra, Ari; Salambue, Roni
Indonesia as an agricultural country has great potential in agriculture. The indicator is shown by the number of people who live from the agricultural sector. One of Indonesia's leading agricultural commodities is palm oil which is a source of income. This study aims to develop an information system for purchasing palm fruit and display geographical visualizations from the stakeholders. The stakeholders in this system are the Plantation Service, Palm Oil Mills and Cooperatives. The flow system starts from the Plantation Office determining the names of cooperatives that can trade and buy their palm fruit to PKS. The PKS party sets a quota of fruit that can be purchased and if the cooperative sells to the PKS exceeds the set quota, the system gives a warning to the PKS. The results showed that information on PKS and Cooperatives could be presented in tabular and visual form. The distribution of PKS, cooperatives, fertility information and land area can also be displayed in the form of a Geographic Information System using the Google Map API

Browsing by Author "Salambue, Roni"

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