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INDONESIA
JURIKOM (Jurnal Riset Komputer)
Published by Sekolah Tinggi Manajemen Informatika dan Komputer Budi Darma
ISSN : 2407389X     EISSN : 27157393     DOI : http://dx.doi.org/10.30865/jurikom.v7i1.1927
Core Subject : Science, Engineering,
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering
JURIKOM (Jurnal Riset Komputer) membahas ilmu dibidang Informatika, Sistem Informasi, Manajemen Informatika, DSS, AI, ES, Jaringan, sebagai wadah dalam menuangkan hasil penelitian baik secara konseptual maupun teknis yang berkaitan dengan Teknologi Informatika dan Komputer. Topik utama yang diterbitkan mencakup: 1. Teknik Informatika 2. Sistem Informasi 3. Sistem Pendukung Keputusan 4. Sistem Pakar 5. Kecerdasan Buatan 6. Manajemen Informasi 7. Data Mining 8. Big Data 9. Jaringan Komputer 10. Dan lain-lain (topik lainnya yang berhubungan dengan Teknologi Informati dan komputer)
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 1,069 Documents
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Implementasi Algoritma Apriori Untuk Menentukan Pola Pembelian Produk Moch. Dwi Febrianto; Aji Supriyanto
JURIKOM (Jurnal Riset Komputer) Vol 9, No 6 (2022): Desember 2022
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/jurikom.v9i6.5230

Abstract

Flanker Distro or known as Flanker Flag Shop is one of the names of distros engaged in the sale of various types of racing-themed t-shirts, jackets and hats. The problem that occurs in Flanker distro is that sales patterns have not yet been formed, making the owner experience difficulties in determining what products must be provided at a certain time and the stored transaction data is only used as an archive, even though the transaction data can be processed and used as useful information to determine future business strategy. With the large number of existing sales transaction data, it will be difficult if the data is analyzed manually, so to overcome this problem a system is needed to process the data automatically so that it is easy to get sales patterns. The results of this processing will produce transaction information to help determine product sales patterns. The implementation will be made in the form of a web application that uses the UML (Unified Modeling Language) modeling method and the a priori algorithm by providing relationships between items in sales data. In this case, it is a product purchased by a consumer so that a consumer buying pattern will be obtained. The application of the Apriori Algorithm helps in forming possible item combination candidates, then testing whether the combination meets the minimum support and confidence parameters which are the threshold values given by the user. The test was carried out with monthly Flanker distro transaction data from January to July 2022 with a total of 316 sales transaction data. The results of the analysis are obtained after calculating the association rule using the minimum support rule of 5 and a minimum confidence of 30%. So that later it will produce information that can be the basis for Flanker distro owners to determine business strategies and carry out product production in the following months, semesters and years.
Sistem Pengambilan Keputusan Pemberian Kredit Pemilikan Rumah Menerapkan WASPAS Sitti Nur Alam
JURIKOM (Jurnal Riset Komputer) Vol 9, No 6 (2022): Desember 2022
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/jurikom.v9i6.5240

Abstract

Decision Support System (DSS) is an interactive information system that provides information, models and manipulates information, or helps someone make accurate and targeted decisions. So a decision support system is needed to determine the eligibility of customers to take home equity loans (HPR). In this study, the Comprehensive Assessment Method or WASPAS is used to determine the eligibility of prospective mortgage holders. Several criteria are used to make decisions, including age, income, debt, occupation, and credit rating.
Evaluasi Pengalaman Pengguna Aplikasi SIMARIS UPN “Veteran” Jawa Timur Menggunakan Metode UEQ Anisa Rahma Salsabila; Tri Lathif Mardi Suryanto; Eristya Maya Safitri
JURIKOM (Jurnal Riset Komputer) Vol 9, No 6 (2022): Desember 2022
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/jurikom.v9i6.5068

Abstract

The implementation of information and communication technology in a university is increasing according to the needs of each university. Research and community service activity carried out by lecturers at UPN "Veteran" East Java have been accommodated by an application called SIMARIS. In its implementation, this application still has several complaints related to the user experience felt by lecturers, such as difficulties when viewing proposal details, limitations for uploading files, no preview feature to view files, and the reviewer assessment menu doesn’t work for lecturers. In this study, the user experience of SIMARIS application was evaluated using the User Experience Questionnaire (UEQ) method. The questionnaire data obtained will be analyzed using UEQ Data Analysis Tool. The measurement results show that each scale has a high mean value with the scale of Attractiveness 1.61, Perspicuity 1.52, Efficiency 1.64, Dependability 1.44, Stimulation 1.51, and Novelty 1.25. The consistency level of all scales shows that Cronbach's Alpha value > 0.70. This means a high level of consistency is owned by all scales.
Grey Forecasting Model Untuk Peramalan Harga Ikan Budidaya Muhammad Shodiq; Bagus Dwi Saputra
JURIKOM (Jurnal Riset Komputer) Vol 9, No 6 (2022): Desember 2022
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/jurikom.v9i6.5120

