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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 13 Documents

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Search results for , issue "Vol 4 No 3 (2022): Period of June 2022" : 13 Documents clear

ANALYSIS OF PREFERRED FREIGHT FORWARDING SERVICE USING ANALYTICAL HIERARCHY PROCESS METHOD Surya Kelana Saputra; Anggi Oktaviani; Dahlia Sarkawi; Deny Novianti
Jurnal Riset Informatika Vol 4 No 3 (2022): Period of June 2022
Publisher : Kresnamedia Publisher

Buyers and sellers who use online transactions for shipping can use two face-to-face shipping methods or delivery services. Everyone needs fast and safe shipping to ensure goods are transported at the right time and place. The demand for courier services is increasingly needed. The current limitations of mobility are forcing most people to buy online rather than in shopping malls. The Analytical Hierarchy Process method was developed in the early 1970s by Dr. Thomas L. Saaty, a mathematician from the University of Pittsburgh. The Analytical Hierarchy Process is designed to rationally capture people's perceptions closely related to specific problems through procedures designed to arrive at a preference scale among various sets of alternatives. This decision model decomposes a complex multi-criteria problem into a single hierarchical structure. From the study results, it can be concluded that J&T has the highest score of 0.345 (34.5%), then JNE with a score of 0.339 (33.9%), SICEPAT with a score of 0.316 (31.6%), so that the most desirable Expedition Service based on data processed from 103 respondents is J&T.

DECISION SUPPORT SYSTEM FOR TOKO ANDA SUPPLIER SELECTION WITH THE SIMPLE ADDITIVE WEIGHTING (SAW) METHOD Ricki Ardiansyah; Maha Rani; Revi Gusriva; Elmi Rahmawati
Jurnal Riset Informatika Vol 4 No 3 (2022): Period of June 2022
Publisher : Kresnamedia Publisher

Choosing a supplier or supplier is an important factor for running a business because suppliers can affect the availability of goods, quality, and profits from the business. However, the selection of suppliers is a complicated problem in business because of the many alternatives and criteria that are the determining factors in supplier selection and the difficulty of choosing the right supplier with objective criteria in a short time. To assist in the selection of suppliers in Toko Anda, an SPK is built that can help provide the best supplier recommendations from several alternatives based on the selection criteria provided by the shop owner so that the selection of suppliers in Toko Anda can be done quickly using the system and produces an objective supplier choice. In carrying out the decision-making process in this SPK, the method that will be used is SAW. In the calculation process, the SAW method performs a weighted summation of the alternatives against all the criteria that are the reference in determining suppliers. The criteria that determine this decision support system are quality, price, completeness, packaging, warranty, delivery time, and service. based on the calculation process using the saw method, the supplier ranking results from several existing alternatives are obtained. The supplier ranking results from this decision support system can be used by Toko Anda owner as a reference in determining the supplier. From the results of the calculation process with SAW, the ranking of Supplier F with the highest value is 22, then Supplier E and Supplier B with a value of 21.4, then Supplier D with a value of 21, then Supplier A with a value of 20.6 and finally Supplier C with a value of 20.4. From this research on making SPK, the SAW method can provide a ranking of suppliers in Toko Anda within an objective and short time.

SENTIMENT ANALYSIS OF THREE-PERIOD POLEMICS USING K-NEAREST NEIGHBOR WITH TF-IDF WEIGHTING Siti Ernawati; Risa Wati
Jurnal Riset Informatika Vol 4 No 3 (2022): Period of June 2022
Publisher : Kresnamedia Publisher

The issue of changing the presidential term which was originally 2 periods of government into 3 periods raises pros and cons in the community. Many 3-period hashtags have sprung up on social media twitter. So that conducted research on sentiment analysis of presidential election polemics 3 period. The purpose of the study was to produce the value of classification on the issue of presidential election change discourse into 3 periods using the K-NN method and whether the k-NN method proved to be well used for classifying text in the review of presidential election polemics 3 periods. Dataset totaling 1152 data, data is processed using Python and Jupyter Notebook as a text editor. The data is classified into positive reviews and negative reviews, then the data is divided into training data and test data with a ratio of 90:10. Weighting words using TF-IDF and sentiment classification using K-NN method. From the results of classification using the K-NN method obtained the highest accuracy when the value of k=17 and k = 18 with an accuracy of 85.3%. The results of the analysis of public sentiment to review the issue of discourse on the change of presidential term into 3 periods tend to be negative with a percentage of 21.26% positive sentiment and 78.74% negative sentiment.

