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Jurnal Riset Informatika

jri
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Published by KresnaMedia Publisher

ISSN : 26561743 EISSN : 26561735 DOI : -

Core Subject : Science,

Computer Science & IT

Jurnal Riset Informatika, merupakan Jurnal yang diterbitkan oleh Kresnamedia Publisher. Jurnal Riset Informatika, berawal diperuntukan menampung paper-paper ilmiah yang dibuat oleh peneliti dan dosen-dosen program studi Sistem Informasi dan Teknik Informatika.

Arjuna Subject : -

Articles 417 Documents

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SENTIMENT ANALYSIS OF REKSADANA ON BIBIT APPLICATIONS USING THE NAÏVE BAYES METHOD AND K-NEAREST NEIGHBOR (KNN) Alisa Fitriyani; Agung Triayudi
Jurnal Riset Informatika Vol 4 No 2 (2022): Period of March 2022
Publisher : Kresnamedia Publisher

The public's lack of interest in the capital market has made the top brass of capital market companies compete with each other to provide services in order to provide convenience for customers in the various services available and provide convenience in accessing financial information. The emergence of several startup companies that provide mutual fund investment products for investors, namely PT Bibit Reksadana Grow Together, which created a mutual fund application, namely Bibit Mutual Fund with more than one million users based on data downloaded on the play store by PT Bibit Grow Bersama which acts as a Mutual Fund Selling Agent (APERD) and sells 134 mutual fund products. So, to provide information to the public, it is necessary to have a sentiment analysis on how the opinions of users of the mutual fund seed application use the methodK-nearest neighbor (KNN) and Naïve Bayes, with the results of crawling data of 3800 tweets and scraping of 5000 reviews, then the text processing and labeling stages are carried out using the textblob library, with a high level of accuracy in the classification of tweet data and review data using the K-nearest neighbor method. Nearest Neighbor as much as 88%, 100%, and Naïve Bayes as much as 100%, 100%, it can be concluded that positive opinions from seed mutual fund users are more than negative sentiments.

APPLICATION OF PROFILE MATCHING ALGORITHM IN SELECTION OF THE BEST EMPLOYEES (CASE STUDY: PT VWX) Laeli Nurchasanah; Annisa Cintakami Firdaus; Desti Fitriati
Jurnal Riset Informatika Vol 4 No 2 (2022): Period of March 2022
Publisher : Kresnamedia Publisher

Giving awards to employees who have advantages and good work performance is one way to increase positive competitiveness among employees in a company. This study aims to find the advantages of each employee to find out which employees excel. Through achievements in the world of work, it can be a benchmark for finding the best employees who deserve awards. Analysis of the data used in this study is sourced from data on sales of property companies for the last three months. This study uses the Profile Matching Method to determine the best employees in property companies. This research was conducted by comparing one employee with another employee candidate based on predetermined criteria. The results of this study are in the form of rankings that show the order of the best employees who are entitled to an award from the company.

PAKPAK LANGUAGE TRANSLATOR APPLICATION INTO INDONESIAN USING ALGORITHM BOYER MOORE BASED ON ANDROID Khairani Purba; Charles Jhony Mantho Sianturi; Mikha Dayan Sinaga; Nita Sari Sembiring; Erwing Ginting; Muhammad Fauzi
Jurnal Riset Informatika Vol 4 No 1 (2021): Period of December 2021
Publisher : Kresnamedia Publisher

The lack of preservation is also the knowledge of the Pakpak Language in Indonesia, which causes the Pakpak Language to be less preserved, especially for young people who continue to keep abreast of the times. This causes the process of globalization and urbanization which causes assimilation and acculturation, especially in urban areas. This situation triggers a new language that is very popular, especially for young people who unconsciously, it makes us lose our identity as a society that has tribes and customs each – and the emergence of international and national schools that require students to speak foreign languages. Therefore, learning is needed to preserve Pakpak Language. By making a Pakpak to Indonesian translator application that uses the Android Based Boyer Moore algorithm. This translator application was made for the introduction of the PakpakLangugae to the wider community so that the sustainability of the Pakpak Language is maintained and this translator application can translate the Pakpak Language into Indonesian or vice versa based on the prevailing Pakpak – Indonesian dictionary.

