Technical job distribution at BSD SHARP service center using combination of naïve Bayes and K-Nearest neighbour

Works distribution is a routine carried out every day by the head of the branch in the SHARP Service Center. The accuracy of the labor division is very important to get customer satisfaction. Inappropriate work distribution can increase complaints from customers. Currently, works distribution in SHARP Service Center is carried out manually, where the works received on the selected system is then shared through the document provided. Time taken for this process is about 1.42 minutes on average for each damage reports. Speed of Service also depends on the Head of Department's expertise and experience. In this study, an automatic system based on Machine Learning will be designed for the technicians work distribution by using a combination of k Nearest Neighbor (k-NN) and Naïve Bayes. Naïve Bayes algorithm is used to improve the feature extraction accuracy by considering the feature below the average (α). Meanwhile, k-NN algorithm is used to classify the experimental data. From the study, it is found that the best of k value for k-NN algorithm is 15. It is known that a high number of accuracy values, the labor distribution can be more accurate. The validation of the proposed method is conducted by using a confusion matrix with a composition of 80% training data and 20% test data. The single Classifier test with the Naïve Bayes algorithm produces the highest accuracy value of 72.7%, while using k-NN algorithm is 81.5%. With a combination of Naive Bayes and k-NN algorithms, the accuracy value is increasing to 86%. This result shows that the proposed method improves the accuracy by 13.3% on single Naive Bayes algorithms and 4% on a single k-NN algorithm. The results obtained show that in the manual process, the average time per job is 1.42 minutes, while by using the proposed method, the average processing time is around 0.03 seconds per job. An increase of 2480 times faster is found and confirmed during the implementation of the proposed method

Image processing-based flood detection

This paper discusses about the design of an online ftood detection and early warning system which integrated to using Raspberry-PI and optical sensor. Raspberry-PI is a single board of computer which in this case we design as an image processor to process image obtained from the webcam and update the result to the twitter. This research can help some of the citizens who live near the river to get tbe updated information regarding water conditions and the possibility of flooding so that they can take action to secure their properties and families as soon as possible. We use OpenCV as an image processing application. The steps are as follows: (1) Region of Interest to create a portion of an image to filter or perform some other operation. (2) Brightness and contrast adjustment in order to get brighter and better image before the next process. (3) Grayscale and threshold to create segmentation object with Otsu-thresholding. ( 4) Edge detection algorithm to find edge points on a roughly horizontal water line and riverbank height By using the above method, the system can read and monitor the \Valer level of a river or other water bodies. If the water level exceeds the specific threshold, the system will generate notification as early warning for the possibility of floodi ng by uploading the text and image to the twitter regarding that condition. The citizens will get the information if they follow that account (early warning system) on Twitter. The result of this simulation using prototype that we have made is that the system can read the water conditions with an increase in accuracy reaching 99.6o/o

Website E-Government sebagai Media Informasi Masyarakat Desa Lontar

Diterima : Direvisi :Diterbitkan : Desa Lontar memiliki kewajiban untuk mendukung program pemerintah yaitu E-Government. E-Government adalah penggunaan teknologi informasi dan komunikasi (TIK) untuk memberikan kemudahan layanan dan memberikan akses informasi kepada masyarakat setempat khususnya dan membuat pemerintahan lebih bertanggung jawab kepada masyarakat. Pemerintahan desa sebagai tingkat paling bawah dalam struktur pemerintahan dituntut untuk dapat menyelenggarakan pemerintahan yang baik (good governance), salah satu solusi untuk mencapai tujuan tersebut adalah dengan menerapkan E-Government. Salah satu cara untuk menerapkan E-Government, pemerintahan desa dapat membuat sebuah situs (website) yang berisi informasi dan fasilitas-fasilitas pelayanan bagi seluruh lapisan masyarakat, pihak swasta maupun dengan pemerintah yang lain. Pembuatan website desa lontar bertujuan sebagai media pelayanan publik resmi desa, yang dibangun dan dikelola oleh tim desa setempat. Dengan memanfaatkan website penyelenggaraan pelayanan publik dapat dilakukan secara cepat dan mudah. Website desa sebagai manajemen informasi dapat digunakan sebagai media informasi publik yang dapat diakses secara online. Berdasarkan hasil pengabdian kepada masyarakat mengenai rancangan website Desa Lontar yang telah diaplikasikan, maka dapat disimpulkan bahwa website ini dapat berjalan dengan baik sesuai yang diharapkan sehingga dapat membantu meningkatkan performa dari pemerintahan Desa Lontar dalam pengolahan data dan memberikan pelayanan kepada masyarakat dengan cepat dan efisien