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EDUMATIC: Jurnal Pendidikan Informatika
Published by Universitas Hamzanwadi
ISSN : -     EISSN : 25497472     DOI : 10.29408
Core Subject : Science, Education,
Computer Science & IT Education
EDUMATIC: Jurnal Pendidikan Informatika (e-ISSN: 2549-7472) adalah jurnal ilmiah bidang pendidikan informatika yang diterbitkan oleh Universitas Hamzanwadi dua kali setahun yaitu pada bulan Juni dan Desember. Adapun fokus dan skup jurnal ini adalah (1) Komputer dan Informatika dalam Pendidikan; (2) Model Pembelajaran dan Model TIK; (3) Pengembangan Media Pembelajaran Berbasis Teknologi Informatika; (4) Interaksi Manusia dan Komputer; (5) Sistem Informasi dan Teknologi Informasi.
Arjuna Subject : -
Articles 439 Documents
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The Application of Practice Rehearsal Pairs Learning Model toward Basic Programming Learning Outcomes Muhammad Zamroni Uska
Jurnal Pendidikan Informatika (EDUMATIC) Vol 1, No 2 (2017): Edumatic : Jurnal Pendidikan Informatika
Publisher : Universitas Hamzanwadi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29408/edumatic.v1i2.945

Abstract

Learning model is a general pattern of learning behavior to achieve conducive and effective learning goals. The PRP (Practice Rehearsal Pairs) model is one of the effective learning models used in this study. The purpose of this study was to determine the effect of PRP learning models on student learning outcomes in basic programming subjects. This type of research is quantitative research using quasi experimental design carried out at Hamzanwadi University. The design in this study uses posttest only control group design with a total population of 54 students and the number of samples taken using the saturated sampling method is 54 students. Data collection used learning outcomes tests. Data analysis used descriptive analysis and paired sample ttest. The results showed that the average value of learning outcomes in the RPS model was 75.07 higher the average value of learning outcomes on the contextual model was 70.37. Hypothesis test results show that ttest (8,619) ttable (2,060) (significant with ρ 0.05). Thus, the conclusion of this study is that there is a significant effect of student learning outcomes after applying the PRP learning model.
Faktor yang Mempengaruhi Pembelajaran Daring Melalui LMS pada Masa Covid 19 Rasyid Ridho Hamidy; Mashur Mashur; Lalu Nurul Yaqin
Jurnal Pendidikan Informatika (EDUMATIC) Vol 5, No 2 (2021): Edumatic: Jurnal Pendidikan Informatika
Publisher : Universitas Hamzanwadi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29408/edumatic.v5i2.4158

Abstract

Online (e-learning) during the Covid-19 pandemic has become a trend in education that causes significant changes in learning, forcing universities to adapt to learning conditions during Covid 19. The purpose of this study was to determine the factors that influence online learning through the use of the Learning Management System (LMS) during the Covid 19 pandemic at Universitas Gunung Rinjani. Differences in LMS use based on some demographic information such as gender, location (place of residence), and age are also discussed to gain an in-depth understanding of the use of LMS during online learning. There are two research methods used in this study, namely quantitative and qualitative. The data collection process was carried out through an online survey instrument distributed to 6 Faculties 7 Study Programs at Universitas Gunung Rinjani. In addition, interviews with students will be conducted to gain an in-depth understanding of LMS use in their learning. The findings of this study indicate that LMS use during Covid 19 learning can run well; this can be seen from the participants' perceptions of usefulness, ease of use, subjective norms and attitudes of self-efficacy and support from lecturers and colleagues.
Pengukuran E-learning Readiness pada Mahasiswa Sebagai Upaya Penerapan Pembelajaran Jarak Jauh Masa Pandemi COVID-19 Aprilia Sulistyohati
Jurnal Pendidikan Informatika (EDUMATIC) Vol 4, No 2 (2020): Edumatic: Jurnal Pendidikan Informatika
Publisher : Universitas Hamzanwadi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29408/edumatic.v4i2.2674

Abstract

One of the efforts to reduce COVID-19 cases is a Distance Learning (PJJ) system for all levels of education. This study aims to determine the e-learning readiness of Cikarang University. Measurement of e-learning readiness implementation is carried out using the ELR framework. In this study, the ELR framework has consist of 4 main components, that are technology, innovation, people and self-development. This research was conducted on student in Cikarang University. Collecting data used structured interview with the campus management and then distributing questionnaires. The data processing used descriptive statistical techniques then mapped the e-learning Readiness index. The results of this study is to show that the Faculty of Engineering Cikarang University  in the third level (ready) in implementing e-learning, but still requires improvement and preparation in several aspects to achieve success in implementing e-learning. Some recommendations are proposed for Cikarang University, that is the availability of an e-learning system that can fulfill students' need for learning and assigning. In addition, the campus is expected to be able to conduct socialization and training on e-learning to students so that it makes students understand the e-learning system at Cikarang University.
Building Synonym Sets for English WordNet with Robust Clustering using Links Method Sarah Suryaningsih; Moch Arif Bijaksana; Widi Astuti
Jurnal Pendidikan Informatika (EDUMATIC) Vol 4, No 1 (2020): Edumatic: Jurnal Pendidikan Informatika
Publisher : Universitas Hamzanwadi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29408/edumatic.v4i1.2063

