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All Journal IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Jurnal Sains dan Teknologi Techno.Com: Jurnal Teknologi Informasi EXPERT: Jurnal Manajemen Sistem Informasi dan Teknologi Telematika : Jurnal Informatika dan Teknologi Informasi Jurnas Nasional Teknologi dan Sistem Informasi Jurnal Ilmiah KOMPUTASI Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) International Journal of Artificial Intelligence Research RABIT: Jurnal Teknologi dan Sistem Informasi Univrab JOURNAL OF APPLIED INFORMATICS AND COMPUTING SELAPARANG: Jurnal Pengabdian Masyarakat Berkemajuan JPPM (Jurnal Pengabdian dan Pemberdayaan Masyarakat) EDUMATIC: Jurnal Pendidikan Informatika Jurnal SITECH : Sistem Informasi dan Teknologi Journal of Information Systems and Informatics Jurnal Aisyah : Jurnal Ilmu Kesehatan Abdimasku : Jurnal Pengabdian Masyarakat International Journal of Marine Engineering Innovation and Research Idealis : Indonesia Journal Information System Jurnal Altifani Penelitian dan Pengabdian kepada Masyarakat Komunita: Jurnal Pengabdian dan Pemberdayaan Masyarakat Jurnal Pengabdian Masyarakat Inovasi Indonesia
Soni Adiyono
Universitas Muria Kudus
Religion Agriculture, Biological Sciences & Forestry Humanities Automotive Engineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Mechanical Engineering Medicine & Pharmacology Nursing Physics Public Health Social Sciences Transportation Veterinary Other

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Implementasi Sistem Informasi Usulan Jabatan Fungsional ASN untuk Mendukung Layanan Kepegawaian di BKPSDM Kudus: Implementation of ASN Functional Position Proposal Information System to Support BKPSDM Kudus Personnel Services Sholichatunnita Nita; Soni Adiyono
JPPM (Jurnal Pengabdian dan Pemberdayaan Masyarakat) VOL. 10 NOMOR 2 JULI 2026 JPPM (Jurnal Pengabdian dan Pemberdayaan Masyarakat)
Publisher : Universitas Muhammadiyah Purwokerto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30595/jppm.v10i2.31008

Abstract

Proses pengusulan jabatan fungsional Aparatur Sipil Negara (ASN) di Badan Kepegawaian dan Pengembangan Sumber Daya Manusia (BKPSDM) Kabupaten Kudus sebelumnya masih dilakukan secara manual sehingga menyebabkan proses administrasi kurang efisien, penyimpanan dokumen belum terintegrasi, serta pemantauan status usulan oleh pemohon menjadi terbatas. Mitra dalam kegiatan pengabdian kepada masyarakat ini adalah BKPSDM Kabupaten Kudus sebagai instansi yang mengelola pelayanan administrasi kepegawaian ASN. Kegiatan ini bertujuan mengembangkan dan mengimplementasikan Sistem Informasi Usulan Jabatan Fungsional ASN berbasis web untuk meningkatkan efektivitas, efisiensi, dan transparansi pelayanan kepegawaian. Metode yang digunakan adalah model Waterfall yang meliputi analisis kebutuhan, perancangan sistem, implementasi, pengujian menggunakan Black-Box Testing, serta pelatihan dan pendampingan kepada pengguna. Sistem dikembangkan menggunakan framework PHP Laravel dengan basis data MySQL. Hasil implementasi menunjukkan bahwa sistem mampu mendukung proses pengajuan usulan, verifikasi berkas, penyimpanan dokumen digital, pelacakan status usulan secara real-time, serta penyusunan laporan secara terintegrasi. Berdasarkan hasil observasi selama implementasi, waktu pemrosesan usulan berkurang dari sekitar 5–9 hari menjadi 2,5–4 hari. Hasil pengujian Black-Box menunjukkan bahwa seluruh fungsi utama sistem berjalan sesuai dengan kebutuhan pengguna. Hasil pengabdian ini menunjukkan bahwa penerapan sistem informasi berbasis web mampu meningkatkan efisiensi proses administrasi, akurasi pengelolaan data, dan transparansi pelayanan kepegawaian serta berpotensi menjadi model pengembangan layanan digital pada instansi pemerintah lainnya.
Comparative Analysis of Machine Learning Algorithms with SMOTE for Imbalanced Sentiment Classification of IndiHome on Platform X Rizky Adisaputra; Muhammad Arifin; Soni Adiyono
Journal of Applied Informatics and Computing Vol. 10 No. 4 (2026): August 2026
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v10i4.13271

Abstract

Sentiment analysis of IndiHome users on social media X faces a severe class imbalance, with negative tweets dominating 88.26% of the dataset. This study compares four machine learning algorithms, Support Vector Machine (SVM), Naive Bayes, Decision Tree, and Random Forest, for sentiment classification using SMOTE to address the imbalance. Initially, 20,001 Indonesian tweets were scraped using Tweet Harvest with the keyword "indihome". After duplicate removal and preprocessing, 7,199 tweets were retained. Each tweet was manually annotated into positive, negative, and neutral categories. TF-IDF was applied for feature extraction, and Stratified 5-Fold Cross Validation was used for evaluation. Algorithms were tested under two conditions: without and with SMOTE. Before SMOTE, SVM achieved the highest accuracy (94.55%) and F1-score (94.05%). After SMOTE, Random Forest outperformed others with 94.14% accuracy and 93.83% F1-score, as the only algorithm showing consistent improvement across all metrics, including balanced accuracy and MCC. Although Wilcoxon tests showed no statistically significant differences between algorithms, Random Forest demonstrated the most stable and consistent performance. These findings confirm that Random Forest with SMOTE is the most effective strategy for imbalanced sentiment classification in this context.
Bridging the Digital Gap: How Soft Skills, Supportive Environments, and Media Usage Drive Teacher Competence in 21st-Century Classrooms Eko Darmanto; Soni Adiyono
JST (Jurnal Sains dan Teknologi) Vol. 14 No. 3 (2025): October
Publisher : Universitas Pendidikan Ganesha

