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Pengembangan Website Desa Berbasis OpenSID di Desa Pesanggrahan Sebagai Digitalisasi Pelayanan Publik Zaenul Amri; Muhamad Wisma Apriadi; Amir Bagja; M. Nurul Wathani; Zulkipli
Jurnal Teknologi Informasi untuk Masyarakat Vol. 4 No. 1 (2026): Jurnal Teknologi Informasi untuk Masyarakat (Teknokrat)
Publisher : Universitas Hamzanwadi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29408/jt.v4i1.35057

Abstract

The current development of information technology requires village governments to continuously adapt in providing excellent, effective, and transparent public services to achieve good governance. However, Pesanggrahan Village still faces challenges regarding the limited utilization of information technology, particularly concerning the slow management of population administration data and the restricted means of disseminating information to the wider community. Therefore, this activity aims to develop and implement an OpenSID-based village website as a tangible effort to realize the digitalization of public services at the village level. The implementation method involved systematic stages, including observation and analysis of village needs, installation and configuration of the OpenSID system, input of basic village data, along with technical training and mentoring for village apparatuses to ensure independent system management. The results indicate that the village website has been successfully developed. It currently functions optimally as an official information medium, an integrated administrative data management center, and a digital service support tool that simplifies the duties of village officials while improving information accessibility for residents. In conclusion, implementing the OpenSID-based website provides a practical and sustainable solution to accelerate public service digitalization in Pesanggrahan Village, effectively addressing the challenges of limited resources and local technological infrastructure, thereby fostering village independence in the current digital era
Pelatihan Pembuatan Sistem Informasi Profil BUMDes di Desa Karang Baru Sebagai Upaya Pengabdian Masyarakat Jumawal; Mahpuz; Zulkipli; Muh. Farid Wajdi
Jurnal Teknologi Informasi untuk Masyarakat Vol. 4 No. 1 (2026): Jurnal Teknologi Informasi untuk Masyarakat (Teknokrat)
Publisher : Universitas Hamzanwadi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29408/jt.v4i1.35309

Abstract

The development of information technology requires Village-Owned Enterprises (BUMDes) to be able to present information quickly, accurately, and transparently to the public to support professional village business management. BUMDes in Karang Baru Village still faces limitations in providing digital information, particularly regarding BUMDes profiles, business units, superior products, and business management activities. This community service activity aims to provide training and assistance in creating a website-based BUMDes profile information system as a medium for information and promotion of village businesses. The implementation method includes observation and analysis of BUMDes needs, system design, development of a BUMDes profile website, training system managers, and evaluation of activity results. This activity was carried out for three months as part of a community service program by students from Hamzanwadi University, involving BUMDes administrators and village officials. The results of the activity show that BUMDes Karang Baru Village has a profile website that contains institutional information, business units, products, activity news, and a documentation gallery. In addition, BUMDes administrators experienced an increase in understanding and skills in managing information systems independently. The conclusion of this activity is that training in creating a website-based BUMDes profile information system can increase information transparency, support village business promotion, and strengthen BUMDes governance in a sustainable manner.
Rancang Bangun Sistem Smart Home Berbasis Google Assistant dengan Kendali Perintah Suara Muh Sofiyan; Aris Sudianto; Zulkipli Zulkipli
Jurnal PRINTER: Jurnal Pengembangan Rekayasa Informatika dan Komputer Vol. 4 No. 1 (2026): Jurnal PRINTER: Jurnal Pengembangan Rekayasa Informatika dan Komputer
Publisher : Fakultas Teknik Universitas Hamzanwadi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29408/jprinter.v4i1.32686

