Drug use is very detrimental to the physical and psychological health of users. Drug abuse also causes addiction and is a global epidemic. Therefore it is not surprising that scientific research related to drugs has attracted attention for research. However, many factors become obstacles in the medical services of the drug user, including cost, flexibility, and a slow process. Meanwhile, electronic systems can speed up handling time, improve work efficiency, save costs and reduce inspection errors. It means that a breakthrough is needed in developing a platform that can identify drug users. Therefore, this research aims to build machine learning with expertise like an expert who can diagnose drug users and distinguish the types of drugs used by drug users. The expert system on machine learning was developed using the Forward Chaining and Certainty Factor methods. This study concludes that the expert system on machine learning developed can be used to diagnose drug users and distinguish the types of drugs used with an accuracy of up to 80%. The implications of the expert system on machine learning are an alternative method for narcotics officers and medical doctors in diagnosing drug users and the types of drugs used.

The impact of the industrial revolution era 4.0 has been switched from a traditional system to a digital. Therefore, craftsmen also must follow the changing of this era to sell their handicrafts that previously used a traditional sales system where buyers have to go to the counter/gallery selling silver, especially the silver handicrafts in the village of Lombok, Central Lombok. The output of this community service is that craftsmen have an online shop as a medium for selling the silver handicrafts in Ungga. This online shop can be accessed by residents all over the world anytime and anywhere in making an online store uses the word press content management system because it probably solves the problem to increase the product sales.

Program Studi S1 Teknik Informatika yang bernaung dibawah Sekolah Tinggi Manajemen Informatika dan Komputer (STMIK Bumigora Mataram), sebagai program studi dengan jumlah peminatnya mendominasi  keluarga besar STMIK Bumigora Mataram. Seiring dengan bertambahnya mahasiswa disertai dengan padatnya operasional yang dijalankan oleh civitas akademik sehingga mendorong pihak internal untuk mampu mendukung fungsi bisnis dengan menyelaraskan strategi bisnis dan teknologi yang digunakan. Pencapaian sebuah keselarasan teknologi informasi dengan bisnis yang dijalankan oleh STMIK Bumigora Mataram, sehingga dirancanglang sebuah arsitektur enterprise yang mampu menghasilkan sebuah Blue Print yang dilengkapi dengan sebuah Framework TOGAF sehingga mampu menganalisis arsitektur bisnis secara lengkap dan menyeluruh untuk periode waktu jangka panjang.

Many universities undertake mixed learning to meet the required needs. Mixed learning is a blend of F2F classroom education and online learning education. The strength of mixed learning is that it supports student cognitive styles more than non-mixed learning. The right mix of mixed learning provides more constructive and conducive learning. Meanwhile, the programming language is the primary skill that students must master to create computer application programs. The question is: Is there an effect on student cognitive style and learning methods on mixed material 30% F2F and 70% asynchronous online and on the contrary mixture on student programming skills? Therefore, this study aims to determine the effect of reciprocal interaction between cognitive styles and mixed learning methods on programming skill achievement. This research method is experimental research. The study found that: Although there is no difference in the achievement of student learning skills based on tests on mixed learning methods, further test on student cognitive styles found that there are differences in the achievement of student learning skills in mixed learning methods; students with auditory and visual cognitive style who learn with mixed learning-2 have better programming skill achievement than students with auditory cognitive style who learn with mixed learning-2; students with kinesthetic and visual cognitive styles who learn with mixed learning-2 have superior programming skill achievement compared to students with kinesthetic cognitive styles who learn with mixed learning-1. The research novelty is: There has been no previous research on the reciprocal effect of cognitive styles and mixed learning methods with a mixture of 30% F2F and 70% online and vice versa.

The problem faced by target partners (target schools) is the low ability of students to solve problems. In fact, the problem-solving ability is one of the skills that must be possessed in the 21st century. This community service aims to improve teacher pedagogical competence in implementing Computational Thinking learning as well as assistance in its implementation. The method used is an educational approach with stages, identification of target schools, socialization of activities, implementation, monitoring, and evaluation. The result of this activity was an increase in teacher knowledge in computational thinking by 95% and teacher interest in applying computational thinking to subjects by 92%. The conclusion of this activity is known that community service partners have increased their knowledge of problem-solving methods using a computational thinking approach and can apply them in mathematics learning.