The use of brainwave signal is a step in the introduction of the individual identity using biometric technology based on characteristics of the body. Brainwave signal has unique characteristics and different on each individual because the brainwave cannot be read or copied by people so it is not possible to have a similarity of one person with another person. To be able to process the identification of individual characteristics, which obtained from the signal brainwave, required a pattern of brain activity that is prominent and constant. Cognitive activity testing using a single-sensor EEG (Electroencephalogram) divided into two categories, called the activity of cognitive involving the ability of the right brain (creativity, imagination, holistic thinking, intuition, arts, rhythms, nonverbal, feelings, visualization, tune of songs, daydreaming) and the left brain (logic, analysis, sequences, linear, mathematics, language, facts, think in words, word of songs, computation) give a different cluster based on two times the test on mathematical activities (no cluster slices of experiment 1 and experiment 2). The result showed that cognitive activity based on math activity can provide a signal characteristic that can be used as the basis for a brain-computer interface applications development by utilizing EEG single-sensor.

Critical thinking skills are competencies that must be trained in students because these skills are essential to compete in the life of the 21st century. The purpose of this study is to determine the level of critical thinking skills of students in biological material in Muhammadiyah High School throughout Palembang. This research is a qualitative descriptive study; the population and sample in this study were students of class XI IPA Muhammadiyah High School in Palembang. The research instrument used was a test of critical thinking skills as many as 20 multiple choice questions of semester XI biology material 1. The data obtained will be analyzed quantitatively. Quantitative analysis is used to analyze students' test results. The results showed the level of critical thinking skills of students in Muhammadiyah High Schools throughout Palembang City varied; the exceptionally high category was obtained at 1.85%, top category amounting to 14.5%, medium category 66.6%, low category 16.4% and category very low at 0.5%. The results of this study provide information on the profile of students 'critical thinking skills in Muhammadiyah High Schools throughout Palembang City with the highest moderate category so that teachers are expected to be able to design learning process activities that can empower students' critical thinking skills.

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Road detection is used to identify road area on image or video. The challenges in road AbstrakDeteksi jalan digunakan untuk mengidentifikasi area jalan pada citra atau frame video. Tantangan dalam mendeteksi jalan diantaranya warna dan tekstur jalan yang beragam serta masalah pencahayaan. Oleh karena itu diperlukan fitur yang sesuai untuk menghadapi permasalahan tersebut. Pada penelitian ini dilakukan analisis fitur warna dan tekstur untuk mendeteksi jalan. Kumpulan 50 sampel jalan diambil untuk diekstrak fitur warna di tiga ruang warna yang berbeda yaitu RGB (Red-Green-Blue), HSV (Hue-Saturation-Value), dan CIE L*a*b* serta diekstrak fitur teksturnya dengan GLCM (Gray Level Co-occurrence Matrix). Fitur-fitur tersebut kemudian dianalisis untuk didapatkan fitur dengan variasi yang rendah dari semua sampel jalan yang digunakan untuk menentukan threshold warna maupun tekstur. Hasil pengujian metode deteksi jalan dari 150 citra uji jalan menggunakan batasan fitur hasil analisis menunjukkan akurasi 90,54%.Kata Kunci: deteksi jalan; ruang warna; fitur warna; fitur tekstur; GLCM PendahuluanDeteksi jalan pada sistem pengawasan lalu lintas secara otomatis digunakan untuk mengidentifikasi area jalan pada masukan citra atau frame video yang diambil dari kamera pengawas lalu lintas. Pada sistem pengawasan lalu lintas secara otomatis, biasanya metode deteksi jalan digunakan untuk melokalisasi area deteksi untuk kendaraan atau pejalan kaki. Hal ini bertujuan untuk meminimalkan kesalahan deteksi dengan cara mengarahkan sistem untuk mendeteksi kemungkinan posisi kendaraan atau pejalan kaki berada.Beberapa tantangan dalam mendeteksi jalan diantaranya adalah warna dan tekstur jalan yang beragam serta masalah pencahayaan karena obyek jalan berada di luar ruangan. Warna dan tekstur jalan tergantung dari material yang digunakan untuk membangun jalan sedangkan pencahayaan tergantung dari kondisi cuaca, pencahayaan matahari atau lampu jalan. Jalanan seringkali tertutup bayangan dari pohon atau gedung disekitar jalan yang membuat warnanya menjadi lebih gelap daripada bagian jalan yang terkena cahaya langsung.Dari beberapa penelitian yang telah dilakukan untuk mendeteksi jalan, deteksi jalan dapat dilakukan menggunakan pembatasan piksel dari fitur warna [1], fitur tekstur [2,3] dan atau

