Penanganan bencana alam di Indonesia menjadi hal yang sangat penting untuk segera dilakukan dalam menentukan prioritas rehabilitasi dan rekonstruksi wilayah pascabencana alam. Penentuan prioritas rehabilitasi dan rekonstruksi pascabencana alam dilakukan dengan pendekatan metodologi Sistem Pendukung Keputusan (SPK) untuk membantu menyelesaikan permasalahan dalam proses pengambilan keputusan. Metode Simple Multi Attribute Rating Technique (SMART) akan diterapkan untuk menentukan prioritas wilayah pada rencana aksi rehabilitasi dan rekonstruksi pascabencana alam karena kesederhanaannya pada proses perhitungan dalam pemilihan alternatif yang telah dirumuskan. Tujuan penelitian ini adalah menghasilkan SPK dengan mengimplementasikan metode SMART untuk menentukan prioritas rehabilitasi dan rekonstruksi wilayah pascabencana, sehingga proses penanggulangan bencana akan tepat sasaran dan sesuai dengan peraturan penanggulangan bencana alam. Proses validasi pada penelitian ini adalah dengan membandingkan hasil metode dengan data fakta atau data kejadian (data histori). Koefisien Korelasi Rank Spearman yang diperoleh yaitu 0,95. Hal ini menunjukan bahwa, metode SMART bisa digunakan untuk menentukan prioritas rehabilitasi dan rekonstruksi pascabencana alam.The handling of natural disasters in Indonesia becomes a very important thing to be done in determining the priority of rehabilitation and reconstruction of post-disaster natural areas. The prioritization of post-disaster natural rehabilitation and reconstruction is done by methodology of Decision Support System (DSS) to help solve problems in decision making process. The Simple Multi Attribute Rating Technique (SMART) method will be applied to determine the priority of the region in the post-disaster natural rehabilitation and reconstruction action plan because of its simplicity in the calculation process in the alternative selection that has been formulated. The purpose of this research is to produce SPK by implementing SMART method to determine priority of rehabilitation and reconstruction of post disaster area, so that disaster management process will be appropriate target and in accordance with natural disaster management regulation. The validation process in this research is by comparing the method result with fact data or event data (historical data). Spearman Rank Correlation Coefficient obtained is 0.95. This indicates that the SMART method can be used to determine priorities for post-disaster rehabilitation and reconstruction.

The Covid-19 pandemic has brought significant changes in all fields, including the tourism sector. This qualitative descriptive study aims to describe tourism promotion through Instagram social media in the city of Semarang. This research is a qualitative descriptive study. Since the research was still ongoing during the Covid-19 pandemic, the research was carried out using an online system using the Questionnaire and Interview instrument which was also conducted online through the WA application. The informants are Instagram account admins, Instagram social media users, academics in the tourism sector, and travel agencies that use Instagram social media as a promotional medium. The result of the research is that tourism promotion in Semarang City through Instagram social media is carried out by designing content, determining platforms, designing programs, program applications, and monitoring and evaluation.

<span>Aplikasi perangkat lunak komputer dan Internet telah berkembang pesat pada dasawarsa ini, demikian pula dengan aplikasi web dan browser internet maupun intranet. Aplikasi </span><em>Ecommerce</em><span> telah lama berkembang diawali dengan EDI (</span><em>Electronic Data Interchange</em><span>) yang telah berkembang dalam lingkup internasional. Dalam makalah ini diuraikan mengenai arsitektur sistem, tool dan konfigurasi yang diperlukan untuk mengimplementasi aplikasi web </span><em>e-commerce</em><span>, konsiderasi masalah keamanan sistem, perancangan dari sisi diagram alur aplikasi dan perancangan basis data, serta kode program PHP yang diperlukan untuk implementasi aplikasi ini. Digunakan bahasa pemrograman PHP karena kemudahan dalam pemrograman, dan kelengkapan fitur untuk mengimplementasi sistem </span><em>e-commerce</em><span>, kemampuan untuk </span><em>cross platform, </em><span>serta kemudahan untuk </span><em>deployment </em><span>bagi pengembang aplikasi.</span>

<span id="docs-internal-guid-210930a7-7fff-b7fb-428b-3176d3549972"><span>The match between the contents of the article and the article theme is the main factor whether or not an article is accepted. Many people are still confused to determine the theme of the article appropriate to the article they have. For that reason, we need a document classification algorithm that can group the articles automatically and accurately. Many classification algorithms can be used. The algorithm used in this study is naive bayes and the k-nearest neighbor algorithm is used as the baseline. The naive bayes algorithm was chosen because it can produce maximum accuracy with little training data. While the k-nearest neighbor algorithm was chosen because the algorithm is robust against data noise. The performance of the two algorithms will be compared, so it can be seen which algorithm is better in classifying documents. The comes about obtained show that the naive bayes algorithm has way better execution with an accuracy rate of 88%, while the k-nearest neighbor algorithm has a fairly low accuracy rate of 60%.</span></span>

Internet provides any information which could help teenagers in many cases, including to communicate with their friends. On the other way, internet technology which makes communication easier, does some negative effects related with interpersonal communication. Teenagers are not willing to do direct communication, including with their families. The purpose of this research is to find out and to prove whether social media impacts to interpersonal communication and cyberbullying of teenagers. Further, this research is giving some solutions for teenagers to hpersonal communication altough they are social media addicted. The subject of this research is 500 students in age of 16 up to 19 years old.