Jurnal Informatika Jurnal Pengembangan IT最新文献

KONTROL PENGGUNAAN LISTRIK PASCABAYAR MENGGUNAKAN ANDROID 透过安卓系统控制邮资使用

Jurnal Informatika Jurnal Pengembangan IT Pub Date : 2023-08-30 DOI: 10.37639/jti.v13i2.349

Subair Bair Yusuf, M. Risal, A. Affandy, Arsianto Arsianto, Mursalim Sawawi

{"title":"KONTROL PENGGUNAAN LISTRIK PASCABAYAR MENGGUNAKAN ANDROID","authors":"Subair Bair Yusuf, M. Risal, A. Affandy, Arsianto Arsianto, Mursalim Sawawi","doi":"10.37639/jti.v13i2.349","DOIUrl":"https://doi.org/10.37639/jti.v13i2.349","url":null,"abstract":"Listrik pascabayar adalah listrik yang pembayaran tagihannya pada akhir bulan sesuai dengan energi yang digunakan. Meteran listrik pascabayar masih menggunakan alat analog yang menunjukkan besarnya daya yang telah digunakan. Sedangkan listrik prabayar adalah listrik yang pembayarannya berada di awal, yaitu dengan sistem pulsa. Dimana pelanggan dapat mengendalikan pemakaian listrik sendiri. Perbedaan yang mencolok dari listrik pascabayar dengan listrik prabayar adalah pada listrik prabayar pelanggan dapat mengontrol, melakukan monitoring atau pengecekan terhadap penggunaan listrik setiap hari dikarenakan sudah menggunakan meteran digital. Sedangkan pada listrik pascabayar alat meteran listriknya analog sehingga sulit untuk dikontrol dan dimonitoring. Adapun tujuan dari penelitian ini yaitu, 1) Merancang sebuah sistem yang dapat mengontrol dan memonitoring penggunaan daya listrik. 2) Menginplementasikan sebuah sistem yang dapat menontrol dan memonitoring penggunaan daya listrik. \u0000Sistem dibuat menggunakan mikrokontroler arduino nano dengan tambahan sensor daya PZEM-004T dan Nodemcu esp8266 untuk komuinikasi dengan internet menggunakan aplikasi firebase dan relay sebagai output tegangan listrik, sistem ini juga dapat dimonitoring dan dikontrol melalui smartphone android. \u0000Dengan adanya teknologi ini pelanggan dapat secara lansgung mengetahui berapa total daya yang digunakan dan berapa besar tarif yang akan dibayarkan. Pelanggan dapat menetukan tarif berdasarkan daya yang akan digunakan melalui smartphone, sensor daya akan membaca berapa daya yang sudah terpakai kemudian di kirim menggunakan NodMcu esp8266 ke data firebase dan dari data tersebut aplikasi dapat mengakses dan mengetahui berapa daya yang sudah terpakai dan berapa tarif yanag akan dibayar. Jika daya melewati batas maksimum pemakaian yang sudah ditentukan maka secara otomatis aliran listrik akan diputus ke arah terminal relay dan jika ingin menghidupkan kembali dilakukan reset daya pada aplikasi MIT APP Inventor pada android.","PeriodicalId":53375,"journal":{"name":"Jurnal Informatika Jurnal Pengembangan IT","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89502675","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

KLASIFIKASI SURAT DIGITAL MENGGUNAKAN ALGORITMA MACHINE LEARNING

Jurnal Informatika Jurnal Pengembangan IT Pub Date : 2023-08-30 DOI: 10.37639/jti.v13i2.350

Yuyun Yuyun

引用次数: 0

RANCANG BANGUN PENGOLES KUNING TELUR PADA ADONAN ROTI BERBASIS ARDUINO

Jurnal Informatika Jurnal Pengembangan IT Pub Date : 2023-07-11 DOI: 10.37639/jti.v13i2.348