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23887/jst-undiksha.v14i3.103062

Abstract

The rapid development of digital technology in the era of Education 4.0 requires teachers to possess strong digital competencies. However, many teachers continue to rely on conventional instructional approaches, resulting in a widening gap between pedagogical capabilities and the demands of digitalized learning. This study aims to analyze, evaluate, and interpret the simultaneous effects of soft skills, environmental support, and digital media utilization on teachers’ digital competence. This research employs a quantitative approach with an associative research design. The study involved 123 teachers selected through purposive sampling as the research sample. Data were collected using standardized questionnaires that had been validated through validity and reliability testing. Data analysis was conducted using Structural Equation Modeling (SEM) to examine both direct and indirect relationships among the variables. The findings indicate that digital media utilization has the strongest influence on enhancing teachers’ digital competence, followed by environmental support, which serves as a key enabling factor. Soft skills do not show a significant direct effect; however, they contribute indirectly when combined with strong environmental support and effective use of digital media. The study concludes that strengthening teachers’ digital competence requires synergy between habitual technology use, institutional support, and personal capacity development. The implications of this study highlight the importance of practice-based training strategies, strengthening digital infrastructure, and fostering a collaborative school culture to build a learning ecosystem that is adaptive to digital transformation.
SENTIMEN ANALISIS MOBILE BANKING MENGGUNAKAN ALGORITMA NAÏVE BAYES DAN SUPPORT VECTOR MACHINE PADA GOOGLE PLAY STORE Dewi Masitoh; R. Rhoedy Setiawan; Soni Adiyono
IDEALIS : InDonEsiA journaL Information System Vol. 9 No. 2 (2026): Jurnal IDEALIS Juli 2026
Publisher : Universitas Budi Luhur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36080/idealis.v9i2.3811

Abstract

The increasing adoption of mobile banking has generated a large volume of user reviews on the Google Play Store, providing valuable insights into customer satisfaction with digital banking services. This study analyzes user sentiment toward four mobile banking applications BRimo, Livin' by Mandiri, BCA Mobile, and SeaBank—and compares the performance of the Naïve Bayes and Support Vector Machine algorithms for sentiment classification. A dataset of 40,000 Play Store reviews was collected through web scraping. Reviews were labeled based on user ratings, followed by preprocessing, TF-IDF feature extraction, and sentiment classification. Model performance was evaluated using the train-test split method and 5-fold cross-validation. The results indicate that Naïve Bayes outperformed and demonstrated greater stability than SVM across all evaluation metrics, achieving an accuracy of 89.23%, precision of 89.76%, recall of 89.23%, and F1-score of 89.37%, while SVM achieved an accuracy of 88.39%. Sentiment analysis revealed that SeaBank received the highest number of positive reviews, whereas BCA Mobile recorded the highest proportion of negative sentiment. These findings provide a comparative evaluation of Naïve Bayes and SVM for mobile banking sentiment classification and offer practical guidance for selecting appropriate classification algorithms while supporting the continuous improvement of digital banking services through user feedback.
Co-Authors - Supriyono Abdul Azis Al Baehaqi Adi Wibowo Alamul Huda, Alamul Alversia, Yeshika Amanda Diyas Setiyoadi Anita Rahmawati Anteng Widodo Aris Puji Widodo Arya Putra Badruzzaman Bagus Joko Winarso Damar Aji Gurowo Dewi Masitoh Diana Laily Fithri Diana Laily Fithri Diana Laily Fithri Diyas Aditya Adi Saputra Eko Darmanto Eko Darmanto Eko Sediyono fatia, imelda annas Febriana Permatasari Fina Fakhriyah Hadiprawoto, Triana Rahajeng Hawari, Syafrie Muhammad Heru Noviyanto Firmansyah Hidayat, Hilmi Bayu Ira Iriyanty Iriyanty, Ira Kurniasari, Nita Kurniawan, Aldhi Ari Laily Fithri, Diana Latifah, Noor Lu'lu'il Laili Mochammad Imron Awalludin Muhammad Arifin Nanda Dea Anggi Maharani Nava Azahra Noor Latifah Nur Mahardika Pratiwi Cahyaningtiyas Pratomo Setiaji Prayogo, Adhie R Rhoedy Setiawan R. Rhoedy Setiawan Rahmat Gernowo Rizky Adisaputra Romadhon, Zainur Romadhon, Zainur Romy Aziz Risaldi Salum Ainayya Alfatikhah Sendi Novianto Sendi Novianto Setyawan, Moh Dodi Sholichatunnita Nita Siti Masfuah Supriyono Supriyono Supriyono Susanti, Nanik Syafiul Muzid Syafrie Muhammad Hawari Taufiq Hidayat Triana Rahajeng Hadiprawoto Yeshika Alversia Yudie Irawan