MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer最新文献_第6页

Tsunami Vulnerability and Risk Assessment in Banyuwangi District using machine learning and Landsat 8 image data 利用机器学习和Landsat 8图像数据对Banyuwangi地区海啸脆弱性和风险进行评估

MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer Pub Date : 2023-03-28 DOI: 10.30812/matrik.v22i2.2677

Gallen Cakra adhi Wibowo, S. Y. Prasetyo, I. Sembiring

{"title":"Tsunami Vulnerability and Risk Assessment in Banyuwangi District using machine learning and Landsat 8 image data","authors":"Gallen Cakra adhi Wibowo, S. Y. Prasetyo, I. Sembiring","doi":"10.30812/matrik.v22i2.2677","DOIUrl":"https://doi.org/10.30812/matrik.v22i2.2677","url":null,"abstract":"The tsunami is a disaster that often occurs in Indonesia, there are no valid indicators to assess and monitor coastal areas based on functional land use and based on land cover which refers to the biophysical characteristics of the earth's surface. One of the recommended methods is the vegetation index. Vegetation index is a method from LULC that can be used to provide information on how severe the impact of the tsunami was on the area.In this study, an increase in the vegetation index was carried out using machine learning. The purpose of this study was to develop a tsunami vulnerability assessment model using the Vegetation Index extracted from Landsat 8 satellite imagery optimized with KNN, Random Forest and SVM. The stages of study, are: 1)extraction Landsat 8 images using algorithms NDVI, NDBI, NDWI, MSAVI, and MNDWI; 2) prediction of vegetation indices using KNN, Random Forest, and SVM algorithms. 3) accuracy testing using the MSE, RMSE, and MAE,4) spatial prediction using the Kriging function and 5) tsunami modelling vulnerability indicators. The results of this study indicate that the NDVI interpolation value is 0 - 0.1 which is defined as vegetation density, biomass growth, and moderate to low vegetation health. the NDWI value is 0.02 - 0.08 and the MNDWI value is 0.02 - 0.09 which is interpreted as the presence of surface water along the coast. MSAVI is a value of 0.1 – 0 which is defined as the absence of vegetation. The NDBI interpolation value is -0.05 - (-0.08) which is interpreted as the existence of built-up land with social and economic activities. From the results of research on the 10 areas studied, there are 3 areas with conditions that have a high level of tsunami vulnerability. 2 areas with medium vulnerability and 5 areas with low vulnerability to tsunami.","PeriodicalId":364657,"journal":{"name":"MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132269853","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

Seamless Security on Mobile Devices Textual Password Quantification Model Based Usability Evaluation of Secure Rotary Entry Pad Authentication 基于文本密码量化模型的移动设备无缝安全旋转入口垫安全认证可用性评估

MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer Pub Date : 2023-03-24 DOI: 10.30812/matrik.v22i2.2700

Herman Kabetta, Hermawan Setiawan, Fetty Amelia, Muhammad Qolby Fawzan

{"title":"Seamless Security on Mobile Devices Textual Password Quantification Model Based Usability Evaluation of Secure Rotary Entry Pad Authentication","authors":"Herman Kabetta, Hermawan Setiawan, Fetty Amelia, Muhammad Qolby Fawzan","doi":"10.30812/matrik.v22i2.2700","DOIUrl":"https://doi.org/10.30812/matrik.v22i2.2700","url":null,"abstract":"Mobile devices are vulnerable to shoulder surfing and smudge attacks, which should occur when a user enters a PIN for authentication purposes. This attack can be avoided by implementing a rotary entry pad mechanism. Despite this, several studies have found that using a rotary entry pad reduces user usability. This study uses a Design Research Methodology approach. It will implement a rotary entry pad authentication in the Android operating system as an authentication method to protect the device against Shoulder Surfing Attacks and Smudge Attacks. Furthermore, it combined JSON Web Token (JWT) to secure the authentication process from the client to the server. At the end of implementation, it compared with other studies in terms of usability and evaluated it using the TQ-Model, which showed that the usability aspect has improved. Regarding security, we conducted a shoulder surfing attack simulation to assess the efficacy of guessing PINs. The results showed that only a limited number of attempts were successful, with two out of five samples failing to guess any numbers and only one sample successfully guessing six 10-digit PIN combinations out of 10 to the power of 10. The security test results show that shoulder surfing attacks are more difficult to perform after implementing the rotary entry pad. The evaluation showed that the JSpinpad performed better, with seven parameters showing improvement, one parameter showing a decline, and ten parameters remaining unchanged.","PeriodicalId":364657,"journal":{"name":"MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129657918","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

