JOMLAI: Journal of Machine Learning and Artificial Intelligence

Foundation Scholars Decision Support System with Simple Additive Weighting

2023-06-14T03:43:20+00:00

Scholarships are one of the solutions in dealing with dropping out of school to increase the quantity of human resources in Indonesia. There are various types of scholarships given to outstanding students, one of which is a foundation scholarship. Foundation scholarships are scholarships whose funding comes from higher education foundations intended for outstanding and economically disadvantaged students. A decision support system (SPK) is needed in determining foundation scholarship recipients. With SPK, the results obtained are more objective based on the criteria used, accurate, effective and efficient. The SPK method used in this study is the Simple Additive Weighting (SAW) method. The SAW method performs a search with a weighted sum of performance ratings for each alternative on all criteria. The criteria used in this study are the Grade Point Average (GPA), parents' income and the number of dependents. Calculations using the SAW method will produce weight values, criteria, alternatives and ranking results of scholarship recipients as material for decision making.

Utilization of the Profile Matching Method for Recommendations for the Appointment of Honorary Teachers to Become Permanent Teachers

2023-08-01T02:52:07+00:00

This study aims to utilize the Profile Matching method in the recommendation process for hiring honorary teachers to become permanent teachers at Taman Siswa Bah Jambi Private High School. Honorary teachers are an important part of the education system in Indonesia, and recommendations for their appointment as permanent teachers require the right approach to ensure fair and efficient selection. In this study, an analysis of the Profile Matching method was carried out in assessing the feasibility and integrity of honorary teachers. Data collection was carried out by collecting information on academic achievement, teaching experience, and other qualifications of honorary teachers at Taman Siswa Bah Jambi Private High School. The results of the study show that Profile Matching provides recommendations that are quite relevant and can be considered in the appointment of honorary teachers to become permanent teachers. The Profile Matching method tends to place more emphasis on suitability of teaching qualifications and experience. This research is expected to provide valuable information for related parties in choosing the appropriate method for recommendations for hiring honorary teachers to become permanent teachers at Taman Siswa Bah Jambi Private High School.

Implementation of the Mamdani Fuzzy Method in Handling Room Availability in 2022 at Hotel Inna Parapat

2023-08-01T09:48:03+00:00

This study aims to implement the Fuzzy Mamdani Method in handling room availability in 2022 at Hotel Inna Parapat. The Fuzzy Mamdani method is a mathematical approach to dealing with uncertainty and ambiguity in decision-making. This study collected and analyzed data regarding the number of hotel rooms, occupancy rates, and room demand during 2022 at Hotel Inna Parapat. Then, the Fuzzy Mamdani model was developed to predict room availability based on predetermined variables. The study results show that implementing the Fuzzy Mamdani Method can provide a more accurate prediction regarding room availability at Hotel Inna Parapat. The Mamdani Fuzzy Model can handle uncertainty and ambiguity in the data and provides membership values that provide a more precise picture of the actual situation. With the Fuzzy Mamdani model, Hotel Inna Parapat management can be more effective in optimizing room utilization, improving customer service, and anticipating high room demand in 2022. Implementing the Fuzzy Mamdani Method is important to handling room availability in 2022 at Inna Hotel Parapat. This approach is expected to help hotels and the hospitality industry make smarter, data-based decisions to deal with changing demands and dynamic business situations.

Prediction of Palm Oil Seed Stock Production Results with the Back-propagation Algorithm

2023-08-07T03:16:17+00:00

Palm oil is the largest plantation export commodity in Indonesia because Indonesia has a soil structure that is suitable for planting oil palms. As is the case with the production of oil palm seed stock, of course, it does not always increase, and the production of oil palm seed stock will undoubtedly decrease. Therefore, an algorithm is needed to predict it so that the company can find out the future development of oil palm seed stock production using the Back-propagation algorithm. The Back-propagation Algorithm is used to predict the yield of oil palm seed stock production using data from the Marihat unit Oil Palm Research Center (PPKS) in 2019-2022. The Back-propagation Algorithm is an algorithm that reduces the error rate by adjusting the weights based on the desired output and target, as well as Testing the Back-propagation algorithm using Matlab. Based on the test results of the five architectural models used, one best architectural model was obtained, namely 2-14-1, using the Back-propagation method, which produced an MSE value of 0.0551030 with a Training time of 08:00 seconds with a test accuracy of 75%. Based on the research results obtained, it is expected to be input, suggestions, and efforts, especially for the Marihat Unit PPKS company, increase the stock of oil palm production seeds in each period to increase company profits more optimally.

Decision Support System in Determining the Level of Success of Teaching Teachers Using the AHP Method

2023-08-09T19:12:46+00:00

This study aims to implement a Decision Support System (SPK) that uses the Analytic Hierarchy Process (AHP) method in assessing and determining the level of success of teachers teaching at SMA Taman Siswa, Bah Jambi Branch. This study uses five assessment criteria, namely the number of attendance, lesson plans, teaching period, learning media, and discipline, as a basis for evaluating teacher performance. In this study, the AHP method was used to calculate the relative weight of each criterion and sub-criteria involved in assessing teacher performance. The data collected from various teachers was evaluated using the AHP method, and the results provide an overview of the level of success of each teacher in carrying out the teaching and learning process. The results showed that among the many existing teachers, Siti Palastri managed to score 0.81002, indicating good performance in the teaching and learning process. The application of this system is expected to assist schools in making decisions regarding teacher performance evaluation in a more objective and structured manner. In addition, this system can provide guidance and recommendations that are more effective in identifying areas for improvement by teachers who have not achieved the expected level of success. Thus, improving the quality of teaching can be achieved through corrective measures that are right on target.

Application of the Naïve Bayes Algorithm in Predicting Sales Prices for Snacks

2023-08-16T01:57:37+00:00

This study aims to apply the Naïve Bayes Algorithm in predicting the selling price of snacks at Toko Timbul II. The data used in this study were obtained from January to December 2018-2021, covering various variables relevant to snack sales. The data collected is divided into two parts, namely Data Training and Data Testing. The Training Data consists of 20 alternatives, which are used to train the prediction model of the Naïve Bayes Algorithm. While Data Testing consists of 16 alternatives, which are used to test the extent of the model's ability to predict the selling price of snacks. Testing was carried out using the Rapid Miner application. The test results show that the implemented model achieves an accuracy rate of 100% in predicting the selling price of snacks. These results indicate that the Naïve Bayes Algorithm has great potential in predicting the selling price of snacks at Timbul II Stores. These findings can provide valuable insights for store managers and snack food industry stakeholders, as well as encourage the use of predictive analytical methods in similar contexts. It is hoped that the results of this study can contribute to optimizing sales strategies and making more informed decisions in the future.