CLASSIFICATION OF BURNED PEATLAND USING PROBABILISTIC NEURAL NETWORK ALGORITHM BASED ON HIGH TEMPORAL DATA Neneng Rachmalia Feta
Jurnal Riset Informatika Vol 4 No 2 (2022): Period of March 2022
Publisher : Kresnamedia Publisher

Forest or land fires in Indonesia do not only occur in drylands but also in peatlands. Peatland fires are more dangerous and more difficult to overcome compared to non-peatland fires and the impacts of peatland fires are very harmful to society. One of the solutions in assessing forest and peatland fires is remote sensing technology. Satellite images obtained from remote sensing technology are usually classified for further analysis. The main objective of this study is to develop a classification model using Probabilistic Neural Network (PNN) to classify areas in peatland before, during, and after being burned on the satellite image Landsat 7 ETM +. Furthermore, the model is used to get the trajectory pattern of the burned area using the DBScan algorithm. The study area is Ogan Komering Ilir District, South Sumatera Province, image Landsat 7 ETM + taken from January 2015 – December 2015.

AUTOIMMUNE DISEASE DETECTION WITH DEMPSTER SHAFER AT TANJUNGBALAI GENERAL HOSPITAL Sukria Novriana Sari; Rizky Fauziah; Tika Christy
Jurnal Riset Informatika Vol 4 No 2 (2022): Period of March 2022
Publisher : Kresnamedia Publisher

Autoimmune diseases are diseases that attack the human immune system. Autoimmunity is a disorder of the immune system due to the failure of the body's defenses to stabilize conditions so that the immune system attacks a healthy body which is considered a foreign object that must be destroyed. Helping the public in the early detection of autoimmune diseases by using an expert system that is expected to detect autoimmune diseases early in Tanjungbalai Hospital so that they can provide early information about autoimmune diseases and appropriate and informative subsequent actions to the community. In this study, an expert system was built using the web-based Dempster-Shafer method based on the value of expert trust in the symptoms felt by the patient. There were 7 types of autoimmune diseases studied: ITP, SLE, Type 1 DM, Graves Disease, RA (Rheumatoid Arthritis), Autoimmune Hepatitis, and Hashimoto's Thyroiditis. This study resulted in ITP with an accuracy rate of 98%, SLE with an accuracy rate of 96%, Diabetes Mellitus Type 1 with an accuracy rate of 96%, Graves Disease with an accuracy rate of 93%, RA (Rheumatoid Arthritis) with an accuracy rate of 99%, Autoimmune Hepatitis with a 94% accuracy, and Hashimoto's thyroiditis with 99% accuracy.

COMPARATIVE ANALYSIS OF THE K-NEAREST NEIGHBOR ALGORITHM ON VARIOUS INTRUSION DETECTION DATASETS Andri Agung Riyadi; Fachri Amsury; Irwansyah Saputra; Tiska Pattiasina; Jupriyanto Jupriyanto
Jurnal Riset Informatika Vol 4 No 1 (2021): Period of December 2021
Publisher : Kresnamedia Publisher

Security in computer networks can be vulnerable, this is because we have weaknesses in making security policies, weak computer system configurations, or software bugs. Intrusion detection is a mechanism for securing computer networks by detecting, preventing, and blocking illegal attempts to access confidential information. The IDS mechanism is designed to protect the system and reduce the impact of damage from any attack on a computer network for violating computer security policies including availability, confidentiality, and integrity. Data mining techniques have been used to obtain useful knowledge from the use of IDS datasets. Some IDS datasets that are commonly used are Full KDD, Corrected KDD99, NSL-KDD, 10% KDD, UNSW-NB15, Caida, ADFA Windows, and UNM have been used to get the accuracy rate using the k-Nearest Neighbors algorithm (k-NN). The latest IDS dataset provided by the Canadian Institute of Cybersecurity contains most of the latest attack scenarios named the CICIDS2017 dataset. A preliminary experiment shows that the approach using the k-NN method on the CICIDS2017 dataset successfully produces the highest average value of intrusion detection accuracy than other IDS datasets.

Enhancing Obesity Risk Classification: Tackling Data Imbalance with SMOTE and Deep Learning Syofian, Muhammad; Maulana, Ilham
Jurnal Riset Informatika Vol. 6 No. 4 (2024): September 2024
Publisher : Kresnamedia Publisher

Data imbalance is a significant challenge in classification models, often leading to suboptimal performance, especially for minority classes. This study explores the effectiveness of the Synthetic Minority Over-sampling Technique (SMOTE) in improving classification model performance by balancing data distribution. The evaluation was conducted using a confusion matrix to measure prediction accuracy for each class. The results indicate that SMOTE successfully enhances minority class representation and improves prediction balance, although some misclassifications remain. Therefore, in addition to oversampling, additional approaches such as class weighting or ensemble learning are required to further improve model accuracy. This study provides deeper insights into the role of SMOTE in addressing data imbalance and its impact on classification model performance.

