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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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Penerapan Metode MOOSRA Dalam Seleksi Pengantaran Pemesanan Kue Online Menggunakan Pembobotan ROC Mohammad Aldinugroho Abdullah; Rima Tamara Aldisa
JURIKOM (Jurnal Riset Komputer) Vol 10, No 2 (2023): April 2023
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/jurikom.v10i2.6108

Abstract

Each cake shop certainly has its own website that can be used to order cakes and of course has its own advantages and disadvantages which can be used as an assessment of the quality of the application, such as the types of cakes provided vary at more affordable prices and even the existence of discounted prices makes consumers more interested in ordering cakes online. The large number of these applications makes service users confused about choosing a better application among the good ones, therefore a study was made that discussed techniques for solving these problems using a decision support system. In this study, there are two methods used in the SPK method, including the ROC method which is used as an arrangement of weights of importance on five features that are used as rules which include application usability, Rating Reviews, Promos (Discounts), Cake Menu and Handling Fees. The second method is the Multiobjective Optimization on the Basis of Simple Ratio Analysis (MOOSRA) method which will be used to select 8 online cake ordering applications by ranking each alternative based on predetermined criteria. The final result after applying the two SPK methods is that Akul cake delivery is declared the best online cake delivery application with a preference value of 38.012.
Sistem Informasi Pajak Reklame Menerapkan Metode Prototype Anisyah Dinda Mawadha; Suyanto Suyanto
JURIKOM (Jurnal Riset Komputer) Vol 10, No 2 (2023): April 2023
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/jurikom.v10i2.5640

Abstract

The Advertising Tax Information System is a system developed to assist the Palembang City Regional Tax Management Agency in managing advertisement tax data and information. This study aims to overcome the problems that exist in the current advertisement tax management system, where the advertisement tax payment process is still manual and inefficient, and difficulties in tracking advertisement tax payments and ensuring that all payments are made on time, therefore it takes a system that can control it all using information technology. Through this system, billboard tax payments can be made online and tax data can be managed more efficiently and accurately. This research uses a system development method using a prototype and is complemented by system analysis and design. The result of this research is a billboard tax information system that is able to simplify the payment process and tax data management, and has succeeded in increasing the accuracy of billboard tax data by 25%, from 80% to 95%. This system is expected to provide benefits for the Palembang City Regional Tax Management Agency and taxpayers in terms of time and cost efficiency which can make it easier for taxpayers, admins, and leaders to properly carry out registration, reporting, extension, and closing advertisement taxes
Redesign Website Pariwisata Berbasis User Centered Design (UCD) Diah Ayu Lestari; Hari Widi Utomo; Abednego Dwi Septiadi
JURIKOM (Jurnal Riset Komputer) Vol 10, No 2 (2023): April 2023
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/jurikom.v10i2.6096

Abstract

The development of information technology in Indonesia is growing rapidly in various existing sectors, including the tourism sector. The tourism sector is a sector in the field of government that has a great opportunity to increase the country's foreign exchange. The Government of Pemalang Regency through the Tourism, Youth and Sports Office (DISPARPORA) of Pemalang Regency has implemented website-based information technology to disseminate information about tourism and culinary objects in Pemalang Regency. This study aims to evaluate and redesign the website from a front-end perspective. Completeness of website content is still the main problem on the Pemalang Regency Tourism website. The User Centered Design (UCD) method was used in developing the design in this study, while the System Usability Scale (SUS) questionnaire was applied for evaluation. Evaluation was carried out twice to 96 respondents, where the first evaluation obtained an average SUS score of 67.43 and the second evaluation was 75.84. The results of this study proved that there was an increase in the average SUS score of 8.41, which means that the design improvements on the website can be well received by users
Shortest Path Clustering Dalam Menyaring Tingkat Kepadatan Arus Lalu Lintas Noni Selvia; Erlin Windia Ambarsari; Nurfidah Dwitiyanti
JURIKOM (Jurnal Riset Komputer) Vol 10, No 2 (2023): April 2023
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/jurikom.v10i2.5979

Abstract

This study explores the application of graph clustering in identifying and analyzing the shortest traffic-related routes. Graph clustering groups points (vertices) based on road attributes. The DBSCAN method and ant algorithm are applied to classify vertices based on traffic intensity and find the optimal shortest path. This case study focuses on the Tangerang Selatan region, resulting in three clusters and identifying seven noises. Two of the three clusters are selected to calculate the shortest distance, resulting in the sequence [7, 6, 0, 1, 2, 3, 4, 8, 5] and a distance of 0.2526. This research provides insights into how to graph clustering can be used to optimize traffic routes and is expected to serve as a foundation for further exploration
Komparasi Kinerja DenseNet 121 dan MobileNet untuk Klasifikasi Citra Penyakit Daun Kentang Umi Khultsum; Ghofar Taufik
JURIKOM (Jurnal Riset Komputer) Vol 10, No 2 (2023): April 2023
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/jurikom.v10i2.6047

