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INDONESIA
Jurnal Riset Informatika
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 432 Documents
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Comparison of SAW, WP, and TOPSIS Methods in Determining the Best Journalists N.I.S. Baldanullah; Febrianti Adhania; Desti Fitriati
Jurnal Riset Informatika Vol. 5 No. 1 (2022): December 2022
Publisher : Kresnamedia Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34288/jri.v5i4.199

Abstract

Journalists are human resources that have a significant influence on journalistic companies. A system is needed to support the company's decision to select and measure its reporters. PT. Inipasti Communika is one of the journalistic companies that has never previously measured and assessed its journalists, so it has difficulty assessing and measuring its journalists. This study aims to provide a solution using the Decision Support System in decision-making using the SAW, WP, and TOPSIS methods and provide the final decision results based on comparing these methods. This study uses criteria and criteria values from these companies. The company's data related to its journalists is the privacy of PT. It is a Community, so the alternative value used is dummy data that is still by the original standards of the company's data. This study concludes that the three methods can provide the best alternatives with the same results.
Decision Support System for Supplier Selection on Time Concept with AHP and SAW Method Warih Dwi Cahyo; Wahyu Ari Wibowo; Suwarno Suwarno; Rizki Ripai
Jurnal Riset Informatika Vol. 5 No. 1 (2022): December 2022
Publisher : Kresnamedia Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34288/jri.v5i1.200

Abstract

Seeing the rapid development of global business causes companies to compete as the best to meet global market demands. In the current era of globalization, technological development is beneficial for human life. All human activities today can be done quickly and easily using a computer. Decision Support System is a computer-based system that assists decision-making in utilizing specific data and models to solve various unstructured problems. Decision makers in selecting the best supplier for Time Concept are still having difficulties, and this is because there are no appropriate criteria and weights. Making a decision support system is expected to help solve the problems in Time Concept. Moreover, it can provide benefits or convenience for Time Concept when selecting the best supplier. The author uses the method of Analytical Hierarchy Process (AHP) and Simple Additive Weighting (SAW). According to the system test results, the Consistency Ratio (CR) calculation value is 0.0752. The comparison assessment is considered CONSISTENT if the Consistency Ratio (CR) value is not greater than 0.1000. So that the comparison of the criteria does not need to be recalculated because it is CONSISTENT.
Behavior Analysis on PLN Mobile Users Using UTAUT Method Amanda Paramita S.; Arista Pratama; Anita Wulansari
Jurnal Riset Informatika Vol. 5 No. 1 (2022): December 2022
Publisher : Kresnamedia Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34288/jri.v5i1.203

Abstract

The advancement of information technology is currently accelerating in all aspects of life. The presence of information technology, which is constantly evolving, makes it easier for users to use information systems. Technological advancements show that information technology is not currently required for businesses or organizations. PT. PLN (Persero) is a State-Owned Enterprise (BUMN) in the electricity sector that controls, supplies, and serves the community's electricity needs. PT. PLN (Persero) is committed to improving electricity services for all customers. PT. PLN (Persero) provides innovation through the PLN Mobile Application to improve electrical services. The PLN Mobile Application provides users with up-to-date information on electricity services, allows them to register independently based on their needs, and calculates costs. This research aimed to identify the behavioral factors influencing users' acceptance of the PLN Mobile Application. The UTAUT model was used for the research, and it was modified with seven variables: performance expectation, effort expectation, social influence, facilitating conditions, trust, information quality, and behavioral Intention. Sampling using the Probability Sampling Technique, with Random Sampling as the sampling type. The sample size was 400 Surabaya City respondents who used the PLN Mobile Application. SEM-PLS and SmartPls 3 software were used to analyze research data. According to the research finding, the factors influencing Behavioral Intention or user behavior on the PLN Mobile Application were Performance Expectancy, Effort Expectancy, Facilitating Conditions, and Social Influence (p-value 0, 05). In contrast, Trust and Information Quality had no positive and insignificant effect on Behavioral Intention.
A Real-Time Web Information System Based on A Global Positioning System for Monitoring Environmental Pollution Gustriyadi, Eko; Sihombing, Volvo; Masrizal, Masrizal; Adi, Puput Dani Prasetyo Adi
Jurnal Riset Informatika Vol. 5 No. 1 (2022): December 2022
Publisher : Kresnamedia Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34288/jri.v5i1.204

