http://repository.unmul.ac.id/handle/123456789/704 Thu, 25 Jun 2026 15:46:05 GMT 2026-06-25T15:46:05Z http://repository.unmul.ac.id/handle/123456789/56606 Expert System for Screening of Borderline Personality Disorder Ramadiani, Ramadiani; Evica Awanda Hendoq, Evica Awanda; Jundillah, Muhammad Labib; Tamrin, Tamrin; Azainil, Azainil; Widarti, Budi Nining Individuals who have symptoms of borderline personality disorder (BPD) usually experience intense feelings of hatred, anger, depression, or anxiety. These feelings are often frightening, overwhelming and difficult to control. In the midst of intense emotions, individuals with BPD may act impulsively to reduce emotional pain, calm themselves, or communicate emotional distress. This results in 10% of people with BPD dying by suicide. The system is made to anticipate and minimize these problems. The expert system built in this study can measure a person's level of borderline personality disorder, so that it can increase knowledge in the general public to help someone who is detected as having mental health problems or BPD. The certainty factor method is used to assume the degree of confidence in the value used, and Forward chaining as forward tracking which starts from gathering facts and events that support the assumption/hypothesis, until a conclusion is obtained. Based on tests using 50 test data using accuracy testing, it shows that the CF method has a presentation of 100% accuracy in the test results that have been carried out in this study. Tue, 31 Oct 2023 00:00:00 GMT http://repository.unmul.ac.id/handle/123456789/56606 2023-10-31T00:00:00Z http://repository.unmul.ac.id/handle/123456789/41476 Table of content Proceding IT-IS 2021 Student and Lecturer Perception and E-Learning Readiness in East Kalimantan Province-Indonesia: Study Case from Mulawarman University Agus, Fahrul Fri, 08 Oct 2021 00:00:00 GMT http://repository.unmul.ac.id/handle/123456789/41476 2021-10-08T00:00:00Z http://repository.unmul.ac.id/handle/123456789/30805 A backpropagation neural network algorithm in agricultural product prices prediction Setyadi, Hario Jati The price of chili is one of the food commodities that can affect the inflation rate. Its uncertain price and even increasing at certain times will negatively impact society and state. The price offer for chili is still highly dependent on the amount of chili produced. At the same time, the amount of chili productivity depends on the harvested area and land productivity. When the supply in the market is lacking, the price will increase far from its average price. Otherwise, when the supply is excessive, the price will fall far below the regular price. Therefore, it requires a method to estimate this chili's price to support decision making related to price issues. Many forecasting methods have been used to predict data, such as Backpropagation Neural Networks (BPNN) and Single Moving Average (SMA), proven in some cases to provide good forecasting results. These two methods will be compared with the lowest error rate and the best method in predicting chili's price. The results of this research will help various parties as a consideration in making decisions and planning. Mon, 17 May 2021 00:00:00 GMT http://repository.unmul.ac.id/handle/123456789/30805 2021-05-17T00:00:00Z http://repository.unmul.ac.id/handle/123456789/15323 Augmented Reality Peripheral Performance: Light Intensity, Distance, Occlusion and Marker Testing Budiman, Edy; Firdaus, Muhammad Bambang; Hairah, Ummul Augmented Reality peripherals (ARP) that use marker detection objects have developed rapidly and are implemented in various forms to support the activities of everyday human life. The challenge that is currently being faced is the increasingly widespread application of ARP technology to the reliability of software product performance in detecting objects. This research has developed and implemented ARP in the academic space. The application development method uses the Multimedia Development Life Cycle (MDLC) approach, developed based on the Android operating system, using the Unity 3D Engine and Vuforia SDK. 3D object modelling with Sweet Home 3D. Whereas for testing the reliability of ARP performance in object detection using testing of light intensity, distance, occlusion and marker with each scenario. Fri, 01 Jan 2021 00:00:00 GMT http://repository.unmul.ac.id/handle/123456789/15323 2021-01-01T00:00:00Z