Abstract

English WordNet is an important synonym set to present the similarity of meanings between words. Synonym Set is built using Oxford Thesaurus which is accessed through lexico.com, which is a part of the lexical database that will be used. After using the extraction process through Oxford Thesaurus it will produce a synonym set with the same meaning between words. The difference between WordNet and ordinary dictionaries is that the word is interconnected with other words. One method employed for this approach is Robust Clustering Using Links method, which is similarity values and synonym sets that have been created to be used to build a lexical database. Therefore the main purpose of the development of the English WordNet is to produce an accurate synonym set using clustering techniques. The evaluation calculation will use the F-measure method and will use the gold standard for the calculation method. With the ROCK method, there is an increase in accuracy output from dataset input. Building the English wordnet is to improve words that can be used to help research and development of other language wordnets with role models using more accurate English wordnets. And the use of ROCK method there is an increase in the accuracy upon results of the development of English wordnet compared to the previous method, which is using hierarchical clustering. The outcome of this study resulted in improved accuracy so that the ROCK method is one of the good methods used in the development of the English wordnet.
Perbandingan Performansi Model pada Algoritma K-NN Terhadap Klasifikasi Berita Fakta Hoaks Tentang Covid-19 Wahyu Hidayat; Ema Utami; Ahmad Fikri Iskandar; Anggit Dwi Hartanto; Agung Budi Prasetio
Jurnal Pendidikan Informatika (EDUMATIC) Vol 5, No 2 (2021): Edumatic: Jurnal Pendidikan Informatika
Publisher : Universitas Hamzanwadi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29408/edumatic.v5i2.3664

Abstract

During Covid-19 pandemic, there was various hoax news about Covid-19. There are truth-clarification platforms for hoax news about Covid-19 such as Jala Hoax and Saber Hoax which categorize into misinformation and disinformation. Classification of supervised learning methods is applied to carry out learning from fact labels. Dataset is taken from Jala Hoax and Saber Hoax as many as 559 data which are made into Class 1 (Misleading Content, Satire/Parody, False Connection), Class 2 (False Context, Imposter Content), Class 3 (Fabricated and Manipulated Content). K-Nearest Neighbor (K-NN) is used to classify categories of misinformation and disinformation. Dissimilarity measure Jaccard Distance is compared with Euclidean, Manhattan, and Minkowski and uses k-value variance in the K-NN to determine the performance comparison results for each test. Results of Jaccard Distance at the value of k = 4 get a higher value than other model with an accuracy 0.696, precision 0.710, recall 0.572, and F1-Score. Maximum Results tend to be on the label of the most data class in Class 1 (Misleading Content, Satire or Parody, False Connection) with a total of 58 correct data from 61 test data.
Perbandingan Prediksi Kualitas Kopi Arabika dengan Menggunakan Algoritma SGD, Naive Bayes, dan Random Forest Veronica Retno Sari; Feranandah Firdausi; Yufis Azhar
Jurnal Pendidikan Informatika (EDUMATIC) Vol 4, No 2 (2020): Edumatic: Jurnal Pendidikan Informatika
Publisher : Universitas Hamzanwadi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29408/edumatic.v4i2.2202

Abstract

Classification is one of the techniques that exist in data mining and is useful for grouping a data based on the attachment of the data with the sample data. The dataset that is used in this study is the coffee dataset taken from Dataset Coffee Quality Institute on the GitHub platform. The attributes that contained in the dataset are Aroma, Aftertaste, Flavor, Acidity, Balance, Body, Uniformity, Sweetness, Clean Cup, and Copper points. There are 3 classification methods that are used in this study, Stochastic Gradient Descent, Random Forest and Naive Bayes. The aim of this study is to find out which algorithm is the most effective to predict the coffee quality in the dataset. After that, the prediction results will be tested using K-Fold Cross Validation and Area Under the Curve (AUC) method. The results show that Stochastic Gradient Descent obtained the best accuracy results compared to the other two methods with an accuracy of 98% and increased to 99% after tested using K-fold Cross Validation and AUC method.
Pengaruh Model Pembelajaran Blanded Learning berbantuan Kahoot terhadap Motivasi dan Kemandirian Siswa Musrohul Izzati; Heri Kuswanto
Jurnal Pendidikan Informatika (EDUMATIC) Vol 3, No 2 (2019): Edumatic: Jurnal Pendidikan Informatika
Publisher : Universitas Hamzanwadi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29408/edumatic.v3i2.1656

