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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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Comparison of Naïve Bayes Algorithm and XGBoost on Local Product Review Text Classification Ivan Rifky Hendrawan; Ema Utami; Anggit Dwi Hartanto
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.v6i1.5613

Abstract

Online reviews are critical in supporting purchasing decisions because, with the development of e-commerce, there are more and more fake reviews, so more and more consumers are worried about being deceived in online shopping. Sentiment analysis can be applied to Marketplace product reviews. This study aims to compare the two categories of Naïve Bayes and XGBoost by using the two vector spaces wod2vec and TFIDF. The methods used in this research are data collection, data cleaning, data labelling, data pre-processing, classification and evaluation. The data scraping process produced 25,581 data which was divided into 80% training data and 20% test data. The data is divided into two classes, namely good sentiment and bad sentiment. Based on the research that has been done, the combination of Word2vec + XGBoost F1 scores higher by 0.941, followed by TF-IDF + XGBoost by 0.940. Meanwhile, Naïve Bayes has an F1-Score of 0.915 with TF-IDF and 0.900 with word2vec. Classification using XGBoost proved to be able to classify unbalanced data better than Naïve Bayes.
Pengembangan Model Pembelajaran Jarak Jauh dengan Control Device Memanfaatkan Aplikasi AirDroid Henny Prasetyani; Desy Nur Cahyani
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.v6i1.5026

Abstract

During distance learning, there are problems. Namely, students tend to underestimate when learning occurs because they are bored with online learning and prefer offline learning. This study aims to monitor the activities carried out by students on their smartphones during distance learning so that knowledge is more varied and students are more focused during education. The ADDIE model and development used in this study consisted of the Analysis, Design, Development, Implementation, and Evaluation stages. Data collection techniques use instruments in media and materials; then, the results are analyzed using descriptive statistics. Developing a distance learning model of a control device utilizing the AirDroid application is effective in learning, showing student response results of 88.53%. This is because the AirDroid application has several convenient features that can be implemented during learning. Therefore, the AirDroid application can be used as a distance learning model.
Implementasi Algoritma Apriori dan FP-Growth pada Penjualan Spareparts Aditya Wadanur; Aprilisa Arum Sari
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.v6i1.5470

Abstract

Data Mining can be applied in various areas, for example in PT. Agung Toyota Denpasar in order to increase sales and determine the sale of replacement parts. The current problem is to determine the replacement parts sale in PT. Agung Toyota Denpasar cannot know the purchasing habits of customers or customers in purchasing replacement parts purchased simultaneously. This research aims to implement apriori algorithms and fp-growth algorithms to form a model or a combination of rules so that businesses can increase their sales. Using the Knowledge Discovery Database (KDD) method should provide significant information on transaction patterns purchased simultaneously using the apriori and fp-growth algorithms. The dataset used to support this research is the sales transactional dataset for the period of January 2022. The results showed that the 10 best association rules of apriori algorithms and fp-growth algorithms were ready to be used to increase sales with a minimum support value of 85%, confidence value of 100%, and the highest lift ratio of 2.03.
Prediksi Penambahan Piutang Iuran Jaminan Sosial Ketenagakerjaan menggunakan Algoritma K-Nearest Neighbor Devi Efriadi; Rahmaddeni Rahmaddeni; Agustin Agustin; Junadhi Junadhi
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.v6i1.5255

Abstract

There are several issues with Social Security Organizing Agency (BPJS) employment at the moment, one of which is contribution receivable. To reduce the BPJS contribution receivables, BPJS has done various ways. However, the resulting effort is not maximal enough to reduce the number of receivables in BPJS. This study aims to provide input by predicting the addition of receivables from social security contributions made by several companies or organizations. This study used the K-Nearest Neighbor (KNN) Algorithm with a cross-validation technique. KNN is a very simple classification method in classifying an image based on the closest distance to its neighbors. This study conducted data processing from BPJS use, which amounted to 1193 data. The data is then preprocessed so that the processed data is clean from missing and noise, this data uses 70:30 data splitting. After the preprocessing and splitting of data were carried out, the next step was to do modeling using KNN, so the cross-validation to improve the accuracy of results obtained from the KNN algorithm. The results obtained from this research get the highest accuracy of 92% with the Optimal K value being 6, then the ROC curve gets 94% accuracy. From these results, it can be said that the use of cross-validation can increase the accuracy of this study.
Aplikasi Panic Buton Untuk Keamanan Warga Berbasis Android Torkis Nasution; Wilda Susanti; Yandri Armi; Rangga Rahmadian Yuliendi
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.v6i1.5127

