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All Journal Jurnal Informatika dan Teknik Elektro Terapan CESS (Journal of Computer Engineering, System and Science) Informatics for Educators and Professional : Journal of Informatics Network Engineering Research Operation [NERO] KOPERTIP: Jurnal Ilmiah Manajemen Informatika dan Komputer METHODIKA: Jurnal Teknik Informatika dan Sistem Informasi Indonesian Journal of Applied Informatics Jurnal ICT : Information Communication & Technology Jurnal Sistem Informasi Kaputama (JSIK) JISKa (Jurnal Informatika Sunan Kalijaga) Jurnal Informatika dan Rekayasa Perangkat Lunak JSR : Jaringan Sistem Informasi Robotik JURSIMA (Jurnal Sistem Informasi dan Manajemen) JATI (Jurnal Mahasiswa Teknik Informatika) JIKA (Jurnal Informatika) MEANS (Media Informasi Analisa dan Sistem) Jurnal Teknik Informatika (JUTIF) Jurnal Mahasiswa Sistem Informasi (JMSI) International Journal of Social Science Jurnal Riset dan Aplikasi Mahasiswa Informatika (JRAMI) Jurnal Janitra Informatika dan Sistem Informasi Prosiding Seminar Nasional Sisfotek (Sistem Informasi dan Teknologi Informasi) INFORMATIKA Journal of Artificial Intelligence and Engineering Applications (JAIEA) Jurnal Mahasiswa Ilmu Komputer TAMIKA: Jurnal Tugas Akhir Manajemen Informatika & Komputerisasi Akuntansi Wawasan : Jurnal Ilmu Manajemen, Ekonomi dan Kewirausahaan Manajemen Kreatif Jurnal JURSIMA Jurnal Ekonomi Manajemen Akuntansi BULLET : Jurnal Multidisiplin Ilmu AMMA : Jurnal Pengabdian Masyarakat NERO (Networking Engineering Research Operation) Jurnal Informatika: Jurnal Pengembangan IT Jurnal Sistem Informasi dan Manajemen INTERNAL (Information System Journal) Intechno Journal : Information Technology Journal
Yudhistira Arie Wijaya
STMIK IKMI Cirebon
Agriculture, Biological Sciences & Forestry Humanities Automotive Engineering Chemistry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Health Professions Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mechanical Engineering Medicine & Pharmacology Nursing Public Health Social Sciences Other

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KLASIFIKASI PENYAKIT DAUN PADI MENGGUNAKAN TRANSFER LEARNING DENGAN ANALISIS PENGARUH VARIASI DIMENSI CITRA PADA KINERJA MODEL Akhmad Taukhid; Martanto; Yudhistira Arie Wijaya; Heliyanti Susana; Nana Suarna
METHODIKA: Jurnal Teknik Informatika dan Sistem Informasi Vol. 12 No. 1 (2026): Volume 12 Nomor 1 Tahun 2026
Publisher : Universitas Methodist Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46880/mtk.v12i1.4940

