Informatics Engineering Study Program Research Articles

The influence of blended learning using the science technology society approach on learning independence

Independent learning facilitates students in improving their competencies according to the challenges of the current era. However, learning in schools often does not empower students to become independent learners. This research aims to find out whether the application of blended learning with the Science Technology Society (STS) approach can increase student independence in learning or not. This research is quantitative. The sample for this research was students from the informatics engineering and communication science study program at Dr Soetomo University. The instrument used in this research was a questionnaire. Questionnaires are used to find out information about independence. Data analysis involved conducting normality and homogeneity tests, followed by an independent sample test. The results of the analysis suggest an influence of blended learning with an STS approach on learning independence in higher education (t = 21.246, p < 0.001), implying the potential effectiveness of integrating STS principles into educational practices to foster greater autonomy among students.

Website Design of Informatics Engineering Alumni Association UIN Sunan Gunung Djati Bandung

The rapid development of technology has penetrated into various sectors, including education. Universitas Islam Negeri Sunan Gunung Djati Bandung realizes the importance of participating in technological advances to improve information and communication services. One of the efforts made is to utilize the website to introduce and manage alumni data. This research is focused on the analysis and design of the Informatics Engineering Study Program alumni website, with the hope that it can support facilities at the university and provide benefits, especially for alumni of the Informatics Engineering Department. The results showed that the development of the Alumni Association website can be done well as a means of facilities for the Alumni Association in informing its work program. In addition, website development is carried out by making front-end with ReactJS and back-end with NodeJS Express on the website can run completed and implemented quite well.

The Addition of Adaboost to The Use of The C4.5 Algorithm to Improve The Accuracy of Classification of Study Interests

Specialization is one of the important things in focusing the student's field of study. At one university that has a faculty of computer science, there is an Informatics Engineering undergraduate study program which is divided into two specializations, namely intelligent systems and software engineering design. At one university that has a faculty of computer science, there is a bachelor's program in Informatics Engineering which is divided into two specializations, namely intelligent systems and software engineering design. students find it difficult to choose one of the specializations in the informatics engineering study program. To overcome these problems, the authors provide solutions in the form of ideas that can recommend students in determining specialization. In this problem, the algorithm that will be used is the C4.5 algorithm based on forward selection plus adaboost. The results of the specialization classification use the selected attributes and iterate over the cross-validation so as to produce the right accuracy. Testing the C4.5 algorithm produces an accuracy of 93.89% and the C4.5 algorithm based on forward selection produces an accuracy of 94.44% while using the C4.5 algorithm based on forward selection with the addition of adaboost produces an accuracy of 94.63%. Based on these tests, it proves that there is an increase in accuracy by adding selection and adaboost features to the C4.5 algorithm.

Penerimaan Teknologi ChatGPT Di Kalangan Mahasiswa: Studi Deskriptif Model TAM Pada Mahasiswa Program Studi Teknik Informatika Universitas Negeri Padang

This research examines the acceptance of ChatGPT technology among students of the 2020 Informatics Engineering study program, Faculty of Engineering, Padang State University using the TAM model. This research aims to describe the acceptance of ChatGPT among students. The type of research used is quantitative research with a case study approach. The method used is descriptive research method. Data collection techniques through observation, interviews and questionnaires. Sampling in this research was by using saturated samples. Research data was obtained from the results of a questionnaire distributed to 89 samples who were informatics engineering students class of 2020. Based on the research results, it can be concluded that there is acceptance of ChatGPT technology among students of the Informatics Engineering Study Program Class of 2020, Faculty of Engineering, Padang State University, with five indicators which are obtained an average value of 2.61. The indicators include (1) Perception of ease of use, obtaining an average value of 2.64 whose interval scale is positive or categorized as good, meaning that the ease of use of ChatGPT so that it does not require special skills can be accepted by students of the Informatics Engineering Study Program Class of 2020. ( 2) Perception of user usefulness, obtained an average value of 2.65 whose interval scale is positive or categorized as good, meaning that ChatGPT provides benefits in helping user performance so that the indicator can be accepted by students of the 2020 Informatics Engineering Study Program. (3) Intention to use , obtained an average score of 2.57, which is a positive interval scale or categorized as good, meaning that the use of ChatGPT which will be reused over a longer period of time can be accepted by students of the 2020 Informatics Engineering Study Program. (4) Real conditions for using the system obtained an average score of 2.60 on a positive interval scale or categorized as good, meaning that users use ChatGPT truly to help user performance so that it can be accepted by students of the Informatics Engineering Study Program Class of 2020. (5) Attitude towards use, gain The average value is 2.61, the interval scale is positive or can be categorized as good, meaning that based on the evaluation of ChatGPT users, the impact of using ChatGPT can be felt so that this indicator can be accepted by students of the 2020 Informatics Engineering Study Program. Even though it is categorized as good, the use of ChatGPT can has a negative impact on students, such as dependence on ChatGPT which will affect students' critical thinking abilities in doing assignments and a lack of social interaction such as discussions because they rely too much on ChatGPT when doing assignments.
 