CLASSIFICATION OF THE POOR IN INDONESIA USING NAIVE BAYES ALGORITHM AND NAIVE BAYES ALGORITHM BASED ON PSO Endang Sri Palupi
Jurnal Riset Informatika Vol 4 No 3 (2022): Period of June 2022
Publisher : Kresnamedia Publisher

The poverty rate in Indonesia is still quite high, due to the large population and uneven development and economic centre. With a large population and an archipelagic country that stretches from west to east, it is not easy for the government to level the economy in order to reduce poverty in Indonesia. This study was conducted to classify the poverty rate in districts on the island of Sumatra and Java using Nave Bayes and Nave Bayes based on Particle Swarm Optimization. Thus, it is hoped that the central government and local governments can monitor the implementation of programs in order to reduce poverty rates, especially in districts with high poverty rates. Based on research conducted on the classification of the poor in districts on the island of Sumatra and Java with confusion matrix testing and validation techniques using the Naïve Bayes algorithm, the accuracy rate is 59.75% and AUC 0.768 is included in the good classification. While the results of the classification using the Naïve Bayes algorithm based on Particle Swarm Optimization produces an accuracy rate of 82.93% and an AUC of 0.849 is included in the good classification. From the results of this study, it can be said that Al-Qur'an Naïve Bayes is a good technique for classification in data mining, and for maximum results using Particle Swarm Optimization.

PERFORMANCE COMPARISON OF MUSHROOM TYPE CLASSIFICATION BASED ON MULTI-SCENARIO DATASET USING DECISION TREE C4.5 AND C5.0 Citra Mirna Wati; Abd. Charis Fauzan; Harliana Harliana
Jurnal Riset Informatika Vol 4 No 3 (2022): Period of June 2022
Publisher : Kresnamedia Publisher

Indonesia has a tropical climate that supports mushroom growth. Mushroom classification into poisonous and non-poisonous mushrooms. Identification of the type of mushroom is vital because mushrooms, especially poisonous mushrooms, risk causing potential hazards to humans, such as causing serious illness and even death. This study aimed to identify the fungus type using a computational approach, namely the Decision Tree C4.5 and C5.0 Algorithms. This research contributes to using multi-scenario datasets and comparing the performance of the C4.5 and C5.0 decision tree algorithms. The dataset used is a fungal classification dataset obtained from kaggle.com. The method stages in this research are literature study, data collection, and data preprocessing, which includes a data cleaning process and a partitioning process for multi-scenario datasets. Afterwards, the Decision Tree Algorithms C4.5 and C5.0 were implemented using the sci-kit-learn library. The last step is to do a performance comparison using the confusion matrix. The results showed that identifying poisonous mushrooms using the Decision Tree C5.0 Algorithm obtained an accuracy of 97.05% for scenario 1, 97.00% for scenario 2, and 97.11% for scenario 3. At the same time, the Decision Tre C4.5 algorithm yielded an accuracy. by 96.92% for scenario 1, 96.90% for scenario 2, and 97.05% for scenario 3. Based on the comparison of the performance of the classification results, we conclude that the Decision Tree C5.0 algorithm in scenario 3 has the highest accuracy for fungal identification poisonous.

EXPERT SYSTEM DEVELOPMENT TO IDENTIFY EMPLOYEE PERSONALITY TYPES USING DEMPSTER SHAFER THEORY Julia Fajaryanti; Rogayah Rogayah
Jurnal Riset Informatika Vol 4 No 3 (2022): Period of June 2022
Publisher : Kresnamedia Publisher

Human resources are an important asset for the company to develop and realize the company's goals. One of the efforts to optimize the capacity of employees is to know their personality. Personality is the form possessed by an individual in behaving and all the characteristics that distinguish one individual from another. Knowing the personality of employees is important for the company and the employees themselves. Because by knowing a person's personality, the company can maximize the potential of employees and can place certain positions that suit the personality of the employee. This study aims to implement dempster-shafer theory on an inference engine in building an expert system to identify employee personality types. Dempster-shafer theory can perform probability calculations so that evidence can be carried out based on the level of confidence and logical reasoning. The system developed is able to identify the personality type of the employee through the nature or symptoms that exist in the employee. In addition, the system can display the results of the diagnosis with an explanation of the personality type, its nature in work and occupations or positions that are suitable for that personality type. Based on the results of the accuracy test obtained from the comparison of expert system diagnoses with the analysis of an expert, the accuracy value reaches 85%.