Abstract

Penelitian ini berfokus pada deteksi dini penyakit daun padi untuk meningkatkan produktivitas pertanian dan mengurangi kesalahan diagnosis yang sering terjadi pada identifikasi manual. Meskipun berbagai penelitian telah menerapkan deep learning untuk klasifikasi penyakit tanaman, pengaruh resolusi citra terhadap kinerja model klasifikasi penyakit daun padi, khususnya pada skenario data terbatas, masih jarang dikaji secara sistematis. Penelitian ini bertujuan menganalisis kinerja model klasifikasi penyakit daun padi berbasis transfer learning dengan arsitektur VGG16 pada citra beresolusi 224×224 piksel, sekaligus menilai efisiensi proses komputasi pelatihan dan pengujian yang dilakukan. Data yang digunakan berupa 320 citra daun padi dari dataset publik “Daun Padi Sultra (Sulawesi Tenggara)” di Kaggle yang komprehensif menjadi data latih, validasi, dan uji dengan perbandingan 60:20:20. Tahapan penelitian utama meliputi eksplorasi karakteristik dan distribusi data, pra-pemrosesan citra (pengubahan ukuran ke 224×224, normalisasi, dan augmentasi terbatas), serta pembangunan model transfer learning dengan VGG16 sebagai ekstraktor fitur yang membekukan dan kepala klasifikasi kustom. Model dibor menggunakan optimizer Adam dengan mekanisme EarlyStopping dan ModelCheckpoint, kemudian dievaluasi menggunakan akurasi, presisi, recall, F1-score, dan konfusi matriks. Hasil pengujian menunjukkan bahwa model mencapai akurasi uji sebesar 98,44% dengan loss 0,1815, serta nilai rata-rata makro dan rata-rata tertimbang untuk presisi, recall, dan F1-score yang mendekati 0,98 dengan hanya satu kesalahan klasifikasi pada data uji. Proses pelatihan dan penyelesaian dapat diselesaikan dengan beban komputasi yang masih moderat pada lingkungan GPU Google Colab, sehingga konfigurasi VGG16 dengan resolusi 224×224 piksel berpotensi menjadi baseline yang efektif dan efisien untuk klasifikasi penyakit daun padi pada skenario data terbatas.
PERBANDINGAN MODEL LSTM DAN GRU UNTUK PREDIKSI HARGA SAHAM TELEKOMUNIKASI INDONESIA Ahmad Jamalul Noor; Dian Ade Kurnia; Yudhistira Arie Wijaya; Heliyanti Susana
Jurnal Mahasiswa Ilmu Komputer Vol. 7 No. 1 (2026): Jurnal Mahasiswa Ilmu Komputer March 2026
Publisher : Universitas Muhammadiyah Metro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24127/ilmukomputer.v7i1.10651

Abstract

Penelitian ini bertujuan untuk mengevaluasi dan membandingkan performa model Long Short-Term Memory (LSTM) dan Gated Recurrent Unit (GRU) dalam memprediksi harga saham harian pada sektor telekomunikasi Indonesia, sebuah sektor yang memiliki karakteristik volatilitas fluktuatif dan dipengaruhi oleh dinamika pasar jangka pendek. Dua emiten yang dianalisis adalah GHON dan EXCL dengan rentang data dua tahun yang diambil dari platform Investing.com. Proses penelitian mencakup tahapan preprocessing, normalisasi menggunakan MinMaxScaler, pembentukan sliding window sepanjang 30 hari, serta pembagian data secara kronologis menjadi data latih, validasi, dan uji. Optimasi hyperparameter dilakukan menggunakan KerasTuner dengan pendekatan Random Search untuk memperoleh konfigurasi terbaik bagi masing-masing model. Evaluasi performa menggunakan tiga metrik utama yakni Root Mean Square Error (RMSE), Mean Absolute Error (MAE), dan Mean Absolute Percentage Error (MAPE). Hasil eksperimen menunjukkan bahwa GRU memberikan performa yang lebih unggul pada saham EXCL yang memiliki volatilitas tinggi, ditunjukkan oleh nilai RMSE, MAE, dan MAPE yang lebih rendah dibandingkan LSTM. Sebaliknya, pada saham GHON yang lebih stabil, kedua model menghasilkan performa yang relatif sebanding. Temuan ini menegaskan bahwa efektivitas model sangat dipengaruhi oleh karakteristik data, di mana GRU lebih adaptif pada pola harga yang dinamis, sedangkan LSTM tetap kompetitif pada pola yang lebih konsisten. Secara keseluruhan, GRU dapat direkomendasikan sebagai model yang lebih efisien dan akurat untuk prediksi harga saham pada lingkungan pasar yang berfluktuasi tinggi.
Algoritma LightGBM dengan SMOTE & ADASYN untuk Prediksi Risiko Serangan Jantung Sugianto, Nanda Putri; Purnamasari, Ade Irma; Pratama, Denni; Marta, Puji Pramudya; Wijaya, Yudhistira Arie
JSR : Jaringan Sistem Informasi Robotik Vol 10, No 1 (2026): JSR : Jaringan Sistem Informasi Robotik
Publisher : AMIK Mitra Gama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58486/jsr.v10i1.633