Blockchain-based Trust, Transparent, Traceable Modeling on Learning Recognition System Kampus Merdeka 基于区块链的信任、透明、可追溯的学习识别系统建模

MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer Pub Date : 2023-03-24 DOI: 10.30812/matrik.v22i2.2780

Irawan Afrianto, A. Heryandi, S. Atin

{"title":"Blockchain-based Trust, Transparent, Traceable Modeling on Learning Recognition System Kampus Merdeka","authors":"Irawan Afrianto, A. Heryandi, S. Atin","doi":"10.30812/matrik.v22i2.2780","DOIUrl":"https://doi.org/10.30812/matrik.v22i2.2780","url":null,"abstract":"Kampus Merdeka is an evolution of education in Indonesia that accommodates various changes. The existence of a mechanism that includes various actors in it makes Kampus Merdeka have many new outcomes which must be recognized by all stakeholders who need it. Blockchain technology and smart contract offer the ability to build trust between all actors in the Kampus Merdeka activities with their transparent nature and reliable, immutable data storage capabilities. Every stage that occurs in it can be traced from upstream to downstream. This study aims to design an architectural model of a blockchain system for the learning recognition system Kampus Merdeka. It uses the analyticalstudy to identify the possible problems and the stakeholders involved and design the model solution proposed. As a result, it proposed the type of blockchain and the most suitable architecture for use in the learning recognition system Kampus Merdeka. In this study, the blockchain model is proposed as a mechanism for identifying and recognizing learning outcomes in the Kampus Merdeka environment more securely, challenging to modify, and traceable by all parties to ensure the authenticity of the learning outcomes. Furthermore, it can be recognized by all parties in it.","PeriodicalId":364657,"journal":{"name":"MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer","volume":"73 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126149080","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

Essay auto-scoring using N-Gram and Jaro Winkler based Indonesian Typos 文章自动评分使用N-Gram和Jaro Winkler基于印尼打字错误

MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer Pub Date : 2023-03-24 DOI: 10.30812/matrik.v22i2.2473

H. Jayadianti, B. Santosa, Judanti Cahyaning, S. Saifullah, Rafał Dreżewski

{"title":"Essay auto-scoring using N-Gram and Jaro Winkler based Indonesian Typos","authors":"H. Jayadianti, B. Santosa, Judanti Cahyaning, S. Saifullah, Rafał Dreżewski","doi":"10.30812/matrik.v22i2.2473","DOIUrl":"https://doi.org/10.30812/matrik.v22i2.2473","url":null,"abstract":"Writing errors on e-essay exams reduce scores. Thus, detecting and correcting errors automatically in writing answers is necessary. The implementation of Levenshtein Distance and N-Gram can detect writing errors. However, this process needed a long time because of the distance method used. Therefore, this research aims to hybrid Jaro Winker and N-Gram methods to detect and correct writing errors automatically. This process required preprocessing and finding the best word recommendations by the Jaro Winkler method, which refers to Kamus Besar Bahasa Indonesia (KBBI). The N-Gram method refers to the corpus. The final scoring used the Vector Space Model (VSM) method based on the similarity of words between the answer keys and the respondent’s answers. Datasets used 115 answers from 23 respondents with some writing errors. The results of Jaro Winkler and N-Gram methods are good in detecting and correcting Indonesian words with the accuracy of detection averages of 83.64% (minimum of 57.14% and maximum of 100.00%). In contrast, the error correction accuracy averages 78.44% (minimum of 40.00% and maximum of 100.00%). However, Natural Language Processing (NLP) needs to improve these results for word recommendations.","PeriodicalId":364657,"journal":{"name":"MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer","volume":"76 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129480682","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

Hybrid Model for Sentiment Analysis of Bitcoin Prices using Deep Learning Algorithm 基于深度学习算法的比特币价格情绪分析混合模型

MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer Pub Date : 2023-03-24 DOI: 10.30812/matrik.v22i2.2640

