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Penerapan Jaringan Syaraf Tiruan pada Hidung Elektronik Cerdas untuk Deteksi Daging Babi
Get PDFTingkat komsumsi daging sapi di Indonesia terus naik dari tahun ke tahun terlihat dari permintaan pasar yang terus meningkat terutama pada perayaan hari besar dan hari raya. Akan tetapi peningkatan permintaan pasar akan daging sapi masih kerap dimanfaatkan oleh oknum tak bertanggung jawab yang mencampur daging sapi dengan daging babi. berdasarkan fakta tersebut maka dibuat sebuah sistem electronic nose yang dapat membedakan antara daging sapi murni dengan daging sapi bercampur babi berdasarkan karakteristik aroma. Alat ini menerapkan jaringan syaraf tiruan (JST) backpropagation yang dilatih menggunakan aplikasi MATLAB untuk mengenali pola dari aroma sampel daging yang ditangkap menggunakan rangkaian sensor gas TGS2602, TGS2620, TGS2610 dan TGS2611, kemudian mengklasifikasikannya dalam dua kelas yaitu MURNI dan CAMPURAN. Sampel daging segar yang digunakan untuk pengujian ada 4 macam yaitu daging sapi murni, daging campuran 25%, 50% dan 75% dengan total sampel sebanyak 30 terdiri dari 15 sampel murni dan 15 sampel campuran. Dari pengujian tersebut didapat nilai akurasi, presisi, sensitivity dan specificity sebesar 100% menggunakan confusion matrix
Development of Applications for Simplification of Boolean Functions using Quine-McCluskey Method
Get PDFPurpose: This research makes an application to simplify the Boolean function using Quine-McCluskey, because length of the Boolean function complicates the digital circuit, so that it can be simplified by finding other functions that are equivalent and more efficient, making digital circuits easier, and less cost.Design/methodology/approach: The canonical form is Sum-of-Product/Product-of-Sum and is in the form of a file, while the output is in the form of a raw and in the form of a file. Applications can receive the same minterm/maksterm input and do not have to be sequential. The method has been applied by Idempoten, Petrick, Selection Sort, and classification, so that simplification is maximized.Findings/result: As a result, the application can simplify more optimally than previous studies, can receive the same minterm/maksterm input, Product-of-Sum canonical form, and has been verified by simplifying and calculating manually.Originality/value/state of the art: Research that applies the petrick method to applications combined with being able to receive the same minterm/maksterm input has never been done before. The calculation is only up to the intermediate stage of the Quine-McCluskey method or has not been able to receive the same minterm/maksterm input
Tahfidz Quran Monitoring System in Islamic Boarding Schools
Get PDFPurpose: development a good tahfidz quran monitoring system, in presenting the data to quran teachers and parents. Presentation of data in the proposed monitoring system is in the form of tables, text, a graph of the Tahfidz progression and a dashboard for the achievement of the Tahfidz target.Design/methodology/approach: waterfallFindings/result: the tahfidz monitoring system that presents data in the form of graphs, charts, tables and text, thus providing monitoring functions that are easy to read and quickly understood.Originality/value/state of the art: dashboard display and chart on the tahfidz quran monitoring syste
Backpropagation with BFGS Optimizer for Covid-19 Prediction Cases in Surabaya
Get PDFCovid-19 is a new type of corona virus called SARS-CoV-2. One of the cities that has contributed the most to infected Covid-19 cases in Indonesia is Surabaya, East Java. Predicting the Covid-19 is the important thing to do. One of the prediction methods is Artificial Neural Network (ANN). The backpropagation algorithm is one of the ANN methods that has been successfully used in various fields. However, the performance of backpropagation is depended on the architecture and optimization method. The standard backpropagation algorithm is optimized by gradient descent method. The Broyden - Fletcher - Goldfarb - Shanno (BFGS) algorithm works faster then gradient descent. This paper was predicting the Covid-19 cases in Surabaya using backpropagation with BFGS. Several scenarios of backpropagation parameters were also tested to produce optimal performance. The proposed method gives better results with a faster convergence then the standard backpropagation algorithm for predicting the Covid-19 cases in Surabaya
Implementation Of Text Mining For Emotion Detection Using The Lexicon Method (Case Study: Tweets About Covid-19)
Get PDFInformation and news about Covid-19 received various responses from social media users, including Twitter users. Changes in netizen opinion from time to time are interesting to analyze, especially about the patterns of public sentiment and emotions contained in these opinions. Sentiment and emotional conditions can illustrate the public\u27s response to the Covid-19 pandemic in Indonesia. This research has two objectives, first to reveal the types of public emotions that emerged during the Covid-19 pandemic in Indonesia. Second, reveal the topics or words that appear most frequently in each emotion class. There are seven types of emotions to be detected, namely anger, fear, disgust, sadness, surprise, joy, and trust. The dataset used is Indonesian-language tweets, which were downloaded from April to August 2020. The method used for the extraction of emotional features is the lexicon-based method using the EmoLex dictionary. The result obtained is a monthly graph of public emotional conditions related to the Covid-19 pandemic in the dataset
Classification of Anemia with Digital Images of Nails and Palms using the Naive Bayes Method
