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All Journal JURIKOM (Jurnal Riset Komputer) Informatics and Digital Expert (INDEX) Community Service Journal : Jurnal Pengabdian Masyarakat Mardira
Rosena Shintabella
Politeknik Negeri Indramayu
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Engineering

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Optimized Fault Prediction in Power Distribution Transformers Using Grey Wolf Optimizer-Based SVM and MLP Models Rosena Shintabella; Silaban, Meyer Mega Eklesia; Basir, Muhammad Ichsan
JURNAL RISET KOMPUTER (JURIKOM) Vol. 13 No. 1 (2026): Februari 2026
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/jurikom.v13i1.9435

Abstract

Distribution transformers are critical components of power distribution systems, and their reliability directly affects the continuity and quality of electrical energy supply. However, early-stage transformer faults are difficult to detect because their operational characteristics often closely resemble normal operating conditions, which can lead to undetected degradation and unexpected failures. This study aims to improve the accuracy and robustness of fault prediction in distribution transformers by proposing a hybrid approach that integrates the Grey Wolf Optimizer (GWO) with Support Vector Machine (SVM) and Multilayer Perceptron (MLP) models. The main contribution of this research is a direct and systematic performance comparison between baseline machine learning models and their GWO-optimized counterparts, highlighting the effectiveness of metaheuristic optimization in enhancing classification performance. GWO is employed to optimize key model parameters, enabling improved convergence behavior, higher classification accuracy, and better generalization capability. The proposed models are evaluated under four transformer operating conditions, namely Light Load Imbalance, Light Overload, Normal, and Normal High Temperature, which represent practical scenarios in power distribution networks. Model performance is assessed using standard classification metrics, including Accuracy, Precision, Recall, and F1-Score. Experimental results show that the baseline SVM achieved an accuracy of 68%, while the baseline MLP reached 87% accuracy. After GWO-based optimization, the SVM–GWO model demonstrated a significant improvement, achieving 92% accuracy, whereas the MLP–GWO model produced the best overall performance, achieving 93% accuracy, precision, recall, and F1-score. These findings confirm that GWO-based optimization substantially enhances transformer fault prediction performance and demonstrates the strong potential of the proposed hybrid models for real-time monitoring and preventive maintenance of power distribution transformers.
Sinergi Transformasi Digital dan Strategi Green Tourism dalam Mendukung Keberlanjutan Bisnis (Studi Kasus: PT Ancol Taman Impian) Sahid Triambudhi; Rosena Shintabella; Meyer Mega Eklesia Silaban
Informatics and Digital Expert (INDEX) Vol. 8 No. 1 (2026): INDEX, Mei 2026
Publisher : LPPM Universitas Perjuangan Tasikmalaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36423/index.v8i1.2661

Abstract

Industri pariwisata menghadapi tekanan ganda pasca-pandemi, yaitu keharusan memulihkan kinerja ekonomi sekaligus memenuhi standar keberlanjutan lingkungan (Environmental, Social, and Governance - ESG). PT Pembangunan Jaya Ancol Tbk menghadapi tantangan dalam mengelola lonjakan pengunjung yang berpotensi meningkatkan jejak karbon dan inefisiensi operasional jika tetap menggunakan sistem manajemen konvensional. Penelitian ini bertujuan untuk menganalisis peran transformasi digital sistem informasi yang mencakup online ticketing website ancol.com, ancol mobile apps (android dan IOS), self-services kiosk, point of sales (untuk kasir dan petugas pintu gerbang), online travel agent (OTA), third-party apps (customer engagement, customer relations management, social media analytics, dll sebagai solusi strategis dalam mendukung keberlanjutan destinasi wisata. Penelitian menggunakan metode deskriptif kuantitatif dengan menganalisis data sekunder dari Laporan Keberlanjutan dan Laporan Tahunan Ancol periode 2022-2024. Fokus analisis mencakup korelasi antara implementasi digitalisasi (sistem e-ticketing, aplikasi pengunjung, dan pemantauan utilitas) dengan indikator efisiensi material, intensitas energi, dan pertumbuhan pendapatan usaha. Hasil penelitian menunjukkan bahwa transformasi digital berkontribusi signifikan terhadap efisiensi sumber daya. Peralihan ke ekosistem digital penuh berbasis pengalaman pengguna (website, mobile apps, self-service kiosk) dan pelayanan oleh tim ancol (sistem POS) pada akhirnya berhasil menurunkan penggunaan material kertas (paperless) secara signifikan di pintu gerbang utama. Secara operasional, sistem informasi mendukung pemantauan energi yang presisi, menghasilkan rasio intensitas energi yang tetap efisien meskipun jumlah kunjungan wisatawan meningkat signifikan dari tahun 2022-2024. Dari aspek ekonomi, digitalisasi memperluas kanal pendapatan dan mempercepat pemulihan finansial perusahaan. Disimpulkan bahwa integrasi teknologi informasi bukan hanya alat pendukung operasional, melainkan fondasi utama dalam mewujudkan pariwisata berkelanjutan.
Evaluasi Efektivitas Fitur Layanan Candi Borobudur Berdasarkan Analisis Sentimen Ulasan Google Maps Menggunakan Teknik Naive Bayes Meyer Mega Eklesia Silaban; Rosena Shintabella; Sahid Triambudhi
Informatics and Digital Expert (INDEX) Vol. 8 No. 1 (2026): INDEX, Mei 2026
Publisher : LPPM Universitas Perjuangan Tasikmalaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36423/index.v8i1.2747