Abstract

Citizens highly expect environmental security, but criminality is inevitable. The level of crime in the community brings unrest and discomfort, so a security system is needed that is connected with the officers concerned. This study aims to build a security system application connected to environmental security officers. This system can help the public provide reports quickly through the panic button application embedded in Android. System development using the spiral model method. A spiral model is an evolutionary software process model assembling the interactive nature of the prototype using control and systematic aspects of a linear sequential model. Meanwhile, the system design stage uses the Unified Modeling Language (UML). The application is in Android Studio for the design stage, a unique Integrated Development Environment (IDE) that runs on the Android platform. The panic button application is a security system designed to assist the public in providing reports and make it easier for security officers to follow up on the messages given. Accelerate the follow-up process of crimes because it is based on Android.
Simple Additive Weighting sebagai Metode Pendukung Keputusan terhadap Sistem Customer Satisfaction Ayu Rahmadani; Dewi Maharani; Sahren Sahren
Jurnal Pendidikan Informatika (EDUMATIC) Vol 6, No 2 (2022): Edumatic: Jurnal Pendidikan Informatika
Publisher : Universitas Hamzanwadi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29408/edumatic.v6i2.6374

Abstract

Nazwa drugstore is one of the stores that still use manual methods to recognize complaints about service for customers who come to the store, so it is felt to be less effective. Therefore, it is necessary to have a system to measure customer satisfaction in the store quickly and accurately. To build this system, we apply the Simple Additive Weighting (SAW) method to determine user satisfaction. The model used to build this system is the System Development Life Cycle (SDLC) with stages of analysis, design, implementation, and trial. At the analysis stage, we used interview and observation methods to collect data. Our design phase consists of a use case, a system interface, and a diagram class. Testing this system uses a black box to see if all the components of the system are working properly. Our findings are to produce a decision support system for customer satisfaction using the SAW method. In addition, this system also has a user-friendly and responsible interface, so this system is easy to use. The results of the black box test show that all components in this system are already functioning properly.
Analisis Quality of Service Jaringan Wireless untuk Teknologi Streaming Rudi Yanto; Dedy Irfan; Asrul Huda
Jurnal Pendidikan Informatika (EDUMATIC) Vol 6, No 2 (2022): Edumatic: Jurnal Pendidikan Informatika
Publisher : Universitas Hamzanwadi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29408/edumatic.v6i2.5840

Abstract

Wireless network services can be known for their quality with the Quality of Service (QoS) method.  This method can measure the quality of streaming services in terms of throughput, delay, packet loss, and jitter. The purpose of this study was to analyze wireless network QoS for streaming technology. This type of research is quantitative with observation methods using the Wireshark application and compared with TIPHON standards. The target of the ICONNET ISP wireless survey on Jalan Nusantara km. 13 Tanjungpinang Timur District. The parameters for measuring QoS use four parameters, namely throughput, delay, packet loss, and jitter. Our findings show that the throughput of obtaining index value is 3.67 and is at a good level. Furthermore, the delay value has an average index of 4 with the best level. Meanwhile, the jitter obtained an index value of 3 at a good level, while the packet loss value obtained an index of 3.3 and had a good level. Based on the results of this study, the quality of ICONNET ISP wireless network services when accessing streaming technology shows data speed instability, data delays, and lost data packets. However, the network quality is still in the "Good" level in terms of throughput, jitter, and packet loss parameters, and the "Best" level in terms of the delay parameter.
Sistem E-SCM untuk Manajemen Suplai Barang Produksi Pecah Belah berbasis Web Cindy Ramadhani; Hambali Hambali; Akmal Akmal
Jurnal Pendidikan Informatika (EDUMATIC) Vol 6, No 2 (2022): Edumatic: Jurnal Pendidikan Informatika
Publisher : Universitas Hamzanwadi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29408/edumatic.v6i2.6373

