Jurnal Informatika Jurnal Pengembangan IT最新文献_第2页

Implementasi Aplikasi Berbasis Mobile Untuk Pelayanan Jasa Kesehatan 为卫生服务服务开发基于移动的应用程序

Jurnal Informatika Jurnal Pengembangan IT Pub Date : 2023-05-30 DOI: 10.30591/jpit.v8i2.5076

Bella Primin, Adityo Permana Wibowo

{"title":"Implementasi Aplikasi Berbasis Mobile Untuk Pelayanan Jasa Kesehatan","authors":"Bella Primin, Adityo Permana Wibowo","doi":"10.30591/jpit.v8i2.5076","DOIUrl":"https://doi.org/10.30591/jpit.v8i2.5076","url":null,"abstract":"Health is one of the important aspects of society's life. Karangampel Health Center is one of the health centers that provide public health services in general. There are several health services provided by the puskesmas including regular medical practices, specialist doctors practices, KIA service practices (Mother and Child Health), and KB service practices. Currently, the queue system at the puskesmas does not yet use the computerization so it is less effective. Many patients who have signed up complain because they don't know for sure the operational schedule at the health center. The purpose of this study was to build a mobile-based computerization application that contains information about the doctor's practice schedule, registering online, the patient's examination history, as well as submitting an online reference letter. The app also had a feature to get an ambulance call quickly. This research method includes observations and System Designers using Systems development of life cycle (SDLC) by the prototype method, and the creation of the system so that it produces a Mobile-based puskesmas information system. Applications are made, then the test is carried out using a black box. The test results result in a value of 80% so it shows that the application is worth using","PeriodicalId":53375,"journal":{"name":"Jurnal Informatika Jurnal Pengembangan IT","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135693197","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Performance Improvement of Random Forest Algorithm for Malware Detection on Imbalanced Dataset using Random Under-Sampling Method 利用随机欠采样方法改进不平衡数据集上恶意软件检测的随机森林算法性能

Jurnal Informatika Jurnal Pengembangan IT Pub Date : 2023-05-30 DOI: 10.30591/jpit.v8i2.5207

Fauzi Adi Rafrastara, Catur Supriyanto, Cinantya Paramita, Yani Parti Astuti, Foez Ahmed

{"title":"Performance Improvement of Random Forest Algorithm for Malware Detection on Imbalanced Dataset using Random Under-Sampling Method","authors":"Fauzi Adi Rafrastara, Catur Supriyanto, Cinantya Paramita, Yani Parti Astuti, Foez Ahmed","doi":"10.30591/jpit.v8i2.5207","DOIUrl":"https://doi.org/10.30591/jpit.v8i2.5207","url":null,"abstract":"Handling imbalanced dataset has their own challenge. Inappropriate step during the pre-processing phase with imbalanced data could bring the negative effect on prediction result. The accuracy score seems high, but actually there are many problems on recall and specificity side, considering that the produced predictions will be dominated by the majority class. In the case of malware detection, false negative value is very crucial since it can be fatal. Therefore, prediction errors, especially related to false negative, must be minimized. The first step that can be done to handle imbalanced dataset in this crucial condition is by balancing the data class. One of the popular methods to balance the data, called Random Under-Sampling (RUS). Random Forest is implemented to classify the file, whether it is considered as goodware or malware. Next, 3 evaluation metrics are used to evaluate the model by measuring the classification accuracy, recall and specificity. Lastly, the performance of Random Forest is compared with 3 other methods, namely kNN, Naïve Bayes and Logistic Regression. The result shows that Random Forest achieved the best performance among evaluated methods with the score of 98.1% for accuracy, 98.0% for recall, and 98.2% for specificity.","PeriodicalId":53375,"journal":{"name":"Jurnal Informatika Jurnal Pengembangan IT","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135693028","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Komparasi Metode Apriori dan FP-Growth Data Mining Untuk Mengetahui Pola Penjualan 杏色和FP-Growth数据挖掘方法的比较，以了解销售模式

Jurnal Informatika Jurnal Pengembangan IT Pub Date : 2023-05-29 DOI: 10.30591/jpit.v8i2.4876

Neni Purwati, Yogi Pedliyansah, Hendra Kurniawan, Sri Karnila, Riko Herwanto

引用次数: 0

Deep Learning untuk Identifikasi Daun Tanaman Obat Menggunakan Transfer Learning MobileNetV2 在学习的过程中，用移动的学习工具来识别药物的叶子

