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All Journal Jurnal sistem informasi, Teknologi informasi dan komputer Proceeding of the Electrical Engineering Computer Science and Informatics Jurnal Ilmiah FIFO Dinamisia: Jurnal Pengabdian Kepada Masyarakat Jurnal Riset Informatika Coverage: Journal of Strategic Communication Journal of Informatics and Advanced Computing
Desti Fitriati
Universitas Pancasila
Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Languange, Linguistic, Communication & Media Library & Information Science Mathematics Social Sciences Other

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SMART SYSTEM FOR AUTOMATIC CROP AND RECOGNITION PLAT NUMBER Desti Fitriati; Nira Ravika Pasha; Bambang Hariyanto; Amir Murtako; Sri Rezeki Candra Nursari
Jurnal Riset Informatika Vol. 3 No. 2 (2021): March 2021 Edition
Publisher : Kresnamedia Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34288/jri.v3i2.60

Abstract

Based on data from the Central Statistics Agency in 2018, it was written that the number of motorbikes for the Indonesian region was 120.10 million or 82% and for cars 26.75 million or around 18% of the total population. With the increasing population of motorized vehicle users, it will result in an increase in problems that occur in traffic violations and also the technology security system in the parking system. Most of the existing parking systems still require parking attendants. In addition, the existing system only discusses the opening and closing of bars and providing information on parking lots. Although the existing system already uses artificial intelligence to read plate numbers, the officers are still matching it. Of course this is not effective and efficient because the use of artificial intelligence is not purely done by the system. To overcome this, the solution given in this study is to create a parking system that can read plate numbers automatically and store vehicle entry data directly into the database. The system created can also open and close the door latch automatically. The template matching image processing technique was chosen to solve this problem. Based on the experimental results, the system can recognize plate numbers with an accuracy of 83%. For further research, it is necessary to introduce vehicle ownership and provide parking information so that the parking system becomes more perfect.
GAS LEAK SOURCE DETECTION ROBOT USING FINITE STATE MACHINE MODEL (FSM) Agung Arya Adi Nugraha; Desti Fitriati
Jurnal Riset Informatika Vol. 3 No. 2 (2021): March 2021 Edition
Publisher : Kresnamedia Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34288/jri.v3i2.66

Abstract

At this time, many gases are at risk in the surrounding area, especially in industrial areas, such as radiological materials and toxic gases that can contaminate the surrounding area as well as the occurrence of gas leaks. From the problem-created gas detection simulation robot using Finite State Machine (FSM) model, the robot can help human work in this case the robot helps detect gas leaks that if faced by humans will be dangerous. The robot was created to detect nearby gases and provide notifications in the event of a gas leak. The robot was tested in several areas to see if the robot could perform the task according to the input given, the trial was conducted 40 times with 4 different arenas, from 40 tests the robot can perform the correct task 37 times and error 3 times so that accuracy results obtained by 92.5%. The creation of this gas detection simulation robot is expected to be developed again as a gas leak detection inspection robot as an early warning system.
SENTIMENT ANALYSIS OF TWITTER DATA ON DISTANCE LEARNING USING NAÏVE BAYES ALGORITHM Putri Rana Khairina; Desti Fitriati
Jurnal Riset Informatika Vol. 3 No. 3 (2021): June 2021 Edition
Publisher : Kresnamedia Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (831.098 KB) | DOI: 10.34288/jri.v3i3.68

Abstract

Covid-19 is widespread, resulting in a global pandemic. Distance Learning System (DLS) is considered as a solution but, the reality of the implementation of DLS is not in accordance with the expectations of the community. Many twitter users wrote their opinions on DLS. The tendency of public sentiment can be used as a way to improve the existing education system in Indonesia and can be an input for the government in improving the DLS method that is being implemented. Thus, this study produced a system that can analyze tweet sentiment towards DLS. The tweet was obtained using the Twitter API. The method used is Naïve Bayes for the process of classification of positive, negative and neutral sentiments using 600 data. Then, data sharing is done 80% data training and 20% data testing that will be in the text preprocessing first. The accuracy of sentiment analysis of DLS using Naïve Bayes method using 3-fold Cross Validation produces an average of 93%.
DECISION SUPPORT SYSTEM TO ELECT THE BEST USTADZ USING SIMPLE ADDITIVE WEIGHTING METHOD Muhammad Abdan Syakuro; Desti Fitriati
Jurnal Riset Informatika Vol. 3 No. 4 (2021): September 2021 Edition
Publisher : Kresnamedia Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34288/jri.v3i4.95

Abstract

Pesantren is a place for students to live and learn religious education. In Pesantren there are human resources that very helpful for learning in boarding school, namely ustadz. In the process of successful education, sometimes pesantren needs to make an assessment to improve the quality of education, one of it is conducting the best selection of ustadz adequate and exceeding the average. The number of ustadz that exist causes difficult decision making of the best ustadz elections quickly, accurately and has not been able to give maximum results and takes a very long time in calculation. In addition, the selection of the best ustadz in Pesantren Qur'an Al Hikmah Bogor is still not objective because the selection of the best ustadz is still appointed directly without using calculations. Based on the problems described above, a Decision Support System (DSS) application is needed using simple additive weighting method to help in making the best ustadz decision in pesantren. This system is a dynamic system where users can set the parameters of criteria and weights themselves. Besides, From the making of the Decision Support System produced accuracy of 90% of 30 samples according to which are 27 samples.
Implementation of Data Mining To Determine the Association Between Body Category Factors Based on Body Mass Index Desti Fitriati; Bima Putra Amiga
Jurnal Riset Informatika Vol. 2 No. 4 (2020): Period September 2020
Publisher : Kresnamedia Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34288/jri.v2i4.128