Abstract

E-SCM is a system that can manage the delivery of goods that can be integrated between consumers, suppliers and traders. The purpose of this research is to create a web-based E-SCM system for glassware inventory management, which will be implemented at the Glosir Raju store. The model used to build this system is the system development life cycle, which includes the analysis, design, implementation, and testing phases. Data collection techniques were carried out by interview and observation. While the design phase in this research consists of making interfaces, use case diagrams, and class diagrams. Our result is a web-based E-SCM system for managing the distribution of glassware. The test results show that all functions work well in this system and follow the set design. Therefore, the E-SCM system for glassware shops makes the delivery of raw materials faster, and there are no delays in delivery, making the production process faster, more effective, and efficient, especially at the Glosir Raju store.
Single Exponential Smoothing: Metode Peramalan Kebutuhan Vaksin Campak Annisa Azzahra; William Ramdhan; Wan Mariatul Kifti
Jurnal Pendidikan Informatika (EDUMATIC) Vol 6, No 2 (2022): Edumatic: Jurnal Pendidikan Informatika
Publisher : Universitas Hamzanwadi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29408/edumatic.v6i2.6299

Abstract

The importance of the measles immunization vaccine for children up to the age of 9 months to prevent children from getting sick with measles or reduce the transmission rate in the surrounding environment, especially at the Gambir Health Center.  This demand is still considered ineffective and there is often an oversupply of vaccines, which results in a buildup of vaccines in storage. The purpose of this study was to create a measles vaccine needs forecasting system using the Single Exponential Smoothing (SES) method. The model used to build this system is the Systems Development Life Cycle (SDLC) with stages of analysis, design, implementation, and trial. Data collection techniques use observation, interviews, or smart phones for shooting or sound recording. The analysis technique for system forecasting uses the SES method, while the system testing uses a Blackbox. Our findings show that the lowest MAPE value was obtained at 49.8%. The results of testing the system using a Blackbox that all components in this system are already functioning properly. With this system, it can make it easier for related parties to predict the number of measles vaccines in the new Gambir health center.
Penerapan Algoritma K-Nearest Neighbor dengan Euclidean Distance untuk Menentukan Kelompok Uang Kuliah Tunggal Mahasiswa Fenny Purwani; Ragil Tri Wahyudi; Irfan Dwi Jaya
Jurnal Pendidikan Informatika (EDUMATIC) Vol 6 No 2 (2022): Edumatic: Jurnal Pendidikan Informatika
Publisher : Universitas Hamzanwadi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29408/edumatic.v6i2.6547

Abstract

Single tuition fee or called UKT is the amount of tuition fee determined based on the student's economic ability. In its application, there are still many students who object to the UKT group that is obtained. Therefore, the university must apply the right and accurate method in determined the UKT group. This study aims to obtain the result of student’s UKT group classification using the K-Nearest Neighbor (KNN) algorithm with Euclidean Distance calculation and determine the accuracy of the algorithm with the optimal k value. This study used a quantitative method with a descriptive approach. The data collection techniques used are interviews, literature study, and documentation. The data that has been collected is 1,650 student’s UKT verification data for 2019-2021 which be processed with data mining using the RStudio software. The results showed that the classification with KNN can be applied in determined student’s UKT. With data testing many as 320 students, 23 students were determined to get UKT I, 149 UKT II, 129 UKT III, 32 UKT IV, and 2 students got UKT V. The accuracy of the algorithm is 87.58% in the Good Classification category. The optimal k for KNN obtained with K-Fold Cross Validation is k=1.

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