Abstract

This research will discuss monitoring pollution in waterways in real time based on GPS. A website-based information system is an essential factor for information media, not only database-based but can be communicated with GPS. GPS is a satellite system that can determine the point of an area with Longitude and Latitude parameters. The Global Positioning System is one of the parameters used in this study. Longitude and Latitude are the primary keys to getting the point in a particular area or point. In research, this location is used in sensor or environmental pollution monitoring. In this paper, we try to review the projects carried out and perform analysis, management, and governance on the server and local host. The program is made by developing the FrontEnd and BackEnd sides. Development can be done on Desktop-based programming and then extended to Mobile by manipulating and modifying programs using Javascript, JSON, and other building scripts for better performance and suitable for deployment on various platforms such as Mobile-based. This system is very efficient in determining various parameters, for example, the environmental pollution factor. From testing, the GPS data is not perfect, all data can be sent, but the accuracy of GPS data can reach 96%. This is due to data errors during uplinking and downlinking data.
Comparison of Breast Cancer Classification Using Decision Tree ID3 and K-Nearest Neighbors Algorithm to Predict the Best Performance of Algorithm Zyhan Faradilla Daldiri; Desti Fitriati
Jurnal Riset Informatika Vol. 5 No. 2 (2023): March 2023
Publisher : Kresnamedia Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34288/jri.v5i2.206

Abstract

One of the leading causes of death is cancer. The most common cancer in women is breast cancer. Breast cancer (Carcinoma mammae) is a malignant neoplasm originating from the parenchyma. Breast cancer ranks first in terms of the highest number of cancers in Indonesia and is among the first contributors to cancer deaths. Globocan data in 2020 shows that the number of new breast cancer cases reached 68,858 (16.6%) of the total 396,914 new cancer cases in Indonesia. Meanwhile, deaths reached more than 22 thousand cases (Romkom, 2022). This death rate is increasing due to insufficient information about breast cancer’s early symptoms and dangers. Of this lack of information, a system is needed that can provide information about breast cancer, such as early diagnosis. Several parameters and classification data mining techniques can predict which patients will develop breast cancer and which do not. In this study, a comparison of the classification of breast cancer using the Decision Tree ID3 algorithm and the K-Nearest Neighbors algorithm will be carried out. Attribute data consists of Menopause, Tumor-Size, Node-Caps, Deg-Malig, Breast-Squad, and Irradiant. The main objective of this study is to improve classification performance in breast cancer diagnosis by applying feature selection to several classification algorithms. The Decision Tree ID3 algorithm has an accuracy rate of 93.333%, and the K-Nearest Neighbors algorithm has an accuracy rate of 76.6667%.
Sentiment Analysis of Pedulilindungi Application Reviews Using Machine Learning and Deep Learning Ahmad Rais Dwijaya; Arif Dwi Laksito
Jurnal Riset Informatika Vol. 5 No. 2 (2023): March 2023
Publisher : Kresnamedia Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34288/jri.v5i2.207

Abstract

The COVID-19 pandemic that hit the world at the end of early 2020 caused many losses. The Indonesian government has established various ways to reduce the path of the COVID-19 pandemic by launching the PeduliLindungi application to reduce the spread of COVID-19. Various layers of society responded to the launch of the application with various opinions. This research mainly analyzes public opinion sentiment toward the PeduliLindungi application, as determined by 10,000 reviews on the Google Play Store. This study aims to compare the performance of deep learning and machine learning models in sentiment analysis. The stages of the research method begin with data collection methods, data pre-processing, and sentiment analysis using a machine learning model with the embedding of the word TF-IDF, which includes the Nave Bayes algorithm, Decision Tree, Random Forest, K-Nearest Neighbour, and SVM. As for the deep learning model with the fastText word embedding word representation technique using the LSTM algorithm, an evaluation is carried out using the confusion matrix. The results of this study state that deep learning models perform better than machine learning models.
IMPLEMENTATION OF 360-DEGREE FEEDBACK AND SAW FOR DECISION SUPPORT SYSTEM OF ACHIEVING TEACHER'S RECOMMENDATION Novita Br Ginting; Zulkarnaen Noor Syarif; Mamay Maesaroh; Jejen Jaenudin; Dahlia Widhyaesteoty; Muhamad Alfian Yusuf; Leny Tritanto Ningrum
Jurnal Riset Informatika Vol. 4 No. 4 (2022): September 2022
Publisher : Kresnamedia Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34288/jri.v4i4.209