M. Akbar, A. Affandy, Andi Edeth Fuari, N. Mustika, Aulia Ramdani, Asna Dewanti

{"title":"RANCANG BANGUN PENGOLES KUNING TELUR PADA ADONAN ROTI BERBASIS ARDUINO","authors":"M. Akbar, A. Affandy, Andi Edeth Fuari, N. Mustika, Aulia Ramdani, Asna Dewanti","doi":"10.37639/jti.v13i2.348","DOIUrl":"https://doi.org/10.37639/jti.v13i2.348","url":null,"abstract":"Penelitian ini bertujuan: (1) Merancang alat pengoles kuning telur pada adonan roti berbasis arduino. (2) Mengimplementasikan rancang bangun pengoles kuning telur pada adonan roti berbasis arduino. (3) Mempermudah dalam sistem pengolesan kuning telur pada adonan roti. Dalam industri roti rumah tangga memiliki beberapa tahap dalam memproduksi atau mengelola adonan roti. Salah satunya tahap pengolesan dimana rata-rata yang dikerjakan oleh tenaga manusia secara manual. Dari permasalahan tersebut, maka di buat rancangan pengoles adonan roti otomatis yang diharapkan dapat memudahkan pengolahan usaha roti mini dibagian pengolesan kuning telur. Rancang bangun pengoles kuning telur pada adonan roti berbasis arduino yang menggunakan motor DC sebagai alat penggerak pengoles adonan yang semuanya diproses di arduino uno. Dalam rancangan ini terdapat beberapa komponen yang digunakan yaitu, Sensor infrared digunakan sebagai pendeteksi adonan ketika adonan tersebut siap untuk dioles. Arduino uno digunakan sebagai pemroses data. Motor DC dan water pump sebagai penggerak bagian dari alat yaitu kuas kuning telur dan wadah kuning telur. Hasil rancangan alat ini membantu dalam proses pengolesan roti pada usaha roti.","PeriodicalId":53375,"journal":{"name":"Jurnal Informatika Jurnal Pengembangan IT","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76810107","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 GAME EDUKASI LABIRIN MATEMATIKA DENGAN ALGORITMA LINEAR CONGRUENT METHOD BERBASIS ANDROID

Jurnal Informatika Jurnal Pengembangan IT Pub Date : 2023-07-04 DOI: 10.37639/jti.v13i1.228

Purnamasari Dewi, M. Razak, Billy Eden William Asrul, Pujianti Wahyuningsih

引用次数: 0

ANALISIS PENERIMAAN DAN PENGGUNAAN APLIKASI PLATFORM FAN COMMUNITY WEVERSE MENGGUNAKAN TECHNOLOGY ACCEPTANCE MODEL(TAM)

Jurnal Informatika Jurnal Pengembangan IT Pub Date : 2023-07-04 DOI: 10.37639/jti.v12i3.221

I. Cantika, M. Ary

引用次数: 0

PERANCANGAN COMPANY PROFIL PT.FAJAR TECHNO SYSTEM BERBASIS WEB Perancangan公司简介。fajar技术系统的基础网站

Jurnal Informatika Jurnal Pengembangan IT Pub Date : 2023-07-04 DOI: 10.37639/jti.v13i2.287

Muhammad Alwi k, Risman Zulfahmi, Sitti Arni

引用次数: 0

Hybrid Fourier Descriptor Naïve Bayes dan CNN pada Klasifikasi Daun Herbal 混合傅立叶描述符奈维贝叶斯和 CNN 在草本植物叶片分类上的应用

Jurnal Informatika Jurnal Pengembangan IT Pub Date : 2023-06-09 DOI: 10.30591/jpit.v8i2.5186

Sunarti Passura Backar, Purnawansyah Purnawansyah, Herdianti Darwis, Wistiani Astuti

