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All Journal Jurnal Simetris E-Dimas: Jurnal Pengabdian kepada Masyarakat JOURNAL OF APPLIED INFORMATICS AND COMPUTING Jurnal DISPROTEK Jurnal Informatika dan Rekayasa Elektronik JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) TIN: TERAPAN INFORMATIKA NUSANTARA Abdi Kami : Jurnal Pengabdian Kepada Masyarakat Jurnal Scientia JINAV: Journal of Information and Visualization Journal of Dinda : Data Science, Information Technology, and Data Analytics SPEED - Sentra Penelitian Engineering dan Edukasi International Journal Software Engineering and Computer Science (IJSECS) Jurnal Minfo Polgan (JMP) Jurnal WIDYA LAKSMI (Jurnal Pengabdian Kepada Masyarakat) Formosa Journal of Applied Sciences (FJAS) Innovative: Journal Of Social Science Research Jurnal Pengabdian Harapan Bangsa Journal of Social Work and Empowerment Jurnal Indonesia : Manajemen Informatika dan Komunikasi TECHNOVATE
Wibowo, Gentur Wahyu Nyipto
Universitas Islam Nahdlatul Ulama Jepara
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Expert System for Student Talent and Interest Using Certainty Factor and Dempster-Shafer Methods Setiady, Teddy; Wibowo, Gentur Wahyu Nyipto; Kusumodestoni, R. Hadapiningradja
International Journal Software Engineering and Computer Science (IJSECS) Vol. 5 No. 2 (2025): AUGUST 2025
Publisher : Lembaga Komunitas Informasi Teknologi Aceh (KITA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijsecs.v5i2.5169

Abstract

Elementary education systems in Jepara Subdistrict currently lack standardized frameworks for identifying student capabilities, leaving educators and parents without reliable tools to recognize individual talents and interests. We developed a hybrid expert system that combines Certainty Factor and Dempster-Shafer methodologies to establish quantitative assessment protocols for elementary student aptitude evaluation. Our research employed a quantitative descriptive approach, gathering data through structured behavioral observations, educator interviews, validated questionnaires, and academic documentation from multiple elementary schools across the district. The system processes student behavioral patterns using Certainty Factor methods for initial inference, then applies Dempster-Shafer algorithms to combine evidence sources while managing assessment uncertainty and subjective evaluation parameters. Preliminary testing reveals the system can generate percentage-based aptitude measurements across various domains, with interest category evaluations reaching 37% in targeted areas. We evaluated performance through accuracy validation, expert correlation analysis, precision-recall calculations, response time measurement, and knowledge base quality assessment. The hybrid approach demonstrates measurable improvements in talent identification accuracy when compared to traditional subjective methods, establishing a quantitative foundation for evidence-based educational planning. The system offers schools a standardized capability assessment tool that reduces evaluation bias while optimizing resource allocation for personalized learning development. Educational institutions can implement the framework to support more objective decision-making in student guidance and curriculum planning, particularly valuable for Indonesia's evolving educational landscape that emphasizes individualized learning pathways
PENDAMPINGAN PERANCANGAN DESAIN MASTERPLAN BERBASIS WISATA PADA DESA BERMI KABUPATEN DEMAK Rochmanto, Decky; Mohammad, Gunawan; Wibowo, Gentur Wahyu Nyipto; Fathurrozi, Muhammad; Nurofi, Muhammad Adib; Anwari, Hilal
Jurnal Widya Laksmi: Jurnal Pengabdian Kepada Masyarakat Vol. 5 No. 1 (2025): Jurnal WIDYA LAKSMI (Jurnal Pengabdian Kepada Masyarakat) - Inpress
Publisher : Yayasan Lavandaia Dharma Bali