Rizky Afrinanda, Lusiana Efrizoni, Wirta Agustin, R. Rahmiati

{"title":"Hybrid Model for Sentiment Analysis of Bitcoin Prices using Deep Learning Algorithm","authors":"Rizky Afrinanda, Lusiana Efrizoni, Wirta Agustin, R. Rahmiati","doi":"10.30812/matrik.v22i2.2640","DOIUrl":"https://doi.org/10.30812/matrik.v22i2.2640","url":null,"abstract":"Bitcoin is a decentralized digital currency, which is not controlled by a single authority or government. Bitcoin uses blockchain technology to verify transactions and guarantee user security and privacy. The fluctuating value of bitcoin is influenced by opinions that develop because many people use these opinions as a basis for buying or selling bitcoins. Knowledge to find out the market conditions of bitcoin based on public opinion is very necessary. This study aims to develop a hybrid model for bitcoin sentiment analysis. The dataset used came from comments on the Indodax website chat room, as many as 2890 data were successfully collected, then do data preprocessing, translate to english, text labeling and used hybrid parallel CNN and LSTM using word embedding glove 100 dimensions. Results of the experiments conducted, at 90:10 data splitting and 100 epochs is the best model with 88% accuracy, 86% precision, 78% recall and 81% f1-score, while the classification of opinion text comments on indodax chat results in 64.22% neutral comments, 21.14% positive comments and 14.63% negative comments. Based on research results, use of a parallel hybrid model provides a high accuracy value in classifying text, from these results positive comments are more than negative so that investors are advised to buy bitcoins. \u0000 ","PeriodicalId":364657,"journal":{"name":"MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114302142","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: 1

The Effect of Class Imbalance Handling on Datasets Toward Classification Algorithm Performance 类不平衡处理对数据集分类算法性能的影响

MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer Pub Date : 2023-03-01 DOI: 10.30812/matrik.v22i2.2515

Cherfly Kaope, Yoga Pristyanto

{"title":"The Effect of Class Imbalance Handling on Datasets Toward Classification Algorithm Performance","authors":"Cherfly Kaope, Yoga Pristyanto","doi":"10.30812/matrik.v22i2.2515","DOIUrl":"https://doi.org/10.30812/matrik.v22i2.2515","url":null,"abstract":"Class imbalance is a condition where the amount of data in the minority class is smaller than that of the majority class. The impact of the class imbalance in the dataset is the occurrence of minority class misclassification, so it can affect classification performance. Various approaches have been taken to deal with the problem of class imbalances such as the data level approach, algorithmic level approach, and cost-sensitive learning. At the data level, one of the methods used is to apply the sampling method. In this study, the ADASYN, SMOTE, and SMOTE-ENN sampling methods were used to deal with the problem of class imbalance combined with the AdaBoost, K-Nearest Neighbor, and Random Forest classification algorithms. The purpose of this study was to determine the effect of handling class imbalances on the dataset on classification performance. The tests were carried out on five datasets and based on the results of the classification the integration of the ADASYN and Random Forest methods gave better results compared to other model schemes. The criteria used to evaluate include accuracy, precision, true positive rate, true negative rate, and g-mean score. The results of the classification of the integration of the ADASYN and Random Forest methods gave 5% to 10% better than other models.","PeriodicalId":364657,"journal":{"name":"MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer","volume":"520 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123062076","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: 1

A computational approach in analyzing the empathy to online donations during COVID-19 新型冠状病毒肺炎疫情期间网络捐赠共情分析的计算方法

MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer Pub Date : 2023-02-06 DOI: 10.30812/matrik.v22i2.2396

