Jurnal SAINTEKOM最新文献

Implementasi Aplikasi Laporjalanku untuk Pemetaan dan Pelaporan Jalan Rusak di Wilayah Kota Tarakan 实施 Laporjalanku 应用程序，用于绘制和报告塔拉干市地区受损道路的情况

Jurnal SAINTEKOM Pub Date : 2024-03-31 DOI: 10.33020/saintekom.v14i1.489

A. Wardani, Miftahurrahma Rosyda

{"title":"Implementasi Aplikasi Laporjalanku untuk Pemetaan dan Pelaporan Jalan Rusak di Wilayah Kota Tarakan","authors":"A. Wardani, Miftahurrahma Rosyda","doi":"10.33020/saintekom.v14i1.489","DOIUrl":"https://doi.org/10.33020/saintekom.v14i1.489","url":null,"abstract":"Tarakan City has road facilities with various degrees of damage, ranging from minor to severe conditions. To address this issue, a WebGIS application is required to provide information about the road conditions. This research aims to develop the \"Laporjalanku\" application, designed to assist the public in reporting road damage in Tarakan City and mapping information about damaged roads. The application enables the public to easily report complaints via the web or their Android smartphones. Its features include information such as images of damaged roads, the location of damage, and estimated repair times. The development methodology used is the waterfall model, ensuring a systematic and sequential system development process. Black-box testing showed that the system functions well. Meanwhile, the System Usability Scale (SUS) test resulted in a score of 84.5%, categorized as good, and meeting user experience requirements. This application streamlines the road mapping and reporting process, providing accurate information to the Department of Public Works. Additionally, it serves as a vital tool for the government and the public to improve collaboration in maintaining the city's road conditions.","PeriodicalId":359182,"journal":{"name":"Jurnal SAINTEKOM","volume":"38 20","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140358045","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

Penerapan Algoritma K-Means untuk Klasterisasi Produksi Budidaya Perikanan Provinsi Sulawesi Utara 北苏拉威西省水产养殖生产聚类中 K-Means 算法的应用

Jurnal SAINTEKOM Pub Date : 2024-03-31 DOI: 10.33020/saintekom.v14i1.528

S. Sakur, Miske Silangen, Desmin Tuwohingide

{"title":"Penerapan Algoritma K-Means untuk Klasterisasi Produksi Budidaya Perikanan Provinsi Sulawesi Utara","authors":"S. Sakur, Miske Silangen, Desmin Tuwohingide","doi":"10.33020/saintekom.v14i1.528","DOIUrl":"https://doi.org/10.33020/saintekom.v14i1.528","url":null,"abstract":"Capture fisheries production is decreasing due to natural resources or weather conditions, so other resources are needed to support fisheries production. One alternative is to increase the production of aquaculture commodities through seawater, freshwater, or brackish water cultivation. Various potentials for developing aquaculture have been developed in various regions, including the North Sulawesi region. Grouping aquaculture commodity production according to container type is very important to maintain and increase aquaculture production. This research aims to cluster aquaculture production in the North Sulawesi area using the K-Means method using Euclidean, Manhattan, and Minkowsky distances. The results of the research obtained three clusters, namely the first cluster, the region with the highest production of pond container types, namely the Sitaro Islands, and for second cluster consisting of 13 regions that have variations in production ranging from low to high for the types of floating net containers and ponds, while third cluster is the region Bitung with moderate production for pond types. It is hoped that this research can help related agencies to create policies to increase the production potential of aquaculture.","PeriodicalId":359182,"journal":{"name":"Jurnal SAINTEKOM","volume":"38 44","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140357985","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

Model Klasifikasi Machine Learning untuk Prediksi Ketepatan Penempatan Karir 用于职业安置准确性预测的机器学习分类模型

Jurnal SAINTEKOM Pub Date : 2024-03-31 DOI: 10.33020/saintekom.v14i1.512

Hendri Mahmud Nawawi, Agung Baitul Hikmah, Ali Mustopa, Ganda Wijaya

{"title":"Model Klasifikasi Machine Learning untuk Prediksi Ketepatan Penempatan Karir","authors":"Hendri Mahmud Nawawi, Agung Baitul Hikmah, Ali Mustopa, Ganda Wijaya","doi":"10.33020/saintekom.v14i1.512","DOIUrl":"https://doi.org/10.33020/saintekom.v14i1.512","url":null,"abstract":"The complexity of the job market requires individuals and organizations to understand the trends and needs of the world of work. One of the main challenges is the right career placement. That is becoming increasingly popular is the use of Machine Learning algorithms in the decision-making process. ML classification models such as Random Forest, Decision Tree, Naïve Bayes, KNN, and SVM have demonstrated their potential in uncovering hidden patterns from data, including a person's educational history, work experience and interests. In this research, the application of the ML classification model is aimed at predicting career placement. From the data sample used of 215, this research evaluates the effectiveness of various ML models in the context of career placement. As a result, the Random Forest Model is superior to other proposed models with an accuracy value of 87% and an AUC/ROC value of 0.93 which indicates a very good classification value. Meanwhile, the SVM model with Linear Kernel shows the lowest performance with an accuracy value of 67%. Apart from getting information on the best accuracy and AUC/ROC values, the results of this research found that the 'ssc_presentage' attribute (high school exam percentage) is an important factor in career placement decisions.","PeriodicalId":359182,"journal":{"name":"Jurnal SAINTEKOM","volume":"19 7","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140361087","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