Abstract

Ketidakseimbangan data merupakan tantangan utama dalam pemodelan prediksi medis, termasuk prediksi serangan jantung, karena jumlah kasus positif jauh lebih sedikit dibandingkan kasus negatif sehingga menurunkan kemampuan model dalam mendeteksi pasien berisiko tinggi. Penelitian ini bertujuan untuk membandingkan efektivitas dua teknik oversampling, yaitu Synthetic Minority Oversampling Technique (SMOTE) dan Adaptive Synthetic Sampling (ADASYN), dalam meningkatkan performa algoritma Light Gradient Boosting Machine (LightGBM) untuk prediksi risiko serangan jantung. Dataset berjumlah 1.319 sampel dengan sembilan fitur klinis dan dianalisis melalui tahapan pra-pemrosesan, normalisasi, penanganan class imbalance, pembangunan model, serta evaluasi menggunakan Accuracy, Precision, Recall, F1-Score, dan AUC-ROC. Hasil menunjukkan bahwa model baseline memiliki akurasi tinggi namun sensitivitas terhadap kelas positif masih rendah. Setelah diterapkan oversampling, model mengalami peningkatan signifikan. LightGBM-SMOTE memperoleh F1-Score terbesar (0.9876) dan AUC-ROC 0.9853, sedangkan LightGBM-ADASYN mencapai F1-Score 0.9855 dan AUC-ROC 0.9861. Temuan ini menunjukkan bahwa SMOTE memberikan peningkatan performa yang lebih stabil dalam mendeteksi kelas minoritas. Dengan demikian, teknik oversampling khususnya SMOTE terbukti efektif untuk meningkatkan akurasi dan sensitivitas model prediksi serangan jantung.
Peningkatan Kompetensi Siswa SMK Melalui Pelatihan Junior Web Developer Dalam Pengembangan Website Ade Irma Purnamasari; Yudhistira Arie Wijaya; Aditiya Arif Firmansyah; Intan Wangi Nur Qibti
AMMA : Jurnal Pengabdian Masyarakat Vol. 3 No. 2 : Maret (2024): AMMA : Jurnal Pengabdian Masyarakat
Publisher : CV. Multi Kreasi Media

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Abstract

This community service program aims to enhance the competencies of vocational high school (SMK) students in web development through a Junior Web Developer training program. The activities were carried out at several SMKs in Cirebon Regency and Cirebon City as an effort to bridge the gap between school curricula and industry needs. The implementation methods included preparation and planning, training execution, monitoring and evaluation, as well as dissemination of results. The outcomes of this program showed a significant improvement in students' understanding and skills in web development technologies, particularly in the use of HTML, CSS, JavaScript, and modern frameworks. In addition, participating teachers also benefited from workshops designed to enhance their ability to teach industry-based materials. This program successfully produced several outputs such as learning modules, student web projects, and collaborations with industry partners to open up job opportunities for graduates. With this program, it is expected that vocational students will have better competencies to face the workforce and the digital industry. The sustainability of this program can be expanded by increasing industrial partnerships and broadening the scope of training participants.
Peningkatan Kompetensi Digital Lulusan SMK Kabupaten Cirebon Melalui Pelatihan Junior Network Administrator Yudhistira Arie Wijaya; Edi Tohidi; Alwan Azhar; Andi Ardiansyah
AMMA : Jurnal Pengabdian Masyarakat Vol. 3 No. 4 : Mei (2024): AMMA : Jurnal Pengabdian Masyarakat
Publisher : CV. Multi Kreasi Media

