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All Journal Buletin Nutrisi dan Makanan Ternak Poltekita : Jurnal Ilmu Kesehatan JURNAL ABDIMAS TRIDHARMA MANAJEMEN Svasta Harena: Jurnal Ilmiah Gizi Jurnal Pengabdian Masyarakat Lentora OKTAL : Jurnal Ilmu Komputer dan Sains Jurnal Pengabdian Masyarakat Svasta Harena JRIIN :Jurnal Riset Informatika dan Inovasi Buletin Ilmiah Ilmu Komputer dan Multimedia (BIIKMA)
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Agriculture, Biological Sciences & Forestry Humanities Astronomy Biochemistry, Genetics & Molecular Biology Chemistry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Health Professions Medicine & Pharmacology Nursing Public Health Social Sciences

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Journal : OKTAL : Jurnal Ilmu Komputer dan Sains

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Penerapan Fuzzy Logic Control Pada Prototype Solar Tracker Berbasis Arduino Mochamad Miftah; Nurjaya
OKTAL : Jurnal Ilmu Komputer dan Sains Vol 3 No 04 (2024): OKTAL : Jurnal Ilmu Komputer Dan Sains
Publisher : CV. Multi Kreasi Media

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Abstract

Solar energy is a renewable energy that can be an alternative energy that can be used for industrial and household needs. And solar energy can be converted into electrical energy. Several industries and households already use solar panels to convert solar energy and make electrical energy. However, conventional solar panels still do not get optimal results. To get optimal results, a control device using a microcontroller is needed. A microcontroller is a complete microprocessor system contained in a chip. The system is designed using the Mamdani fuzzy control method. The Mamdani method is a fuzzy inference method. The Mamdani method has the advantage of being easier to implement in a programming language and easier to understand. The control system that has been built is proven to be able to control the movement of solar panels in relation to sunlight so that it can increase the required electrical power.
Implementasi Metode MTCNN (Multitask Cascaded Convolutional Neural Neteowk) Pada Sistem Absensi Berbasis Face Recognition Mohd.Faizal Bin Laranti; Nurjaya
OKTAL : Jurnal Ilmu Komputer dan Sains Vol 3 No 06 (2024): OKTAL : Jurnal Ilmu Komputer Dan Sains
Publisher : CV. Multi Kreasi Media

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Abstract

Human facial expressions can describe a person's emotions, by knowing human facial expressions, the process of recognizing human emotions will be helped. For example is to recognize individual satisfaction of a service. One method that is well-known today for facial expression recognition systems is the Convolutional Neural Network (CNN). In this study, a CNN architecture will be built which has 8 convolution layers, with a depth of 32 layers. Almost all research on facial expression recognition has used datasets of non-Indonesian races. Therefore, the authors conducted an analysis of the non-Indonesian racial dataset with the Indonesian race dataset using the cross dataset technique. In this system the self- built CNN is compared with other popular CNN architectures. The results obtained from this study are the accuracy of the test data by 91.29%, sensitivity or recall or True Positive Rate (TPR) by 91.29%, precision or Positive Predictive Value (PPV) by 91,29%, and overall accuracy by 97.51%. Therefore, with a high recall value and precision, it means that the classes in the test data are handled perfectly by the model built.
Co-Authors Abd Farid Lewa Adhyanti Aditya Nugroho Aminuddin Anis Syamsu Rizal Ansar Aslinda, Wery Bahja Budiman Nohong, Budiman Candriasih, Putu Dwi Erma Kusumawati Dwi Ratna Sari, Dwi Ratna Fahmi Hafid Fahrezi, Ryan Faisal, Elvyrah Irsanty Collein Liansafitri, Dita Mochamad Miftah Mohd.Faizal Bin Laranti Mursyidi, Reihan Ni Sayu Kadek Sri Astuti Putra Pratama, Rafly Rizka, Dian Ruskanda Danda Anugrah Ruskandi Dinda Anugrah Sakti Alfindo Bihalalika Saputri, Sarni Sevty Wahiddirani Saputri Taruna, Gilang Wery Aslinda