Abstract

Education requires quality teacher resources in the current era of industry 4.0 and society 5.0. Teachers act as educators, teachers, mentors, directors, trainers, assessors, and evaluators. Students must have critical thinking competencies, creativity and innovation, interpersonal and communication skills, teamwork and collaboration, and self-confidence. At SMK Yasbam, the selection process for outstanding teachers is carried out every year. The problem faced is that the selection process is still assessed, selected, and determined by the school principal only, so there is still a process that is deemed not transparent, accountable, and fair. To make the assessment process fairer, try using the 360-degree feedback method, a multi-source assessment, and then weighting the performance value using the Simple Additive Weighting method to obtain recommendations for outstanding teachers. Respondents consisted of principals, fellow teachers, students, and themselves (the assessed teachers). Furthermore, combining these two methods is applied in a decision support system to make the assessment process and selection of outstanding teachers more objective.
Implementation of PDDIKTI Neo Feeder Web Service in Recording of Independent Campus Activities Herlambang Brawijaya; Slamet Widodo; Samudi Samudi
Jurnal Riset Informatika Vol. 5 No. 2 (2023): March 2023
Publisher : Kresnamedia Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34288/jri.v5i2.210

Abstract

Independent Learning-Independent Campus Program (MBKM) is a policy of granting the right for students to be able to take study activities outside the study program as many as three semesters with the division of two semesters of study outside the college and one semester in different study programs in one college. As well as teaching and learning activities, universities must report Independent Learning-Independent Campus activities to DIKTI every semester through the Neo Feeder PDDIKTI application. The Neo Feeder PDDIKTI application has a feature to enter the activities the operator will carry out. The operator enters this data individually on the Neo Feeder PDDIKTI application. This is a significant problem because the data entry process will take quite a lot of time, even though PDDIKTI has provided web service access to universities to optimize the data reporting process using the Neo Feeder PDDIKTI application. Building an application that can be used for recording MBKM activities by utilizing web services provided by PDDIKTI is the primary purpose of this study. The development of an application certainly requires a method as a framework or guide in facilitating the manufacturing process. The extreme Programming (XP) method becomes essential for applications with variable or non-fixed needs. This method has four working elements: planning, designing, coding, testing and software increment. The output generated by this study is an application for recording MBKM activities that use web service restful API technology so that data entry can be done en masse and not one by one.
The Implementation of C4.5 Algorithm for Determining the Department of Vocational High School Mirza Sutrisno; Jefri Kusuma Rambe; Asruddin Asruddin; Ade Davy Wiranata
Jurnal Riset Informatika Vol. 5 No. 2 (2023): March 2023
Publisher : Kresnamedia Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34288/jri.v5i2.211

Abstract

The selection of departments in vocational high schools (SMK) is a must for students to determine the concentration of student learning interest for three years in a school. The lack of student knowledge and outreach about this department caused many students to choose their majors by the most choices and following other students. This problem can cause some difficulties for the students to participate in learning, and most fail. Students must select their major based on their interests, abilities, and talents because every student has different abilities and talents. The C4.5 algorithm can provide convenience in grouping students based on majors. Using the decision tree method with attributes such as grades in mathematics, English, interests, and talents, the system can recommend majors based on students' interest levels. The results of this study are the determination of the departments with the accuracy of the calculation using the confusion matrix method with a 98,55% accuracy rate and 100% recall rate value.
Enhancing Risk Management in an IT Service Company: A COBIT 2019 Framework Approach Emmanuel Enrique; Melissa Indah Fianty
Jurnal Riset Informatika Vol. 5 No. 4 (2023): September 2023
Publisher : Kresnamedia Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34288/jri.v5i4.212

Abstract

The application of information technology is utilized to support the business activities of companies engaged in IT services. One of the prevailing issues pertains to service delivery delays. This issue is paramount as customer satisfaction ranks among the most pivotal factors for business success, significantly influencing the company's continued prosperity. In response to these challenges, this study assesses the level of IT governance within the company using the 2019 COBIT framework. The methodology employed combines a qualitative approach, integrating data collected through interviews and literature analysis. The study's key performance indicators include APO12 (Managed Risk), BAI10 (Managed Configuration), and DSS04 (Managed Continuity). The findings reveal that the measured capability levels for these objectives are at levels 3, 3, and 2, respectively, falling short of the targeted levels, which are 4, 4, and 3. This indicates a 1-level gap in each process. The recommendations provided concentrate on the management of risk records associated with service delay causes, the proper management of IT resources, and the maintenance of a continuous service system to prevent future delays.

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