Journal of Informatics, Electrical and Electronics Engineering
Fokus kajian Journal of Informatics, Electrical and Electronics Engineering, yaitu: 1. Control System, 2. Artificial Intelligence, 3. Informatics Engineering, 4. Electronics, 5. Advanced energy material, 6. Automatic power control, 7. Battery technology, 8. Distributed generation, 9. Distribution system, 10. Electric power generation, 11. Electric vehicle, 12. Electrical machine, 13. Energy optimization, 14. Energy conversion, 15. Energy efficiency, 16. Energy exploitation, 17. Energy exploration, 18. Energy management, 19. Energy mitigation, 20. Energy storage, 21. Energy system, 22. Fault diagnostics, 23. Green energy, 24. Green technology, 25. High voltage, 26. Insulation technology, 27. Intelligent power optimization, 28. Monitoring operation, 29. Motor drives, 30. Natural energy source, 31. Power control, 32. Power data transaction, 33. Power economic, 34. Power electronics, 35. Power engineering, 36. Power generation, 37. Power optimization, 38. Power quality, 39. Power system analysis, 40. Power system information, 41. Power system optimization, 42. Protection system, 43. Renewable energy, 44. SCADA, 45. Security operation, 46. Smart grid, 47. Stability system, 48. Storage system, and 49. Transmission system
Articles
72 Documents
<![CDATA[Penerapan Algoritma C4.5 untuk Klasifikasi Tingkat Kedisiplinan Siswa Sekolah Menengah ]]>
<![CDATA[selipuri]]>;
<![CDATA[Rosyana Fitria Purnomo]]>;
<![CDATA[Yodhi Yuniarthe]]>
<![CDATA[ Journal of Informatics, Electrical and Electronics Engineering Vol. 5 No. 1 (2025): September 2025 ]]>
Publisher : <![CDATA[Forum Kerjasama Pendidikan Tinggi (FKPT) ]]>
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DOI: 10.47065/jieee.v5i1.2630
<![CDATA[Abstract?This study aims to evaluate the performance of the Decision Tree algorithm based on the entropy criterion (C4.5) in classifying student eligibility by considering both academic and non-academic data. The dataset consists of 200 entries with nine attributes, including attendance percentage, number of lateness incidents, disciplinary violations, average academic scores, participation, study hours, and extracurricular activities. Data processing was carried out through several stages, namely cleaning, transformation, feature selection, training and testing data splitting, and model evaluation using a confusion matrix. The experimental results show that the proposed model achieved an accuracy of 87.5%, an average precision of 85.6%, an average recall of 84.2%, and an F1-Score of 84.8%. These findings confirm that the C4.5 algorithm can be effectively applied to support student performance classification with a fairly high level of reliability.]]>
<![CDATA[Analisis Sistem Informasi Keuangan Punia.Id Dengan Menggunakan Rapidminer ]]>
<![CDATA[Nasrudin, Ahmad Nasrudin]]>
<![CDATA[ Journal of Informatics, Electrical and Electronics Engineering Vol. 5 No. 1 (2025): September 2025 ]]>
Publisher : <![CDATA[Forum Kerjasama Pendidikan Tinggi (FKPT) ]]>
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DOI: 10.47065/jieee.v5i1.2691
<![CDATA[With the development of information technology, digital systems are increasingly being adopted by companies to improve efficiency and transparency in financial management. PT Kanzun Bahriyah Sentosa uses Punia.id as a financial information system to record and manage company transactions, including ship operations and fish sales. However, during implementation, several technical and non-technical obstacles were encountered, such as users' difficulty in understanding the Chart of Accounts, which affected the accuracy of financial reports. Therefore, an analysis of the effectiveness of using Punia.id in improving the efficiency of the company's financial system is needed. This study uses observation, interviews, documentation, and questionnaires with the Likert scale technique to measure the effectiveness and obstacles in using Punia.id. In addition, a problem-solving approach and linear regression analysis were used to evaluate the relationship between the level of difficulty in managing the Chart of Accounts and the level of errors in financial reporting. Based on the results of tests conducted on the Financial Information System using the Rapidminer method, it can be seen that the results are quite significant based on the tests that have been carried out. The independent variable (X), based on the correlation test results, has an R Square value of 0.42, which is 42%. With these results, the value can be calculated]]>
<![CDATA[Penerapan Model Transfer Learning Dalam Mendalami Penyakit Daun Jagung Menggunakan Arsitektur VGG19 ]]>