Jurnal Informatika Jurnal Pengembangan IT Pub Date : 2023-05-29 DOI: 10.30591/jpit.v8i2.5217

Rio Juan Hendri Butar-Butar, Noveri Lysbetti Marpaung

{"title":"Deep Learning untuk Identifikasi Daun Tanaman Obat Menggunakan Transfer Learning MobileNetV2","authors":"Rio Juan Hendri Butar-Butar, Noveri Lysbetti Marpaung","doi":"10.30591/jpit.v8i2.5217","DOIUrl":"https://doi.org/10.30591/jpit.v8i2.5217","url":null,"abstract":"Medicinal plants are plants used as alternative medicines for healing or preventing various diseases due to their active substances. The utilization of medicinal plants in Indonesia has been widespread among the community since ancient times and is a heritage passed down from ancestors. Medicinal plants have leaf structures that are almost similar between one plant and another, which can lead to confusion for some people and require precision in identifying the leaves of medicinal plants. Incorrect identification can have negative consequences for the users. In recent years, deep learning has been used to identify objects because of its ability to interpret images. This study used a transfer learning method to identify medicinal plants. Transfer learning utilizes a pre-trained model to learn and perform new tasks, making it suitable for smaller datasets. The pre-trained model used in this study is MobileNetV2. MobileNetV2 has a lightweight architecture and high accuracy. Fine-tuning techniques were applied in this study to improve the model's performance. Several experiments were conducted with parameters such as epochs and fine-tuning layers to obtain the best results. The research yielded a training accuracy of 97%, validation accuracy of 96%, and testing accuracy of 93%.","PeriodicalId":53375,"journal":{"name":"Jurnal Informatika Jurnal Pengembangan IT","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135831926","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Tabel Partisi Pada STARS: Konsep Dan Evaluasi (Studi Kasus STARS UKSW) 恒星上的分分区表:概念和评价(UKSW星空研究)

Jurnal Informatika Jurnal Pengembangan IT Pub Date : 2023-05-29 DOI: 10.30591/jpit.v8i2.4753

Infraim Oktofianus Boymau, Penidas Fiodinggo Tanaem, Andeka Rocky Tanaamah

{"title":"Tabel Partisi Pada STARS: Konsep Dan Evaluasi (Studi Kasus STARS UKSW)","authors":"Infraim Oktofianus Boymau, Penidas Fiodinggo Tanaem, Andeka Rocky Tanaamah","doi":"10.30591/jpit.v8i2.4753","DOIUrl":"https://doi.org/10.30591/jpit.v8i2.4753","url":null,"abstract":"Database performance is one of the main components in supporting the sustainability of a system, in this case, STARS. In the system context, data will usually be collected into a database. Tied to the data collection process, this really affects the performance of a system as a whole, in this case when executing a query to get a return of the execution results, because the performance of the database itself will be affected by the amount of data available. One way to improve the performance of the database is to use the partition table concept. Thus, in this research a design and evaluation of the partition table will be carried out which will then be applied to the SWCU STARS database. This research focuses more on the use of vertical partitions and list partitions by utilizing PostgreSQL version 14. The stages used in this study. These stages include data collection, partition design, technical partition, testing and implementation. The results of this study indicate that partition tables have better performance than non-partition tables. Judging from some of the sql syntax, namely update, delete and select, while insert has poor performance for partition tables compared to non-partition tables","PeriodicalId":53375,"journal":{"name":"Jurnal Informatika Jurnal Pengembangan IT","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135832246","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Implementasi Aplikasi Sentimen Pada Data Twitter Jelang Pemilu 2024 在 2024 年大选前利用推特数据实施情感应用程序

Jurnal Informatika Jurnal Pengembangan IT Pub Date : 2023-05-29 DOI: 10.30591/jpit.v8i2.5051