Akmal Setiawan Wijaya, Dhomas Hatta Fudholi, A. R. Pratama

{"title":"A computational approach in analyzing the empathy to online donations during COVID-19","authors":"Akmal Setiawan Wijaya, Dhomas Hatta Fudholi, A. R. Pratama","doi":"10.30812/matrik.v22i2.2396","DOIUrl":"https://doi.org/10.30812/matrik.v22i2.2396","url":null,"abstract":"The COVID-19 pandemic has a negative impact on many aspects of life. The global economic downturn is one of these negative consequences. Nonetheless, even though everyone feels the threat of this pandemic for themselves, some people still have the empathy to help others. An empirical analysis of this empathy attitude is expected to be a catalyst in realizing a social force for the community to work together to combat this pandemic. This study will look at how people felt about donating during the COVID-19 pandemic on Twitter. The goals of this study are to (1) compare differences in donor desire before and during the COVID-19 pandemic using the developed model, and (2) determine whether there is a significant difference in empathy for donating before and during the pandemic. This study employs computational social science (CSS) techniques to achieve this goal. The data was obtained from Twitter using the keyword \"donation\" in the 24 months preceding the pandemic and in the 24 months following the pandemic's arrival in Indonesia. Data analysis includes hypothesis testing using Mann-Whitney and Cohen's D statistical tests, showing a significant increase in online donation support among Indonesian Twitter users since the COVID-19 pandemic hit. From the results of data processing data obtained 159.995 data in accordance with the criteria to be analyzed. From the results of the Mann-Whitney test, all variables showed significant results between before and during the Covid-19 pandemic and in the results of the Cohen's d test, all variables got a large effect size. From the results of the two tests, it can open Twitter social media users who have increased empathy to donate during the Covid-19 pandemic in Indonesia","PeriodicalId":364657,"journal":{"name":"MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133216869","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

Smart Assessment Menggunakan Backpropagation Neural Network 智能评估。孟古那坎反向传播神经网络

MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer Pub Date : 2022-07-31 DOI: 10.30812/matrik.v21i3.1469

Agung Teguh Wibowo Almais, Cahyo Crysdian, Khadijah Fahmi Hayati Holle, Akbar Roihan

{"title":"Smart Assessment Menggunakan Backpropagation Neural Network","authors":"Agung Teguh Wibowo Almais, Cahyo Crysdian, Khadijah Fahmi Hayati Holle, Akbar Roihan","doi":"10.30812/matrik.v21i3.1469","DOIUrl":"https://doi.org/10.30812/matrik.v21i3.1469","url":null,"abstract":"Penerapan scraping dan Backpropagation Neural Network dapat menjadikan penilaian Self- Assessment Questionnaire (SAQ) website Pemerintah Daerah Provinsi Jawa Timur lebih smart jika dibandingkan dengan model assessment yang sudah ada. Langkah awal yaitu melakukan scraping website Pemerintah Daerah Provinsi Jawa Timur untuk mendapatkan nilai SAQ. Hasil scraping tersebut akan digunakan sebagai data uji pada metode Backpropagation Neural Network, kemudian hasil data uji akan di proses menggunakan 4 jenis model data yang berbeda-beda dari segi jumlah iterasi dan hidden layer untuk mendapatkan akurasi terbaik. Pada model data A menggunakan iterasi 1000 dan 5 hidden layer menghasilkan nilai Mean Squared Error (MSE) 0,0117, Mean Absolute Percent Error (MAPE) 39,36% dan Akurasi 60.64%. Model data B menggunakan iterasi 1000 dan 7 hidden layer menghasilkan nilai MSE 0,0087, MAPE 29,49% dan Akurasi 70,50%. Model data C dengan menggunakan iterasi 2000 dan 9 hidden layer menghasilkan nilai MSE 0,0064, MAPE 24,46% dan Akurasi 75,53%. Model data D menggunakan iterasi 2000 dan 9 hidden layer menghasilkan nilai MSE 0,0036, MAPE 18,71% dan Akurasi 81,28%. Dari hasil ujicoba tersebut bahwa model data D yang menggunakan iterasi 2000 dan 9 hidden layer menghasilkan tingkat akurasi yang terbaik sehingga model data D dapat dijadikan acuan hasil penilaian website Pemerintah Daerah Provinsi Jawa Timur tahun 2021.","PeriodicalId":364657,"journal":{"name":"MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121480378","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: 1

Aplikasi Dynamic Cluster pada K-Means BerbasisWeb untuk Klasifikasi Data Industri Rumahan 基于web的动态集群对家庭企业数据分类的应用

MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer Pub Date : 2022-07-31 DOI: 10.30812/matrik.v21i3.1720

