Learning path in online learning systems refers to a sequence of learning objects which are designated to help the students in improving their knowledge or skill in particular subjects or degree courses. In this paper, we review the recent research on learning path adaptation to pursue two goals, first is to organize and analyze the parameter of adaptation in learning path; the second is to discuss the challenges in implementing learning path adaptation. The survey covers the state of the art and aims at providing a comprehensive introduction to the learning path adaptation for researchers and practitioners. Abstract-Learning path in online learning systems refers to a sequence of learning objects which are designated to help the students in improving their knowledge or skill in particular subjects or degree courses. In this paper, we review the recent research on learning path adaptation to pursue two goals, first is to organize and analyze the parameter of adaptation in learning path; the second is to discuss the challenges in implementing learning path adaptation. The survey covers the state of the art and aims at providing a comprehensive introduction to the learning path adaptation for researchers and practitioners.

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Dynamic learning environment has emerged as a powerful platform in a modern e-learning system. The learning situation that constantly changing has forced the learning platform to adapt and personalize its learning resources for students. Evidence suggested that adaptation and personalization of e-learning systems (APLS) can be achieved by utilizing learner modeling, domain modeling, and instructional modeling. In the literature of APLS, questions have been raised about the role of individual characteristics that are relevant for adaptation. With several options, a new problem has been raised where the attributes of students in APLS often overlap and are not related between studies. Therefore, this study proposed a list of learner model attributes in dynamic learning to support adaptation and personalization. The study was conducted by exploring concepts from the literature selected based on the best criteria. Then, we described the results of important concepts in student modeling and provided definitions and examples of data values that researchers have used. Besides, we also discussed the implementation of the selected learner model in providing adaptation in dynamic learning.

The spread of Lumpy Skin Disease (LSD) that infects livestock is increasingly widespread in various parts of the world. Early detection of the disease’s spread is necessary so that the economic losses caused by LSD are not higher. The use of machine learning algorithms to predict the presence of a disease has been carried out, including in the field of animal health. The  study aims to predict the presence of LSD in an area by utilizing the LSD dataset obtained from Mendeley Data. The number of lumpy infected cases is so low that it creates imbalanced data, posing a challenge in training machine learning models. Handling the unbalanced data is performed by sampling technique using the Random Under-sampling technique and Synthetic Minority Oversampling Technique (SMOTE). The Random Forest classification model was trained on sample data to predict cases of lumpy infection. The Random Forest classifier performs very well on both under-sampling and oversampling data. Measurement of performance metrics shows that SMOTE has a superior score of 1-2% compared to the use of Random Undersampling. Furthermore, Re-call rate, which is the metric we want to maximize in identifying lumpy cases, is superior when using SMOTE and has slightly better precision than Random Undersampling. This research only focuses on how to balance unbalanced data classes so that the optimization of the model has not been implemented, which creates opportunities for further research in the future.

Perkembangan dalam dunia teknologi informasi memanfaatkan teknologi komputer menjadikan salah satu pilihan dalam melakukan berbagai hal yang terdapat di dalamnya dapat berupa aplikasi, sms atapun sistem pegamanan data yang menjaga keamanan dan kerahasiaan data informasi dalam ilmu pengembangan seperti kriptografi. Pada penerapan yang di lakukan tidak dari satu teknik keamanan saja melainkan dapat dilakukan dengan bebagai kombinasi  ataupun modifikasi dalam keamanan data dan informasi. Konsep utama pada kriptografi yakni enkripsi dan dekripsi. Sebuah pesan , informasi ataupun data yang di enkripsi agar orang yang tidak berhak untuk membaca pesan tersebut tidak akan dapat membacanya. Dari perkembangan berbagai metode penggunaan kriptografi dapat sering kali di pecahkan dan di selesaikan oleh pihak lain yang tidak berhak di karenakan kunci dari informasi pesan data tersebut tidak sulit memecahkannya. Dalam tulisan yang di buat ini penulis memodifikasi metode Caesar chiper menggunakan beberapa symbol dan angka sehingga menghasilkan pola dengan beberapa tahap metode.