{"title":"Hybrid Fourier Descriptor Naïve Bayes dan CNN pada Klasifikasi Daun Herbal","authors":"Sunarti Passura Backar, Purnawansyah Purnawansyah, Herdianti Darwis, Wistiani Astuti","doi":"10.30591/jpit.v8i2.5186","DOIUrl":"https://doi.org/10.30591/jpit.v8i2.5186","url":null,"abstract":"Plants are vital to human life on earth, and the leaves and their whole parts have many benefits. These parts of the plant can help distinguish between different species. The leaf identification can be performed at any time, while the other parts of the plants can only be identified at a certain time. The study aims to classify two types of herbs i.e. saur-opus androgynous and moringa oleifera, implementing the Fourier Descriptor method to extract the shape and texture features. In the process of classification using the Naïve Bayes method with three types of nuclei (Gaussian, Bernoulli, and Multinomial) and a Convolutional Neural Network. The testing process was carried out using two scenarios, dark and light, where each scenario consisted of 240 images for a total of 480 images divided into 20% of the data testing and 80% of the training data. The Fourier Descriptor-Bernoulli Naive Bayes method gives the lowest accuracy in both light and dark scenarios, at 46% and 52%, respectively. As for the classification of herbal leaves using a combination of the Fourier Descriptor-Convolutional Neural Network method, it is recommended to be used in light image scenarios and Fourier Descriptor-Gaussian Naive Bayes in the dark scenarios because it is able to detect herbal leaf types with 100% accuracy.","PeriodicalId":53375,"journal":{"name":"Jurnal Informatika Jurnal Pengembangan IT","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-06-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135215534","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

KENDALI MONITORING DAN PENYIRAMAN TANAMAN CABAI DAN MONSTERA MENGGUNAKAN NODEMCU ESP8266 BERBASIS INTERNET OF THINGS 控制监测和给植物浇水，怪兽使用的是基于事物的NODEMCU esp266

Jurnal Informatika Jurnal Pengembangan IT Pub Date : 2023-06-07 DOI: 10.37639/jti.v13i3.335

M. T. Hidayat, Daud Bin, Guntur, Muhammad Akbar, Stmik Handayani Makassar, Kendali Monitoring, dan penyiraman, Tanaman Cabai, dan Monstera, Menggunakan Nodemcu

{"title":"KENDALI MONITORING DAN PENYIRAMAN TANAMAN CABAI DAN MONSTERA MENGGUNAKAN NODEMCU ESP8266 BERBASIS INTERNET OF THINGS","authors":"M. T. Hidayat, Daud Bin, Guntur, Muhammad Akbar, Stmik Handayani Makassar, Kendali Monitoring, dan penyiraman, Tanaman Cabai, dan Monstera, Menggunakan Nodemcu","doi":"10.37639/jti.v13i3.335","DOIUrl":"https://doi.org/10.37639/jti.v13i3.335","url":null,"abstract":"Sulitnya merawat tanaman agar tetap terjaga kelembaban tanahnya menjadi tantangan tersendiri karena penyesuaian dengan kontur tanah juga menyebabkan sulitnya mengurus setiap jenis tanaman yang mempunyai kebutuhan Kadar air dan kelembaban tanah yang berbeda-beda, faktor itulah yang menyebabkan kurangnya lingkungan hijau di setiap pemukiman di Kota. Kendali Monitoring dan penyiraman tanaman cabai dan monstera menggunakan nodemcu berbasis internet of things ini diharapkan mampu memberikan solusi pada masalah tersebut diatas. Sistem ini dirancang menggunakan metode R&D (Research and Development), microcontroller Arduino Nano pada alat ini akan membaca data dari sensor soil moisture dan diproses sebagai data perbandingan untuk membuka keran solenoid untuk menyiram bila data kelembaban pada tanaman berada dibawah limit tertentu yang akan disesuaikan pada setiap tanaman dan secara otomatis keran solenoid akan mati bila data kelembaban pada tanaman telah memenuhi nilai idealnya. Data kelembaban juga akan dikirim menggunakan Nodemcu esp8266 ke database firebase dan dari data tersebut, aplikasi dapat mengakses dan mengetahui keadaan tanaman yang kering melalui perangkat android. Hasil pengujian yang didapatkan, sensor kelembaban tanah dapat mengirimkan data yang telah dikonversi dalam bentuk persen dan dikirimkan pada aplikasi android serta melakukan penyiraman otomatis bila kelembaban tanah pada cabai atau monstera dibawah minimum kebutuhannya.","PeriodicalId":53375,"journal":{"name":"Jurnal Informatika Jurnal Pengembangan IT","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-06-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88685647","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