Evaluasi Keamanan Teknologi Informasi Menggunakan Indeks Keamanan Informasi 5.0 dan ISO/EIC 27001:2022 使用信息安全指数 5.0 和 ISO/EIC 27001:2022 评估信息技术安全

Jurnal SAINTEKOM Pub Date : 2024-03-31 DOI: 10.33020/saintekom.v14i1.623

Lucia Devlina Adventia Jelita, Moh. Noor Al Azam, A. Nugroho

{"title":"Evaluasi Keamanan Teknologi Informasi Menggunakan Indeks Keamanan Informasi 5.0 dan ISO/EIC 27001:2022","authors":"Lucia Devlina Adventia Jelita, Moh. Noor Al Azam, A. Nugroho","doi":"10.33020/saintekom.v14i1.623","DOIUrl":"https://doi.org/10.33020/saintekom.v14i1.623","url":null,"abstract":"In the era of digital transformation, data has become something valuable but vulnerable to leaks. According to Lanskap Keamanan SIber Indonesia 2022, there were 311 data leakage incidents that occurred in Indonesia. Many tools can be used to evaluate information security, one of which is the Information Security Index (ISI). KAMI is a tool to assess the level of information security readiness of an organization based on the SNI ISO / IEC 27001 standard. PT Kano Teknologi Utama is a company that uses information technology in its daily operations. Therefore, researchers conducted an information technology security evaluation to determine the condition of information security and can evaluate it so that security becomes better. The evaluation is carried out by conducting observations and interviews at the company. The data that has been obtained will then be assessed according to OUR Index. Based on the results of the Our Index assessment, the electronic system category score obtained is 19 and is included in the high category. While the final evaluation result is \"Good Enough\" with a final score of 674 and the level of completeness of implementation based on the ISO 27001 standard is at levels II to IV.","PeriodicalId":359182,"journal":{"name":"Jurnal SAINTEKOM","volume":"24 9","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140359886","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

Pengukuran Kematangan Keamanan Siber pada Perusahaan Teknologi Informasi dengan Framework Center for Internet Security Controls 利用互联网安全控制框架中心衡量信息技术公司的网络安全成熟度

Jurnal SAINTEKOM Pub Date : 2024-03-31 DOI: 10.33020/saintekom.v14i1.610

Mohammad Afdhal Jauhari, Bheta Agus Wardijono, Ega Hegarini

引用次数: 0

Klasifikasi Sentimen Terhadap Kualitas Aplikasi Bahan Ajar Digital Akademik Universitas Terbuka di Google Play 开放大学学术数字教材质量的情感分类应用于 Google Play

Jurnal SAINTEKOM Pub Date : 2024-03-31 DOI: 10.33020/saintekom.v14i1.591

Rhini Fatmasari, Windu Gata, Nia Kusuma Wardhani, Kurnia Prayogi, Modesta Binti Husna

{"title":"Klasifikasi Sentimen Terhadap Kualitas Aplikasi Bahan Ajar Digital Akademik Universitas Terbuka di Google Play","authors":"Rhini Fatmasari, Windu Gata, Nia Kusuma Wardhani, Kurnia Prayogi, Modesta Binti Husna","doi":"10.33020/saintekom.v14i1.591","DOIUrl":"https://doi.org/10.33020/saintekom.v14i1.591","url":null,"abstract":"Terbuka University is a leading institution that implements the optimization of digital transformation, especially in distance learning systems. To improve the quality of service to students and stakeholders, Terbuka University has developed the Terbuka University Digital Learning Materials application. This application offers several learning modules that can be accessed through the Google Play Store. This research aims to classify data using different labels related to reviews of the Terbuka University Digital Learning Materials application using the Long Short-Term Memory classification algorithm. Evaluation is conducted to find accuracy, f1-score, precision, and recall values. The research results show that classification with Long Short-Term Memory achieves an accuracy of 76.72% with the Vader label, and the accuracy with the TextBlob label reaches 74.21%. Confusion matrix evaluation shows precision results of 0.91 and recall of 0.78, with an f1-score of 0.84 for the Vader label. For the TextBlob label, the precision is 0.96, recall is 0.45, and the f1-score is 0.61. This research contributes positively to understanding the evaluation and classification of reviews of the Terbuka University Digital Learning application. Implementing the Long Short-Term Memory algorithm with the Vader label can be an effective choice to improve service and learning quality through the application.","PeriodicalId":359182,"journal":{"name":"Jurnal SAINTEKOM","volume":"11 24","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140358981","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

