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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 Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) Jurnal Abdi Insani 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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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.
Penerapan Metode Asosiasi Menggunakan Algoritma Apriori pada Penjualan Produk Tenun Abthol, Muhammad Rijalul; Wibowo, Gentur Wahyu Nyipto; Maori, Nadia Annisa
TIN: Terapan Informatika Nusantara Vol 6 No 8 (2026): January 2026
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/tin.v6i8.9044

Abstract

The development of information technology has led to a significant increase in the volume of sales transaction data stored in business information systems. Such data possess substantial potential to generate strategic insights when properly analyzed. However, in many small and medium-sized enterprises (SMEs), transaction data have not yet been optimally utilized. This study aims to apply association analysis using the Apriori algorithm to sales transaction data of woven products at Sientong Tenun in order to identify consumer purchasing patterns based on support and confidence values. The research adopts a quantitative approach employing data mining methods on sales transaction data that have undergone a data preprocessing stage. The final dataset used in this study consists of 120 sales transactions. The parameters applied in the analysis include a minimum support threshold of 20% and a minimum confidence threshold of 60%. The results indicate that all main products meet the criteria for frequent 1-itemsets, with Woven Fabric and Shawl exhibiting the highest support values, at 65.00% and 58.33%, respectively. The strongest association rule identified is Woven Fabric → Shawl with a confidence value of 70.51%, followed by Woven Fabric and Shawl → Woven Sarong with a confidence value of 63.64%. These findings demonstrate a significant purchasing relationship among woven products. The results of this study can be utilized by business practitioners to support marketing strategies, sales bundle development, product arrangement, and data-driven inventory management. Furthermore, this research contributes academically to the application of the Apriori algorithm within the culturally based creative industry sector.
Peningkatan Akurasi Prediksi Stok Bahan Baku Furnitur Menggunakan Algoritma Random Forest Regressor Berbasis Web Nafi’uzzahidi, Ahmad; Wibowo, Gentur Wahyu Nyipto; Sarwido, Sarwido
Journal of Information System Research (JOSH) Vol 7 No 2 (2026): January 2026
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josh.v7i2.9095

Abstract

This study aims to address the uncertainty of raw material inventory in the furniture industry through the implementation of the Random Forest Regressor machine learning algorithm. The primary problem addressed is demand fluctuation, which frequently leads to stock management inefficiencies, including overstocking or material shortages that disrupt production processes. The research method employs a quantitative approach with an experimental design, developing a web-based system using the Flask framework and MySQL database. The data sample includes historical sales transaction records and Bill of Materials (BOM) data for furniture products, such as dining tables and minimalist chairs. Prior to modeling, the data underwent a preprocessing stage comprising data cleaning, handling missing values, and normalization to minimize the impact of noise on transaction data. Data collection was conducted through the extraction of internal databases, which were then processed through feature engineering stages based on temporal trends. The results demonstrate that the Random Forest model can predict future raw material requirements with high accuracy, evidenced by a coefficient of determination ($R^2$) of 0.84 and a Mean Absolute Error (MAE) of 5.4.5 These findings prove that a data-driven approach provides more precise stock requirement estimations than conventional methods. In conclusion, the integration of this predictive technology offers practical contributions to accelerating managerial decision-making and optimizing operational efficiency in the medium-scale manufacturing sector. The implications of this study support the theoretical development of artificial intelligence-based decision support systems in supply chain management.
PELATIHAN DAN PENDAMPINGAN APLIKASI BANK SAMPAH BERBASIS WEB UNTUK PENGUATAN TATA KELOLA DI KRAPYAK BERSINAR JEPARA Rochmanto, Decky; Wibowo, Gentur Wahyu Nyipto; Ma'arif, Syamsul
Jurnal Abdi Insani Vol 12 No 11 (2025): Jurnal Abdi Insani
Publisher : Universitas Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/abdiinsani.v12i11.3069

Abstract

This community service activity was carried out to improve the management of the Waste Bank in Krapyak Bersinar through training and mentoring in the use of a web-based information system. The main problem faced by the Waste Bank is manual transaction recording, which often results in errors, data loss, and a lack of transparency. Furthermore, managers also have a limited understanding of accounting and financial management in accordance with standards. Therefore, the objective of this activity was to provide training to Waste Bank managers on the use of an information system application that can simplify transaction recording and financial reporting. The methods used in this activity included problem identification through interviews and observations, socialization regarding the importance of technology in Waste Bank management, training in the use of the web-based application, and mentoring in implementing the application. The results of the activity showed that with the web-based application, Waste Bank managers can record transactions more accurately and efficiently. In addition, the resulting financial reports are more transparent and accountable. The evaluation showed that 90% of managers found it easier to record transactions and manage customer data, and 85% reported a reduction in recording errors. In conclusion, this training and mentoring successfully improved the operational efficiency of the Waste Bank in Krapyak Bersinar, as well as increasing managers' understanding of the use of information technology for better financial management.
Sistem Face Recognition Berbasis Web menggunakan OpenCV Serta Evaluasi dengan Metode System Usability Scale Putri, Vanessa Shinta; Wibowo, Gentur Wahyu Nyipto; Zen, Ahmad Khanif
TIN: Terapan Informatika Nusantara Vol 6 No 8 (2026): January 2026
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/tin.v6i8.8924