<![CDATA[Setiyo Adi Wibowo]]>;
<![CDATA[Rudi Kurniawan]]>;
<![CDATA[Budi Santoso]]>
<![CDATA[ Journal of Informatics, Electrical and Electronics Engineering Vol. 5 No. 1 (2025): September 2025 ]]>
Publisher : <![CDATA[Forum Kerjasama Pendidikan Tinggi (FKPT) ]]>
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DOI: 10.47065/jieee.v5i1.2702
<![CDATA[The process of processing corn leaf disease data using the VGG 19 architecture based on deep learning is to analyze corn leaf diseases that result in low yields. In describing the values to be managed in this study, a digital image dataset of corn leaf diseases consisting of 5 classes with 3923 images per class was used. The objectives of this study are to enable easy prediction of corn leaf disease and to treat the disease. It also aims to enable pattern recognition of corn leaf disease based on digital images using the VGG19 architecture model. The results of corn leaf disease classification obtained from the VGG19-based model show excellent performance in identifying various plant health conditions. With an overall accuracy of 97.96%, this model successfully distinguishes between five disease classes, namely Common Rust, Grey Leaf Spot, Healthy, Northern Leaf Blight, and Northern Leaf Spot. This figure reflects the effectiveness of the model in recognizing the distinctive visual patterns of each disease, which is very important for effective crop management.]]>
<![CDATA[Pengukuran Akuisisi Pelanggan Insyira Oleh-Oleh Berdasarkan Analisis Sentimen Pengguna Instagram ]]>
<![CDATA[Wira Mulia, M. Roid]]>;
<![CDATA[Inggih Permana]]>;
<![CDATA[Febi Nur Salisah]]>;
<![CDATA[Eki Saputra]]>;
<![CDATA[Arif Marsal]]>
<![CDATA[ Journal of Informatics, Electrical and Electronics Engineering Vol. 4 No. 4 (2025): June 2025 ]]>
Publisher : <![CDATA[Forum Kerjasama Pendidikan Tinggi (FKPT) ]]>
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DOI: 10.47065/jieee.v4i4.2472
<![CDATA[Social media, especially Instagram, has transformed how businesses interact with customers and market products. However, there remains a literature gap regarding customer acquisition measurement through sentiment analysis of Instagram comments. This research aims to measure customer acquisition at Insyira Oleh-Oleh Pekanbaru by analyzing 1,363 comments from May 2024 to May 2025 using Python-based Natural Language Processing (NLP). The results show neutral sentiment dominates (47.7%) with the highest acquisition rate (50.9%) - meaning every 2 neutral comments yield 1 acquisition - compared to positive (37.7%) and negative comments (41.8%). The Chi-square test confirms the significant relationship between sentiment and acquisition (?²=21.78; p<0.0001), while (OR=0.58; CI[0.46,0.73]) indicates positive comments have 42% lower acquisition probability than neutral ones, forming triangular consistency that eliminates doubts. Negative sentiment also yields higher acquisition than positive sentiment, challenging the assumption that positive comments are most effective for acquisition. This reveals neutral comments containing product inquiries have greater acquisition potential. The study provides new insights for digital marketing strategy, emphasizing the importance of quick responses to neutral comments to enhance new customer conversion.]]>
<![CDATA[Evaluasi Kesiapan Calon Mahasiswa Terhadap Teknologi Sistem Pendaftaran Online Dengan Pendekatan Technology Readiness Index ]]>
<![CDATA[Naufal Fikri, R. Adlian]]>;
<![CDATA[Permana, Inggih]]>;
<![CDATA[Nur Salisah, Febi]]>;
<![CDATA[Saputra, Eki]]>;
<![CDATA[Marsal, Arif]]>
<![CDATA[ Journal of Informatics, Electrical and Electronics Engineering Vol. 4 No. 4 (2025): June 2025 ]]>
Publisher : <![CDATA[Forum Kerjasama Pendidikan Tinggi (FKPT) ]]>
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DOI: 10.47065/jieee.v4i4.2481
<![CDATA[This study aims to evaluate the technological readiness of prospective students in using the online registration system facilitated by LPSDM Aparatur, employing the Technology Readiness Index (TRI) approach. TRI comprises four key dimensions: Optimism, Innovativeness, Discomfort, and Insecurity, which measure an individual's readiness to adopt new technologies. The research objects are newly enrolled students who registered through the online system provided by LPSDM Aparatur at two partner universities: Universitas Ekasakti and Universitas Nurdin Hamzah. The research uses a descriptive quantitative method with a proportional stratified sampling technique. The sample size of 43 respondents—28 from Universitas Ekasakti