Abstract

Perkembangan pariwisata digital telah mentransformasi interaksi wisatawan dengan destinasi wisata, menjadikan platform ulasan daring seperti Google Maps sebagai sumber informasi penting sekaligus aset data yang bernilai untuk evaluasi kualitas layanan. Penelitian ini bertujuan untuk menganalisis persepsi wisatawan terhadap efektivitas fitur layanan Candi Borobudur berdasarkan sentimen ulasan Google Maps menggunakan algoritma Naive Bayes. Data penelitian berupa 1000 ulasan pengguna Google Maps yang dikumpulkan melalui observasi digital dan proses ekspor data ulasan pada periode tertentu. Tahapan penelitian meliputi pengumpulan data, preprocessing teks menggunakan Orange Data Mining, pelabelan sentimen otomatis berbasis lexicon multibahasa, ekstraksi fitur TF-IDF, serta klasifikasi sentimen menggunakan algoritma Naive Bayes ke dalam tiga kelas, yaitu positif, netral, dan negatif. Evaluasi model dilakukan menggunakan metode 5-fold cross validation. Hasil penelitian menunjukkan bahwa model Naive Bayes memperoleh performa yang baik dengan nilai accuracy sebesar 0,894, precision sebesar 0,896, recall sebesar 0,894, F1-score sebesar 0,894, dan Area Under Curve (AUC) sebesar 0,983. Hasil analisis menunjukkan bahwa sebagian besar ulasan pengunjung cenderung memiliki sentimen positif, khususnya terhadap aspek keindahan wisata, fasilitas, dan pengalaman berkunjung, meskipun masih ditemukan sentimen negatif terkait kepadatan pengunjung, harga tiket, dan pengelolaan fasilitas tertentu. Penelitian ini diharapkan dapat menjadi sumber evaluasi berbasis data bagi pengelola wisata dalam meningkatkan kualitas layanan dan pengalaman pengunjung secara berkelanjutan.
COUNSELING OF THE PILLARS OF DEMOCRACY IN INDONESIA IN THE FRAMEWORK OF THE PROJECT TO STRENGTHEN THE PROFILE OF PANCASILA STUDENTS (P5) PHASE F AT SMAN 1 KADIPATEN Enang Rusnandi; Rosena Shintabella; Fikri Emsa Silmi; Fadli Emsa Zamani
Community Service Journal : Jurnal Pengabdian Masyarakat Mardira Vol. 1 No. 1 (2025): Community Service in Indonesia
Publisher : Politeknik Mardira Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.71266/mcsj.v1i1.34

Abstract

The pillars of democracy are an important foundation in the life of the nation and state that must be understood by the younger generation, especially high school students. This service activity was carried out in the form of counseling on the pillars of Indonesian democracy to students of SMAN 1 Kadipaten, as part of the implementation of the Pancasila Student Profile Strengthening Project (P5) in Phase F. The main purpose of this activity is to foster students' critical awareness of the importance of democratic values in daily life and instill an active attitude as a responsible citizen. The methods used in this activity include material presentations, group discussions, and participant reflections. The results of the activity showed an increase in students' understanding of democratic principles, as well as the emergence of student initiatives in conveying aspirations and opinions in an orderly manner. This activity is a concrete step in instilling contextual and applicable national values in the educational environment.
Enhancing Graduate Competencies toImprove Industry Employability throughPre-Internship Training and Industrial Internship Programs Sahid Triambudhi; Rosena Shintabella; Meyer Mega Eklesia Silaban
Community Service Journal : Jurnal Pengabdian Masyarakat Mardira Vol. 1 No. 2 (2025): Community Service in Indonesia
Publisher : Politeknik Mardira Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.71266/csj.v1i2.61

Abstract

This community service project aims to strengthen student competencies through the implementation of both pre-internship briefing sessions and industrial internship placement. The program was carried out by the Department of Informatics Engineering at the Indramayu State Polytechnic (Polindra) as part of its commitment to improving students’ job readiness and aligning vocational education with industrial demands. The activity involved a structured workflow including industry needs identification, coordination with the Industrial Internship Program Team (PMI), preparation of learning materials, arrangement of seminar logistics, on-site briefing seminars, and post-program evaluations. A total of 182 students were successfully placed in various partner industries for internship programs following the briefing seminar. The results show significant improvements in students’ soft and technical skills, confidence levels, workplace adaptability, and understanding of professional ethics. Partner industries also provided positive feedback regarding student performance and contribution. The program demonstrated the essential role of vocational institutions in bridging academic knowledge and industrial application, while offering measurable benefits to both students and industry partners.
Co-Authors Basir, Muhammad Ichsan Enang Rusnandi Fadli Emsa Zamani Fikri Emsa Silmi Meyer Mega Eklesia Silaban Sahid Triambudhi Silaban, Meyer Mega Eklesia