Choirul Humam, Arif Dwi Laksito

{"title":"Implementasi Aplikasi Sentimen Pada Data Twitter Jelang Pemilu 2024","authors":"Choirul Humam, Arif Dwi Laksito","doi":"10.30591/jpit.v8i2.5051","DOIUrl":"https://doi.org/10.30591/jpit.v8i2.5051","url":null,"abstract":"Elections are one of the most important democratic processes, giving citizens the right to choose their leaders. In today's digital era, social media is an increasingly important information source influencing public perception. Twitter has been a social media from the past until now that still exists in finding information. Tweets are one of the most frequently used services to express opinions or opinions to the public. Sentiment analysis as an application of Natural Language Processing (NLP) is helpful in understanding public opinion towards prospective leaders and issues discussed during election campaigns. The motivation for this study is to conduct text classification using a deep learning model called LSTM and to compare the use of oversampling and non-oversampling methods. This research started by collecting datasets from Twitter, labelling, pre-processing, creating and evaluating the model, and implementing it into the web application. The experiment showed that the random oversampling technique gets more significant accuracy than non-oversampling. Random oversampling produces an accuracy of 0.82 at epoch 25, while non-oversampling reaches an accuracy of 0.61 at epoch 50","PeriodicalId":53375,"journal":{"name":"Jurnal Informatika Jurnal Pengembangan IT","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135831925","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Rancang Bangun Aplikasi Bon Permintaan Dan Pengeluaran Barang Menggunakan Metode Prototype Berbasis Website 利用网站原型设计Bon应用程序和产品支出

Jurnal Informatika Jurnal Pengembangan IT Pub Date : 2023-05-29 DOI: 10.30591/jpit.v8i2.5220

Aielsa Naomi Athaya, Noveri Lysbetti Marpaung

{"title":"Rancang Bangun Aplikasi Bon Permintaan Dan Pengeluaran Barang Menggunakan Metode Prototype Berbasis Website","authors":"Aielsa Naomi Athaya, Noveri Lysbetti Marpaung","doi":"10.30591/jpit.v8i2.5220","DOIUrl":"https://doi.org/10.30591/jpit.v8i2.5220","url":null,"abstract":"Goods purchase requisitions and goods issue documents are receipts for purchase requisitions and goods issues for distribution goods from the unit of work to the warehouse. pt. Perkebunan Nusantara V still uses the manual method of registering and approving the Goods Request Form using a form filled out by a factory assistant and signed by multiple parties. Therefore, it takes 5-30 business days to collect all signatures. If all parties are present, the product request notification can be signed and approved immediately. However, if this is not the case, the bill of goods approval process will be delayed. For this reason, urgent needs often result in goods being released from the warehouse before the invoice has been fully approved. Therefore, there is a need for an application that helps companies manage good purchase requisitions from warehouses. The application is implemented as a website that allows users to approve notes step-by-step online. The prototyping method allows developers to design and build systems more efficiently because discussions take place between users and developers during the system development process. PHP Laravel is used as programming language and MySQL as database. The tests for this application are based on the ISO 9126 test standard and give the following results: According to the USE survey, functionality scored 100%, reliability scored A, usability scored 90.07 across the four factors, efficiency scored B, performance score 88%, The structural score was 87%. Maintainability was evaluated as A grade with a debt ratio of 2.6%, and portability was evaluated as 100%. This application reduced the approval time to less than 5 hours and test results showed that the application works well and is suitable for enterprise use","PeriodicalId":53375,"journal":{"name":"Jurnal Informatika Jurnal Pengembangan IT","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135832237","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Pengenalan Alfabet SIBI Menggunakan Convolutional Neural Network sebagai Media Pembelajaran Bagi Masyarakat Umum SIBI字母表导论利用神经连接网络作为公共学习媒介

Jurnal Informatika Jurnal Pengembangan IT Pub Date : 2023-05-29 DOI: 10.30591/jpit.v8i2.5221

Zahrah Fadhilah, Noveri Lysbetti Marpaung

{"title":"Pengenalan Alfabet SIBI Menggunakan Convolutional Neural Network sebagai Media Pembelajaran Bagi Masyarakat Umum","authors":"Zahrah Fadhilah, Noveri Lysbetti Marpaung","doi":"10.30591/jpit.v8i2.5221","DOIUrl":"https://doi.org/10.30591/jpit.v8i2.5221","url":null,"abstract":"SIBI is one of the Sign Languages used in Indonesia and has been widely used in the community, especially the school (SLB). Communication limitations of the deaf and speech community cause limited communication with the general public, especially many general public who do not know Sign Language or SIBI. For this reason, this research was conducted in order to become a learning media for the general public in recognizing the SIBI alphabet so that it can support communication with the deaf and speech community. This research was conducted to become a medium that can be used as a learning medium in the introduction of the SIBI alphabet. The method used in this research is CNN. CNN is used because it is a deep learning method that has the most significant results in image recognition. The data used is 2,600 images which are divided into 80% training data and 20% validation data. Training was done ten times by comparing the parameters that produce the best accuracy. The parameters used are batch size and epoch. From ten trials, the best accuracy is obtained using batch size 8 and epoch 50. The best accuracy produced is 85% training accuracy and 87% validation accuracy.","PeriodicalId":53375,"journal":{"name":"Jurnal Informatika Jurnal Pengembangan IT","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135832232","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Pemanfaatan Algoritma K-Means untuk Membuktikan Implementasi Undang-Undang Pelanggaran Hukum Korupsi di Pengadilan Negeri Banjarmasin 利用k -均值算法来证明班雅尔马辛的《非法腐败法》的实施