Abstract

This research aimed  to know: The Effect of kahoot-assisted Blanded Learning model towards students’ motivation and Learning independence in subject of digital simulation for student of XI TKJ at SMK Bajang NW Ajan in the academic years 2019/2020. This research was a quantitative method of transfortation. The research design was a pre-ekperimental design in the form of one group pretest and posttest design. The population wa all students of XI TKJ consisting 30 students. The techniques used to collegt data were questionnaires and observation sheets. The questionnaire was used to measure students motivation and observation sheets. The questionnaire was used to measure students    motivation and observation sheets were used to measure students’ learning independence. Analysis tehniques used was to measure students’ motivation and observation sheets were used to measure students’ learning independence. The analysis technique was the Paired Sample T-tes using SPSS. The test results showed that: (1) there was the influence of kahoot-assisted Blanded Learning models towards students’ learning motivation with a significance value of 11.3901,699 and 0,0000,05 (ρ0.05).: (2) there was an influence of blanded learning assisted kaoot-assisted learning model -towards students’ learning indepedence  of woyh a significance value of 21.8921,699 and 0,0000,05 (ρ0.05).
Pengembangan Media Pembelajaran Berbasis Buku Digital Elektronic Publication (Epub) Menggunakan Software Sigil pada Mata Kuliah Pemrograman Dasar Rasyid Hardi Wirasasmita; Muhammad Zamroni Uska
Jurnal Pendidikan Informatika (EDUMATIC) Vol 1, No 1 (2017): Edumatic : Jurnal Pendidikan Informatika
Publisher : Universitas Hamzanwadi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29408/edumatic.v1i1.732

Abstract

This study aims to develop the learning media in basic programming courses and know the feasibility of learning media of electronic book publication (epub) using software sigil. This research uses research and development approach (Research and Development). The place of this research in the department of Informatics Education, Hamzanwadi University. The object of this research in the form of epub media digital book learning using sigil software in basic programming course. This research is included in the type of Research and Development (R D). Data collection techniques used in this study is a questionnaire method. Questionnaire is used to collect data about the feasibility of learning media made and will be answered by respondents related among others: material experts, media experts, users of instructional media and student responses. The method used to analyze the data is disclosed in the distribution of the five scale scores to the predetermined rating scale category. From the research result, among others: material expert test obtained score 3.53 with good category, media expert test obtained score 4.02 with good category, score of student response 4,03 with good category, so epub learning media digital book using sigil software at basic programming courses are appropriate for use in teaching and learning activities.
Aplikasi Dashboard Visualisasi Data Calon Mahasiswa Baru mengunakan Metabase Yumarlin MZ; Jemmy Edwin Bororing; Sri Rahayu; Tan Anugrah Ramadhani
Jurnal Pendidikan Informatika (EDUMATIC) Vol 6, No 1 (2022): Edumatic: Jurnal Pendidikan Informatika
Publisher : Universitas Hamzanwadi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29408/edumatic.v6i1.5483

Abstract

New student data Information systems can be used as a supporting tool to support decisions. Janabadra University is one of the universities in Yogyakarta, the information system for recording transactional data for students is still done simply in the form of text and numbers. The purpose of this research is to design and build a dashboard application for data visualization of prospective students at Janabadra University for new student admissions (PMB). The method used is a business intelligence roadmap with six stages, the stages are (1) justification, (2) planning, (3) business case, (4) design, (5) construction, and (6) deployment which is a reference in the design and construction of a data warehouse using Metabase. The results of this study can build 7 (seven) visualization dashboards are  (1) Dashboard of information students grouped based on the total number of PMB registrants, (2) Dashboard of the number of registrants based on the academic year, (3) Dashboard of income from PMB registration based on the payment date, (4) Dashboard of the number of students based on the academic year of each study program, (5) Dashboard of the number of registrants by class, (6) Dashboard of the number of PMB registrants by semester and (7) Dashboard of the number of PMB registrants by study program and class.
Klasifikasi Teks menggunakan Genetic Programming dengan Implementasi Web Scraping dan Map Reduce Wirarama Wedashwara; Andy Hidayat; Budi Irmawati; Ariyan Zubaidi
Jurnal Pendidikan Informatika (EDUMATIC) Vol 6, No 1 (2022): Edumatic: Jurnal Pendidikan Informatika
Publisher : Universitas Hamzanwadi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29408/edumatic.v6i1.5274

Abstract

Classification of text documents on online media is a big data problem and requires automation. Research has developed a text classification system with pre-processing using map-reduce and web scraping data collection. This study aims to evaluate text classification performance by combining genetic programming algorithms, map-reduce and web scraping for processing large data in the form of text. Data collection was carried out by observing web-based scraping. Data was collected by reducing 8126 duplicates. Map-reduce has tokenized and stopped-word removal with 28507 terms with 4306 unique terms and 24201 duplication terms. Text classification evaluation shows that a single tree produces better accuracy (0.7072) than a decision tree (0.6874), and the lowest is a multi-tree (0.6726). For the acquisition of genetic programming support values with the multi-tree, the highest average support is 0.3854, followed by the decision tree with 0.3584 and the smallest single tree with 0.3494. In general, the amount of support is not in line with the accuracy value achieved.

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