Abstract

Price is an important factor to consider because it determines the profit or loss from selling a product. The difficulty of controlling the volatility of fish prices is related to many factors, including stock availability, natural factors, and the level of demand. One way to solve the problem of fish price volatility is to predict fish prices in the future. The purpose of this study is to apply the gray forecasting method to forecasting fish prices, especially in the aquaculture industry. Gray forecasting is a method for creating forecasting models with a small amount of data that provides accurate forecasts. This study uses daily data on prices of Tilapia fish for the period of June 2022 for analysis of gray forecasting calculations. The results show that gray forecasting provides very accurate predictions with aa mafe value of 2.39% of the price of Tilapia fish
Identifikasi Kematangan Buah Menggunakan Metode Gray Level Co-occurence Matrix pada Citra Digital Arnes Sembiring; Sayuti Rahman; Mufida Khairani; Ilham Faisal; Sri Eka Riyani Harahap; Muhammad Zen
JURIKOM (Jurnal Riset Komputer) Vol 9, No 6 (2022): Desember 2022
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/jurikom.v9i6.5163

Abstract

In the current era of information technology, the use of images is widely applied in various aspects of life. Some of the uses of image processing include the fields of military, medicine, education, agriculture and so on. One example of the use of image processing that will be discussed in this study is in the agricultural sector. Farmers can take advantage of technology in selecting fruit with the appropriate maturity level. In terms of selecting fruit based on the level of maturity, some fruit farmers still use the conventional method or with the human sense of sight, namely the eye. Therefore, this study was conducted for preliminary research that can change the conventional method into system that uses technology that makes a computerized way of identifying fruit maturity levels. The system that will be used to identify fruit maturity uses the Gray Level Co-occurance Matrix method on digital images and Euclidean Distance as a classification method. This application is built using MatLab 2019a programming. The test results show that the Gray Level Co-occurance Matrix and Euclidean Distance methods can be used to identify the ripeness of guava, oranges, bananas, papayas and mangoes into three categories, namely raw, unripe and ripe. The Gray Level Co-occurance Matrix and Euclidean Distance classification methods succeeded in identifying fruit maturity with an overall success rate of 87%.
Perbandingan Sistem Pendukung Keputusan Menggunakan Metode WP Dan TOPSIS Studi Kasus Program Keluarga Harapan (PKH) Desa Kampung Kramat Arya Dimas Setiadi; Agung Triayudi; Agus Iskandar
JURIKOM (Jurnal Riset Komputer) Vol 9, No 6 (2022): Desember 2022
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/jurikom.v9i6.5358

Abstract

PKH or the Family HopehProgram that is a conditional social assistance program for poor families as the initial basis for achieving family happiness which is a long-term problem. Therefore, the government introduced the Family Hope program (PKH) to reduce poverty. The Family Hope Program (PKH) is a social policy that provides social services in the form of cash and basic necessities to poor families who depend on school children and pregnant women for their lives. Family hope in the future, family poverty alleviation is a form of social investment in poverty alleviation. In this case, the Family Hope Program (PKH) was established in Kramat village as a forum to increase socialization and poverty alleviation. A decision support system (DSS) will be built using the weighted product (WP) method and a priority control technique similar to the ideal solution (TOPSIS) to calculate the problem
Xiaomi Smartphone Sentiment Analysis on Twitter Social Media Using IndoBERT Priyan Fadhil Supriyadi; Yuliant Sibaroni
JURIKOM (Jurnal Riset Komputer) Vol 10, No 1 (2023): Februari 2023
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/jurikom.v10i1.5540

Abstract

The extraordinary evolution of technology has resulted in smartphones becoming important devices in people's daily lives. As a result, today's smartphones impact many people's lives, with more and more people owning smartphones. One of the most popular smartphone products today is Xiaomi. This popularity cannot be separated from various opinions on Twitter. Twitter is a social media that makes it easy for people to express their opinions regarding Xiaomi products called sentiment. Sentiment analysis is needed to classify various opinions on Twitter into positive, neutral, and negative classes. This study aims to analyze the sentiment of public opinion on Xiaomi smartphone products on Twitter social media. The models used in this study were BERT and IndoBERT because they produced a good performance in previous studies. This study's stages of work consisted of collecting, preprocessing, separating training and test data, building models with BERT and IndoBERT to detect sentiment, and carrying out training and testing stages. Test results using IndoBERT get a very good accuracy value with an accuracy value above 90%. The sentiment classification results for Xiaomi smartphone products show that positive sentiment on batteries has a greater number, with a positive percentage of 78%. In comparison, neutral sentiment is 4%, and negative sentiment is 18%. Furthermore in the camera aspect, positive sentiment has a greater number, with a positive percentage of 68%, while neutral sentiment is 18% and negative sentiment is 14%. Moreover, on the screen, positive sentiment has more numbers, with a positive percentage of 67%, neutral sentiment is 10%, and negative sentiment is 23%. Last, in the ram aspect, positive sentiment has a greater number with a positive percentage of 76%, while neutral sentiment is 17% and negative sentiment is 7%. The highest number of positive sentiments is in the camera aspect, which has 1935 positive sentiments from 2830 data. The sentiment analysis results can be used as an evaluation along with insights for the Xiaomi company so that in the future, the company can maintain and even improve the quality of the aspects that smartphone users like about Xiaomi products, namely cameras.
Penerapan Metode K-Nearest Neighbor pada Sentimen Analisis Pengguna Twitter terhadap KTT G20 di Indonesia Herda Andriana; Shofa Shofia Hilab; Agustia Hananto
JURIKOM (Jurnal Riset Komputer) Vol 10, No 1 (2023): Februari 2023
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/jurikom.v10i1.5427