Abstract

The attendance system is one of the important aspects for Tabebuya Resort and Restaurant for systematic human resource processing, the attendance system needed to be the basis for calculating salaries, evaluating discipline, and assessing the work of each employee. Therefore, an accurate, efficient, and transparent abscess system is needed so that the company’s productivity can be properly maintained. This research aims to develop the attendance system used by Tabebuya into a web-based face recognition system to make it easier for every employee to access the attendance system used by Tabebuya which originally had a problem in attendance recapitulation which had an effect on salary dan the failure of finger detection which had an effect in operational speed and long queues to become a web-based face recognition atttandance system to make it easier for every employee to access the attendance system with their own device with a certain coordinate point for avoiding operational disruptions and providing roleaccess limits to avoid manipulation of data. In the development of the system the programming, the software development method uses the waterfall method with the python program language implementation by OpenCV library to process facial features using biometric identification to recognize individuals based on facial characteristics and becomes an additional value to avoid the problem of attendance manipulation. The system evaluation is carried out using the system usability scale (SUS) method to ensure that the system created is technically functional. With >80,3 score of SUS indicate the web-based face detection attendance system developed using OpenCv is successful in usability and can help improvement of human resource management in company.
Expert System for Student Talent and Interest Using Certainty Factor and Dempster-Shafer Methods Teddy Setiady; Gentur Wahyu Nyipto Wibowo; R. Hadapiningradja Kusumodestoni
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
Stunting Prediction in Toddlers Using the K-Nearest Neighbor (KNN) Method Based on a Web Application at Batealit Community Health Center, Jepara Lisa Falichatul Ibriza; Gentur Wahyu Nyipto Wibowo; Teguh Tamrin
International Journal Software Engineering and Computer Science (IJSECS) Vol. 5 No. 3 (2025): DECEMBER 2025
Publisher : Lembaga Komunitas Informasi Teknologi Aceh (KITA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijsecs.v5i3.5553

Abstract

Stunting is still a nutritional problem that exists in Indonesia and it needs immediate intervention in Jepara Regency. At the primary healthcare level, Batealit Public Health Center uses manual anthropometric recording for toddlers' growth assessment. This method can be prone to human recording errors and operational delays which hinder prompt clinical decision-making. To improve this condition, this study develops a web-based system for predicting stunting based on the K-Nearest Neighbor (KNN) algorithm. The research method was applied research with system development using the Waterfall model by processing main variables such as age, weight, and height. We tested the algorithm intensively by trying different neighbor values (k) to obtain the maximum value for accuracy, precision, and recall. From experiments, the KNN algorithm is best at k=3 with a 95.23% accuracy rate; this configuration is better compared to larger k values since they increase misclassification rates on normal and stunted categories. By porting this logic into a web interface, detection moves from being a manual task to an automated one occurring in real-time thus application becomes an essential part of decision support enabling health workers to bypass administrative delays and find stunting much faster more accurately within Batealit service area.
Implementasi Blockchain Quorum Berbasis IBFT dalam Pengamanan dan Integritas Log Aktivitas Server Nugroho Adi Prasetyo; Sarwido Sarwido; Gentur Wahyu Nyipto Wibowo
Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) Vol 10 No 3 (2026): JULY 2026
Publisher : Lembaga Otonom Lembaga Informasi dan Riset Indonesia (KITA INFO dan RISET) - Lembaga KITA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/jtik.v10i3.6275

Abstract

This research uses a blockchain-based system for audit logging that relies on Quorum IBFT to ensure that data can't be altered and to handle potential server failures. The AuditLog smart contract was placed on a network of 7 validators, all of which were connected to each other. Logs were processed in batches every 5 minutes, which led to a logging rate of 0.0954 logs per second, or about 8,244 logs each day, with an efficiency gain of 2 to 9 times. When analyzing 651 transactions, the average time to confirm a log was 6.16 seconds, and 81.8% of them were confirmed within 2 to 5 seconds. Tests showed that the system can handle up to 2 failed nodes, but if 3 nodes stop working, the system can't reach agreement and stops creating new blocks, proving that the IBFT system works as intended. The system also sends real-time alerts via Telegram every 5 seconds, giving early warnings about any problems. A review of the smart contract confirmed that it can't be changed because it doesn’t have functions like editLog(), deleteLog(), or updateLog(). The contract has five functions: addLog, addLogBatch, getLog, getLogCount, and logs. These only allow adding data or viewing it, ensuring that logs are permanent and can’t be changed, with proof through cryptographic transaction hashes. This solution provides better audit trails than traditional databases because it uses built-in immutability, transparency across a network, cryptographic proof that can't be denied, and the ability to handle server failures. It is suitable for important systems like government infrastructure, financial systems, and security monitoring.
Co-Authors Abdilllah, Muh Sajid Abthol, Muhammad Rijalul 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 Fanida Muta’aliyur Rohmah Fathurrozi, Muhammad Gogor Christmass Setyawan Gun Sudiryanto Hanifah Nurul Muthmainah Hasan Ibrohim Haydar, Muhammad Rifqi Fajrul Huda, Muhammad Syafi’ul 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 Lisa Falichatul Ibriza Ma'arif, Syamsul Maori, Nadia Annisa Mohammad, Gunawan Muchammad Dwi Rivaldo Mulyo, Harminto Nadia Annisa Maori Nadia Annisa Maori Nafissatus Zahro Nafi’uzzahidi, Ahmad Nanda, Meindita Andriano Nugroho Adi Prasetyo Nugroho, Muhammad Bayu Nur Aeni Widiastuti Nur Ali Nurofi, Muhammad Adib Puji Sa’adah Putri, Vanessa Shinta R Hadapiningradja Kusumodestoni Rahma Dwi Ningsih Ricardus Anggi Pramunendar Rizky Alhusani Gifari Safrizal Safrizal Saludin Saludin Sarwido Sarwido Sarwido Sarwido Sarwido, Sarwido 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 Zen, Ahmad Khanif