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INDONESIA
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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Penerapan Metode OPTICS dan ST-DBSCAN untuk Klasterisasi Data Kesehatan Hastuti, Siti Hariati; Septiani, Ayu; Hendrayani, Hendrayani; Nurmayanti, Wiwit Pura
Jurnal Pendidikan Informatika (EDUMATIC) Vol 8 No 1 (2024): Edumatic: Jurnal Pendidikan Informatika
Publisher : Universitas Hamzanwadi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29408/edumatic.v8i1.25765

Abstract

One way to extract valuable insights from large datasets is through cluster analysis. This statistical technique involves grouping data objects based on their similarities, aiming to create distinct groups where objects within each group share high similarities but differ significantly from objects in other groups. Cluster analysis, such as the OPTICS and ST-DBSCAN methods, can be utilized in various domains, including healthcare workforce and demographic data. In a case study focusing on health workers in East Lombok, these clustering methods were employed. The study aimed to present the outcomes of clustering health workers using OPTICS and ST-DBSCAN and determine the superior method through internal validation. The results from OPTICS revealed the formation of 5 clusters: cluster-1 with two sub-district members, cluster-2 with three members, cluster-3 with two members, cluster-4 with three members, and cluster-5 with seven members. Conversely, ST-DBSCAN produced only 2 clusters: cluster-1 with six members and cluster-2 with four members. Based on the internal validation findings, OPTICS emerged as the more effective method for categorizing health workers in East Lombok.
Inovasi Pembelajaran Musik melalui Audio Visual berbasis Multimedia Interaktif Murcahyanto, Hary
Jurnal Pendidikan Informatika (EDUMATIC) Vol 8 No 1 (2024): Edumatic: Jurnal Pendidikan Informatika
Publisher : Universitas Hamzanwadi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29408/edumatic.v8i1.25772

Abstract

Education in Indonesia faces various challenges, particularly due to the Covid-19 pandemic, which has forced a shift to online learning. However, the use of technology can help overcome difficulties faced by teachers and increase interactivity and student interest in learning music arts. This study aims to evaluate the effectiveness of developing a learning media for staff notation based on Macromedia Flash 8 in enhancing student comprehension. The research methodology follows the Borg and Gall development model, involving the analysis of learning objectives, product design, implementation, expert validation, and field testing. Media content analysis focused on the learning of staff notation introduction. The research results indicate that the developed learning media successfully achieved the learning objectives. Validation by media and material experts showed positive assessments of the media’s design and content. Field testing also showed positive responses from students, indicating increased interest and understanding of staff notation material. Based on the N-Gain score calculations, the use of audiovisual media based on Macromedia Flash 8 for learning staff notation is considered quite effective, with an average N-Gain score of 0.72 and an accumulated N-Gain percentage of 72%. The conclusion of this study is that the development of audiovisual media based on Macromedia Flash 8 is effective in enhancing students' interest, understanding, and learning outcomes in staff notation material.
Penerapan Metode Vulnerability Assessment untuk Identifikasi Keamanan Website berdasarkan OWASP ID Tahun 2021 Darmawan, Candra; Naibaho, Julius Panda Putra; Kweldju , Alex De
Jurnal Pendidikan Informatika (EDUMATIC) Vol 8 No 1 (2024): Edumatic: Jurnal Pendidikan Informatika
Publisher : Universitas Hamzanwadi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29408/edumatic.v8i1.25834

Abstract

Universities, as educational institutions, are potential targets of cyber attacks. This is inevitable problem, one of which  the University of Papua (UNIPA). The purpose this research is to find the security gaps the UNIPA website based on OWASP ID in 2021 and implement mitigation. Type of research is quantitative research with Vulnerability Assessment and Penetration Testing Life Cycle (VAPT) method. The VAPT method in research goes through five stages, namely scope, information gathering, vulnerability assessment, risk assessment, and reporting. The object of research is UNIPA website. Data collection uses primary data, the results of scanning the Zed Attack Proxy (ZAP) application. Data obtained from alerts ID, alerts, risk, and OWASP ID as information on vulnerability of UNIPA website. Research data analysis using OWASP ID. The results our findings, the vulnerability of UNIPA website is influenced by two factors, website security weaknesses and user negligence. Vulnerabilities with alerts ID A1, A2, A3, A4 A5, and A6 are a group website security weaknesses. The solution, vulnerabilities need utilize special systems such as anti-CSRF, CSP, CDN, Strict-Transport-Security Header, and timestamp checking so that the website is proportional. Meanwhile, the vulnerability with alerts ID A7 is a classification of user negligence. The solution is users must use the latest version of the browser. Browsers with latest version have X-Content-Type-Options: nosniff security mechanism to prevent sniffing attacks.
Penerapan Random Oversampling dan Algoritma Boosting untuk Memprediksi Kualitas Buah Jeruk Ananda, Imanuel Khrisna; Fanani, Ahmad Zainul; Setiawan, Dicky; Wicaksono , Duta Firdaus
Jurnal Pendidikan Informatika (EDUMATIC) Vol 8 No 1 (2024): Edumatic: Jurnal Pendidikan Informatika
Publisher : Universitas Hamzanwadi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29408/edumatic.v8i1.25836