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Abstract

Junior Network Administrator training for SMK graduates in Cirebon Regency aims to improve skills and competencies in the field of computer networks. The program is designed as a solution to employment challenges by providing competency-based training that refers to industry standards. Training methods include theory, hands-on practice, and case studies relevant to the needs of the world of work. The program evaluation showed an increase in participants' understanding and skills in managing computer networks, configuring network devices, and basic troubleshooting. In addition, participants obtained certifications that can increase their competitiveness in the job market. The training results showed that most of the participants were successful in obtaining jobs or internships in technology companies and related institutions. The success of this program is supported by cooperation between educational institutions, local governments, and the industrial sector. Challenges faced include limited facilities and participants' readiness to deal with rapid technological developments. To improve the effectiveness of the program, it is recommended to improve training facilities, update the curriculum in line with industry developments, and collaborate more closely with the private sector.
Digitalisasi Administrasi Desa Melalui Pelatihan Pengelolaan Data Berbasis Sistem Informasi Willy Prihartono; Yudhistira Arie Wijaya; Arya Hadi Wicaksana; Astri Amelia
AMMA : Jurnal Pengabdian Masyarakat Vol. 2 No. 4 (2023): AMMA : Jurnal Pengabdian Masyarakat
Publisher : CV. Multi Kreasi Media

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Abstract

Digitalization of village administration is a solution to improve the efficiency and transparency of data management at the village level. This transformation allows village governments to manage information more systematically, reduce administrative errors, and improve services to the community. This research focuses on training on data management based on information systems implemented in villages, to provide village officials with an understanding of the importance of digitization in governance. The method used in this training includes a participatory approach with a combination of theory and hands-on practice in the use of information systems. The results of the training showed that the majority of participants experienced improved understanding and skills in operating digital systems for village administration. The implementation of digitalization also contributed to improving transparency, data accuracy, and accelerating the process of administrative services to village communities. The challenges faced include limited technological infrastructure, resistance to change, and the need for continuous assistance. Therefore, policies that support the development of human resource capacity and investment in information technology infrastructure in villages are needed. Thus, the digitization of village administration can run optimally and sustainably to support technology-based village development.
Digitalisasi Administrasi Desa Melalui Pelatihan Pengelolaan Data Berbasis Sistem Informasi Yudhistira Arie Wijaya; Tati Suprapti; Athaullah Abrar Bayan; Beby Maryam
AMMA : Jurnal Pengabdian Masyarakat Vol. 2 No. 4 (2023): AMMA : Jurnal Pengabdian Masyarakat
Publisher : CV. Multi Kreasi Media

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Abstract

The rapid development of information technology has encouraged educational institutions and village government institutions to improve the efficiency of administrative services, one of which is in terms of recording attendance. This research aims to develop a QR Code-based attendance system implemented for schools and village institutions as a solution to the manual attendance system that is still vulnerable to fraud and inefficiency. The system development method used is the waterfall method which includes the stages of needs analysis, system design, implementation, testing, and maintenance. This system is designed using PHP programming language and MySQL database, and integrated with QR Code technology that allows users to scan through mobile devices. The test results show that this system is able to record attendance in real-time, generate reports automatically, and improve the accuracy and efficiency of the attendance process. Users also responded positively to the system's simple and easy-to-use interface. With this system, educational institutions and villages can manage attendance data more effectively and transparently. In conclusion, this QR Code-based attendance system is a relevant and applicable innovation in supporting administrative digitization at the local level. This research is expected to be a reference for the development of similar systems in other environments.
Optimalisasi Infrastruktur Jaringan Internet Desa untuk Mendukung Digitalisasi UMKM dan Pendidikan Willy Prihartono; Yudhistira Arie Wijaya; Aliya Anisa Rahma; Irma Agustina
AMMA : Jurnal Pengabdian Masyarakat Vol. 1 No. 04 (2022): AMMA : Jurnal Pengabdian Masyarakat
Publisher : CV. Multi Kreasi Media

