On Friday, December 5, 2025, Dr. Syarifah Inayati, M.Sc., a lecturer in the Statistics Study Program at UNY, delivered a guest lecture hosted by the Statistics Study Program at UIN A.M. Sangadji Ambon online via Zoom Meeting. The event raised the topic "Development and Application of Regression Models in Time Series Analysis." The event was attended by students of the Statistics Study Program at UIN A.M. Sangadji Ambon, as well as several lecturers and students from various study programs and other universities.

The event, held from 9:00 a.m. to 12:00 p.m. WIT, began with remarks from Mr. Djafar Lessy, M.Sc., Ph.D., Deputy Dean I of the Faculty of Islamic Education and Teacher Training at UIN A.M. Sangadji Ambon, representing the Dean of the Faculty of Islamic Education and Teacher Training. In his remarks, he stated that this guest lecture was part of the implementation of the collaboration between the Statistics Study Program at UIN A.M. Sangadji Ambon and the Statistics Study Program at UNY. This guest lecture is expected to provide new insights, especially for students of the Statistics Study Program at UIN A.M. Sangadji Ambon, as well as other participants. Ms. Yuli Hastuti, M.Sc., Head of the Statistics Study Program at UIN A.M. Sangadji Ambon, also accompanied the event.

The guest lecture proceeded smoothly, with a one-hour presentation followed by an hour of active discussion. Students, mostly from their first and third semesters, expressed increasing interest in exploring regression models in time series analysis and various other time series models. Topics discussed in the Q&A session included the challenges of managing complex data patterns, the importance of selecting the right model, and how to handle non-stationary data. Participants also inquired about modeling steps for beginners and the relevance of using data over long periods.

With this guest lecture, it is hoped that the material presented will enrich the participants' insights and provide significant benefits for the development of statistical science, particularly in the field of time series.