PEMANFAATAN GOOGLE PLATFORM UNTUK EVALUASI DAN KOLABORASI BAGI CIVITAS ACADEMICA DI MASA PANDEMI COVID-19

Abstrak: Kolaborasi merupakan hal yang sangat penting dalam menunjang produktivitas kerja bagi civitas academica. Namun aturan Pemberlakuan Pembatasan Kegiatan Masyarakat (PPKM) karena pandemi covid-19 mengakibatkan banyaknya institusi pendidikan yang menerapkan sistem Work From Home (WFH). Dengan sistem WFH civitas academica tidak dapat melakukan kolaborasi secara langsung seperti biasanya. Hal ini menjadi tantangan bagi civitas academica dalam menjalankan setiap tugas mereka, terutama dalam kegiatan yang membutuhkan kolaborasi atau kerjasama dalam pengelolaan berkas atau dokumen. Google Platforms menyediakan berbagai fitur dan layanan (seperti drive, docs, form, sheet) yang dapat digunakan sebagai solusi untuk kolaborasi pengelolaan berkas secara daring tanpa dibatasi ruang dan waktu. Kegiatan pengabdian kepada masyarakat ini menjadi solusi terhadap kondisi tersebut. Kegiatan pengabdian ini mengenalkan platform dari Google yang dapat digunakan untuk melakukan evaluasi dan kolaborasi dan melakukan pelatihan penggunaan platform tersebut. Tahapan kegiatan dimulai dengan mengenalkan platform google, dilanjutkan dengan pelatihan dan pendampingan. Dengan adanya kegiatan tersebut, peserta pengabdian merasa lebih mudah dalam melakukan evaluasi dan kolaborasi dalam manajemen bekas secara daring. Kegiatan ini mendapatkan respon positif dari mayoritas peserta, ditunjukkan dengan 90% peserta menyatakan tertarik untuk menggunakan google platform untuk menunjang produktivitas kerja.Abstract: Collaboration is important in supporting work productivity for the academic community. However, the rules for the Implementation of Community Activity Restrictions due to the COVID-19 pandemic have resulted in many educational institutions implementing the Work From Home system. With the WFH system, the academic community cannot collaborate directly as usual. This is a challenge for the academic community in carrying out their duties, especially in activities that require collaboration in managing documents. Google Platforms provides various features (such as drives, docs, forms, sheets) that can be used as solutions for collaborative online file management without being limited by place and time. This community service activity is a solution to this condition. This service activity introduces a platform from Google that can be used to evaluate and collaborate and conduct training on the use of the platform. The stages of the activity begin with introducing the Google platform, followed by training and mentoring. With this activity, devotion participants find it easier to evaluate and collaborate in online former management. This activity also received a positive response from the majority of activity participants, indicated by 90% of participants interested to use the Google platform to support their work productivity

Drowsiness Detection Based on Yawning Using Modified Pre-trained Model MobileNetV2 and ResNet50

Traffic accidents are fatal events that need special attention. According to research by the National Transportation Safety Committee, 80% of traffic accidents are caused by human error, one of which is tired and drowsy drivers. The brain can interpret the vital fatigue of a drowsy driver sign as yawning. Therefore, yawning detection for preventing drowsy drivers’ imprudent can be developed using computer vision. This method is easy to implement and does not affect the driver when handling a vehicle. The research aimed to detect drowsy drivers based on facial expression changes of yawning by combining the Haar Cascade classifier and a modified pre-trained model, MobileNetV2 and ResNet50. Both proposed models accurately detected real-time images using a camera. The analysis showed that the yawning detection model based on the ResNet50 algorithm is more reliable, with the model obtaining 99% of accuracy. Furthermore, ResNet50 demonstrated reproducible outcomes for yawning detection, considering having good training capabilities and overall evaluation results

PGawean: Aplikasi Mobile Lowongan Pekerjaan Kota Tegal Berbasis Unified Modeling Language (UML)