Abstract

Potato plants are one of the plants that are included in horticultural commodities that are widely cultivated by farmers. Potatoes are the part produced from this plant and are the fourth largest agricultural food crop in the world after corn, wheat and rice. Potato plants are susceptible to attacks by various diseases in the leaf area, resulting in delays in potato production. This disease can be recognized by farmers visually, because the infected leaves have a different color and texture from healthy or fresh leaves. However, it was found that detection using the naked eye by farmers required more processing time and often gave inappropriate results. Methods in the field of image processing can be applied, namely by using pattern recognition or characteristics from the image of diseased potato leaves. Through this technique it is hoped that it can detect diseases on potato leaves correctly and accurately. Based on this description, this study aims to design a Convolution Neural Network (CNN) model and evaluate the performance of two architectures, namely DenseNet 121 and MobileNet. From the results of research conducted by the author on potato leaf disease images, it shows that the MobileNet algorithm is better than the DenseNet 12 algorithm. The MobileNet algorithm produces an accuracy of 98.00%, therefore the MobileNet algorithm has better performance for image classification of potato leaf disease
Analisis Trend Berita Media Online di Masa Pandemi Covid-19 dengan Metode Monte Carlo Maria Yuhilda Lima; Hustinawati Hustinawati
JURIKOM (Jurnal Riset Komputer) Vol 10, No 2 (2023): April 2023
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/jurikom.v10i2.6107

Abstract

The News reports for online media always follows the trending issues that are actually predictable. In general, online media news apart from presenting various events that have occurred, also focuses on reporting issues which is of concern to the public. During the Covid-19 pandemic, almost all mass media, including online media, continued to report various news about the Covid-19 case and its impact on society. The problem is how to understand the news accumulation in a certain period of time to find out the trend in reporting on Covid-19. Because the news has resulted in a huge accumulation of data related to Covid-19 news which can be used to build data mining. The purpose of this study is to analyze online media coverage during the Covid-19 pandemic using the Monte Carlo method to find out news trends. The process uses a data mining approach by collecting a lot of data from existing reports and processing the data to find important information from the data set. The data used to analyze news trends were taken from the main news on the online media Suarapembaruan.com for seven (7) months and processed using knowledge discovery in database (KDD) techniques. The Monte Carlo method is applied to data mining to calculate probability values or possible values that will occur in the future. The results of this study indicate that the trend of news related to Covid-19 in the future will be dominated by News on the Handling of Covid-19 with a trend percentage rate of 23.12 percent. Meanwhile, the news about the Covid-19 Case and the Impact of Covid-19 was getting lower with a trend rate of 21.82 percent and 19.22 percent. Meanwhile, The Other News with related to Covid-19 has a higher trend percentage of 35.84 percent
Klasterisasi Data Penerima Bantuan Langsung Tunai Menggunakan Algoritma K-Means Nurahman Nurahman; Jetri Susanto
JURIKOM (Jurnal Riset Komputer) Vol 10, No 2 (2023): April 2023
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/jurikom.v10i2.5807

Abstract

Increasing population and unequal distribution of population even with conditions of varying poverty levels need to be the center of attention and proper handling. In Pelangsian Village, there were 202 residents who received BLTD in 2021. The existence of a quota of beneficiaries and the number of recipients' conditions that were not suitable often became an obstacle in determining beneficiaries. So that from the data obtained in this study it is necessary to do clustering. Clustering results can be used to find out if the population receiving BLTD meets predetermined criteria. so that it can further assist the government in seeing the categories of people who are really entitled to get this assistance. Data clustering can be done using algorithms in data mining. The algorithm used in the data clustering of Pelangsian villagers in this study is the K-Means algorithm. The research methodology was carried out in several stages, such as problem selection, data collection, data preprocessing, data mining algorithm selection, results evaluation, and results interpretation. Clustering is done by forming 2 data clusters. Before the data is clustered, 202 records need to be preprocessed so that it is found that there are 196 valid data records that can be processed according to research needs. The results of data processing are done by clustering the data into 2 groups. Clustering uses the K-Means algorithm by determining the value of K = 2 so that it is obtained that cluster0 has 115 residents and cluster1 has 81 residents. Algorithm performance testing shows that the K-Means Algorithm obtains a Devies-Bouldin value of -0.794. With a Davies-Bouldin-0.794 value, it can be said that the performance of the clustering algorithm is quite good.
Penerapan Augmented Reality Dalam Replikasi Tata Letak Studio Foto Sandi Wahyu Maulana; Rohman Dijaya; Cindy Taurusta; Ika Ratna Indra Astutik
JURIKOM (Jurnal Riset Komputer) Vol 10, No 2 (2023): April 2023
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/jurikom.v10i2.6003

