Offline cursive handwriting becomes a major challenge due to the huge amount of handwriting varieties such as slant handwriting, space between words, the size and direction of the letter, the style of writing the letter and handwriting with contour similarity on some letters. There are some steps for recursive handwriting recognition. The steps are preprocessing, morphology, segmentation, features of letter extraction and recognition. Segmentation is a crucial process in handwriting recognition since the success of segmentation step will determine the success level of recognition. This paper proposes a segmentation algorithm that segment recursive handwriting into letters. These letters will form words using a method that determine the intersection cutting point of image recursive handwriting with an ideal image distance. The ideal distance of recursive handwriting image is an ideal distance segmentation point in order to avoid the cutting of other letter’s section. The width and height of images are used to determine the accurate segmentation point. There were 999 recursive handwriting input images taken from 25 researchers used for this study. The images used are the images obtained from preprocessing step. Those are the images with slope correction. This study used Support Vector Machine (SVM) to recognize recursive handwriting. The experiments show the proposed segmentation algorithm able to segment the image precisely and have 97% success recognizing the recursive handwriting.

Corona Virus Disease 2019 (Covid-19) has stopped all aspects of human life, including the world of education. The Ministry of Education of the Republic of Indonesia has stopped face-to-face teaching and learning activities in schools, replacing them with online methods. Work from Home (WFH) is an adaptation of activities as applied online methods to anticipate learning activities during the Covid-19 Pandemic. Learning based on digital transformation technology utilizes network technology entirely online. The application of e-learning technology in the teaching and learning process is a choice for various educational institutions. The use of technology can maximize students 'learning time efficiency and increase students' concentration. Learning with the Virtual Reality (VR) method directs students to discoveries, motivates, encourages, and provides more curiosity for students in learning. Besides VR, Augmented Reality (AR) is a learning method for students to interact with virtual objects and real objects. The author proposes e-learning based learning in Natural Sciences (IPA) subjects in grade 3 in Elementary Schools. The research proposal develops lessons using a virtual approach from real events and provides phenomena of natural occurrences. Science lessons in Elementary Schools increase the curiosity of students scientifically. This method will help students develop the ability to ask questions and find answers to natural phenomena. The research stages carried out in application development are analysis, design, implementation, and application testing. The test results by adding e-learning to traditional learning methods impacted students' understanding of the material with an increased level of understanding by 24%.

Dinas Tenaga Kerja Kabupaten Bogor merupakan salah satu organisasi perangkat daerah yang telah menerapkan sistem informasi dalam melayani kebutuhan masyarakat melalui program Bogor Career Center (BCC). Sebuah tata kelola Teknologi Informasi (TI) yang memadai diperlukan untuk memaksimalkan program ini diperlukan sehingga memberikan hasil yang maksimal dan sesuai dengan tujuan organisasi. Penelitian ini bertujuan untuk melakukan evaluasi terhadap tata kelola TI pada Dinas Tenaga Kerja Kabupaten Bogor dan memberikan rekomendasi perbaikan tata kelola. Metode yang digunakan mengacu pada Process Assessment Model (PAM) kerangka kerja COBIT 5. Hasil penelitian menunjukkan bahwa domain tingkat kapabilitas proses TI yang sesuai dengan prioritas organisasi adalah EDM01, EDM02, EDM04, EDM05, DSS01, DSS02, DSS03, DSS04, DSS06 dan MEA01. Hasil pengukuran menunjukkan bahwa domain MEA01 berada pada tingkat kapabilitas 0 (incomplete process) yang artinya proses tidak diimplementasikan atau gagal mencapai tujuan prosesnya. Sedangkan sisanya berada pada tingkat kapabilitas 1 (performed process) yang artinya proses telah diimplementasikan dan mencapai tujuan prosesnya. Sedangkan tingkat kapabilitas yang diharapkan adalah pada level 3 (established process) yang artinya proses memiliki dokumentasi terhadap proses baik pada perencanaan, kebijakan, standar dan dokumen kinerja.

Abstract-A signature is the oldest security techniques to verify the identification of a person. This is due to every person has a different signature, and each signature has the characteristic physiological and behavior. There are two kinds of signature such as offline and online signatures used to verify someone identity. Offline signatures were used in this study because offline signature does not have dynamic features such as an online signature. This study proposed an identification system of offline signature by using k-NN based on the features that were stored in the database. The proposed identification system consists of preprocessing, feature extraction and verification stages. We collected the data samples from 10 persons. Each person wrote ten signatures. Total data was 100 signatures. The first stage used in this study was preprocessing such as noise removal, binarization, skeleton, and cropping. The second stage was feature extraction. Feature extraction had some vital information such as height-width ratio, the ratio of the density of signatures, edge distance ratio, the ratio of the number and proximity of the column, and the number of connected components in the signature. That information was stored in a separate database. We separated ten signatures of each person into six signatures as data sample and four signature as test data. We verified 40 signatures of test data from 10 persons using k-NN. It is shown that from 40 signatures used in our test data, 28 signatures were correctly identified and 12 signatures belong to others.

The development of Indonesian tourism after the Covid-19 pandemic began to rise again. Various efforts have been made by the government and tourism actors to be able to revive  the tourism sector. The purpose of this study is  to analyze tourism communication in the development of a Sustainable Smart Tourism Village in East Lombok as a supporting area for  Mount Rinjani Global Geopark and the Mandalika Special Economic Zone. This study uses a qualitative descriptive method by conducting interviews and direct observations of Loyok Village. The data collected were analyzed using data analysis techniques from Miles Huberman. The results of the study indicate that the development of a sustainable smart tourism village in East Lombok requires collaboration from various parties such as the government, tourism actors, communities, and researchers all at once. The Gunadarma University Matching Fund team is here to help implement five information and communication technologies (ICT) in tourist villages such as making smart homestays, making virtual reality videos, and QR Codes, making new designs for bamboo crafts, and tourist village websites. The application of this technology is also part of communication and is expected to support the development of Loyok Tourism Village in East Lombok Regency. The implementation of ICT in East Lombok Regency is also expected to serve as a pilot project in the development of smart homestays in Indonesia.