The Covid-19 pandemic has a broad impact on all sectors, including the education sector. Almost all learning from elementary to tertiary level (university) which was originally face-to-face has turned into distance learning (PJJ) or online. This study aims to see the effectiveness of online learning, especially in exact subjects. For example, in learning Basic Physics which has practical aspects, there are several problems during the pandemic, such as, 1) the limitations of the face-to-face implementation of the Basic Physics practicum during the pandemic, 2) the limitations and inconsistencies of conventional modules used in practicum implementation in distance education, and 3) The use of a Content Management System (CMS) in e-lerning that has not been maximized is an obstacle that requires immediate handling. Therefore, the researcher tried to develop a practicum e-Module using the Research & Development research method with the Rowntree development model collaborated with the Tessmer evaluation model. The results obtained in the study showed an increase in student positive motivation in doing independent practicum with the help of e-modules. The resulting E-module development can be said to have met the practical criteria, shown from the recapitulation of the percentage results of the questionnaire sheet assessment at the one-to-one stage of 84.66% and and the small group stage of 78.22%. The feasibility of the e-module that has been made is also quite good, seen from the validation results by the validator on the aspects of material, media, design and accessibility, on average, it is> 80%.

Alhamdulillah, shalawat dan salam semoga selalu tercurahkan kepada Nabi Muhammad shallallahu ‘alaihi wa sallam. Puji syukur kami panjatkan ke hadirat Allah Ta’ala yang telah memberikan rahmat-Nya sehingga kami bisa menyelesaikan pembuatan buku ajar Algoritma dan Pemrograman Dalam Bahasa C++ ini. Sesuai dengan Rencana Pembelajaran Semester (RPS) mata kuliah Algoritma dan Pemrograman Prodi Informatika, buku ajar ini membahas langkah-langkah pemecahan masalah yang disebut algoritma, struktur dasar, dan notasi algoritma menggunakan flowchart dan pseudo-code, serta cara menerjemahkannya ke dalam notasi bahasa pemrograman C++ sesuai kaidah yang benar. Terima kasih kepada Dr. Hindarto, S.Kom., MT., DekanFakultas Saintek, Arif Senja Fitrani, S.Kom., M.Kom, Kaprodi Informatika, dan Mochamad Alfan Rosid, S.Kom., M.Kom., SekProdi Informatika yang telah memberikan arahan dan dukungan untuk menyusun buku ajar ini. Serta kepada semua pihak yang telah membantu penyelesaian buku ajar ini. Saran dan kritik sangat kami harapkan untuk mewujudkan buku ajar Algoritma dan Pemrograman yang lebih baik. Semoga bermanfaat.

This study aims to analyze the sentiment towards potential presidential candidates for the 2024 election in Indonesia based on Twitter users' opinions. Three prominent figures, Ganjar Pranowo, Anies Baswedan, and Prabowo Subianto, were surveyed to gauge their electability. Using machine learning classification methods, Support Vector Machine, Bernoulli Naïve Bayes, and Logistic Regression, sentiment classification was performed. The findings indicate that Twitter users expressed predominantly positive sentiments towards each potential candidate. The evaluation of the classification algorithms showed SVM with 84% accuracy, Bernoulli Naïve Bayes with 77%, and Logistic Regression with 84%. This research sheds light on public sentiment towards potential leaders, offering valuable insights for political strategists and decision-makers in shaping effective election campaigns. Highlight: Sentiment Analysis: The study employs machine learning techniques to analyze the sentiments expressed by Twitter users towards potential presidential candidates for the 2024 election in Indonesia. Positive Sentiments: The findings reveal that Twitter users predominantly exhibit positive sentiments towards all three potential candidates, Ganjar Pranowo, Anies Baswedan, and Prabowo Subianto. Election Insights: This research provides valuable insights into public sentiment, offering valuable information for political strategists and decision-makers in devising effective election campaigns for the upcoming presidential election. Keyword: Sentiment Analysis, Twitter Users, Potential Presidential Candidates, Machine Learning, Election 2024

The uniformity of the flora is still not widely known. Therefore, natural knowledge has an important role in education considering the limitations of print media as a learning medium. Innovation by utilizing Augmented Realityp technology is very helpful as a learning medium that can support the learning process more effectively and efficiently, on the other hand Augmented Reality that displays 3D models of objects in real time can also increase interest in learning in knowing Indonesia's rare flora attractively and interactively.So, researchers designed and developed the application "Digital Flora Langka Indonesia Using Augmented Reality" with SDLC (Software Development Life Cycle) methods which are expected to help as an interesting learning medium.

Aquascape is the art of arranging plants in water. The large number of complaints from aquascape buyers were not up to expectations, causing sellers to have difficulty in setting an example of an orderable aquascape, so researches created an aquascape application system to increase their promotional activities with augmented reality technology accessible through smartphone. One uses the methode MDLC (Multimedia Development Life Cycle). As a result, the application can implement a markless augmented reality to display 3D objects in real time with the help of a camera on a smartphone or a trilib feature by importing 3D object files found on file managers on a smartphone. User can easily provide the desired aquascape example of the aquascape application.