Jurnal Informatika Jurnal Pengembangan IT Pub Date : 2023-05-29 DOI: 10.30591/jpit.v8i2.5216

Cinantya Paramita, Fauzi Adi Rafrastara, Catur Supriyanto

{"title":"Pemanfaatan Algoritma K-Means untuk Membuktikan Implementasi Undang-Undang Pelanggaran Hukum Korupsi di Pengadilan Negeri Banjarmasin","authors":"Cinantya Paramita, Fauzi Adi Rafrastara, Catur Supriyanto","doi":"10.30591/jpit.v8i2.5216","DOIUrl":"https://doi.org/10.30591/jpit.v8i2.5216","url":null,"abstract":"This research aims to demonstrate the implementation of the Anti-Corruption Law in the Banjarmasin District Court by utilizing the K-Means algorithm. Corruption, which persists in Indonesia over a prolonged period, has reached a critical level, making it crucial to enforce the law fairly and firmly. In this study, the panel of judges in the Banjarmasin District Court was analyzed using the K-Means Clustering method and silhouette coefficient to decide corruption cases that result in state losses. The research findings indicate that the optimal number of clusters is 3, with a value of 0.686. However, there is also a lowest value among the 4 clusters, which is 0.454. These clusters are then divided into three categories of enforcement, namely cases that have been executed (108 cases), cases that will be executed (26 cases), and cases that have not been executed (2 cases). All clusters have a silhouette score of 0.742, indicating successful enforcement. This research provides concrete evidence that the panel of judges in the Banjarmasin District Court has implemented the Anti-Corruption Law while considering state losses. By utilizing the K-Means algorithm, this study also contributes to a better understanding of enforcement practices in the court. It is expected that the results of this research will support efforts to enhance the implementation of the Anti-Corruption Law in Indonesia, particularly in the Banjarmasin District Court","PeriodicalId":53375,"journal":{"name":"Jurnal Informatika Jurnal Pengembangan IT","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135832240","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Sistem Pakar Diagnosis Penyakit Pada Ikan Bawal Bintang dengan Pendekatan Naive bayes 采用 Naive Bayes 方法诊断海星疾病的专家系统

Jurnal Informatika Jurnal Pengembangan IT Pub Date : 2023-05-28 DOI: 10.30591/jpit.v8i2.4750

Dasril Aldo, Yohani Setiya Rafika Nur, M. Yoka Fathoni

{"title":"Sistem Pakar Diagnosis Penyakit Pada Ikan Bawal Bintang dengan Pendekatan Naive bayes","authors":"Dasril Aldo, Yohani Setiya Rafika Nur, M. Yoka Fathoni","doi":"10.30591/jpit.v8i2.4750","DOIUrl":"https://doi.org/10.30591/jpit.v8i2.4750","url":null,"abstract":"The star pomfret is a type of cultivated fish that has high economic prospects. The focus of the main problem in this study is the disease that attacks the star pomfret fish commodity. If this is allowed to continue, it will cause crop failure and cause the fishermen to lose money. Through this research, an expert system is one solution that can overcome these problems. The expert system built will apply the Naive Bayes method with the stages of entering the dataset into the database which will be used as training data, then the user inputs testing data to be processed into the Bayes method, in the final result the probability value of each disease will be displayed which will then be given recommendations on how to control it disease. From the symptoms selected by the user, namely: white or pale spots on the surface of the body, bleeding on the surface of the body, protruding eyes, the fish looks difficult to breathe, mucus production increases until the body runs out of mucus / roughness, fish lose their appetite, slow movement and slow growth get disease results Cryptocaryon with a value of 93.4. The results of tests carried out on 17 data obtained an accuracy value of 94% so that the expert system is suitable for use as a tool for diagnosing disease in pomfret","PeriodicalId":53375,"journal":{"name":"Jurnal Informatika Jurnal Pengembangan IT","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135895766","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0