and 15 from Universitas Nurdin Hamzah—was determined using the Slovin formula. Data were collected using Likert scale-based questionnaires and analyzed with SPSS version 20 through validity and reliability tests, as well as descriptive statistical analysis. The findings reveal that the overall level of technological readiness is high, with a TRI score of 4.49 for Universitas Ekasakti and 4.36 for Universitas Nurdin Hamzah, both exceeding the threshold for the “high” category (>3.51). Students from Universitas Ekasakti scored highest in the Innovativeness dimension (1.11), indicating a strong tendency to try and adopt new technologies. In contrast, students from Universitas Nurdin Hamzah scored relatively high in negative dimensions, namely Insecurity (1.162) and Discomfort (1.08), suggesting psychological barriers and discomfort in using the online registration system. The study recommends training, socialization, and system simplification to ensure inclusivity and accessibility for users from diverse backgrounds. Academically, this research expands the application of TRI in the context of online-based rural education. Practically, it offers a foundation for LPSDM to develop targeted training and outreach strategies for students in regions with lower readiness levels]]>
<![CDATA[Perancangan dan Pengembangan Aplikasi Absensi Berbasis Kotlin yang Terintegrasi dengan Website Backoffice Menggunakan Rest API Laravel ]]>
<![CDATA[Arkan, Faiz]]>;
<![CDATA[Aziz Zuama, Robi]]>;
<![CDATA[Setia Budi, Eko]]>
<![CDATA[ Journal of Informatics, Electrical and Electronics Engineering Vol. 4 No. 4 (2025): June 2025 ]]>
Publisher : <![CDATA[Forum Kerjasama Pendidikan Tinggi (FKPT) ]]>
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DOI: 10.47065/jieee.v4i4.2491
<![CDATA[The attendance system is a fundamental aspect of managing employee presence in both corporate and educational institutions. Conventional methods that rely on manual attendance, such as paper-based records or spreadsheets, have numerous limitations. These weaknesses include susceptibility to data manipulation, time-consuming data recap processes, and lack of system integration. This study develops a digital attendance system based on Android using the Kotlin programming language, integrated with a BackOffice website through a REST API built on Laravel. The development methodology used is the Waterfall model, which is systematic and well-suited for projects with clearly defined requirements. The REST API serves as a communication bridge between the mobile application and the web system, utilizing the JSON format over the HTTP protocol. System testing results show that the application can manage attendance data in real-time, automatically validate location, and provide a web interface for administrators to monitor employee attendance. The system also integrates the Google Drive API to store photo evidence of attendance in a cloud-based environment. Through this approach, the study contributes to the development of an efficient, transparent, and scalable attendance system.]]>
<![CDATA[Pengembangan Aplikasi Absensi Mobile Terintegrasi dengan Sistem Backoffice Berbasis Web Menggunakan Metode Pengembangan Perangkat Lunak Waterfall ]]>
<![CDATA[Nasya Putri Restyarna]]>;
<![CDATA[Andi Taufik]]>;
<![CDATA[Eko Setia Budi]]>
<![CDATA[ Journal of Informatics, Electrical and Electronics Engineering Vol. 5 No. 1 (2025): September 2025 ]]>
Publisher : <![CDATA[Forum Kerjasama Pendidikan Tinggi (FKPT) ]]>
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DOI: 10.47065/jieee.v5i1.2504
<![CDATA[Attendance systems play a crucial role in human resource management by serving as the foundation for accurate and efficient employee presence tracking. PT Urun Bangun Negeri previously used a manual attendance method that was prone to data errors, manipulation, and inefficiencies in reporting. This study aims to develop a digital attendance application based on Android that integrates with a web-based backoffice system. The software development method used is the Waterfall model, consisting of requirement analysis, system design, implementation, and testing phases. Kotlin was used to develop the mobile application, while Laravel was used for the web system. Key features include GPS-based location validation and selfie verification for attendance authenticity. System testing using Blackbox and User Acceptance Test (UAT) methods showed that the application performed well, with a success rate of more than 95% and a very high level of user satisfaction. These results demonstrate that the developed system effectively enhances efficiency, accuracy, and transparency in the company’s attendance process.]]>