Abstract

According to the 2019 data, global orange production has increased significantly, reaching 79 million tons. However, despite the availability of various types of oranges in Indonesian markets, many vendors still sell low-quality oranges. To address this issue, researchers have applied random oversampling and boosting algorithms to predict orange quality, using the public Orange Quality Analysis Dataset. This study uses random oversampling to address data imbalance and combines it with boosting algorithms like Adaboost, Gradient Boosting, Light GBM, and CatBoost. The data features considered include size, weight, sweetness level, acidity level, and others. The accuracy of the boosting algorithms used varied, with CatBoost showing the highest accuracy rate of 91.42%. The hope is that this research can help orange producers create high-quality products and reduce the occurrence of low-quality oranges, ultimately providing consumers with better oranges. Additionally, this can help producers market their oranges both domestically and internationally.
Peningkatan Performa Model Hard Voting Classifier dengan Teknik Oversampling ADASYN pada Penyakit Diabetes Anugrah, Muhammad Ikhsan; Zeniarja, Junta; Setiawan, Dicky Setiawan
Jurnal Pendidikan Informatika (EDUMATIC) Vol 8 No 1 (2024): Edumatic: Jurnal Pendidikan Informatika
Publisher : Universitas Hamzanwadi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29408/edumatic.v8i1.25838

Abstract

Diabetes is a chronic disease that arises from excess sugar levels in the body and lack of exercise intensity resulting in a buildup in the blood. Indonesia ranks fifth as the country with the largest number of people with diabetes based on a report from the International Diabetes Federation (IDF). The reason is that people with diabetes do not realize that they have diabetes, so there is a need for early detection in knowing this. The purpose of this research is to improve the performance of the Hard Voting Classifier model combining the Decision Tree, Random Forest, and XGBoost algorithms with the ADASYN oversampling technique that handles data imbalance in diabetes prediction. This study uses patient information data with a total of 1000 data and 14 features from the Medical City Hospital laboratory, Iraq. The results of this study show an increase in the performance of the prediction model with an accuracy value of 99.0%, precision 99.1%, recall 99.0%, and f1-score 98.98% without using ADASYN. Then get an accuracy value of 99.8%, precision 99.8%, recall 99.8%, and f1-score 99.8% by using ADASYN as an oversampling technique. This shows that there is an increase in the performance of the Hard Voting Classifier model so that it produces accurate predictions of diabetes, where the correctness of diabetes prediction is very good.
Aplikasi E-Comerce Produk UMKM menggunakan Metode Filtrasi Kolaboratif berbasis Mobile Purba, Pria Mitra; Suendri, Suendri
Jurnal Pendidikan Informatika (EDUMATIC) Vol 8 No 1 (2024): Edumatic: Jurnal Pendidikan Informatika
Publisher : Universitas Hamzanwadi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29408/edumatic.v8i1.25880

Abstract

Micro, Small, and Medium Enterprises (UMKM) in Tebing Tinggi City, North Sumatra have great potential to encourage local economic growth. However, most UMKM in this city still face obstacles in marketing their products online. This research aims to develop a mobile-based e-commerce application with a collaborative filtration method for local UMKM to increase sales and turnover. The type of research is Research and Development (R&D) using the waterfall model including requirements analysis, system design, implementation, testing, and maintenance. The data analysis used includes a collaborative filtration method to recommend products to users based on the highest rating of all UMKM products on the application. Needs analysis through observation, interviews, and literature study. Design using UML diagrams. The implementation applies collaborative filtration for product recommendations based on user preferences, and functionality testing using black boxes. This research produces an e-commerce application that can provide product recommendations that are relevant and by user preferences based on the highest rating patterns and similar behavior of other users. Apart from that, this application also runs smoothly without any problems after black box testing.
Optimasi Convolutional Neural Networks untuk Deteksi Kanker Payudara menggunakan Arsitektur DenseNet Mas'ud, Ryan Ali; Junta Zeniarja
Jurnal Pendidikan Informatika (EDUMATIC) Vol 8 No 1 (2024): Edumatic: Jurnal Pendidikan Informatika
Publisher : Universitas Hamzanwadi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29408/edumatic.v8i1.25883