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59458/jwl.v5i1.162

Abstract

Desa Bermi memiliki karakter sumber daya alam yang kuat, khususnya dibidang pertanian dan juga mempunyai potensi lingkungan yang memadai untuk dikembangkan. Dalam perkembangannya, potensi yang ada belum terpetakan dengan baik, sehingga belum ada skema perencanaan dalam pengembangan yang utuh. Desa Bermi belum memiliki arah tujuan untuk mengembangkan sarana dan prasarana dalam mengembangkan kawasan desa wisata yang memadai. Agar desa tersebut dapat berkembang dan terarah dalam pembangunan sarana dan prasarana, maka pihak Pemerintah Desa Bermi bekerjasama atau berkolaborasi dengan Tim PKM dari UNISNU Jepara untuk dibuatkan Perencanaan Masterplan dengan tujuan untuk mendapatkan arahan perencanaan desa dalam mengelola potensi sumber daya alam dan lingkungan menuju kemandirian desa. Konsep menuju desa mandiri, menjadi perioritas utama sebagai desa wisata yang akan berkembang. Produk dari kegiatan ini berupa arahan pendampingan dan konsep desain seperti pemanfaatan sumur gandeng sebagai area kawasan wisata, gerbang desa sebagai penanda kawasan wisata, lahan kandang ternak sebagai rumah biogas, perabot jalan untuk lampu penerangan jalan, penampungan air sebagai fasilitas sarana untuk dapat dimafaatkan oleh masyarakat sebagai sumber air bersih, poskamling sebagai tempat pos jaga untuk keamanan desa, branding desa dan packaging produk menjadi elemen desain yang dihasilkan.
Optimizing Decision Tree and Random Forest with Grid Search and SMOTE for Malware Classification on IoT Network Traffic Siroj, Muhammad Nurus; Zyen, Akhmad Khanif; Wibowo, Gentur Wahyu Nyipto
Journal of Applied Informatics and Computing Vol. 9 No. 5 (2025): October 2025
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v9i5.10542

Abstract

The rapid growth of the Internet of Things (IoT) has increased the risk of malware attacks, posing serious threats especially to micro, small, and medium enterprises (MSMEs) that often lack sufficient cybersecurity resources. This study aims to optimize Decision Tree (DT) and Random Forest (RF) classifiers using Grid Search, while addressing the class imbalance problem through the Synthetic Minority Oversampling Technique (SMOTE). The Security Attacks Malware IoT Networks dataset with five classes (Benign, Malware, DDoS, Brute Force, Scanning) was used and divided into training and testing sets with stratified 80:20 split. Experimental results show that DT achieved 67.3% accuracy with a macro F1-score of 42.9%, while RF achieved 70.7% accuracy but a very low macro F1-score of 21.4%, indicating bias toward the majority class despite balancing. Boosting methods provided stronger baselines, with XGBoost reaching 87.0% accuracy and 66.7% F1-score, while LightGBM achieved 85.6% accuracy and 64.4% F1-score. ROC curves and confusion matrices confirmed that boosting methods were more balanced in recognizing minority classes. In terms of efficiency, DT required the shortest training time (8 seconds), while LightGBM provided the best trade-off between accuracy and computational cost (26 seconds). Paired t-tests further confirmed that performance differences between DT and RF were not significant, while boosting methods significantly outperformed RF. Overall, optimizing DT and RF with Grid Search and SMOTE enhances their performance, but boosting methods remain more robust for malware detection in IoT traffic. These findings provide practical insights for MSMEs in balancing accuracy and efficiency when deploying intrusion detection systems.
Exploratory Data Analysis: Visualization of Average Wages of Workers in Indonesia by Region of Residence using Google Data Studio Wibowo, Gentur Wahyu Nyipto; Kraugusteeliana, Kraugusteeliana
TECHNOVATE: Journal of Information Technology and Strategic Innovation Management Vol. 1 No. 3 (2024): July 2024
Publisher : PT.KARYA GEMAH RIPAH

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52432/technovate.1.3.2024.10-116

Abstract

This study analyzes the average hourly wage of workers in Indonesia by region of residence, using data from the Central Bureau of Statistics (BPS) for the period 2018-2022. The data is divided into three categories: rural, urban, and combined urban and rural. The analysis was conducted using Exploratory Data Analysis (EDA) method and data visualization using Google Data Studio. The results of the analysis show that there is significant variation between wages in urban and rural areas. In rural areas, the highest average wage was recorded in 2020 at IDR 14,242, and the lowest in 2018 at IDR 11,557. Wages in rural areas increased from 2018 to 2020, then decreased in 2021 and 2022. In urban areas, the highest wage in 2021 reached IDR 20,234 per hour, while the lowest in 2018 was IDR 17,326 per hour. The wage trend in urban areas increased from 2018 to 2021, followed by a decline in 2022. The combined urban and rural data shows the highest wage in 2021 at 18,089 Rupiah per hour and the lowest in 2018 at 15,275 Rupiah per hour. The data visualization reveals that workers in urban areas have higher wages than workers in rural areas, with a five-year average of 28,957 Rupiah per hour in urban areas and 13,067 Rupiah per hour in rural areas. In conclusion, there is a significant disparity between wages in urban and rural areas, with a decline in wages by 2022 indicating an economic impact that requires adaptive policies.
Analisis Tantangan dan Peluang Penggunaan Artificial Intelegence Pada Mahasiswa Teknologi Informasi: Pendekatan K-Means Clustering Ali, Nur; Kusumodestoni, R. Hadapiningradja; Wibowo, Gentur Wahyu Nyipto
Innovative: Journal Of Social Science Research Vol. 5 No. 4 (2025): Innovative: Journal Of Social Science Research
Publisher : Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/innovative.v5i4.20868

