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PH control for deep flow technique hydroponic IoT systems based on fuzzy logic controller 基于模糊控制器的深流技术水培物联网系统PH控制
Jurnal Teknologi dan Sistem Komputer Pub Date : 2020-10-13 DOI: 10.14710/jtsiskom.2020.13822
Adnan Rafi Al Tahtawi, R. Kurniawan
{"title":"PH control for deep flow technique hydroponic IoT systems based on fuzzy logic controller","authors":"Adnan Rafi Al Tahtawi, R. Kurniawan","doi":"10.14710/jtsiskom.2020.13822","DOIUrl":"https://doi.org/10.14710/jtsiskom.2020.13822","url":null,"abstract":"In hydroponic cultivation sites, pH control is still carried manually by checking the pH level with a pH meter and providing a pH balancing liquid manually. This study aims to design an automatic pH control system in the Deep Flow Technique (DFT) hydroponic system that uses the Internet of Things (IoT) based Fuzzy Logic Controller (FLC). The SKU SEN0161 sensor detects the pH value as FLC inputs in an error value and its changes. These inputs are processed using Mamdani FLC embedded in the Arduino Mega 2560 microcontroller. The FLC produces an output in a pH liquid feeding duration using the peristaltic pump. The results showed that FLC could maintain the pH value according to the set point with a settling time of less than 50 seconds, both with disturbance by adding pH liquid and without disturbance. The pH value can also be displayed on the website interface system as a monitoring system.","PeriodicalId":56231,"journal":{"name":"Jurnal Teknologi dan Sistem Komputer","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"67018169","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: 4
Implementation of vigenere cipher 128 and square rotation in securing text messages vigenere密码128和正方形旋转在保护文本消息中的实现
Jurnal Teknologi dan Sistem Komputer Pub Date : 2020-07-31 DOI: 10.14710/jtsiskom.2020.13476
Rihartanto Rihartanto, Riris Kurnia Ningsih, A. F. O. Gaffar, Didi Susilo Budi Utomo
{"title":"Implementation of vigenere cipher 128 and square rotation in securing text messages","authors":"Rihartanto Rihartanto, Riris Kurnia Ningsih, A. F. O. Gaffar, Didi Susilo Budi Utomo","doi":"10.14710/jtsiskom.2020.13476","DOIUrl":"https://doi.org/10.14710/jtsiskom.2020.13476","url":null,"abstract":"Information that can be in the form of text, image, audio, and video, is a valuable asset that needs to be secured from unauthorized parties. This research aims to study the implementation of Vigenere cipher 128 (VC-128) and square rotation to secure text information. The square rotation is applied to increase the security of the encryption results obtained from VC-128. The randomness of the rotation results was measured using Shannon entropy based on the distance between characters, and the Avalanche Effect measured changes in the encryption results compared to the original text. The square rotation can increase the randomness of the VC-128 encryption results, as indicated by an increase in entropy values. The highest increase in entropy of 34.8 % occurs in repetitive texts with the square size that produces optimal entropy was a 9x9 medium-size square. The Avalanche effect for each test data shows inconsistent results ranging from 44.5 % to 49 %.","PeriodicalId":56231,"journal":{"name":"Jurnal Teknologi dan Sistem Komputer","volume":"8 1","pages":"201-209"},"PeriodicalIF":0.0,"publicationDate":"2020-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46090619","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: 4
Discrimination of civet coffee using visible spectroscopy 果子狸咖啡的可见光谱鉴别
Jurnal Teknologi dan Sistem Komputer Pub Date : 2020-07-31 DOI: 10.14710/jtsiskom.2020.13734
Graciella Mae L. Adier, C. A. Reyes, Edwin R. Arboleda
{"title":"Discrimination of civet coffee using visible spectroscopy","authors":"Graciella Mae L. Adier, C. A. Reyes, Edwin R. Arboleda","doi":"10.14710/jtsiskom.2020.13734","DOIUrl":"https://doi.org/10.14710/jtsiskom.2020.13734","url":null,"abstract":"Civet coffee is considered as highly marketable and rare. This specialty coffee has a special flavor and higher price relative to regular coffee, and it is restricted in supply. Establishing a straightforward and efficient approach to distinguish civet coffee for quality; likewise, consumer protection is fundamental. This study utilized visible spectroscopy as a non-destructive and quick technique to obtain the absorbance, ranging from 450 nm to 650 nm, of the civet coffee and non-civet coffee samples. Overall, 160 samples were analyzed, and the total