Abstract

The development of the increasing flow of globalization in the field of science and technology as well as increased income has resulted in reduced physical activity of the community which results in diverging diet and physical activity which makes a person not pay attention to his body shape. This method of calculating the Body Mass Index can be used to determine a person's body shape. Several factors can affect the value of the Body Mass Index, including individual factors, consumption patterns, and lack of physical activity which leads to a sedentary lifestyle. These factors are made into 69 itemsets which will be used as the basis for questions in the questionnaire to collect a dataset that will later be processed using the FP Growth algorithm and looking for association rules that have the highest support x confidence value. From the 490 calculation data, the results are categorized into 10, each of which is Men with a Very Thin BMI with the highest support x confidence value of 39.56%, Men with a Thin BMI of 55.90%, Men with a Normal BMI of 70%, men with a fat BMI of 49.23%, men with an obese BMI of 41.34%, women with a very thin BMI of 41.37%, women with a thin BMI of 37.21%, Normal BMI is 68.83%, women with obese BMI are 41.65%, and women with obese BMI are 42.91%.
APPLICATION OF PROFILE MATCHING ALGORITHM IN SELECTION OF THE BEST EMPLOYEES IN PROPERTY COMPANY Laeli Nurchasanah; Annisa Cintakami Firdaus; Desti Fitriati
Jurnal Riset Informatika Vol. 4 No. 2 (2022): March 2022
Publisher : Kresnamedia Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34288/jri.v4i2.150

Abstract

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.
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.
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%.
Implementation of Hybrid Method in Tourism Place Recommendation System Based on Image Features Steven Christ Pinantyo Arwidarasto; Desti Fitriati
Jurnal Riset Informatika Vol. 5 No. 3 (2023): June 2023
Publisher : Kresnamedia Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34288/jri.v5i3.235

Abstract

In the industrial 4.0 era, there is an explosion of unstructured and structured data that produces broad and varied knowledge information that humans cannot process quickly. This issue makes the existence of recommendation systems meaningful. This system studies the existing information and provides suggestions according to the user's will. In the past, many recommendation systems have focused more on content-based filtering methods where recommendation results are similar based on the features of the Content that match the user's personality. This method limits the variety of information that is relevant to users. In addition, in the context of tourist attractions, many studies have not used image data that can contain many objects in one frame as a determining factor in providing recommendations. Therefore, in this study, the authors propose to add image features as one of the parameters of the recommendation system to determine the impact of using image features on the model performance. The best performance obtained is 0.364 RMSE metric using the Hybrid Image method.
KLASIFIKASI RIMPANG MENGGUNAKAN CONVOLUTION NEURAL NETWORK Yuvan Feberian; Desti Fitriati
Journal of Informatics and Advanced Computing (JIAC) Vol 3 No 1 (2022): Journal of Informatics and Advanced Computing
Publisher : Teknik Informatika Universitas Pancasila

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Rimpang dalam ilmu botani dapat didefinisikan sebagai tanaman yang tumbuh di bawah permukaan tanah seperti jahe, kencur, kunyit, lengkuas dan temulawak. Rimpang dapat digunakan sebagai pengobatan tradisional di Indonesia untuk mengobati beberapa penyakit seperti karminativa, diaforetika, stimulansia, kolagoga dan lain-lain. Peneliti membuat survei dalam bentuk kuisioner untuk mengetahui apakah orang dapat membedakan rimpang dengan responden sebanyak 56 orang dan hasil dari kuisioner tersebut menunjukan bahwa 12 orang menjawab dengan benar, 16 orang menjawab ragu-ragu, 28 orang menjawab tidak benar. Peneliti membuat sebuah aplikasi untuk membantu orang-orang dalam kebingungan menyebutkan nama tanaman rimpang atau membedakan tanaman rimpang dengan menggunakan metode CNN. Keseluruhan jumlah data rimpang yang digunakan adalah 250 data dengan setiap kelas 50 data jahe, kencur, kunyit, lengkuas dan temulawak. Hasil menunjukkan akurasi sebesar 0.9 atau 90%.
Co-Authors Agung Arya Adi Nugraha Amir Murtako Annisa Cintakami Firdaus Audrey Raihannisa Bambang Hariyanto Bima Putra Amiga Elvina Lathifa Faeqal Hafidh Muhammad Asfian Fairuz Astari Devianty Febri Maspiyanti Febrianti Adhania Iqbal Gibran Laeli Nurchasanah Muhamad Rosit Muhammad Abdan Syakuro N.I.S. Baldanullah Nadiah Nadiah Nira Ravika Pasha Nur Yulianti Hidayah, Nur Yulianti Nura Meutia Nessrayasa Pateh Ulum Putri Rana Khairina Riza Darma Putra Steven Arwidarasto Steven Christ Pinantyo Arwidarasto Wina Finka Yuvan Feberian Zyhan Faradilla Daldiri