Abstract

This study aims to identify the perceptions, challenges, and opportunities of Information Technology students in utilizing Artificial Intelligence (AI) in the learning process. Using a quantitative approach with the K-Means Clustering method, this study groups students based on their level of knowledge and utilization of AI. The results indicate two main profiles: students with high AI literacy but moderate utilization, and students with low understanding but intensive utilization. The second group faces similar challenges but views AI opportunities differently. These findings highlight the importance of user profile-based learning strategies to create an adaptive and sustainable AI ecosystem. This research contributes to the development of higher education policy.
Penerapan Teknologi Roaster Berbasis Internet of Thing (IoT) dan Sachet Forming Machine untuk Meningkatkan Produktifitas dan Kualitas Usaha Kopi Jawico Jepara Safrizal, Safrizal; Wibowo, Gentur Wahyu Nyipto; Nadhifah, Isyfa Fuhrotun; Kusuma, Tahta Rias Tika C
E-Dimas: Jurnal Pengabdian kepada Masyarakat Vol 16, No 2 (2025): E-DIMAS
Publisher : Universitas PGRI Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26877/e-dimas.v16i2.20429

Abstract

Kegiatan pengabdian masyarakat ini bertujuan untuk memberdayakan bisnis kopi lokal, Jawico Coffee di Jepara, melalui penerapan teknologi roaster berbasis Internet of Things (IoT) dan mesin pembentuk sachet. Tujuannya adalah untuk meningkatkan produktivitas dan kualitas produksi kopi dengan memanfaatkan inovasi teknologi modern. Selama 8 bulan, tim memberikan bantuan manajemen keuangan kepada bisnis tersebut, termasuk pencatatan keuangan, pelaporan keuangan, dan dukungan administratif secara keseluruhan. Selain itu, pengembangan branding dan bantuan hukum untuk perizinan usaha juga diberikan untuk memastikan pertumbuhan dan keberlanjutan bisnis kopi tersebut. Penerapan sistem manajemen keuangan sederhana dan strategi branding berhasil meningkatkan transparansi, akuntabilitas, dan efisiensi operasional perusahaan kopi. Proyek ini menunjukkan bagaimana usaha kecil dan menengah (UMKM) lokal dapat memanfaatkan teknologi canggih untuk meningkatkan kualitas produk dan praktik bisnis mereka. Inisiatif ini juga memberikan kontribusi kepada masyarakat dengan memberikan pengalaman praktis bagi mahasiswa di bidang akuntansi dan manajemen bisnis.
Co-Authors Abdilllah, Muh Sajid Ah Dani Fian Cahya Akhmad Khanif Zyen, Akhmad Khanif Anis Sofiyati Anwari, Hilal Beni Ernando Charles Firmansyah Decky Rochmanto, Decky Dewantara, Rizki Faisti, Muhammad Jazum Fathurrozi, Muhammad Gogor Christmass Setyawan Gun Sudiryanto Hanifah Nurul Muthmainah Haydar, Muhammad Rifqi Fajrul I Nengah Sandi Indriyani Indriyani Isyfa Fuhrotun Nadhifah Jeperson Hutahaean Joko Minardi, Joko Khasan Galuh Ramadhan Kraugusteeliana Kraugusteeliana Kusuma, Tahta Rias Tika C Laros Tuhuteru Maori, Nadia Annisa Mohammad, Gunawan Mulyo, Harminto Nadia Annisa Maori Nadia Annisa Maori Nafissatus Zahro Nanda, Meindita Andriano Nugroho, Muhammad Bayu Nur Ali Nurofi, Muhammad Adib R Hadapiningradja Kusumodestoni Rahma Dwi Ningsih Ricardus Anggi Pramunendar Rivaldo, Muchammad Dwi Safrizal Safrizal Saludin Saludin Sarwido Sarwido Sarwido Sa’adah, Puji Siroj, Muhammad Nurus Sitorus, Lamhot Susatyo Adhi Pramono, Susatyo Adhi Syamsul Ma'arif TEDDY SETIADY Teguh Tamrin Tobias Duha Wenda, Alex Yatusifa, Cecilia Zaenal Arifin