Get PDFPurpose: Early detection of anemia based on nails and palms images by applying the Naive Bayes method, as well as to measure the level of accuracy in detecting anemia.Design/methodology/approach: Using the Naive Bayes method. System development uses the waterfall method.Findings/result: Based on the results of the tests that have been carried out, the resulting accuracy is 87.5% with varying light intensities and is 92.3% by using a light intensity of 5362 Lux.Originality/value/state of the art: The difference between this study and previous research is in the image pre-processing method and classification method. In this study, the images of the nails and palms were converted to the YCbCr color space to be segmented and color features extracted. Then the color features will be classified using the Naive Bayes classification method. The output of this system is the result of the input image classification, whether normal or anemic
VGG16 Transfer Learning Architecture for Salak Fruit Quality Classification
Get PDFPurpose: This study aims to differentiate the quality of salak fruit with machine learning. Salak is classified into two classes, good and bad class.Design/methodology/approach: The algorithm used in this research is transfer learning with the VGG16 architecture. Data set used in this research consist of 370 images of salak, 190 from good class and 180 from bad class. The image is preprocessed by resizing and normalizing pixel value in the image. Preprocessed images is split into 80% training data and 20% testing data. Training data is trained by using pretrained VGG16 model. The parameters that are changed during the training are epoch, momentum, and learning rate. The resulting model is then used for testing. The accuracy, precision and recall is monitored to determine the best model to classify the images.Findings/result: The highest accuracy obtained from this study is 95.83%. This accuracy is obtained by using a learning rate = 0.0001 and momentum 0.9. The precision and recall for this model is 97.2 and 94.6.Originality/value/state of the art: The use of transfer learning to classify salak which never been used before
Decision Support System For Determining The Type Of Workout Using The Fuzzy Analythical Hierarchy Process (F-AHP) In GYM STIKI
Get PDFPurpose: Decision Support System for Determining the Type of Workout Using the Fuzzy Analythical Hierarchy Process (F-AHP) Method The STIKI GYM was created to make it easier for trainers to provide training for STIKI GYM participants who carry out workouts at STIKI GYM. Meanwhile, for STIKI GYM participants, the system can make it easier to carry out workout activities according to their respective body loads.Design/methodology/approach: Fuzzy Analythical Hierarchy Process (F-AHP) Method and being tested with black box testingFindings/result: Users can find out workout activities by entering the criteria for body weight, height, and exercise intensity into the system and helping trainers provide training in accordance with the recommendations for workout activities from the Decision Support System for Determining the Types of Workout Using the Fuzzy Analythical Hierarchy Process (F-AHP) Method at STIKI GYM.Originality/value/state of the art: The Decision Support System for determining the Type of Workout is indeed implemented at STIKI GYM by using data support in the form of interview results and participant data from STIKI GYM
Prediction Of Drug Sales Using Methods Forecasting Double Exponential Smoothing (Case Study : Hospital Pharmacy of Condong Catur)
Get PDFPurpose: Knowing the best alpha value from the data for each type of drug with various alpha parameters in the Double Exponential Smoothing Method and knowing the prediction results on each type of drug data at the Condong Catur Hospital pharmacy.Design/methodology/approach: Applying the Double Exponential Smoothing method with alpha parameters 0.1; 0.2; 0.3; 0.4; 0.5; 0.6; 0.7; 0.8; 0.9Findings/result: The test results on a system built using test data show that the double exponential smoothing method provides accuracy below 20% by producing a different Alpha (α) for each type of drug because the trend patterns in each drug sale are different at the Pharmacy at the Condong Catur Hospital. .Originality/value/state of the art: Based on previous research, this study has similar characteristics such as themes, parameters and methods used. Previous researchers used smoothing methods such as Double Exponential Smoothing in predicting stock / sales of goods
Sistem Informasi Manajemen Notulen (E-RISALAH) Konversi Voice to Text
Get PDFTujuan:Penelitian ini dilakukan untuk membantu notulis merisalahkan hasil rapat atau pertemuan dari suara menjadi tulisan. Sehingga kerja notulis lebih ringan dan menjaga kesehatan pendengaran. Perancangan/metode/pendekatan:Penelitian ini melalui beberapa tahap, yaitu perencaaan (planning), analisis (analysis), perancangan (design), dan implementasi (implementation). Hasil:Sistem Informasi Manajemen Notulen (E-RISALAH) Konversi Voice to Text berbasis website. Keaslian/state of the art:Risalah rapat adalah kegiatan mencatat atau menyalin seluruh hasil dari pertemuan. Dalam pelaksaan masih dikerjakan secara manual, dengan mendengarkan rekaman dan menyalin atau diketik secara manual, selain kurang efektif penggunaan headset dalam waktu yang lama dapat menggangu kesehatan pendengaran. Seiring perkembangan ilmu dan teknologi, maka dibuatlah sebuah sistem yang akan membantu merisalahkan hasil rapat dari suara menjadi tulisan. Dengan teknologi speech recognition dimana ini adalah sebuah kemampuan yang dimiliki oleh mesin atau aplikasi untuk mengindentifikasi kata dan frasa yang terdapat dalam bahasa lisan. Sehingga kerja notulis lebih ringan dan menjaga kesehatan pendengaran