Pendampingan Membaca Al-Quran Menggunakan Metode Ummi pada Mahasiswa Teknik Informatika di STT Wastukancana Purwakarta

The Ummi method can lead students and female students to be able to read the Al-Quran well and correctly according to the tajwid, in reality the underlying problems are low activity in studying the Al-Quran, lack of motivation to learn the Al-Quran, non-varied learning methods and models, and ability. reading the Koran is still lacking. In this community service activity, the author wants to research the extent to which female students read the Koran by carrying out various methods including: Lectures, questions and answers and demonstrations on the practice of reading the Koran. This technique is used to make it easier for female students to read and practice the Al-Quran, especially in family, school and community environments. The ummi method is one method of studying the Koran. Ummi itself means Mother, who remains patient and gentle. And you can invite all students from the LDK (Student Da'wah Institute) informatics engineering study program at STT Wastukancana to learn to read the Koran using the Ummi method. Easily, quickly and according to the tajwid. This ummi method is starting to motivate female students because the method is easy, fun and calms the hearts of the readers. After learning the Koran using the Ummi method, it is easy for students to memorize wherever they are, of course it will be easy to remember.

Efikasi Diri Mahasiswa Pada Perkuliahan Matematika Diskrit

Abstract The purpose of this qualitative research is to describe in detail the profile of students' self-efficacy in dealing with discrete mathematics courses. The subjects of this study were 21 students of class TI21A4 Informatics Engineering Study Program, Duta Bangsa University, Surakarta, who were taking a Discrete Mathematics course. The information gathering tool consisted of a self-efficacy questionnaire and a guide for interview sessions. Participants filled out a questionnaire related to self-efficacy. The output of the self-efficacy questionnaire showed that 5% of students showed a very high level of self-efficacy, 39% had a high level of self-efficacy, 33% had a moderate level of self-efficacy, and 23% experienced a low level of self-efficacy. After that, 6 students were selected to be research subjects, consisting of 2 students each with high, medium, and low self-efficacy levels. Students with high and medium self-efficacy in solving Discrete Mathematics questions do not give up easily, while students with low self-efficacy give up easily when solving these problems. Students with high and moderate self-efficacy have been able to learn independently, while students with low self-efficacy have not been able to learn difficult Discrete Mathematics material independently and need guidance from the lecturer. Even so, students with high, medium, and low self-efficacy were able to complete assignments and submit assignments on time. Students with low self-efficacy, their learning efforts are less than optimal for various reasons so that they have not been able to achieve the targeted learning achievements. While students with high and moderate self-efficacy are already optimal with regard to their learning efforts Keywords: self-efficacy; student; discrete mathematics

PENGEMBANGAN SISTEM REPOSITORI SKRIPSI DI TEKNIK INFORMATIKA UNIVERSITAS NEGERI MANADO BERBASIS WEB

Based on observations made by researchers at Informatics Engineering Universitas Negeri Manado, there is no Thesis Repository that functions to accommodate data on Thesis Titles of Informatics Engineering Study Program Students. Based on this, researchers plan to develop a web-based Thesis Repository System at Universitas Negeri Manado Informatics using the Agile Software Development method. After the web-based Thesis Repository System in Informatics Engineering Universitas Negeri Manado was successfully developed using the Agile Software Development method, testing carried out using the black box testing method obtained good results, where 12 test points were successfully achieved and the developed system could help the study program in recording thesis data from students.

Virtual Programming Laboratory in Collaborative Inquiry Learning to Improve Higher Order Thinking Skills for Work Readiness in the Industrial World

This study aims to determine the effectiveness of using Virtual programming Lab software as a practicum tool in inquiry learning, collaboration, and increasing the ability of higher-order thinking skills (HOTS) students who take programming courses. Pseudo-experimental studies are designed with experimental and control groups. This research was attended by 35 first-semester students from the Pelita Indonesia Informatics Engineering Study Program. Quantitative methods are used to determine students' HOTS levels and their acceptance of the use of virtual programming labs as computer practicum tools. The data analysis technique used is the Kolmogrof Smirnov technique. For inquiry-based collaborative learning using 7 stages of learning. The effectiveness of virtual programming with collaborative inquiry learning through HOTS questions is tested with the N-gain test. Based on the findings, it is stated that virtual programming applications with collaborative inquiry learning in programming courses are quite effective in improving students' higher-order thinking skills with an average N Gain of 60%. The ability of students to do HOTS questions in C4, C5, and C6 has increased after post-tests in experimental classes.