IMPLEMENTATION OF CRM METHODS TO IMPROVE SALES QUALITY OF BUNUT SEBRANG UMI CLOTHING SHOP Windi Safitri; Guntur Maha Putra; Febby Madonna Yuma
Jurnal Riset Informatika Vol 4 No 2 (2022): Period of March 2022
Publisher : Kresnamedia Publisher

Along with the times, the business world is experiencing rapid development, especially in the business world, such as selling fashion products. Therefore, a good strategy is needed. In maintaining more advanced competitiveness, companies must develop information technology. Another thing that must be considered in making our business more advanced is the relationship with customers, which is also an important thing to always maintain, to manage good relationships with new customers or regular customers by using the Customer Relationship Management (CRM) method. The Customer Relationship Management (CRM) method can make it easier for Umi Clothing Store owners to retain existing customers and make it easier for shop owners to get new customers. The research method used in this research is qualitative research. This research will only utilize data obtained from the research location and input it without changing anything.

FORECASTING HEALTH INSURANCE PAYER INCOME: A COMPARATIVE ANALYSIS OF DECISION TREE AND SVR ALGORITHMS Mokodaser, Wilsen Grivin; Soewignyo, Tonny Irianto; Tangka, George Morris William; Soewignyo, Fanny
Jurnal Riset Informatika Vol. 7 No. 3 (2025): Juni 2025
Publisher : Kresnamedia Publisher

An insurance company is a type of non-bank financial institution that protects clients from risks and collects premiums over a certain period, these facts provide an overview of the insurance business and highlight its role in the economy, this study evaluated the performance difference between the Decision Tree Regressor and Support Vector Regression (SVR) in predicting insurance payer income. The Decision Tree model demonstrated strong predictive accuracy, achieving a Mean Absolute Error (MAE) of approximately 57 million and an R-squared (R²) value of 0.896, meaning it could explain around 89.6% of the variance in the data. Additionally, the model maintained high consistency, as evidenced by 5-fold cross-validation scores ranging from 0.908 to 0.967, indicating strong generalization and low risk of overfitting. In contrast, the SVR model significantly underperformed. It recorded a much higher MAE of over 237 million and a large Mean Squared Error (MSE), reflecting substantial deviations from the actual values. Its R² score of -0.299 suggests that SVR performed worse than a naive mean predictor, failing to identify meaningful patterns. This poor performance was consistent across all cross-validation folds, which also produced negative R² scores. The SVR model’s inadequacy is likely due to the large scale of the income data and the lack of proper preprocessing, such as normalization, or parameter tuning. Overall, these findings clearly demonstrate that the Decision Tree Regressor is a more suitable, accurate, and stable model for predicting insurance payer income.

MODELING THE DISTRIBUTION OF HIV CASES WITH K-MEANS CLUSTERING CASE STUDY OF WEST JAVA PROVINCE Difa Prakoso Fuadi, Muhammad; Tukino; Hananto, Agustia; Nurafriani, Fitria
Jurnal Riset Informatika Vol. 7 No. 3 (2025): Juni 2025
Publisher : Kresnamedia Publisher

In Indonesia, the problem of HIV/AIDS is a serious concern because the trend of cases tends to increase in several regions, including in West Java Province, 2018 data from the Health Office shows a significant variation in the number of HIV cases among districts and cities in the province, in this journal, a visualization process is carried out using Google Colaboratory (Google Colab) to provide an overview of the distribution pattern of cases based on the results of the K-Means Clustering algorithm. The results showed the existence of three main clusters, namely areas with low, medium, and high numbers of cases. Large cities such as Bandung and Bekasi were in the group with the highest number of cases, while peripheral and rural areas showed lower numbers of cases. This finding is expected to be the basis for formulating more effective health policies, especially in education programs, early detection, and community-based interventions to support the goal of eliminating HIV by 2030, then what can be done is to carry out intervention strategies or steps to prevent the spread of HIV tailored to the risk level of each cluster resulting from clustering analysis. Local governments are expected to utilize the results of this mapping to develop more detailed prevention strategies according to the characteristics of each region.

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Contact Name
Tati Mardiana

Contact Email
jurnal.jri@kresnamediapublisher.com

Phone
-

Journal Mail Official
jurnal.jri@kresnamediapublisher.com

Editorial Address
-

Location
Kota banjar,

Jawa barat

INDONESIA