Abstract

The role of information technology is very influential in a person's life, thanks to technology it is possible to produce various conveniences so that people get what they want. Information technology is used in different fields, one of which is the field of information transmission. In the delivery of information, it is necessary to have a visual device so that the delivery is easily understood by the community. The delivery of information is an important support for all human activities.The delivery of information, one of which is in the field of architecture through information technology, which includes hardware and software to describe various infrastructures such as buildings.However, in terms of photo studios, many photo studios only think about the design of the studio to make it look attractive without thinking about whether or not the space for taking photos taken by photographers is sufficient.So that photographers sometimes have difficulty taking pictures because the studio space is too narrow due to designs that almost fill the space or studio designs that are not suitable in the size of the room.By using this application, it is hoped that a person can determine the design that suits the studio space. The system will be built based on Android, in the application will be made with a markerless method (without marker) which means that the 3d object will come out if it is triggered with a flat field. The camera will identify a flat field and will display a studio design object that the user has chosen before. In this application there is also an import feature that aims to input new object data from the internal storage of the user's device. Produce a digital product catalog application based on Augmented reality named DeStudio, and can also help photographers to design studio designs / themes that are clear and specific by utilizing Augmented reality technology. In the testing process alpha testing was successfully applied and got 84% smooth results. In beta testing, the average results are very satisfying from some responding, meaning that the application can be used and applied without any obstacles. In the new additional features, the results are very good because the user does not bother to rebuild. Each user can add 3D objects.
Analisis Sentimen HateSpeech pada Pengguna Layanan Twitter dengan Metode Naïve Bayes Classifier (NBC) Murni Murni; Imam Riadi; Abdul Fadlil
JURIKOM (Jurnal Riset Komputer) Vol 10, No 2 (2023): April 2023
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/jurikom.v10i2.5984

Abstract

In January 2023, Twitter users experienced a significant increase of 27.4% compared to the previous year. The social media platform Twitter is commonly used to share various types of information. One type of information frequently shared by users is Hate Speech. Hate Speech involves the dissemination of messages that nurture feelings of hatred and hostility towards specific individuals or groups, including ethnicity, religion, race, and other categories. Forms of Hate Speech encompass insults, defamation, blasphemy, provocation, incitement, and the spread of fake news. In order to address the potential for division and threats to Indonesia's unity, sentiment analysis capable of categorizing tweets as Hate Speech or Non-Hate Speech is necessary. This research aims to conduct sentiment analysis on Hate Speech tweets posted by Twitter users using the Naïve Bayes Classifier method. The dataset consists of 5000 samples processed using the Python programming language. Data processing stages involve preprocessing (including case folding, tokenization, stopword removal, normalization, and stemming), labeling, and assigning word weights (Term Weighting) using the Term Frequency (TF) and Inverse Document Frequency (IDF) methods. The data is then divided into training and testing sets, with three different data splits: 70% training and 30% testing, 30% training and 70% testing, and 50% training and 50% testing. Evaluation using the Confusion Matrix yields the highest accuracy of 81%, precision of 81%, recall of 100%, and F1-Score of 90% in the 70% training and 30% testing data split.
Implementasi Algoritma Monte Carlo Untuk Memprediksi Permintaan Aksesoris Mobil Muhammad Faisal; Ahmad Mutatkin Bakti
JURIKOM (Jurnal Riset Komputer) Vol 10, No 2 (2023): April 2023
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/jurikom.v10i2.5907

Abstract

Toko ADS Variasi dan AC Mobil is a shop engaged in the sale of car accessories, repairing and replacing car air conditioning spare parts in Kota Palembang, Toko ADS Variasi dan AC Mobil faces challenges in predicting the demand for the right car accessories to sell so that there is no excess or shortage of stock items. So that a method is needed that can be implemented into the inventory system and sales and purchase records. In this research, the author uses the Monte Carlo Algorithm which will generate predictions of demand for car accessories by considering variations in factors that affect demand, taking historical data on car accessories sales from the relevant period, then conducting Monte Carlo simulations using the data as input. The simulation will be repeated as many times as needed and provide results in the form of probability distributions of demand for car accessories that may occur. By taking the average value of the probability distribution, an accurate demand prediction can be generated. The result obtained from this research is a more accurate prediction of demand for car accessories based on the latest historical data  so that stores can determine the right amount of stock and avoid overstocking or understocking. In addition, by considering the factors that affect demand, stores can plan more effective marketing strategies and increase store profits

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