The impact of the coronavirus pandemic has been felt in the business and financial world. In a fairly short time, marketing patterns have changed, especially when social distancing is enforced and micro-restrictions. Business actors have to rack their brains to be able to market their products or services to consumers as a brand strategy to survive amid the coronavirus pandemic. Business people optimize online marketing and digital branding to communicate with their target consumers. The COVID-19 PANDEMIC has also accelerated digitalization in the marketing sector. Online sales are one of the solutions to the limited physical movement of people to visit shopping centres. The switch to online marketing is also one strategy that determines whether or not a product can survive during a pandemic. This study describes how small and Medium Enterprises in Indonesia face the Covid 19 pandemic. It is hoped that this literature study can provide an overview of the condition of MSMEs in Indonesia during the pandemic to improve welfare through online marketing.

The brain controls the center of human life. Through the brain, all activities of living can be done. One of them is cognitive activity. Brain performance is influenced by mental conditions, lifestyle, and age. Cognitive activity is an observation of mental action, so it includes psychological symptoms that involve memory in the brain's memory, information processing, and future planning. In this study, the concentration level was measured at the age of the adult-early phase (18-30 years) because in this phase, the brain thinks more abstractly and mental conditions influence it. The purpose of this study was to see the level of concentration in the adult-early phase with a stimulus in the form of cognitive activity using IQ tests with the type of Standard Progressive Matrices (SPM) tests. To find out the IQ test results require a long time, so in this study, a recording was done to get brain waves so that the results of the concentration level can be obtained quickly.EEG data was taken using an Electroencephalogram (EEG) by applying the SPM test as a stimulus. The acquisition takes three times for each respondent, with a total of 10 respondents. The method implemented in this study is a classification with the k-Nearest Neighbor (kNN) algorithm. Before using this method, preprocessing is done first by reducing the signal and filtering the beta signal (13-30 Hz).The results of the data taken will be extracted first to get the right features, feature extraction in this study using first-order statistical characteristics that aim to find out the typical information from the signals obtained. The results of this study are the classification of concentration levels in the categories of high, medium, and low. Finally, the results of this study show an accuracy rate of 70%.

The focus of this research is to describe the effectiveness and response of students on the use of Digital Electronic Practicum with Logisim Application using Google Meet. The research subjects were 50 Physics Education Students of Lambung Mangkurat University taking the Digital Electronic course. The data of this study were collected by using practicum assessment sheets and students’ response questionnaire. The results showed that the mean score of practicum results from digital electronic practicum with Logisim application using Google Meet was 70.58. Thus, the effectiveness of the implementation of the Digital Electronic Practicum with Logisim application using Google Meet is in a good category. Data from the students’ response questionnaire was 3.83 in average, so it was categorized as good. Thus, it is concluded that the Digital Electronic Practicum with Logisim application using Google Meet is effective to implement and obtains a very good response from the students.

The natural ability of humans to receive messages from the surrounding environment can be obtained through the senses. The senses will respond to stimuli received in various conditions including emotional conditions. Psychologically, recognizing human emotions directly can be assessed from several criteria, such as facial expressions, sounds, or body movements. This research aims to analyze human emotions from the biomedical side through brainwave signals using EEG sensors. The EEG signal obtained will be extracted using Fast Fourier Transform and first-order statistical features. four emotional conditions (normal, focus, sadness and shock emotions). The results of this research are expected to help improve users in knowing their mental state accurately. The development of this kind of emotional analysis has the potential to create wide applications in the future environment. Research results have shown and compared frequency stimuli from normal emotions, sadness, focus and shock in a variety of situations. Monitoring of EEG Signals is obtained by grouping based on