Klasifikasi Citra Virus SARS-COV Menggunakan Deep Learning 利用深度学习进行 SARS-COV 病毒图像分类

Jurnal Informatika Jurnal Pengembangan IT Pub Date : 2023-05-31 DOI: 10.30591/jpit.v8i2.4587

Indah Susilawati, Supatman Supatman, Arita Witanti

{"title":"Klasifikasi Citra Virus SARS-COV Menggunakan Deep Learning","authors":"Indah Susilawati, Supatman Supatman, Arita Witanti","doi":"10.30591/jpit.v8i2.4587","DOIUrl":"https://doi.org/10.30591/jpit.v8i2.4587","url":null,"abstract":"Various variants of the SARS-COV virus emerged from 2003 to early 2022. This resulted in a heavy burden on the health sector in carrying out its duties and public services. It would be very helpful if a computer-assisted application was available that could distinguish between the variants of the SARS-CoV virus. From a scientific point of view, this is an opportunity for information technology to play its role to classify SARS-COV variants using supporting algorithms, including the use of artificial intelligence. Artificial intelligence-based and computer-assisted processes are certainly more immune to negative effects due to repetitive works and fatigue. In this study, Classification of the SARS-COV Virus Image Using Deep Learning (CNN) was carried out based on microscopic data called Transmission Electron Microscopy (TEM) images. The aim of the research is to produce a neural network (CNN/Deep Learning) that has been trained to classify two types of variants of the SARS virus, namely SARS-COV and SARS-COV2. The research phase includes data collection, data pre-processing (consists of the image format conversion and enhancing process), and the classification stage. The classification is carried out using both of the original and enhanced image data. The highest classification accuracy was obtained when the original image data was used, namely 77.66%. It was also found that the classification accuracy increased with an increase in the input image size, but the image data enhancing process used was not able to increase the classification accuracy beyond the classification accuracy achieved when using the original image.","PeriodicalId":53375,"journal":{"name":"Jurnal Informatika Jurnal Pengembangan IT","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135439421","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

Klasifikasi Jamur Berdasarkan Genus Dengan Menggunakan Metode CNN 通过CNN的方法对真菌属进行分类

Jurnal Informatika Jurnal Pengembangan IT Pub Date : 2023-05-30 DOI: 10.30591/jpit.v8i2.5229

Ummi Sri Rahmadhani, Noveri Lysbetti Marpaung

{"title":"Klasifikasi Jamur Berdasarkan Genus Dengan Menggunakan Metode CNN","authors":"Ummi Sri Rahmadhani, Noveri Lysbetti Marpaung","doi":"10.30591/jpit.v8i2.5229","DOIUrl":"https://doi.org/10.30591/jpit.v8i2.5229","url":null,"abstract":"Mushrooms are plants that do not have true roots and leaves. There are many types of mushrooms that have been identified worldwide, with various shapes, sizes, and colors. Mushrooms have many benefits in the fields of economy, health, and others. One of the benefits of mushrooms is as a food source in Indonesia, but not all types can be consumed. To identify mushroom species, the concepts of Genus and species can be used. The concept of Genus is considered easier because it groups mushroom types based on similar morphological characteristics. Therefore, a model is needed to classify mushrooms based on consumable and toxic genera. The method used in this research is Convolution Neural Network (CNN) due to its good predictive results in image recognition. The model in the research utilizes three convolution layers, three MaxPooling layers, and two dropout layers. The use of dropout aims to reduce overfitting in the model. The research uses a dataset of 1200 images with a training and testing data ratio of 70:30, resulting in 840 training data and 360 testing data. The best accuracy achieved by this model is 89% for training and 82% for validation. Therefore, it can be concluded that the model is able to classify mushrooms based on Genus using the CNN method","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":"135693196","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