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Abstract

Digital transformation is a crucial element in improving the quality of education and developing Micro, Small and Medium Enterprises (MSMEs), especially in rural areas. However, limited internet network infrastructure is a major challenge that must be overcome. This research aims to identify problems and propose strategies for optimizing village internet networks to support the digitalization of the education sector and MSMEs. The method used was direct observation in Ketapanrame Village, Trawas District, Mojokerto Regency, as well as a literature study approach to network technology solutions. The results showed that although the availability of internet networks already exists, the quality and equity of access is still low. Therefore, it is necessary to strengthen the infrastructure through increasing bandwidth, placing strategic access points, and utilizing technologies such as wireless mesh networks (WMN). In addition, community empowerment through digital literacy training is also very important to ensure optimal utilization of the available infrastructure. The implementation of this strategy is expected to encourage the improvement of the quality of digital-based learning and expand the MSME market through online platforms. Optimizing village internet networks is not only about technical aspects, but also includes strengthening human resource capacity and local government policy support. Thus, the digitization of education and MSMEs can be an important pillar in the economic and social development of villages.
Pelatihan Penggunaan Smartphone dan Aplikasi Komunikasi Digital untuk Peningkatan Kompetensi Lansia Yudhistira Arie Wijaya; Riri Narasati; Mifta Almaripat; Mita Amelia
AMMA : Jurnal Pengabdian Masyarakat Vol. 1 No. 04 (2022): AMMA : Jurnal Pengabdian Masyarakat
Publisher : CV. Multi Kreasi Media

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Abstract

Advances in digital technology have had a significant impact in various aspects of life, including for the elderly. However, limited digital knowledge and skills cause many elderly people to not be able to utilize technology optimally. This community service activity aims to improve the digital competence of the elderly through training on the use of smartphones and daily communication applications such as WhatsApp and Google Meet. The methods used include a participatory approach, direct assistance, and repeated practice of using digital applications in a friendly and fun atmosphere. The activity was carried out at Posyandu Lansia Kelurahan Jatimakmur, Bekasi, involving 30 elderly participants aged 60-75 years. The results of the activity showed a significant improvement in the participants' ability to use smartphones, access communication applications, and understand digital communication ethics. Evaluation was conducted through pre-test and post-test, as well as direct observation during the training. The majority of participants stated that they felt more confident and motivated to continue learning to use technology. Supporting factors for the success of this activity included the personal approach, the patience of the facilitators, and the use of visual and practical methods. Meanwhile, the challenges faced included participants' physical limitations, such as visual and hearing impairments, and memory limitations. This activity makes a real contribution to the digital empowerment efforts of the elderly, and opens up opportunities for the development of similar programs in other regions. Hopefully, this kind of training can be the first step towards comprehensive digital inclusion for all levels of society.
ADAPTIVE CLASS WEIGHTING DAN AUGMENTATION UNTUK KLASIFIKASI BATIK KERATON Witriyani Witriyani; Dian Ade Kurnia; Yudhistira Arie Wijaya; Mulyawan Mulyawan; Irfan Ali
Informatika: Jurnal Teknik Informatika dan Multimedia Vol. 6 No. 1 (2026): MEI : JURNAL INFORMATIKA DAN MULTIMEDIA
Publisher : LPPM Politeknik Pratama Kendal