Abstract

Breast cancer is a disease commonly suffered by women worldwide, ranking as the second-largest disease burden. In response to the urgent need for improved detection accuracy, Convolutional Neural Networks (CNNs) promise significant advancements. The objective of this research is to optimize the use of CNNs with the DenseNet architecture for breast cancer detection. The study employs quantitative methods, leveraging Deep Learning through CNNs. Mammography data is sourced from Kaggle, specifically the “Breast Histopathology Images” dataset. This dataset comprises 90,000 digital mammography images, which are preprocessed and divided proportionally for training, validation, and model testing. Research variables encompass CNN model parameters, training techniques, and the integration of imaging modalities to enhance breast cancer detection performance. The research focuses on processed mammography data, with accuracy and image quality as key evaluation metrics for breast cancer sample identification. Our findings demonstrate that the DenseNet architecture within CNNs achieves an impressive 92% accuracy in breast cancer detection. This remarkable performance signifies success in enhancing image quality and class prediction, aligning with the DenseNet architecture’s flow diagram. Ultimately, these results contribute significantly to effective breast cancer diagnosis by optimizing CNNs with the DenseNet architecture to improve image quality during breast cancer sampling.
Sistem Informasi Pelaporan Perkembangan Pasien (SI-PELPASI) berbasis Mobile Android Gea, Yusuf Abdul Aziz; Muhamad Alda
Jurnal Pendidikan Informatika (EDUMATIC) Vol 8 No 1 (2024): Edumatic: Jurnal Pendidikan Informatika
Publisher : Universitas Hamzanwadi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29408/edumatic.v8i1.25938

Abstract

The use of Android mobile applications in the healthcare sector as tools for patient progress reporting has become a significant innovation. The mobile Android-based patient progress reporting information system (SI-PELPASI) serves as a solution to enhance efficiency and accuracy in patient monitoring. This study aims to develop a mobile Android-based patient progress reporting information system at the Bukit doa rehabilitation centre, an Institution for Mandatory Reporting (IPWL). The system development in this study employs the System Development Life Cycle (SDLC) method, which consists of systematic stages: the planning stage aims to plan the system, the analysis stage involves reviewing existing and current systems and collecting data through interviews and observations, the design stage includes designing Unified Modelling Language (UML) diagrams and the user interface, the implementation stage uses the Kodular app creation platform, and the testing stage uses the black box method to test system functionality. Our findings resulted in the Patient Progress Reporting Information System in the form of a Mobile Android application named SI-PELPASI. The application runs smoothly and can be operated on Android-based mobile devices. With this application, the process of reporting patient progress becomes faster and real-time.
Penerapan Metode Perbandingan Eksponensial dalam Menentukan Kinerja Perangkat Desa Sari, Fatimah Rama; Ramdhan , William; Dermawan , Ari
Jurnal Pendidikan Informatika (EDUMATIC) Vol 8 No 1 (2024): Edumatic: Jurnal Pendidikan Informatika
Publisher : Universitas Hamzanwadi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29408/edumatic.v8i1.25945

Abstract

Village apparatus is an important thing in the village for serving the community. However, carrying out the assessment process takes a long time and also requires determining which village officials are worthy of being given the best village officials. The aim of this research is to build a decision support system by applying the MPE method to determine the assessment of village officials. The model used to build this system is the Software Development Life Cycle with stages of planning, analysis, design, implementation, testing and management. This research was carried out at the Prapat Janji Village Office. The planning stage is carried out to obtain a performance assessment plan for village officials. Next, the analysis stage was carried out to obtain the system requirements that we developed using the MPE method. Next, the coding and testing stages carried out system creation and testing using a black box. The results of our findings are in the form of a decision support system to determine the best assessment of village officials. The test results show that this system is running well, and is in accordance with the design and model implemented. With this system, it can help the village in determining whether or not village officials will be given rewards.
Sistem Pendukung Keputusan Cerdas untuk Pemilihan Jenis Tanaman Pertanian Kota Ramadhan, Jeri; Hermadi, Irman; Sitanggang, Imas Sukaesih
Jurnal Pendidikan Informatika (EDUMATIC) Vol 8 No 1 (2024): Edumatic: Jurnal Pendidikan Informatika
Publisher : Universitas Hamzanwadi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29408/edumatic.v8i1.25982

Abstract

Urban farming activities have become increasingly popular to meet their food needs in urban areas. Jakarta as provinces with a population density of high, have a program of urban farming is developed by the farmers to urban Balkot Farm. This study aims to support system to develop a clever move the crop farm a town with the simple additive weighting (SAW). The methods used to obtain the highest related alternative plant assessed according to its parameters that affect the eligibility of land and a room with a variety of plants. The methodology used software development life cycle (SDLC) prototyping model consisting of five of the communication, quick plan, modeling quick design, construction of prototype deployment and delivery and feedback. Data collection method using interviews and the study of literature. Research results of a web application system that has an alternative menu, criteria, subcriteria, rating match and results. Smart decision support system based on black box testing and user acceptance testing successfully shows menus according to land criteria that will be used according to stakeholder needs.

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