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All Journal Conference on Innovation and Application of Science and Technology (CIASTECH) Scientific Journal of Informatics G-Tech : Jurnal Teknologi Terapan Jurnal Aplikasi Teknologi Informasi dan Manajemen (JATIM) As-Sidanah : Jurnal Pengabdian Masyarakat JUSTIFY : Jurnal Sistem Informasi Ibrahimy JEECS (Journal of Electrical Engineering and Computer Sciences) NJCOM: Community Service Journal
Fatah, Zaehol
Fakultas Sains Dan Teknologi Universitas Ibrahimy
Religion Agriculture, Biological Sciences & Forestry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Energy Engineering Environmental Science Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Social Sciences Other

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Seminar Desain Grafis Untuk Meningkatkan Keterampilan Siswa Di Smk Ibrahimy 1 Sukorejo Ali Muhajir; Ahmad Efendi; Zaehol Fatah
NJCOM: Community Service Journal Vol. 1 No. 2 (2025): July
Publisher : RAM PUBLISHER

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5281/zenodo.15854741

Abstract

Seminar tentang desain grafis ini bertujuan untuk memberikan pemahaman dan wawasan mendalam mengenai pentingnya desain grafis di masa kini. Di area digital saat ini, desain grafis tidak hanya berfungsi sebagai elemen estetika, tetapi juga berperan sebagai alat stategis untuk menyampaikan pesan, membagun edentitas merek, dan daya tarik informssi. Corel DRAW salah satu perangkat lunak yang banyak dipakai untuk desain grafis dalam dunia pendidikan dan dunia kerja. Kemampuan desain grafis menjadi penting bagi siswa SMK. Kegiatan ini di lakukan dengan metode seminar di SMK Ibrahimy 1 Sukorejo. Hasilnya, siswa mampu memahami dan menerapkan desain grafis untuk mengembangkan keterampilan mereka di dunia pendidikan maupun di dunia kerja.
Application of K-means Clustering Data Mining in Grouping Data of People with Disabilities Moh. Bahauddin; Zaehol Fatah
JEECS (Journal of Electrical Engineering and Computer Sciences) Vol. 10 No. 1 (2025): JEECS (Journal of Electrical Engineering and Computer Sciences)
Publisher : Fakultas Teknik Universitas Bhayangkara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54732/jeecs.v10i1.6

Abstract

Data mining is critical in enabling organizations to derive reliable insights from data. Social welfare remains a significant challenge in Indonesia, particularly for people with disabilities, emphasizing the need for targeted strategies. However, developing research has not used natural characteristics according to disability problems. This study utilizes the K-Means Clustering algorithm to analyze and categorize the population of people with disabilities in East Java. The attributes include the type of disability, population size, and regional distribution. We employs a dataset from the East Java Central Bureau of Statistics, comprising 342 data points across eight attributes, including region, disability type, and year. The analysis involves data preprocessing, transformation, clustering, and evaluation using the Davies-Bouldin Index (DBI). The results identify two optimal clusters, achieving the lowest DBI score of 0.097, indicating high cluster quality. Cluster 0 represents regions with fewer people with disabilities, while Cluster 1 highlights areas with higher populations. These findings provide a foundation for developing more focused and inclusive welfare programs tailored to regional needs, enhancing the quality of life for people with disabilities.
Comparative Study of Naïve Bayes Classifier and Support Vector Machine Methods in Public Sentiment Analysis of Prabowo-Gibran's Free Lunch Program Fikri Febrian; Zaehol Fatah; Achmad Baijuri
G-Tech: Jurnal Teknologi Terapan Vol 9 No 3 (2025): G-Tech, Vol. 9 No. 3 July 2025
Publisher : Universitas Islam Raden Rahmat, Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70609/g-tech.v9i3.7248

Abstract

In today's digital era, social media has become the main platform for people to voice their opinions on social and political issues. One of the most discussed topics is the free lunch program of President-elect Prabowo Subianto and Vice President-elect Gibran Rakabuming Raka. The program triggered various public reactions, making it relevant for sentiment analysis. The purpose of this study is to compare the performance of two text classification algorithms-Naïve Bayes and Support Vector Machine (SVM)-in classifying public sentiment towards the program. The dataset was obtained from Kaggle, with 657 initial data. After preprocessing, 156 data remained, consisting of 127 negative sentiments and 31 positive sentiments. Data processing followed the CRISP-DM framework, with Python and Scikit-learn used in model training. The results showed that the naive bayes classifier performed better with 84.38% accuracy, 86.90% precision, and 84.38% recall. Support Vector Machine showed lower performance in all metrics. In addition, the Naive Bayes Classifier was able to classify sentiments in a more balanced manner. The analysis was performed using Jupyter Notebook, and the final model was implemented through a Streamlit-based web interface.
Design of Mobile and Web-Based Geolocation Attendance and Payroll Information System for Teachers And Employees at Madrasah Aliyah As'adiyah Meneng Ketapang Banyuwangi Rohiqim Mahtum; Zaehol Fatah; Ahmad Homaidi
G-Tech: Jurnal Teknologi Terapan Vol 9 No 3 (2025): G-Tech, Vol. 9 No. 3 July 2025
Publisher : Universitas Islam Raden Rahmat, Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70609/g-tech.v9i3.7332

Abstract

Attendance recording and payroll management are important elements in maintaining discipline and operational efficiency in madrasahs. Currently, Madrasah Aliyah As'adiyah Meneng Ketapang uses a manual system based on attendance sheets and spreadsheets, which are prone to errors and data manipulation. To address this issue, this study designed and developed a geolocation-based attendance and payroll information system accessible via mobile and web platforms. Key features include location validation within a 20-meter radius, selfie photo verification, fake GPS detection, and automatic payroll calculation based on attendance and teaching hours. The system was developed using the Waterfall model through field observations, interviews, and literature reviews. Evaluation using Blackbox Testing involving actual users showed that all system functions operated as expected, with no significant errors identified. This system improves accuracy, efficiency, and transparency in the attendance and payroll processes. However, this research is limited to small-scale madrasahs and Android-based platforms. Future development should include better fraud detection methods and integration with broader academic management systems to enhance scalability and functionality.
Co-Authors Abdul Jalil Abu Dzarrin Al Ghifari Achmad Baijuri Ahmad Efendi Ahmad Homaidi Ahmad Yogianto Akhlis Munazilin Ali Muhajir Cindy Nur Dina Alifia Fikri Febrian Irma Yunita Jarot Dwi Prasetyo Jarot Dwi Prasetyo Lukman Aliyasin Lukman Fakih Lidimilah Moh. Aqil Mukhtar Alfarera Moh. Bahauddin Neny Yuli Susanti Neny Yuli Susanti Nur Azizah Rohiqim Mahtum Taufik Saleh Taufik Saleh Zainur Rohman