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APLIKASI KEHADIRAN SISWA BERBASIS ANDROID MENGGUNAKAN QR CODE DI BIMBEL EXCELLENT INSTITUTE

Jurnal Teknoinfo Pub Date : 2022-01-14 DOI: 10.33365/jti.v16i1.1362

Darul Mukminin, Ameliana Ameliana, Adiiba Dwikanthi, Lukas Umbu Zogara

引用次数: 0

PENGGUNAAN USER CENTERED DESIGN DALAM PEMBUATAN WEBSITE PORTAL MGBK SMA KOTA MALANG

Jurnal Teknoinfo Pub Date : 2022-01-14 DOI: 10.33365/jti.v16i1.1358

Arif Tirtana, H. Hadi, Adnan Zulkarnain

引用次数: 3

ANALISIS CART (CLASSIFICATION AND REGRESSION TREES) UNTUK PREDIKSI PENGGUNA SEPEDA BERDASARKAN CUACA

Jurnal Teknoinfo Pub Date : 2022-01-14 DOI: 10.33365/jti.v16i1.1478

Annida Purnamawati, Monikka Nur Winnarto, Mely Mailasari

引用次数: 4

IMPLEMENTASI ALGORITMA YOLO DAN TESSERACT OCR PADA SISTEM DETEKSI PLAT NOMOR OTOMATIS 采用自动车牌检测系统的YOLO算法和TESSERACT OCR算法

Jurnal Teknoinfo Pub Date : 2022-01-14 DOI: 10.33365/jti.v16i1.1522

Imam Husni Al amin, Awan Aprilino

{"title":"IMPLEMENTASI ALGORITMA YOLO DAN TESSERACT OCR PADA SISTEM DETEKSI PLAT NOMOR OTOMATIS","authors":"Imam Husni Al amin, Awan Aprilino","doi":"10.33365/jti.v16i1.1522","DOIUrl":"https://doi.org/10.33365/jti.v16i1.1522","url":null,"abstract":"Currently, vehicle number plate detection systems in general still use the manual method. This will take a lot of time and human effort. Thus, an automatic vehicle number plate detection system is needed because the number of vehicles that continues to increase will burden human labor. In addition, the methods used for vehicle number plate detection still have low accuracy because they depend on the characteristics of the object being used. This study develops a YOLO-based automatic vehicle number plate detection system. The dataset used is a pretrained YOLOv3 model of 700 data. Then proceed with the number plate text extraction process using the Tesseract Optical Character Recognition (OCR) library and the results obtained will be stored in the database. This system is web-based and API so that it can be used online and on the cross-platform. The test results show that the automatic number plate detection system reaches 100% accuracy with sufficient lighting and a threshold of 0.5 and for the results using the Tesseract library, the detection results are 92.32% where the system is successful in recognizing all characters on the license plates of cars and motorcycles. in the form of Alphanumeric characters of 7-8 characters.","PeriodicalId":344455,"journal":{"name":"Jurnal Teknoinfo","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121275295","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

PENERAPAN AUGMENTED REALITY PADA ANATOMI TUBUH MANUSIA UNTUK MENDUKUNG PEMBELAJARAN TITIK TITIK BEKAM PENGOBATAN ALTERNATIF 采用人体解剖学的增强现实，以支持替代医学的点焊点的学习

Jurnal Teknoinfo Pub Date : 2022-01-14 DOI: 10.33365/jti.v16i1.1521

Imam Ahmad, S. Samsugi, Y. Irawan

引用次数: 6

IMPLEMENTASI METODE AHP PADA SISTEM PENDUKUNG KEPUTUSAN PARIWISATA JAWA TIMUR AHP方法的实施支持东爪哇旅游决策系统

Jurnal Teknoinfo Pub Date : 2022-01-14 DOI: 10.33365/jti.v16i1.1401

Putri Lannidya Parameswari, Ida Astuti, Winda Widya Ariestya

引用次数: 3

PENERAPAN METODE MARKER BASED TRACKING AUGMENTED REALITY PESUT MAHAKAM 基于跟踪增强现实的日本方法标记

Jurnal Teknoinfo Pub Date : 2022-01-14 DOI: 10.33365/jti.v16i1.1270

M. Firdaus, E. Budiman, Fernando Elda Pati, Andi Tejawati, Lathifah Lathifah, M. Anam

引用次数: 1

IMPLEMENTASI DENSITY-BASED CLUSTERING PADA SEGMENTASI CITRA Betta Fish 实现基于密度的聚类PADA分割

Jurnal Teknoinfo Pub Date : 2022-01-14 DOI: 10.33365/jti.v16i1.1273

Yunda Heningtyas, Fathur Rahmi, Kurnia Muludi

{"title":"IMPLEMENTASI DENSITY-BASED CLUSTERING PADA SEGMENTASI CITRA Betta Fish","authors":"Yunda Heningtyas, Fathur Rahmi, Kurnia Muludi","doi":"10.33365/jti.v16i1.1273","DOIUrl":"https://doi.org/10.33365/jti.v16i1.1273","url":null,"abstract":"During the COVID-19 pandemic, the number of ornamental fish enthusiasts has increased, especially those of the Betta Fish species. Betta Fish is a type of ornamental Fish with various species with beautiful colors and morphology, especially the shape of the tail. The more diverse the color patterns of the Fish and the unique shape, the more expensive the selling price of this type of ornamental Fish. The market demand for Betta Fish is getting higher, causing the selling price of Betta Fish also to increase. However, not all ornamental fish lovers recognize the species name of the Betta Fish. For this reason, a pattern recognition-based system is needed that can recognize Betta Fish species. Pattern recognition has several stages, namely segmentation, extraction, and classification. This study aims to separate the object from the background on a digital image. The dataset used is 160 images consisting of 40 images of each species, namely Halfmoon, Double Tail, Serit, and Plakat. The first step is to convert the image into a saturation and intensity color model. The method used in the segmentation process is Density-Based Clustering. Density-Based Clustering is a segmentation method by forming clusters based on the density level of the object area. The segmentation process using the DensityBased Clustering method achieves an accuracy rate of 92.82%. Keyword: Betta Fish, Density-Based Clustering, HSI, Image Recognition, Image Segmentation","PeriodicalId":344455,"journal":{"name":"Jurnal Teknoinfo","volume":"402 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126678362","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 CUACA PROVINSI DKI JAKARTA MENGGUNAKAN ALGORITMA RANDOM FOREST DENGAN TEKNIK OVERSAMPLING

Jurnal Teknoinfo Pub Date : 2022-01-14 DOI: 10.33365/jti.v16i1.1533

Faqih Hamami, Iqbal Ahmad Dahlan

引用次数: 1

PENGEMBANGAN SISTEM INFORMASI PENYAKIT TIDAK MENULAR (PTM) BERBASIS TEKNOLOGI INFORMASI 以信息技术为基础的非传染性信息系统(PTM)的发展

Jurnal Teknoinfo Pub Date : 2022-01-14 DOI: 10.33365/jti.v16i1.1520

Hesti Kurniasih, Katrin Dwi Purnanti, Rangga Atmajaya

引用次数: 4