Stream Clustering for Selection Recommendations Using K-Means Algorithm: A Case Study in the Informatics Study Program

Concentration Stream for a major is a process where students focus their attention on a specific discipline according to their interests. The purpose of specialization is to better orient students to the knowledge they have gained from previous courses, so that they can have a clearer focus. In the Informatics Engineering study program at Bina Darma University there are 3 concentrations, namely: Software Engineering, Network Engineering, Data Analytics. The absence of a system that helps students choose a major concentration makes it quite difficult for students to know their academic abilities. By looking at these problems, this research aims to build a Recommendation system for selecting Mk-Stream Concentrations using the K-Means grouping approach using the K-Means cluster method. Where student academic achievement data from the first semester to the 4th semester is used as a variable in the calculations.

Comparison of Different Classification Techniques to Predict Student Graduation

Every year, the number of students accepted at the Maulana Malik Ibrahim State Islamic University of Malang continues to increase. Still, not all students can graduate on time according to the specified study period, resulting in a buildup of students who have not graduated according to their graduation period. One of the aspects evaluated in the Study Program accreditation process is the student graduation rate. Apart from that, for each semester, Study Programs are also required to report educational data to DIKTI, and student graduation is one of the factors considered in the report. There is an imbalance between the number of students graduating each year and the number of new students accepted. To overcome this problem, it is necessary to predict student graduation to determine whether they will graduate on time. In science and data analysis, predictions are often used to make predictions based on existing data and information. Classification models in predicting student graduation include the Nave Bayes method, Support Vector Machine SVM, and Random Forest, as well as the level of accuracy of these three methods. From the results of experiments and model evaluations carried out, with data from 458 Informatics Engineering Study Program students with details of 366 training data and 92 testing data, it was obtained that the SVM model had the highest accuracy, reaching around 87% and Random Forest also had good accuracy, around 82%. At the same time, the Naïve Bayes model has lower accuracy, around 76%.

Application of the K-Means Clustering Algorithm to Determine Student Academic Ability Levels during Covid-19

Since the existence of the COVID-19 pandemic in Indonesia, various ways and efforts have been made by the government to prevent the spread of the corona virus. One of them is by implementing an online learning system, so that it causes differences in the learning process that is usually carried out by lecturer face to face with students. Changes in the learning process are expected to be carried out effectively and efficiently. The purpose of this research is to find out how the level of students' academic ability is during online learning in the Informatics Engineering study program at Universitas Malikussaleh and aims to produce a system model that can cluster the level of student academic ability using the K-Means Clustering Algorithm. The variables used in this study are 3 parameters, namely the teaching and learning process, facilities and infrastructure and learning outcomes. The stages carried out in this study were collecting questionnaire data filled out by 200 students. The data obtained would be processed using the K-Means Clustering Algorithm and forming 3 clusters, namely low, medium and high. The clustering results of 200 data obtained 27 students having low academic ability levels (Cluster 1), 87 students having moderate academic ability levels (Cluster 2) and as many as 86 students having high academic ability levels (Cluster 3). The contribution of this research is to help the management of the Informatics Engineering Study Program at Universitas Malikussaleh to find out how the level of student academic ability is during the online learning period during the COVID-19 pandemic, so that evaluation of learning can be carried out online.

Implementasi Kebijakan Kurikulum Merdeka dalam Meningkatkan Capaian Hasil Belajar Mahasiswa Prodi Teknik Informatika Universitas Bhayangkara Surabaya

This research examines the implementation of the independent curriculum policy in improving student learning outcomes in the Informatics Engineering Study Program, Bhayangkara University, Surabaya. The research method used is qualitative, namely interviews and documentation, then the data is linked to the theory that has been obtained in lectures. Data was obtained by asking several question instruments to the head of the information engineering study program, Bhayangkara University, Surabaya. The results of the research show that in implementing the independent curriculum, especially in the information engineering study program at Bhayangkara University, Surabaya, they always try to provide the best in providing services in the form of educational services to students. Namely by providing facilities or infrastructure that are tailored to the study program's learning achievements, always communicating everything related to Independent Learning on the Independent Campus (MBKM) to students, providing training and competency development for educators and education staff, and providing continuous mentoring or supervision to students who are currently studying. did it mbkm. The implementation of the independent curriculum has had a positive impact not only on students who participate in MBKM but also on the image of the institution in the eyes of the public.

