While Indonesia is recorded as one of the greatest social media republics in the world, the gap of rural-urban internet access remains a great challenge. As reported in the 2016 Information and Communication Technology (ICT) Indicators, the number of households with internet access in rural areas is nearly half of those in urban areas; 26.3% and 48.5% in a consecutive way. Rather than simply seeing the internet as a medium, this paper discusses the internet as material culture; therefore, it goes beyond the access and focuses on the ways people use the internet to define their culture. From this perspective, this paper draws the two levels of the digital divide of Indonesian rural-urban dwellers. Lack of motivation and limited material access due to social inequality is at the very base of the digital divide. Subsequently, digital skills and usage deepen the digital divide. While splitting people into either rural or urban categories often produces misleading policies, this paper proposes the rural-urban linkages to bridge the digital divide in Indonesia. The rural-urban linkages particularly incorporate the flow of people and information across space as well as the interconnection between sectors, such as agriculture and service.

SMAN 10 Padang is one of the leading schools in the city of Padang State School which has two majors, namely Science (Science Knowledge) and Social Sciences (Social Sciences). A distinctive feature of this school is one of the international standard pilot schools (RSBI) by implementing bilingual and accelerating classes. On average students lack understanding in the selection of majors according to their abilities. Many people fail in the way they have found. To facilitate the determination of majors, a Decision Making System (SPK) is needed to find criteria. In SPK there are several methods in searching criteria, which are usually used by SAW with MFED. Based on the research carried out, by comparing the two methods, the data are grouped into three criteria, namely the value of the Natural Sciences National Examination, Psychology tests, and Interests. The results of this study show about MFEP method take a high accuration between SAW. An accuration of SAW have 38.3 % and MFEP have 70.5%.

The reseach aims to predict the unemployment in the province of North Sumatra in 2020 using the Double Exponential Smoothing (DES) method. The data used is derived from the Central Agency Statistik (BPS) of North Sumatra province where the actual data is taken within 20 years from 2000 to 2019. The accuracy method in this research uses MAD to count the number of errors, MSE to evaluate forecasting methods, and MAPE to calculate the percentage of errors. Results of this research in the form of forecasting the number of unemployment in North Sumatra in 2020 that is 381459 people in the value of alpha 0.6 with a MAD value of 77402.12, MSE value of 12524690448.31, and MAPE value of 16.35%.

Mutations are needed in a company to improve the quality of workers. mutations are based on the capabilities of individual workers in the company. HRD assesses the abilities of workers from various aspects. manually the accuracy of mutations based on the value of the criteria is only 38%. with a low value of accuracy resulting in mutations of workers not as expected. the criteria given are FFB Production (C1), Core CPO Production (C2) and Field Care (C3). Range of mutation decision weights are 10-30% Giving First Warning Letter, 31 - 70% Position setting and 71 - 100% Giving promotion. with the SAW method the analysis is done by computerization. after testing the criteria obtained. HRD assesses that the accuracy of workers reaches 85%. and better and in accordance with what the company wants.

Penelitian ini bertujuan untuk mengembangkan model blended learning pada pendidikan kejuruan. Penelitian ini menggunakan tahapan model ADDIE. Penelitian ini dilaksanakan di Universitas Putra Indonesia YPTK Padang. Instrumen yang digunakan adalah kuesioner, lembar observasi, dan tes kognitif, afektif, dan psikomotorik. Hasil penelitian adalah (1) Model blended learning meliputi: (a) komponen filosofis esensialisme dan pragmatisme; (b) teori belajar: behaviorisme, kognitivisme, dan konektivisme (c) komponen 4C yaitu komunikasi, kolaborasi, kerjasama, dan kreativitas; (d) komponen revolusi industry 4.0: mencakup pembelajaran dengan elemen digital dengan literasi data, literasi teknologi, dan literasi manusia. (2) Model blended learning yang berpusat pada pembelajaran yang dilakukan secara offline dan online menjadikannya memiliki proporsi pola pembelajaran yang jelas. Fleksibilitas belajar kapan saja dan di mana saja melalui komunikasi tatap muka, serta interaksi online menggunakan chat dan forum online untuk menggali pemikiran kritis melalui diskusi. Termasuk juga unsur mahasiswa untuk berkreasi dan inovatif dalam proyek dan perbaikan proyek, serta bahan ajar online yang dibuat menarik dengan kehadirannya.komponen multimedia (teks, gambar, dan video). (3) Produk hasil berupa buku model, buku pedoman dosen dan pedoman mahasiswa, serta buku teks yang dinyatakan valid dan praktis sehingga model blended learning dapat diterapkan dalam pembelajaran. (4) Pencapaian yang ditemukan berkaitan dengan kemampuan kognitif, afektif, psikomotorik dan 4C.