Abstract

Perkembangan teknologi Internet of Things IoT memberikan peluang besar dalam menciptakan sistem rumah cerdas (smart home) yang mampu meningkatkan efisien, kenyamanan, serta aksesibilitas bagi pengguna. Penelitian ini merancang dan membangun sistem smart home berbasis Google Assistant dengan kendali perintah suara untuk mengontrol perangkat elektronik rumah tangga, khususnya lampu dan kipas. Sistem ini menggunakan mikrokontroler ESP32 sebagai pengendali utama, modul relay sebagai saklar elektronik, serta integrasi dengan Arduino Cloud yang berfungsi sebagai perantara komunikasi antara Google Assistant dengan perangkat keras. Metode pengembangan sistem menggunakan pendekatan prototype dengan tahapan identifikasi masalah, pengumpulan kebutuhan sistem, perancangan sistem, pengembangan sistem, pengujian sistem, dan evaluasi sistem. Hasil implementasi menunjukkan bahwa sistem mampu mengendalikan perangkat elektronik secara otomatis melalui perintah suara dengan tingkat keberhasilan rata-rata 98.33% dan rata-rata waktu respon 1.83 detik. Hal ini membuktikan bahwa sistem yang dibangun cukup responsif, akurat, serta dapat diandalkan dalam penggunaan sehari-hari. Sistem ini juga memberikan kemudahan bagi pengguna dengan keterbatasan mobilitas seperti lansia dan penyandang disabilitas.
Pengembangan Web Dashboard Monitoring Kadar Nitrogen, Fosfat, Kalium (NPK), PH Tanah Berbasis Artificial Intelegence (AI) dan Internet Of Things (IoT) Indra Gunawan; M Nurul Wathani; Zulkipli; Sappatin
Infotek: Jurnal Informatika dan Teknologi Vol. 9 No. 2 (2026): Infotek : Jurnal Informatika dan Teknologi
Publisher : Fakultas Teknik Universitas Hamzanwadi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29408/jit.v9i2.34982

Abstract

Indonesia is an agrarian country where the agricultural sector plays an important role in supporting the national economy. However, agricultural land management is still largely carried out using conventional methods, resulting in suboptimal monitoring of soil nutrient conditions. Nitrogen (N), Phosphorus (P), Potassium (K), and soil acidity (pH) are critical parameters influencing soil fertility and crop productivity. This study aims to develop a soil monitoring system for NPK and pH levels based on Artificial Intelligence (AI) and the Internet of Things (IoT) using an NPK Modbus sensor, an analog soil pH sensor, and an ESP32 microcontroller. Sensor data are transmitted in real-time to a Firebase database via a Wi-Fi network and displayed on a web dashboard through numerical visualizations, graphs, and ChatGPT-based AI analytic interpretations. The experimental results show that the system successfully acquires and transmits soil condition data consistently. Accuracy testing demonstrated that the system is highly precise, with the pH sensor readings showing an average difference (error rate) of only 0.2% when compared to a standard pH tester. The NPK sensor also exhibited excellent reactivity to changes in soil macronutrients. Furthermore, the integrated AI system successfully provided stable fertility evaluations and fertilization recommendations across multiple repeated tests. This system is expected to facilitate remote field monitoring for farmers and support precise, efficient fertilization decision-making.
Improving Imbalanced Polycystic Ovary Syndrome Classification Using a Leakage-Free Machine Learning Pipeline Baiq Andriska Candra Permana; Zulkipli; Muhammad Wasil; Harianto
JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING Vol. 9 No. 2 (2026): Issues January 2026
Publisher : Universitas Medan Area