spectra accumulated was 960. The data gathered from the first 120 samples were fed to the classification learner application and were used as a training data set. The remaining samples were used for testing the classification algorithm. The study shows that civet coffee bean samples have lower absorbance values in visible spectra than non-civet coffee bean samples. The process yields 96.7 % to 100 % classification scores for quadratic discriminant analysis and logistic regression. Among the two classification algorithms, logistic regression generated the fastest training time of 14.050 seconds. The application of visible spectroscopy combined with data mining algorithms is effective in discriminating civet coffee from non-civet coffee.","PeriodicalId":56231,"journal":{"name":"Jurnal Teknologi dan Sistem Komputer","volume":"8 1","pages":"239-245"},"PeriodicalIF":0.0,"publicationDate":"2020-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45847966","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
Face recognition system with PCA-GA algorithm for smart home door security using Rasberry Pi 基于PCA-GA算法的Rasberry Pi智能家居门安全人脸识别系统
Jurnal Teknologi dan Sistem Komputer Pub Date : 2020-07-31 DOI: 10.14710/JTSISKOM.2020.13590
S. Subiyanto, Dina Priliyana, Moh. Eki Riyadani, N. Iksan, Hari Wibawanto
{"title":"Face recognition system with PCA-GA algorithm for smart home door security using Rasberry Pi","authors":"S. Subiyanto, Dina Priliyana, Moh. Eki Riyadani, N. Iksan, Hari Wibawanto","doi":"10.14710/JTSISKOM.2020.13590","DOIUrl":"https://doi.org/10.14710/JTSISKOM.2020.13590","url":null,"abstract":"Genetic algorithm (GA) can improve the classification of the face recognition process in the principal component analysis (PCA). However, the accuracy of this algorithm for the smart home security system has not been further analyzed. This paper presents the accuracy of face recognition using PCA-GA for the smart home security system on Raspberry Pi. PCA was used as the face recognition algorithm, while GA to improve the classification performance of face image search. The PCA-GA algorithm was implemented on the Raspberry Pi. If an authorized person accesses the door of the house, the relay circuit will unlock the door. The accuracy of the system was compared to other face recognition algorithms, namely LBPH-GA and PCA. The results show that PCA-GA face recognition has an accuracy of 90 %, while PCA and LBPH-GA have 80 % and 90 %, respectively.","PeriodicalId":56231,"journal":{"name":"Jurnal Teknologi dan Sistem Komputer","volume":"65 5","pages":"210-216"},"PeriodicalIF":0.0,"publicationDate":"2020-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41288929","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
Optimization of k value and lag parameter of k-nearest neighbor algorithm on the prediction of hotel occupancy rates k-最近邻算法在酒店入住率预测中的k值和滞后参数优化
Jurnal Teknologi dan Sistem Komputer Pub Date : 2020-07-31 DOI: 10.14710/jtsiskom.2020.13648
Agus Subhan Akbar, R. H. Kusumodestoni
{"title":"Optimization of k value and lag parameter of k-nearest neighbor algorithm on the prediction of hotel occupancy rates","authors":"Agus Subhan Akbar, R. H. Kusumodestoni","doi":"10.14710/jtsiskom.2020.13648","DOIUrl":"https://doi.org/10.14710/jtsiskom.2020.13648","url":null,"abstract":"Hotel occupancy rates are the most important factor in hotel business management. Prediction of the rates for the next few months determines the manager's decision to arrange and provide all the needed facilities. This study performs the optimization of lag parameters and k values of the k-Nearest Neighbor algorithm on hotel occupancy history data. Historical data were arranged in the form of supervised training data, with the number of columns per row according to the lag parameter and the number of prediction targets. The kNN algorithm was applied using 10-fold cross-validation and k-value variations from 1-30. The optimal lag was obtained at intervals of 14-17 and the optimal k at intervals of 5-13 to predict occupancy rates of 1, 3, 6, 9, and 12 months later. The obtained k-value does not follow the rule at the square root of the number of sample data.","PeriodicalId":56231,"journal":{"name":"Jurnal Teknologi dan Sistem Komputer","volume":"8 1","pages":"246-254"},"PeriodicalIF":0.0,"publicationDate":"2020-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41959128","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
Optimization for prediction model of palm oil land suitability using spatial decision tree algorithm 基于空间决策树算法的棕榈油土地适宜性预测模型优化