Abstract

Indonesia will host the KTT (Konferensi Tingkat Tinggi) G20 summit on the island of Bali on November 15, 2022. The G20 was formed with one goal in mind: to boost the global economy, which had just entered a period of crisis. However, Indonesia's participation as a full member of the Group of Twenty (G20) has sparked controversy among the country's general populace and the population of Indonesia itself, necessitating a thoughtful analysis of the group's motives. Sentiment analysis was gleaned from tweets on KTT G20 posted on the social media platform Twitter. Data scraping yielded a total of 2,500 tweets for inclusion in the collection. Methods for classifying tweets into positive, neutral, and negative groups are required because of the large amount of data that has already been collected. The purpose of this study was to analyze public opinion on Twitter during the KTT G20. The data was processed using the Orange neural network using a number of tools and the K-Nearest Neighbor method, yielding a total of 1,107 tweets that were successfully added to the original set, with an average recall and precision of 99%. According to the analysis of sentiment, there were 89 negative tweets, 614 neutral tweets, and 404 positive tweets, with the most common emotions being happiness, surprise, and fear
Comparative Analysis of Naive Bayes Model Performance in Hate Speech Detection in Media Social Twitter Muhammad Hadyan Baqi; Yuliant Sibaroni; Sri Suryani Prasetiyowati
JURIKOM (Jurnal Riset Komputer) Vol 10, No 1 (2023): Februari 2023
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/jurikom.v10i1.5493

Abstract

Twitter is a popular social media in Indonesia, and for some people, it is a place to find and disseminate information. Hate speech is aggressive behavior against individuals or groups such on race, gender, religion, nationality, ethnicity, sexual orientation, gender identity, or disability. In this study, hate speech is modeled using Naive Bayesian models, which consist of Multinomial, Bernoulli, and Gaussian Naïve Bayes Models. These methods were chosen because Naïve Bayes is a simple method but has good performance in the case of sentiment analysis. This research aims to get the method with the highest accuracy value in analyzing hate speech. Thus, the Naïve Bayes model can provide the best solution for hate speech problems. The process carried out in this study is to process all data which obtained from Twitter social media and then classify it using the Multinomial Naïve Bayes, Gaussian Naïve Bayes, and Bernoulli Naive Bayes models based on the classification of HS and non-HS sentiment categories.  In this study, to get the best accuracy, two different scenarios were used. The result of the analysis of the accuracy is 82.13% of the Multinomial Naïve Bayes model which is the best accuracy rate value compared with other models.
Rancang Bangun Sistem Informasi Pengadaan Barang Menggunakan Teknologi Cloud Computing Deni Hardiansyah; Ade Priyatna
JURIKOM (Jurnal Riset Komputer) Vol 10, No 1 (2023): Februari 2023
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/jurikom.v10i1.5580

Abstract

Cloud computing or what is commonly called cloud computing is being widely discussed in this digital era, the ease of procuring servers is very helpful in the system design process within an organization or company in implementing it, PT Arcelon uses this technology in building a procurement information system to speed up the development stage, procurement of goods and management of goods in and out of goods is currently still in a manual process so a goods procurement information system is needed in the form of a web that can be accessed from the internet network to be able to process and make reporting in every transaction in and out of goods, PT Arcelon has a problem in build a system into a server, by buying a very expensive server, long installation and procurement time, and maintenance that is done often causes a problem, such as an electric short circuit when carrying out maintenance, hindering ongoing business processes in carrying out system deployments that are being carried out because it requires a Cloud Computing technology to bridge this where the system development model that will be used is the waterfall SDLC model (waterfall) by utilizing cloud technology which can guarantee very high server availability. high and can serve many requests from many users under certain conditions. The results of the study show that the system built makes it easier for companies to carry out transactions both procurement, checking, and entering and leaving goods.

Page 74 of 107 | Total Record : 1069

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