Timeline reminder system bot and telegram assistant chatbot for a university student and lecturer

This research relates to the development of a chatbot application to help lecturers and students in the D3 Informatics Engineering study program remember schedules of activities and answer questions related to the study program. The background of this research is due to the difficulties of lecturers in managing activity schedules and answering questions that come from D3 Informatics Engineering study program students effectively and efficiently. This shows that having chatbot reminder and assistant applications will be very useful for study programs. The purpose of this research is to develop a bot and chatbot application that can help lecturers and students at Diploma 3 Informatics Engineering in managing activity schedules and answering questions related to study programs. The research method used is the Waterfall system development method, which is a type of System Development Life Cycle (SDLC). This method follows the sequential stages of system development starting from requirements analysis, system design, implementation, testing and maintenance. In this study, the chatbot application was developed using the Golang programming language, Codeigniter4 as the dashboard platform.

Comparative Analysis of Prediction Results of Decision Support Systems Simple Additive Weighting Method with Preference Selection Index in Determining Scholarship Recipients

Educational Assistance needs to be a concern because currently the majority of students have the potential and ability but are constrained financially so this needs to be taken seriously by the government, currently, the government through the Ministry of Education has been trying to provide financial assistance in the form of scholarships including achievement improvement scholarships academic. Currently, to get a scholarship, each university certainly gets a limited quota. This is done to provide equal distribution of educational assistance, due to the large difference between the quota obtained and students who need assistance, so it is necessary to provide eligibility selection for students who are entitled to get scholarships. This study took sample data from the 2023 even semester scholarship list at Manado State University, especially in the Informatics Engineering Study Program, then normalized the data to use the SAW and PSI methods. After normalization, calculations were carried out using the SAW and PSI methods. predictions from the two methods will then be tested for the level of accuracy using the confusion matrix method. The result is that the SAW method has an accuracy rate of 98.13% and then the PSI accuracy rate is 97.24% based on the results of the prediction accuracy, the SAW method has a higher accuracy rate than PSI.

E-Modul Pembelajaran Mata Kuliah Peminatan Kecerdasan Buatan Program Studi Teknik Informatika IIB Darmajaya Berbasis Android

The problem of this research is that the modules available in courses specializing in artificial intelligence are still in printed form, so it is necessary to develop learning media to adapt to technological developments that can be used as facilities to facilitate the learning process, especially in material that requires a certain understanding. The purpose of this research is to build an android-based learning e-module application that is more practical and easy to use in the subject of specialization in artificial intelligence, IIB Darmajaya informatics engineering study program. This research method uses Research and Development (R&D) with the ADDIE model development procedure which consists of 6 stages, namely analysis, design, development, implementation, evaluation. The results of this study are an e-module application for learning subjects in the specialization of artificial intelligence which can make it easier for students and lecturers of the IIB Darmajaya informatics engineering study program to carry out learning activities.

Digital Learning Training for PKBM 31 Bangka Educators for Classroom Transformation After the Covid-19 Pandemic

Digital learning is a form of transformation in the classroom that focuses on the use of technology. In Indonesia, the Covid-19 pandemic that has been going on for the last few years has forced educational institutions, both formal and non-formal, to apply this learning concept, even with all of its limitations. This is at least experienced by PKBM 31 Bangka which has attempted to implement digital learning with limited capabilities and minimal infrastructure. This is even worse with the diverse characteristics of the students as non-formal institutions. Therefore, through a community service program, the informatics engineering study program at Paramadina University seeks to provide training to PKBM 31 Bangka so that they are better prepared to carry out digital learning. The training was held for 2 days and divided into 4 sessions. The understanding and ability of PKBM 31 Bangka educators regarding digital learning increased from the previous 2.67 to 4.25 after attending the training. Participants also rated the implementation of this training at 4.5 or very satisfied.