Jurnal Teknologi dan Sistem Komputer Pub Date : 2020-07-31 DOI: 10.14710/JTSISKOM.2020.13657
Andi Nurkholis, I. S. Sitanggang
{"title":"Optimization for prediction model of palm oil land suitability using spatial decision tree algorithm","authors":"Andi Nurkholis, I. S. Sitanggang","doi":"10.14710/JTSISKOM.2020.13657","DOIUrl":"https://doi.org/10.14710/JTSISKOM.2020.13657","url":null,"abstract":"Land suitability evaluation has a vital role in land use planning aimed to increase food production effectiveness. Palm oil is a leading and strategic commodity for Indonesian people, which is predicted consumption will exceed production in the future. This study aims to evaluate palm oil land suitability using a spatial decision tree algorithm that is conventional decision tree modification for spatial data classification with adding spatial join relation. The spatial dataset consists of eight explanatory layers (soil nature and characteristics), and a target layer (palm oil land suitability) in Bogor District, Indonesia. This study produced three models, where the best model was obtained based on optimizing accuracy (98.18 %) and modeling time (1.291 seconds). The best model has 23 rules, soil texture as the root node, two variables (drainage and cation exchange capacity) are uninvolved, with land suitability visualization obtains percentage S2 (29.94 %), S3 (53.16 %), N (16.57 %), and water body (0.33 %).","PeriodicalId":56231,"journal":{"name":"Jurnal Teknologi dan Sistem Komputer","volume":"8 1","pages":"192-200"},"PeriodicalIF":0.0,"publicationDate":"2020-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46888670","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: 12
People counter on CCTV video using histogram of oriented gradient and Kalman filter methods 人们对CCTV视频进行了定向梯度直方图和卡尔曼滤波
Jurnal Teknologi dan Sistem Komputer Pub Date : 2020-07-31 DOI: 10.14710/jtsiskom.2020.13660
F. Adhinata, M. Ikhsan, W. Wahyono
{"title":"People counter on CCTV video using histogram of oriented gradient and Kalman filter methods","authors":"F. Adhinata, M. Ikhsan, W. Wahyono","doi":"10.14710/jtsiskom.2020.13660","DOIUrl":"https://doi.org/10.14710/jtsiskom.2020.13660","url":null,"abstract":"CCTV cameras have an important function in the field of public service, especially for convenience. The objects recorded through CCTV cameras are processed into information to support service satisfaction in the community. This study uses the function of CCTV for people counting from objects recorded by a camera. Currently, the process of detecting and tracking people takes a long time to detect all frames. In this study, the frame selection into keyframes uses the mutual information entropy method. The keyframes processing uses the Histogram of Oriented Gradient (HOG) and Kalman filter methods. The proposed method results F1 value of 0.85, recall of 76 %, and precision of 97 % with winStride parameter (12,12), scale 1.05, and the distance of the human object to CCTV 4 meters.","PeriodicalId":56231,"journal":{"name":"Jurnal Teknologi dan Sistem Komputer","volume":"8 1","pages":"222-227"},"PeriodicalIF":0.0,"publicationDate":"2020-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42595978","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: 5
Deep learning model for metagenome fragment classification using spaced k-mers feature extraction 基于间隔k-mers特征提取的宏基因组片段分类深度学习模型
Jurnal Teknologi dan Sistem Komputer Pub Date : 2020-07-31 DOI: 10.14710/jtsiskom.2020.13407
Nur Choiriyati, Y. Arkeman, W. Kusuma
{"title":"Deep learning model for metagenome fragment classification using spaced k-mers feature extraction","authors":"Nur Choiriyati, Y. Arkeman, W. Kusuma","doi":"10.14710/jtsiskom.2020.13407","DOIUrl":"https://doi.org/10.14710/jtsiskom.2020.13407","url":null,"abstract":"Tantangan dalam analisis dunia bioinformatika adalah analisis sekuens metagenom yang diambil dari berbagai lingkungan. Proses binning pada sampel metagenom dapat dilakukan dengan menghitung frekuensi kemunculan k-mers dari suatu sekuens metagenom. Ekstraksi fitur spaced k-mers dilakukan dengan membandingkan fragmen metagenom dengan substring berukuran k atau k-mers, namun membolehkan kondisi inexact matching (don’t care position). Deep Learning muncul kembali sebagai paradigma baru dalam machine learning yang memberikan solusi terbaik untuk banyak masalah dalam pengenalan pola. Penelitian ini bertujuan untuk membandingkan kinerja dua arsitektur deep learning, yaitu DNN dan CNN, untuk klasifikasi data metagenom menggunakan spaced k-mers sebagai ekstraksi fitur. Klasifikasi dengan menggunakan deep learning memberikan hasil yang lebih baik, yaitu 90,89 % menggunakan DNN dan 88,89 % menggunakan CNN, dibandingkan dengan naive Bayes yang menghasilkan akurasi sebesar 85,42 % pada taksonomi tingkat genus.","PeriodicalId":56231,"journal":{"name":"Jurnal Teknologi dan Sistem Komputer","volume":"8 1","pages":"234-238"},"PeriodicalIF":0.0,"publicationDate":"2020-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45350859","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: 4
