Infectious diseases are common diseases and are caused by microorganisms such as viruses, bacteria, and parasites. Indicators of the spread of this disease can be seen based on the population level and the number of confirmed cases. This study aims to develop a machine learning (ML) analysis model using the K-means cluster, artificial neural network (ANN), and decision tree (DT) methods. The dataset used in this study was obtained based on the number of confirmed patients and the distribution of the population. The analysis process is divided into two stages, namely preprocessing and the classification process. The pre-processing stage aims to produce a classification pattern that can describe the level of distribution status. The classification pattern will be continued at the classification analysis stage using ANN and DT. Classification analysis gave significant results with an accuracy rate of 99.77%. The results of the classification analysis can also describe the level of knowledge distribution based on the decision tree. Overall, the contribution of this research is to develop a classification analysis model that presents the latest information and knowledge. The results of the research presented also have an impact on the control process in environmental management and public health.

Kerusakan sepeda motor matic merupakan salah satu masalah yang sering muncul dari pengguna, sehingga tidak jarang dari pengguna langsung membawa kendaraan tersebut ke pakar/teknisi, dimana hal tersebut terkadang memberikan dampak terhadap waktu dan lainnya. Sehingga sistem yang berhubungan dengan komputer sangat dibutuhkan untuk kondisi seperti ini. Penelitian ini bertujuan untuk membantu para pengguna sepeda motor matic dalam mencari solusi terhadap kendaraan yang digunakan sehingga para pengguna paham dengan kendaraan tersebut. Sistem dibangun dengan menggunakan metoda hybrid yang menggabungkan dua metode yakni forward chaining dan certainty factor. Sistem ini bekerja dengan menyadurkan kepakaran teknisi dibidang sepeda motor matic dan beberapa ahli dibidang teknik mesin sehingga bisa memberikan solusi kepada user berupa persentase nilai keyakinan mengenai kondisi sepeda motor matic pada saat konsultasi. Dari hasil konsultasi yang didapatkan bisa digunakan sewaktu-waktu ketika dibutuhkan.

Penyakit radang usus buntu (Apendisicitis) terdapat di seluruh dunia dan dapat menyerang semua orang, baik pria maupun wanita. Jika radang usus buntu tidak dapat dikenali atau diobati, usus buntu bisa pecah, membuat kantung meradang di luar usus tersebut dan menimbulkan nanah.Akibat lanjut, benda dari usus buntu masuk ke rongga perut, menyebabkan peradangan serius.Untuk mengetahuinya Penyakit Radang Usus Buntu mereka harus mengunjungi dokter.Dengan kondisi demikian dirancanglah sebuah sistem yang mampu memberikan solusi terhadap pasien atau user yang mengalami kondisi tersebut.Sistem yang dibangun merupakan sistem pakar dengan melibatkan dokter yang ahli dibidangnya sebagai pakar dan menyadurkan informasi melalui pakar dan diterapkan kedalam sebuah sistem.Sistem pakar ini menggunakan metode backward chaining dalam pembacaan datanya ketika user atau pasien konsultasi.Sistem ini berbasiskan website dan bisa digunakan di berbagai smartphone, hasil dari sistem ini juga bisa digunakan dalam bentuk hardcopy.

The research aims to provide information for the wider community about bulimia nervosa that often afflicts the community especially teenagers. Bulimia nervosa is one type of psychiatric disorder that is habitual that has ingrained from the community itself. No people understand the symptoms or indications of eating disorder in adolescents, and not infrequently among sufferers not doing direct treatment or looking for a direct solution to this disorder. To communicate with doctors also have constraints with time and confusion about what is to be conveyed. Expert system is a solution, this system is able to provide information to researchers about eating disorders in adolescents and provide solutions like a doctor or nutrition expert. It was built using by hybrid method which combines certainty factors and forward chaining.

The implementation of online lectures using blended learning needs to be assessed to find out the performance activities of lecturers with students in using the learning activity management system (LAMS) feature and reward lecturers with the best performance. Based on the assessment system of the best lecturers previously have not used the right methods so that the resulting decision is still not right and not accurate. This research aims to implement the Analytical Hierarchy Process (AHP) method in the assessment process of lecturers who are the best in using LAMS. The performance of the AHP method can determine the weight value of criteria consistently and can perform a role to produce solutions in decision making. The criteria indicators used to consist of Interactive Video Teaching Materials (C1), Audio Teaching Materials (C2), URLs (C3), Forum/FBL (C4), Slide Teaching Materials (C5), Assignments (C6), Quiz (C7), Attendance (C8), and Labels (C9). The results of this study showed that the performance of the Decision Support System (DSS) using the AHP method can determine a better weight value with a consistency level of 0.080049762 from 0.1. These results presented with AHP performance can provide weighting value on each criterion and continue the multiplication process with the best lecturer assessment data to get the results of the battle. Overall these results concluded that each criterion had a degree of consistent relationship in the best lecturer assessment on LAMS.