Hadi Santoso, Hilyah Magdalena, Helna Wardhana

{"title":"Aplikasi Dynamic Cluster pada K-Means BerbasisWeb untuk Klasifikasi Data Industri Rumahan","authors":"Hadi Santoso, Hilyah Magdalena, Helna Wardhana","doi":"10.30812/matrik.v21i3.1720","DOIUrl":"https://doi.org/10.30812/matrik.v21i3.1720","url":null,"abstract":"Masalah utama yang dihadapi Pemerintah Daerah Provinsi Kepulauan Bangka Belitung saat ini adalah sulitnya mengklasifikasikan data industri rumahan berdasarkan Peraturan Menteri PPPA No 2 Tahun 2016 yaitu pemula, berkembang dan maju. Berdasarkan permasalahan tersebut diusulkan pengembangan algoritma Kmeans yaitu algoritma Dynamic cluster pada K-means dengan tujuan agar dapat menghasilkan klaster yang optimal dalam pengelompokan data industri rumahan dengan membangun aplikasi cerdas berbasis web. Penelitian ini menggunakan metode analisis data mining SEMMA, yang meliputi tahapan-tahapan seperti data sampel, deskripsi data, transformasi data, pemodelan data, dan evaluasi data. 3.466 industri rumah tangga digunakan sebagai sampel data. Kinerja algoritma dievaluasi menggunakan pengukuran validitas klaster Davies Bouldin Index (DBI). Hasil eksperimen menunjukkan bahwa algoritma Dynamic cluster pada K-means memberikan nilai yang optimal pada iterasi ke lima, dengan perolehan sebagai berikut: klaster pemula (C1) diperoleh sebanyak 3214, kemudian klaster berkembang (C2) diperoleh sebanyak 167 dan klaster maju (C3) diperoleh sebanyak 85. Hasil evaluasi validitas klaster menunjukan bahwa algoritma Dynamic cluster pada Kmeans memperoleh nilai DBI lebih kecil dibandingkan dengan algoritma K-means dengan nilai DBI sebesar 0.184. Implementasi algoritma dynamic cluster pada K-means untuk pengelompokan data industri rumahan pada Dinas P3ACSKB di Provinsi Kepulauan Bangka Belitung terbukti menghasilkan kualitas cluster yang lebih optimal.","PeriodicalId":364657,"journal":{"name":"MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134431260","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: 1

Sistem Rumah Pintar Menggunakan Google Assistant dan Blynk Berbasis Internet of Things 基于物联网、使用谷歌助手和 Blynk 的智能家居系统

MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer Pub Date : 2022-07-31 DOI: 10.30812/matrik.v21i3.1646

Sirojul Hadi, Puspita Dewi, Radimas Putra Muhammad Davi Labib, Parama Diptya Widayaka

{"title":"Sistem Rumah Pintar Menggunakan Google Assistant dan Blynk Berbasis Internet of Things","authors":"Sirojul Hadi, Puspita Dewi, Radimas Putra Muhammad Davi Labib, Parama Diptya Widayaka","doi":"10.30812/matrik.v21i3.1646","DOIUrl":"https://doi.org/10.30812/matrik.v21i3.1646","url":null,"abstract":"Internet of things (IoT) merupakan topik yang banyak dikembangkan pada dekade terakhir. Pada saat ini, banyak pengembang teknologi membuat perangkat-perangkat pintar yang dapat mempermudah pekerjaan manusia. Sistem rumah pintar adalah salah satunya. Pada sistem rumah pintar, perangkatperangkat fisik dapat melakukan komunikasi melalui jaringan internet atau jaringan near cable lainnya untuk bertukar informasi atau melakukan perintah dari penghuni rumah. Agar bisa bertukar informasi maka perangkat fisik tersebut di integrasikan dengan sensor dan aktuator. Salah satu implementasi dari rumah pintar yaitu pengontrolan lampu yang dapat diaktifkan atau dinonaktifkan menggunakan perintah suara atau menggunakan gawai pengguna. Tujuan dari penelitian ini yaitu agar pengguna dapat mengontrol lampu rumah dengan menggunakan perintah suara dengan bantuan google assistant untuk mengenali kalimat yang di ucapkan oleh penghuni rumah. Metode yang digunakan dalam penelitian ini yaitu IoT. Metode komunikasi berbasis IoT memungkinkan terjadinya pertukaran data antar device. Hasil dari penelitian ini yaitu dapat dibangun sistem kontrol lampu menggunakan Blynk-Google assistant. Pada sistem tersebut telah di tambahkan fitur untuk memantau konsumsi daya listrik pengguna. Dari hasil pengujian yang dilakukan maka didapatkan hasil bahwa presentase keberhasilan dari sistem tersebut yaitu 96,667%. Keberhasilan dari sistem tersebut dipengaruhi oleh kekuatan sinyal internet dan ketepatan dalam pengucapan kata yang telah terprogram.","PeriodicalId":364657,"journal":{"name":"MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134581454","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: 2