The problem experienced by every person is looking for job vacancies. Job vacancy is an information about a job that available for job seekers, especially for a person who have not been employed and/or person who are freshly looking for a job accompanied under certain conditions. One reason of difficulty of getting a job is due to a lack of information about job vacancies. To overcome the problem, there needy urgent to build a system that capable to provide information about job vacancy. The purpose of this research is to build a mobile-based application named "PGawean" which can be used to help everyone, especially those located in the city of Tegal in finding job vacancy information. Mobile-based apps named "PGawean" are built with the method Unified Modeling Language (UML) to simplify the application creation process. Because the method of Unified Modeling Language (UML) provides an easy understanding of the role of each actor and class of the system created. Based on evaluation results by applying black box method, to mobile based application that has been made, it is proven that 95% function of the application that has been made can run well. The system has been created, will be implemented to facilitate the user / job seekers get job vacancy information, especially in the area of Tegal City and its neighborhood.Keywords : job vacancies, mobile-based application, Unified Modeling Languge (UML

Studi Mengenai Kejahatan dan Keamanan Internet bagi Guru dan Siswa SMK Muhammadiyah Bulakamba

SMK Muhammadiyah Bulakamba merupakan sekolah menengah kejuruan yang ada di wilayah kecamatan Bulakamba, kabupaten Brebes. Hasil survey yang dilakukan, bahwa hampir semua guru, karyawan, dan siswa (99%) menggunakan internet untuk keperluan pembelajaran, kegiatan sosial, hobi dan lainnya pada saat di dalam maupun diluar sekolah. Dengan penggunaan internet yang maksimal maka potensi terhadap kejahatan internet juga sangat tinggi. Kejahatan internet sangat penting diketahui oleh penggunanya, demikian pula bagi guru, karyawan, dan siswa SMK Muhammadiyah Bulakamba. Ini dikarenakan kejahatan internet dapat menyebabkan akibat yang fatal, seperti: hilangnya data, pemalsuan akun, perusakan data dan lainnya.      Oleh karena itu dibutuhkan sebuah pembelajaran bagi guru dan siswa SMK Muhammadiyah Bulakamba mengenai kejahatan dan keamanan internet. Metode yang dilaksanakan yakni dengan memberikan presentasi, diskusi, pelatihan dan pendampingan. Berdasarkan kegiatan yang telah dilaksanakan, maka hasil yang didapatkan adalah pengetahuan, pemahaman, kompetensi guru dan siswa SMK Muhammadiyah Bulakamba mengenai kejahatan dan keamanan internet semakin meningkat

APLIKASI PENJUALAN PADA CAFE KAMIZUKA KOTA TEGAL DENGAN MENGGUNAKAN VISUAL BASIC 6.0

Aplikasi sebagai basis data transaksi penjualan pada Café Kamizuka yang dibuat dalam penelitian ilmiah inimerupakan aplikasi yang bertujuan untuk memudahkan dalam memasukan data, pencarian data, pembuatanlaporan serta memperlancar dan mempercepat proses transaksi pada café tersebut. Dalam penyusunan penulisanlaporan ini menggunakan flowchart dan DFD guna membangun struktur aplikasi data basis data. Dalampembuatan aplikasi ini menggunakan Microsoft Visual Basic 6.0 dan Microsoft Access 2007 yang digunakan.Kata kunci: Aplikasi, Penjualan, Microsoft Visual Basic 6.0, Microsoft Access 2007

Comparative Study of KNN, SVM and Decision Tree Algorithm for Student’s Performance Prediction

Students who are not-active will affect the number of students who graduate on time. Prevention of not-active students can be done by predicting student performance. The study was conducted by comparing the KNN, SVM, and Decision Tree algorithms to obtain the best predictive model. The model making process was carried out by the following steps: data collecting, pre-processing, model building, comparison of models, and evaluation. The results show that the SVM algorithm has the best accuracy in predicting with a precision value of 95%. The Decision Tree algorithm has a prediction accuracy of 93% and the KNN algorithm has a prediction accuracy value of 92%

Klasifikasi Rentang Usia Dan Gender Dengan Deteksi Suara Menggunakan Metode Deep Learning Algoritma Cnn (Convolutional Neural Network)