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/informatika.v6i1.1516

Abstract

This study aims to improve the performance of Batik Keraton motif classification on an imbalanced dataset through the integration of adaptive class weighting and data augmentation within a transfer learning framework. The dataset consists of 1,799 images across four classes (Kawung, Mega Mendung, Parang, Truntum), preprocessed to 224×224 pixels and split stratifiedly into training, validation, and test sets (80/10/10). Three transfer learning architectures—ResNet50V2, VGG16, and EfficientNetB0—were evaluated with adaptive class weighting and geometric augmentation to enhance minority-class representation. The results indicate that ResNet50V2 with pretrained weights achieved the best performance, reaching a test accuracy of 92.78%, macro precision of 93.13%, macro recall of 92.79%, and a macro F1-score of 92.83%. Adaptive class weighting improved sensitivity toward minority classes, while augmentation contributed to model stability and generalization. These findings demonstrate that combining adaptive weighting and augmentation effectively enhances Batik Keraton motif classification under imbalanced data conditions.  
Co-Authors Abubakar Sidik Ade Irma Purnama Sari Ade Irma Purnamasari Ade Irma Purnamasari Adi Hermawan Aditiya Arif Firmansyah Adiyanto, Alfian Adjie Setyadj, Mochammad Agni, Vega Putra Dwi Ahmad Faqih Ahmad Jamalul Noor Ahmad Rifai Ikhsanudin AKBAR, MUHAMAD DENI Akhmad Taukhid Alfirda Sofyan, Zahra Aliya Anisa Rahma Alwan Azhar Alya Fadia An-naziz Safaat, Wafik Andi Ardiansyah Andriyani, Wini Anggara, Doni Anjar Permadi Aprianto, Wili Arya Hadi Wicaksana ASEP SAEFUDDIN Asmana, Asmana Astri Amelia Athaullah Abrar Bayan Beby Maryam Cintia Putri Prasetia Dadang Sudrajat Darma Irawan, Bobi Darussalam, Luthvi Nurfauzi Denni Pratama Denni Pratama Dermawan, Hibrizi Dzaky Dian Ade Kurnia Dian Ade Kurnia Dodi Solihudin Edi Tohidi Edi Wahyudin Falih, Alfi Rizqi Falih FANDI ACHMAD Fauzan, Muhamad Nur Fianita Rusadi Fianita Rusadi Firmansyach, Wildan Attariq Hajijin Amri Hamonangan, Ryan Hayati, Umi Hegarmanah Muhabatin Heliyanti Susana Herman Hermawan, Adi Hidayat, Zaids Syarif Ibnu Ubaedila Ikhwan Fahruddin, Yusuf Inawati, Windi Intan Wangi Nur Qibti Irfan Ali Irfan Ali Irma Agustina Jaelani Sidik Jayawarsa, A.A. Ketut Jurnal Konsera Khoeri, Yajid Komala, Wulan Kurnia, Dian Ade Kurniawan , Rudi Kusmiyaty, Agesty Laela Laela Leli Oktaviani Lukmanul Hakim Manzis, Zian Marta, Puji Pramudya Martanto Martanto . Martanto Martanto Masjunedi, Masjunedi Maulana, Tedy Mifta Almaripat Mita Amelia Moh Nurdayat Dayat MUHAMAD DENI AKBAR Muhamad Nur Fauzan Muhammad Aditya Rabbani Adit Mulyawan Nabila, Aynun Nana Suarna Nana Suarna Narasati, Riri Narasati Nashir, Mukhtar Nining Rahaningsih Nisa Dieanwati Nuris Nisa Dienwati Nuris Nur Amalia, Yustika Nurazijah, Wulan Nurdiawa, Odi Nurholipah, Titin Nurrahman, Rizki Odi Nurdiawa Odi Nurdiawan Pebriyanto, Ramdhan Pratama, Denni Puji Pramudya Marta Purnamasari, Ade Irma Restu Normalasari Rini Astuti Rini Astuti Rini Astuti Rio Febriyan Rizal Rizal Roni Saputra, Roni Rubangiya Rubangiya Rudi Kurniawan Rudi Kurniawan Rudi Kurniawan Saeful Anwar Saeful Anwar, Saeful Satria Turangga Septian Nugraha, Titan Septiani Gumilar, Tia Shifa Dwi Oktaviani Siti Sopiyah Suarna, Nana Sugianto, Nanda Putri Sulaeman, Muhammad Suteja Syach Putra, Yanuar Tati Suprapti Taufik Hidayat Tegar Lazuardi, Muhammad Thomas Agam Tiana Dewi Tri Anelia Trian Nurmansyah Triswanto, Triswanto Tuti Hartati Tuti Hartati Tuti Hartati Wahyudi Wahyudi Wartumi Wartumi Willy Prihartono Winayah, Winayah Windy Astuti Witriyani Witriyani Yudis Firmansyah Yufita, Ayura yulani, Yulani - Yulia, Yuli