Perancangan User Interface dan User Experience Aplikasi Klinik Gigi Menggunakan Metode Design Thinking 用设计思维方法设计牙科诊所应用程序的用户界面和用户体验

Jurnal SAINTEKOM Pub Date : 2024-03-31 DOI: 10.33020/saintekom.v14i1.601

Dhea Putri Salsabila, Risqy Siwi Pradini, Ahsanun Naseh Khudori

{"title":"Perancangan User Interface dan User Experience Aplikasi Klinik Gigi Menggunakan Metode Design Thinking","authors":"Dhea Putri Salsabila, Risqy Siwi Pradini, Ahsanun Naseh Khudori","doi":"10.33020/saintekom.v14i1.601","DOIUrl":"https://doi.org/10.33020/saintekom.v14i1.601","url":null,"abstract":"Klinik Gigi drg. Ema Medika so far still provides services to patients manually and keeps medical records using paper documents. This causes data invalidity and sometimes the confidentiality of patient data cannot be maintained properly. To increase efficiency, this research designed an application Prototype for Klinik Gigi drg. Ema Medika. The Design Thinking method is used as an approach in Prototype development, which consists of the stages of knowing user problems and needs, identifying user problems, determining solution ideas, creating a Prototype, and conducting testing. Through the designed Prototype, users can interact with the user interface and experience the user experience. Testing was carried out using User Acceptance Testing (UAT) and produced a value of 97.37. Thus, it can be concluded that the Prototype design of the Klinik Gigi drg. Ema Medika application can meet user needs very well. The expectation is that the outcomes of this study can play a role in the adoption of information technology solutions that are both effective and efficient within the dental clinic setting, leading to an enhancement in the level of service provided to patients.","PeriodicalId":359182,"journal":{"name":"Jurnal SAINTEKOM","volume":"95 8","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140360304","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

Analisis Opini Terhadap Aplikasi Riliv di Twitter Menggunakan Algoritma Naïve Bayes dan Random Forest 使用奈维贝叶斯和随机森林算法对 Twitter 上的 Riliv 应用程序进行舆情分析

Jurnal SAINTEKOM Pub Date : 2024-03-31 DOI: 10.33020/saintekom.v14i1.526

Diana Nurfitriana, Taufik Ridwan, A. Voutama

{"title":"Analisis Opini Terhadap Aplikasi Riliv di Twitter Menggunakan Algoritma Naïve Bayes dan Random Forest","authors":"Diana Nurfitriana, Taufik Ridwan, A. Voutama","doi":"10.33020/saintekom.v14i1.526","DOIUrl":"https://doi.org/10.33020/saintekom.v14i1.526","url":null,"abstract":"In the current era of technological advancement and the internet, people can easily access various information. This technological advancement brings innovation in the mental health field, such as services in the form of apps. This research conducts sentiment analysis using the Naïve Bayes and Random Forest algorithms. The study aims to analyze Twitter users’ opinions regarding the Riliv apps and compare the results of classification using Naïve Bayes and Random Forest. This research methodology uses the AI Project Cycle method. The data used is tweet data from Twitter with the keyword 'aplikasi riliv’. The dataset consisted of 1035 data, which was processed to produce 273 positive, 273 neutral, and 39 negative sentiments data. The Naïve Bayes and Random Forest algorithms were applied to compare the classification results of the two. The most optimal classification results are Naïve Bayes with SMOTE with the division of 90% training data and 10% testing data, which results in an accuracy value of 82.72%, a value of precision is 82.89% and a value of recall is 82.72%. Based on the results of the distribution of sentiment data, most users gave positive reviews and were knowledgeable about the Riliv application, while only a few were disappointed","PeriodicalId":359182,"journal":{"name":"Jurnal SAINTEKOM","volume":"11 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140360869","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 Chatbot untuk Layanan Frequently Asked Question Akademik dengan Penggunaan Dialogflow

Jurnal SAINTEKOM Pub Date : 2023-03-31 DOI: 10.33020/saintekom.v13i1.337

Zain Ahmad Taufik, S. Supriyanto

引用次数: 2

Algoritma K-Means dalam Pengelompokan Surat Keluar pada Program Studi Teknik Informatika STMIK Palangkaraya

Jurnal SAINTEKOM Pub Date : 2023-03-31 DOI: 10.33020/saintekom.v13i1.356

Lili Rusdiana, V. Hardita

引用次数: 0