The research discusses the identification of human voices based on gender by utilizing the differences in voice characteristics between males and females. In addition to differences in vocal tract size, factors such as length, thickness, and stiffness of the vocal cords also play a role in producing the differences in fundamental frequency between the two genders. Fundamental frequency serves as an indicator used in acoustic analysis to classify gender based on voice. In the automatic classification of voices, sound processing techniques and machine learning are key in system development. Gender recognition methods based on voice involve acoustic analysis using voice features such as fundamental frequency, formants, duration, intensity, and intonation patterns. Diverse voice datasets containing recordings of both male and female voices are used to train gender recognition models. From the results of research from modeling using CNN on audio to get 92% accuracy and for testing results it is good enough in classifying. Keywords – Deep Learning, Voice Recognition, Audio Classification, CNN, Gende

Peningkatan Kualitas Gerakan Taman Baca “Pustaka Daun” melalui Penerapan Library Automatization

IMPROVING THE QUALITY OF GARDEN READ MOVEMENT ”PUSTAKA DAUN” THROUGH THE IMPLEMENTATION OF AUTOMATED LIBRARY. Pustaka Daun is a reading park at the Politeknik Harapan Bersama Tegal which is managed by a group of students. The existence of this library is to enliven and enliven the tradition of traditional literacy. The traditional literacy tradition that discusses sitting together studying and discussing certain themes from a book then discussing it together. Until now Pustaka Daun already has quite a large collection of books. However, library management is still limited and has not been finalized, especially in the collection of collection books. Seeing this phenomenon emerged to help Pustaka Daun managers in managing their library automatically. For this reason, through Community Service activities will provide training to the Leaf Library administrators to manage the library automatically with SLiMS software. The software is a Contents Management System (CMS) web-based tool that can be used easily and is simply installed. Through the implementation of SLiMS, Pustaka Daun management process will be even more organized because everything has been automated by the system. Community Service activities are carried out by providing training using SLiMS, starting from installation to library management. This activities are carried out well thanks to teamwork between lecturers and students. The lecturer presents the material and students participate in assisting and assisting the participants who helped during the training. In addition, the Community Service team provided books to add to the Pustaka Daun collection. After attending the training, the management succeeded in implementing SLiMS in library management

DIAGNOSIS KERUSAKAN BANTALAN GELINDING PADA SISTEM INDUSTRI DENGAN METODE SELF ORGANIZING MAP (SOM)

This research is discussing about the usage of data mining which addressed to damage diagnosis of rolling bearings. Data input was obtained from signal frequency feature extraction which taken from calibration against rolling bearings. The diagnosis was extremely important to industrial machines since this diagnosis can help to discover damages that occurred so that total failure of cessation of the machines can be avoided and industrial machines treatment costs can be optimized. Method used in this research is Self Organizing Map (SOM), SOM method on this research was done by sequence: signal frequency data that have been through the process of acquisition and preprocessing, feature extraction, Principal Component Analysis (PCA), then come into the process of SOM so that accuracy of the diagnosis process can be discovered. The result of this research is a software that can diagnose rolling bearings damage on industrial system. From tests result, software that has been produced was able to diagnose rolling bearings damage. Accuracy result shown 87.5% success, this software can be developed further to help technicians in diagnosing rolling bearings damage. This research method can be developed further to detect other damages in industrial systems

USABILITY TESTING SISTEM PADA E-ACADEMIC POLITEKNIK HARAPAN BERSAMA

Layanan publik yang berbasiskan web saat ini sudah menjadi bagian yang sangat penting dalam menunjang keberhasilan dari suatu instansi pendidikan,  akan tetapi layanan yang berbasiskan web masih banyak yang kesulitan dalam menggunakannya, bahkan tidak menarik dan tidak berfungsi sebagai mana mestinya. Alasan laman web perlu diukur adalah untuk mengetahui kualitas situs web tersebut dari sisi pengguna. Apakah laman web tersebut sesuai dengan standarisasi yang dikeluarkan oleh Kementrian Komunikasi Republik Indonesia tahun 2003. Pengukuran ini bisa menggunakan metode usablility testing atau uji kebergunaan. Menurut Jacob Nielson (2003), Pengujian Kebergunaan (Usability Testing) memiliki lima komponen dasar yaitu dipelajari (learnability), efisien (efficiency), mudah diingat (memorability), aman untuk digunakan dan mengurangi tingkat kesalahan (error) dan memiliki tingkat kepuasan (satisfaction