Klasterisasi Hasil Belajar Matematika dengan Algoritma K-Means Clustering

Mathematics has an important role in the computer field and provides a theoretical foundation for people working in the computer field. The facts show that in the Informatics Engineering study program, Unisba Blitar, the selection of specializations is carried out without considering the grades of courses that teach basic mathematical skills. In fact, mathematical ability is needed by a computer expert. For this reason, research was conducted that aimed to cluster student mathematics learning outcomes. Clustering was carried out on 51 students in semester 4, through the application of the K-means clustering algorithm. The attributes used are school origin data, majors currently in high school, and student learning outcomes in informatics logic, statistics, computational mathematics, and advanced computational mathematics courses. The results show that through clustering with the K-Means Clustering algorithm, 5 clusters are obtained, starting from the highest average score, namely cluster 2 with a value of 86.81 and the lowest average value is cluster 5 with a value of 76.50. In cluster 2, it is dominated by students from SMK graduates majoring in TKJ. Meanwhile, cluster 5 was dominated by students from high school graduates majoring in natural sciences. In addition, there are findings indicating that vocational high school graduates do not always have lower mathematical abilities than high school graduates, because intrinsic motivation also influences the level of learning outcomes.

Website Based Student Absence Application Design Using Extreme Programming Method

Absenteeism application is one of the systems where attendance is critical data in every activity, be it lecture activities. Nevertheless, often, the data - this absence of data is less noticed. The proof is that many educational institutions still use conventional absenteeism. Conditions like this are certainly very vulnerable to fraud. Therefore, the Informatics Engineering Study Program of the Faculty of Engineering needs a system that can create an absence process that can produce information more efficiently and by its standards, of course, using methods that can solve the problems in the Informatics Engineering Study Program of the Faculty of Engineering—using the Extreme Programming Method. The extreme Programming method was chosen because the software to be created is simple and classified as small-scale software, and development takes little time. This system development method is one of the agile methods. Which has several stages, namely: 1. Planning, 2. Design, 3. Coding, and 4. Testing. Of course, with some design processes that use UML, such as Use Case Diagram, Activity Diagram, Flowchart &, and DFD, the student attendance website application built has been tested for eligibility using Blackbox testing. The results of this study create a system that can help informatics engineering programs to help in terms of student retirement. Design a system that can produce reports that suit needs effectively and efficiently.

Penerapan Algoritma K-Means Clustering untuk Mengetahui Pola Penerima Beasiswa Bank Indonesia (BI)

Bank Indonesia Scholarships are a type of scholarship sourced from Bank Indonesia for students from selected State Universities, Private Universities, and Polytechnics. From the data on scholarship recipients who have passed the selection from 2020, 2021, 2022 universities in Riau, it is necessary to look for the behavior patterns of scholarship recipien because Bank Indonesia does not yet have a pattern. To find the pattem from scholarship recipients using the method of data mining with K-Means Clustering algorithm. The parameters used are 4, namely study program, semester, GPA, and level. The results of the study using RapidMiner showed that cluster 0 was dominated by students from the Commerce Shipping Management study program, who were in semester 5 and D3 level. Cluster 1 is dominated by students from the Accounting and Management study program, in semester 7, with GPA greater than or equal to 3.51, and S1 level. Cluster 2 is dominated by students from the Nursing study program, in semester 5, with GPA greater than or equal to 3.51, and D3 level. Cluster 3 is dominated by students from the International Relations study program, in semester 7, with GPA greater than or equal to 3.51, and S1 level. Cluster 4 is dominated by students from the Informatics Engineering study program, in semester 5, with GPA greater than or equal to 3.51, and S1 level. It show that the recipients of Bank Indonesia scholarships are dominated by students with high GPA scores or equal to 3.51. In addition, it is also dominated by students who are at the S1 level. Tests were carried out using DBI with k=5 resulting in a validity value of 0.121.

Prediksi Kategori Kelulusan Mahasiswa Menggunakan Metode Regresi Logistik Multinomial

Students must meet certain goals to earn a degree but can extend their time at university or drop out (DO). The problem of dropping out of students has become an important issue for tertiary institutions to ensure the success or graduation of students and reduce dropouts. DO can affect the accreditation of the tertiary institution. The quality of higher education institutions in Indonesia is measured based on accreditation from the National Accreditation Board for Higher Education or BAN-PT. One of the main standards measured is the Quality of Students and Graduates. The quality of educational accreditation is measured by the percentage of student graduation and the university's strategy to retain students. To predict student graduation based on graduation time categories, researchers collected academic data from students in 2012-2018 at the Informatics Engineering Study Program, State Islamic University of Maulana Malik Ibrahim Malang. The variables used as predictors are gender, type of entry pathway, and grade point average from semesters one to six. The resulting model was evaluated to obtain an accuracy value of 85.5%, a precision of 78.5%, a recall of 93.9%, and a micro f1-score of 89.8%. An accuracy value of 85.5% indicates that the system can classify properly using the logistic regression model.