BANDWIDTH MODELING ON SMART CAMPUS BASED ON ENGINEERING METHOD – STATISTICS Ewi Ismaredah; Hasdi Radiles
Jurnal Riset Informatika Vol 4 No 3 (2022): Period of June 2022
Publisher : Kresnamedia Publisher

The importance of generating internet traffic as one of the basic considerations in bandwidth allocation policies between faculties is increasing due to the number of students who complain about connection services on campus. This study proposes internet traffic generation based on the statistical - engineering method. The population is calculated based on class capacity in each faculty, as the main alibi of student attendance on campus where traffic arrivals are generated based on the arrival model through information on possible scheduling variations. Although internet services have different characteristics, they are physically determined by the bitrate and idle mode in the traffic time series. The results show recommendations in three application bitrate categories, namely 200kbps, 400kbps, and 800kbps Traffic Shaping.

DESIGN OF WEB-BASED VIRTUAL TOURISM INFORMATION SYSTEM AT GEOPARK CILETUH SUKABUMI Elsa Ramadanti; Muhamad Muslih; Nunik Destria Arianti
Jurnal Riset Informatika Vol 4 No 3 (2022): Period of June 2022
Publisher : Kresnamedia Publisher

Geopark Ciletuh Sukabumi is an earth park that has biodiversity such as geological, social, and cultural elements, to locations that can be used for research and tourism. Tourist destinations in the Ciletuh Geopark include waterfalls, beaches, mountain peaks, islands, cultural tourism, and available biodiversity. Due to the lack of information media about tourist objects in the Ciletuh Geopark, not many tourists visit to enjoy the beauty of natural attractions and local cultural wisdom that is still maintained at the Ciletuh Geopark. Based on these problems, research was carried out to design and build a tourist information system with a virtual tour feature based on the Geopark Ciletuh Sukabumi website. In this study, the author designed the system using the Zachman Framework system development method and was built using CMS WordPress and Page Builder as well as PHP and MySQL programming languages. Testing the Virtual Tourism Information System at the Ciletuh Sukabumi Geopark using Blackbox Testing. The results of the design of a web-based virtual tourist information system at the Ciletuh Sukabumi Geopark can be used as a medium of tourist information for the general public and visitors who will travel to the tourist attraction

COMPARISON OF LINEAR REGRESSIONS AND NEURAL NETWORKS FOR FORECASTING COVID-19 RECOVERED CASES Tyas Setiyorini; Frieyadie Frieyadie
Jurnal Riset Informatika Vol 4 No 3 (2022): Period of June 2022
Publisher : Kresnamedia Publisher

The emergence of the Covid-19 outbreak for the first time in China killed thousands to millions of people. Since the beginning of the emergence of the number of cases of Covid-19 continues to increase until now. The increase in Covid-19 cases has a very bad impact on health, social and economic life. The need for future forecasting to predict the number of deaths and recoveries from cases that occur, so that the government and the public can understand the spread, prevent and plan actions as early as possible. Several previous studies have forecast the future impact of Covid-19 using the Machine Learning method. Time series forecasting can be done using traditional methods with Linear Regression or Artificial Intelligent methods with neural networks. In this study, it has been proven that there is a linear relationship in the time series data of Covid-19 recovered cases in China, so it is proven that the performance of Linear Regression is better than the Neural Network.

COMPARATIVE ANALYSIS OF PATHFINDING ARTIFICIAL INTELLIGENCE USING DIJKSTRA AND A* ALGORITHMS BASED ON RPG MAKER MV Riska Nurtantyo Sarbini; Irdam Ahmad; Romie Oktovianus Bura; Luhut Simbolon
Jurnal Riset Informatika Vol 4 No 3 (2022): Period of June 2022
Publisher : Kresnamedia Publisher

In most games, an artificial pathfinding intelligence is required for traversing the fastest discovery. It is essential for many video games, particularly Role Playing Games (RPGs). The algorithm pathfindings implemented in this game are A* and Dijkstra Algorithms. This study aims to test an artificial intelligence system for discovering routes using the A* and Dijkstra algorithms based on RPG Maker MV. The result showed that from the time obtained, in the experiment on eight nodes using the Pathfinding mechanism of A* algorithm has faster result in discovering the nearest route with the time 08:15:23 with format (mm:ss: ms) whereas Dijkstra Algorithm has a 34:47:43 time result. The time record needed represents the distance between the search nodes. It indicates that the multiple weighting in the impassable nodes caused the cost calculation process becomes faster and more efficient.

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Home Page

OAI Link

Editorial Team

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Contact Name Tati Mardiana

Contact Email jurnal.jri@kresnamediapublisher.com

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Location Kota banjar, Jawa barat INDONESIA

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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