Profiling of victims of crime is intended to facilitate the targeting of information dissemination and carry out prevention efforts. Profiling is helpful to increase the awareness of internet users against cybercrime. This study aims to create a sociodemographic profile based on online fraud victims using Instant Messengers in Indonesia based on the sociodemography of online fraud victims, namely age, gender, education level, domicile, occupation, duration of using the internet in a day, and Instant Messenger media used. The method used in this research is the descriptive statistical method, namely Data Mining using the snowball sampling method by sharing a link via WhatsApp. Participants were given a link to fill out several survey questions about the sociodemographic of the victim, such as age, gender, occupation, domicile, and online fraud that had been experienced through the IM application. The survey was created using GoogleForms and sent online via WhatsApp to participants who had been victims of online fraud. The Data Mining technique was used to analyze the responses of 1910 participants and then classified using the Naïve Bayes Algorithm. The results showed that the Naïve Bayes Algorithm has an accuracy percentage of 75.28%. The prediction model for the vulnerability of online fraud victims is a female respondent, aged 27.3 years, using Instagram and WhatsApp, currently living in Central Java Province, education background is high school, and the duration of using the internet more than eight hours a day, and status as a Student/College Student.
Music and language acquiring spots may be different in the brain yet share the same sound production. Skills to acknowledge music is beneficial to produce musical arts while the ability to recognize phonology in English leads to not only native-like pronunciation but also word-class identification and implicature. This study attempts to look at how musical sensitivity affects phonological awareness of both trained and untrained vocalists. The objects of this research are elements of music (rhythm and pitch) that reflected English phonology (rhythm and intonation). Toward two groups of trained and untrained vocalists, the instrument of evaluation which includes 46 tests in listening for each subject (music and phonology) was given. The test is to measure participants' ability to duplicate sound based on the instruction given. Data for this study -score from both subjects -were analyzed by using variance and interpretation. From the sound production of all respondents, the problem occurs on English pronunciation as the effects of elements of rhythm and pitch in misunderstanding, accent and robotic utterance. The effect of music on untrained (x2) vocalist toward phonology (y) seems to outperform trained (x1) vocalist by more than 10 percent. However, both are able to give above 50 percent contribution on English phonology. By this, musical practice on rhythm and pitch is recommended to be conducted on English pronunciation class.
Classification is one of the most often employed data mining techniques. It focuses on developing a classification model or function, also known as a classifier, and predicting the class of objects whose class label is unknown. Categorizing applications include pattern recognition, medical diagnosis, identifying weaknesses in organizational systems, and classifying changes in the financial markets. The objectives of this study are to develop a profile of a victim of online fraud and to contrast the approaches frequently used in data mining for classification based on Accuracy, Classification Error, Precision, and Recall. The survey was conducted using Google Forms, which is an online platform. Naive Bayes, Decision Tree, and Random Forest algorithms are popular models for classification in data mining. Based on the sociodemographics of Indonesia's online crime victims, these models are used to classify and predict. The result shows that Naïve Bayes and Decision Tree are slightly superior to the Random Forest Model. Naive Bayes and Decision Tree have an accuracy value of 77.3%, while Random Forest values 76.8%.
SMPN 43 Kota Bandar Lampung tidak luput dari penyelenggaraan pembelajaran secara daring akibat adanya pandemi Covid-19. Program pelatihan optimalisasi Google Apps ini diharapkan dapat mendukung proses belajar mengajar agar bisa berjalan efektif dan optimal. Tujuan pengabdian ini adalah untuk mengenalkan Google Apps (Forms, Docs, Sheets, Slides), Google Meet dan Google Classroom kepada para guru SMPN 43 Kota Bandar Lampung sehingga bisa proses belajar mengajar menjadi lebih optimal. Peserta pelatihan adalah 19 guru SMP Negeri 43 Bandar Lampung dengan berbagai background pendidikan. Pelatihan dilaksanakan secara daring melalui Google Meet. Survei dilakukan kepada peserta untuk mendapatkan kondisi sebelum dan setelah pelatihan. Evaluasi terhadap peserta dilakukan berdasarkan respon peserta terhadap pertanyaan dalam angket sebelum dan sesudah pelatihan. Hasil menunjukkan bahwa 100% guru merasa terbantu dengan adanya pelatihan ini. Tingkat keberhasilan sebesar 100% terlihat pada pengetahuan guru tentang Google Apps yang meliputi Google Form, Google Meet, Google Classroom, Google Docs, Google Sheet, dan Google Slide bertambah setelah mengikuti pelatihan.
In a family, the role of women is not only as a housewife (domestic) but also in the public sector. Some of the motivations that encourage women to work are husband is not working, low household income, while the number of family dependents is quite high. Sasak Sade women work in the public sector as spinners, weavers, and weaving traders because of their economic motives they want to help the family economy. The role in the family becomes more visible. Income can be used to support the family's economic needs. In addition, women have the same economic responsibility as men, and some are even bigger. Sasak Sade women are able to manage their functions well in both the domestic and public sectors. It can be seen that age, working time, and number of children simultaneously have a significant effect on the family income of Sasak Sade women, while education does not affect their income because Sasak Sade women work as farmers and weavers so the need of higher education is not required. Sasak Sade women are able to manage their functions well in both the domestic and public sectors. Even though they have been active in the public sector by working as weavers and trading, they never forget about the role in the domestic sector.
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