Maturity classification of cacao through spectrogram and convolutional neural network 基于谱图和卷积神经网络的可可成熟度分类
Jurnal Teknologi dan Sistem Komputer Pub Date : 2020-06-04 DOI: 10.14710/jtsiskom.2020.13733
Gilbert E. Bueno, Kristine A. Valenzuela, Edwin R. Arboleda
{"title":"Maturity classification of cacao through spectrogram and convolutional neural network","authors":"Gilbert E. Bueno, Kristine A. Valenzuela, Edwin R. Arboleda","doi":"10.14710/jtsiskom.2020.13733","DOIUrl":"https://doi.org/10.14710/jtsiskom.2020.13733","url":null,"abstract":"Cacao pod's ideal harvesting time is when it is about to be ripe. Immature harvest would result in hard cacao beans not suitable for fermentation, while overripe cacao pods lead to fungal-infected, defective, and poor-quality yields. The demand for high-quality cacao products is expected to rise due to advancing technology in the present. Pre-harvesting needs to provide optimal identification of which amongst the pods are ripened enough and ready for the next stage of the cacao process. This paper recommends a technique to determine the ripeness of cacao. Nine hundred thirty-three cacao samples were used to collect thumping audio data at five different pod's exocarp locations. Each sound file is 1 second long, creating 4665 cacao sound file datasets at 16kHz sample rate and 16-bit audio bit depth. The process of the Mel-Frequency Cepstral Coefficient Spectogram was then applied to extract recognizable features for the training process. The deep learning method integrated was a convolutional neural network (CNN) to classify the cacao sound successfully. The experimental design model's output exhibits an accuracy of 97.50 % for the training data and 97.13 % for the validation data. While the overall accuracy mean of the classification system is 97.46 %, whether the cacao is unripe or ripe.","PeriodicalId":56231,"journal":{"name":"Jurnal Teknologi dan Sistem Komputer","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45261726","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: 5
Clothing size recommender on real-time fitting simulation using skeleton tracking and rigging 使用骨骼跟踪和索具进行实时试穿模拟的服装尺寸推荐
Jurnal Teknologi dan Sistem Komputer Pub Date : 2020-04-30 DOI: 10.14710/jtsiskom.8.2.2020.127-132
Arik Kurniawati, Ari Kusumaningsih, Yanuar Aliffio
{"title":"Clothing size recommender on real-time fitting simulation using skeleton tracking and rigging","authors":"Arik Kurniawati, Ari Kusumaningsih, Yanuar Aliffio","doi":"10.14710/jtsiskom.8.2.2020.127-132","DOIUrl":"https://doi.org/10.14710/jtsiskom.8.2.2020.127-132","url":null,"abstract":"Virtual fitting room (VFR) is a technology that replaces conventional fitting rooms. The VFR is not only available in shops, malls, and any shopping center but also in online stores, which makes VFR technology more and more developed, primarily to support online garment sales. VFR become a trending research interest since Microsoft has developed a Kinect tracking system. In this paper, we proposed the interactive 3D virtual fitting room using Microsoft's Kinect tracking and the rigging technique from 3D Modeling Blender and to implement the VFR. VFR manages the progress of virtual fitting that forms the three-dimensional simulations and visualization of garments on virtual counterparts of the real prospective buyer (user). Users can view the clothing animation on the various poses that are following the user body movements. The system can evaluate the user’s match, guiding them to choose the suitable size of the clothes using Euclidean distance.","PeriodicalId":56231,"journal":{"name":"Jurnal Teknologi dan Sistem Komputer","volume":"8 1","pages":"127-132"},"PeriodicalIF":0.0,"publicationDate":"2020-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"67028378","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: 5
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