<![CDATA[Klasifikasi Penerimaan Peserta Didik Baru Berdasarkan Sistem Zonasi Menggunakan Algoritma K-Nearest Neighbors ]]>
<![CDATA[Syah Fiqri, Muhammad]]>;
<![CDATA[Andi Taufik]]>
<![CDATA[ Journal of Informatics, Electrical and Electronics Engineering Vol. 5 No. 1 (2025): September 2025 ]]>
Publisher : <![CDATA[Forum Kerjasama Pendidikan Tinggi (FKPT) ]]>
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DOI: 10.47065/jieee.v5i1.2595
<![CDATA[The implementation of the zoning system in student admission (PPDB) often raises challenges in determining eligibility based on domicile, requiring a data-driven approach to support the selection process. This study aims to classify new students of SMPN 16 Bogor for the 2025 academic year using the K-Nearest Neighbors (KNN) algorithm. The dataset consists of 1,153 student records with attributes including longitude, latitude, distance from home to school, and zoning labels. Preprocessing involved data cleaning, label encoding, and feature standardization before splitting the data into 75% training and 25% testing sets. The optimal parameter was found at K=18 with a minimum error rate of 0.1591. Experimental results showed an accuracy of 97% for training data and 84% for testing data, indicating that the model performs reasonably well despite signs of overfitting. This research contributes by demonstrating that spatial attributes can be effectively integrated into zoning-based classification and provides a foundation for developing more objective and adaptive decision support systems in the context of student admissions.]]>
<![CDATA[Perancangan Website E-Commerce shop.ruanginterio.com dengan Integrasi Payment Gateway Paypal ]]>
<![CDATA[Monoarfa, Fachrin]]>;
<![CDATA[Setiyani, Hari]]>
<![CDATA[ Journal of Informatics, Electrical and Electronics Engineering Vol. 5 No. 1 (2025): September 2025 ]]>
Publisher : <![CDATA[Forum Kerjasama Pendidikan Tinggi (FKPT) ]]>
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DOI: 10.47065/jieee.v5i1.2606
<![CDATA[Digital transformation drives companies to adopt online-based sales systems. PT Ruang Inovasi Teknologi (RIT), which previously relied on conventional sales methods, requires an integrated e-commerce system to increase efficiency, expand market reach, and provide secure transactions. This study aims to design and develop an e-commerce website integrated with the PayPal payment gateway, including system requirements analysis, UI/UX design, and Laravel-based implementation. The method involves field studies, interviews with stakeholders, and a Minimum Viable Product (MVP) development approach. The outcome is an e-commerce platform (shop.ruanginterio.com) that supports automatic transactions and digital financial reporting, provides user-friendly checkout, and enables global market expansion.]]>
<![CDATA[Sistem Penunjang Keputusan Pemilihan Aplikasi Streaming Terbaik dikalangan Remaja Menggunakan Metode SAW ]]>
<![CDATA[Farhanah, Elsa]]>;
<![CDATA[Agustine Prihatini, Virna]]>;
<![CDATA[Bisabakti, Harry]]>;
<![CDATA[Munawar, Achmad]]>;
<![CDATA[Zuraidah, Eva]]>
<![CDATA[ Journal of Informatics, Electrical and Electronics Engineering Vol. 5 No. 1 (2025): September 2025 ]]>
Publisher : <![CDATA[Forum Kerjasama Pendidikan Tinggi (FKPT) ]]>
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DOI: 10.47065/jieee.v5i1.2620
<![CDATA[The increasing number of movie streaming services such as Netflix, Disney+ Hotstar, and Viu provides a variety of choices for users, but it also causes confusion in choosing the platform that best suits their needs, especially among teenagers. This problem is reinforced by differences in preferences regarding various aspects such as subscription price, content quality, ease of use, access speed, and variety of shows. To address these challenges, this study proposes a solution in the form of a decision support system using the Simple Additive Weighting (SAW) method. This method is used to evaluate and rank alternative applications based on five main criteria. Data were obtained from 200 adolescent respondents through an online questionnaire, and then processed using the Simple Additive Weighting normalization and weighting technique. The results showed that Netflix was ranked first with the highest preference value (0.97), followed by Disney+ Hotstar (0.88) and Viu (0.79). These findings indicate that the Simple Additive Weighting method is effective in helping users choose the best streaming application objectively and measurably based on the preferences of today's teenagers.]]>