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31289/jite.v9i2.16752

Abstract

Polycystic Ovarian Syndrome (PCOS) is a complex endocrine disorder affecting women of reproductive age and poses challenges for early diagnosis due to heterogeneous clinical presentations and imbalanced clinical datasets. This study aims to develop a data leakage–free machine learning pipeline to enhance the accuracy and reliability of PCOS classification using clinical data. The dataset underwent preprocessing and normalization, followed by stratified data splitting with an 80:20 ratio to maintain class proportions. The proposed pipeline was implemented within a unified computational framework integrating feature selection based on the ANOVA F-test, class imbalance handling using the Synthetic Minority Over-sampling Technique (SMOTE), and classification using a Support Vector Machine (SVM) with a Radial Basis Function (RBF) kernel. Hyperparameter tuning was performed using GridSearchCV combined with K-Fold Cross-Validation to ensure model robustness and consistency. The experimental results indicate that the proposed model achieved an accuracy of 0.9074, with precision, recall, and F1-score values of 0.8378, 0.8857, and 0.8611, respectively. Furthermore, ten dominant clinical features were identified, primarily related to hormonal profiles and ovarian morphology. These results demonstrate that the data leakage–free pipeline improves the validity and stability of PCOS prediction. The findings suggest that this approach may serve as a supportive tool for clinical decision-making, particularly in facilitating early and objective identification of PCOS.
Integrasi Progressive Web App dan Sistem Informasi Geografis untuk Penyediaan Informasi Lokasi dan Harga Penyewaan Gendang Beleq di Lombok Baiq Andriska Candra Permana; Zaenul Amri; Gunawan Rohadi; Zulkipli
Infotek: Jurnal Informatika dan Teknologi Vol. 9 No. 1 (2026): Infotek : Jurnal Informatika dan Teknologi
Publisher : Fakultas Teknik Universitas Hamzanwadi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29408/jit.v9i1.33068

Abstract

Gendang Beleq is a traditional musical art of the Sasak people that continues to be preserved in Lombok. However, the process of renting Gendang Beleq instruments in East Lombok is still done manually, which makes it difficult for people to access clear and reliable information about rental locations, prices, and provider contacts. This study aims to develop a Progressive Web App (PWA)-based Geographic Information System that can provide accurate, fast, and easy-to-access information related to Gendang Beleq rentals. The research uses a Research and Development (R&D) approach with the ADDIE model, which includes the stages of analysis, design, development, implementation, and evaluation. The developed system displays an interactive map showing the locations of rental providers along with complete details such as prices, contacts, and descriptions of the instruments. The system also supports key PWA features, including app installation and offline access. Performance testing using GTMetrix resulted in scores of 98% for the admin application and 97% for the user application. Functional testing showed that the system is highly feasible, with alpha testing results of 94.5% for the admin system and 100% for the user interface, while beta testing achieved a 98% feasibility score. Overall, the PWA-based GIS developed in this study is considered effective, user-friendly, and capable of supporting the availability of Gendang Beleq rental information in East Lombok.
Analisis Perbandingan Kinerja Metode GFPGAN dan RestoreFormer dalam Restorasi Foto Lama Hariman Bahtiar; Amri Muliawan Nur; Almi Yulistia Alwanda; Zulkipli Zulkipli
Jurnal Informatika: Jurnal Pengembangan IT Vol 11, No 2 (2026)
Publisher : Politeknik Harapan Bersama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30591/jpit.v11i2.10291

Abstract

A This study aims to analyze and compare the performance of two artificial intelligence–based image restoration methods, namely GFPGAN (Generative Facial Prior GAN) and RestoreFormer, in enhancing the quality of old photographs of TGKH. Muhammad Zainuddin Abdul Madjid. Both methods were tested on images that had undergone visual degradation, with OpenCV used as a conventional baseline. The evaluation was conducted using two main parameters: processing time and result quality, measured through the Peak Signal-to-Noise Ratio (PSNR) metric. The results show that GFPGAN produced the best outcome, achieving the highest PSNR value (32.8 dB) and the fastest processing time (9 seconds), generating sharp and realistic facial details. RestoreFormer yielded nearly comparable quality with a PSNR of approximately 30 dB and a slightly longer processing time (10 seconds), but it demonstrated greater consistency in preserving the authenticity of textures and structural details. Meanwhile, the manual OpenCV-based method achieved only moderate improvement (25.2 dB) with the longest processing time (12.5 seconds). These findings indicate that AI-based technologies, particularly GFPGAN and RestoreFormer, hold great potential for the preservation of historical visual archives, as they can significantly enhance the quality of old photographs while maintaining their original visual character. The combination of both methods is recommended for digital restoration efforts that balance technical efficiency and cultural authenticity.