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Jurnal Teknoif Teknik Informatika Institut Teknologi Padang
Published by Institut Teknologi Padang
ISSN : 23382724     EISSN : 25989197     DOI : 10.21063/jtif
Core Subject : Science, Engineering,
Computer Science & IT Control & Systems Engineering
The editors of the Jurnal TeknoIf Institut Teknologi Padang (Teknoif) are pleased to present this call for papers on Information Technology. Teknoif specifically focuses on experimental study, design, planning and modeling, implementation method, and literature study. Topics include, but are not limited to: Artificial intelligence technologies Cloud computing Digital forensics Genetic algorithms and programming Grid computing Human Computer Interaction Image and speech recognition Internet of Things Mobile technology development Network architectures Network technologies Pattern recognition Sensor technologies Virtualization Wearable computing Wireless technologies ISSN : 2598-9197 (online), 2338-2724(print) Subject: Informatics Engineering Frequency: Semiannual Language: Indonesia Indexed at: Crossref, PKP Index, Citation: Google Scholar DOI :10.21063/jtif
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 259 Documents
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PERANCANGAN APLIKASI PERHITUNGAN BEBAN KERJA DOSEN TERINTEGRASI DENGAN PENDEKATAN WATERFALL Ratmana, Danny Oka; Syaifur Rohman, Muhammad; Firdausillah, Fahri; Wilujeng Saraswati, Galuh
Jurnal Teknoif Teknik Informatika Institut Teknologi Padang Vol 12 No 2 (2024): TEKNOIF OKTOBER 2024
Publisher : ITP Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21063/jtif.2024.V12.2.139-148

Abstract

Digital transformation in higher education emphasizes the importance of information technology in enhancing management efficiency, including the management of lecturers' workloads. This study aims to design a Full-Time Equivalent Teaching Load (EWMP) calculation system integrated with the Integrated Resource Information System (SISTER), implemented by the Ministry of Education, Culture, Research, and Technology (KEMDIKBUDRISTEK). The application was developed using the Waterfall methodology and leverages the SISTER Application Programming Interface (API) to automate the collection of lecturer activity data at Universitas Dian Nuswantoro Semarang (UDINUS). By integrating the workload calculation application into the internal management system, this solution streamlines data recording, reduces manual errors, and enhances accuracy in the evaluation of lecturer performance. The test results indicate that the application successfully synchronizes data with SISTER in an accurate and real-time manner, supporting more effective workload management for lecturers. Additionally, the system provides reports and analyses of lecturer workloads, facilitating resource planning and allocation. This application is expected to contribute to a more transparent, accurate, and quality-driven human resource management process in higher education.
SISTEM PENYIRAMAN OTOMATIS PADA PEMBIBITAN PRE-NURSERY KELAPA SAWIT BERBASIS INTERNET OF THINGS Rosman, Edwar; Flomina G, Katrina; Hasanah, Miftahul; Salam, Riyan Ikhbal; Eka Putra, Dian
Jurnal Teknoif Teknik Informatika Institut Teknologi Padang Vol 12 No 2 (2024): TEKNOIF OKTOBER 2024
Publisher : ITP Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21063/jtif.2024.V12.2.131-138

Abstract

The application of automation technology in the agricultural sector is a highly effective solution for improving the efficiency and productivity of seedling cultivation, particularly in oil palm nurseries. CV Pangean Raya TBS is an oil palm nursery business located in Solok Selatan Regency. CV Pangean Raya TBS is currently facing challenges in the watering process of oil palm seedlings, as it is still done manually. This manual method leads to wasted time, labor, and water. Manual watering often results in uneven water distribution, which can affect the quality of the oil palm seedlings. This research aims to design and implement an efficient Internet of Things (IoT)-based automatic watering system using a soil moisture sensor, ESP32 module, and RTC. The system is designed to monitor soil moisture conditions in real time and regulate watering automatically. The automatic watering is based on the moisture values detected by the sensor. Watering can also be manually controlled via a smartphone when needed, such as during rainfall, to prevent water wastage and overwatering of the oil palm seedlings. This system can help plantation owners optimize water usage, increase seedling productivity, and reduce dependence on manual labor. The research results indicate that the watering system can operate automatically based on the moisture data received, making it effective in conserving resources, improving productivity, and providing better control over plant conditions.
PENGEMBANGAN WEB SERVICE MENGGUNAKAN FRAMEWORK FASTAPI UNTUK MENINGKATKAN KEMUDAHAN INTEGRASI SISTEM INFORMASI AKADEMIK MULTIPLATFORM Safitri, Aprilyani Nur; Harkespan, Imanuel
Jurnal Teknoif Teknik Informatika Institut Teknologi Padang Vol 12 No 2 (2024): TEKNOIF OKTOBER 2024
Publisher : ITP Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21063/jtif.2024.V12.2.149-157

Abstract

Academic activities at Dian Nuswantoro University are managed using a web-based and mobile-based (Android and IOS) academic information system for students, lecturers, educators, and parents (guardians). The data retrieval process used by the academic information system is currently in each system itself so that it is prone to errors. Therefore, a back-end service is needed in the form of a web service that acts as a portal for the data retrieval process that can be used by the multiplatform academic information system. In addition to helping to avoid data retrieval errors, the web service that is built also provides complete and easy-to-understand documentation of web service usage. The average time required for the web service to provide a response when accessed by 1000 users is 6198ms (minimum 17ms and maximum 10017ms), meaning that the web service has good performance under high loads. The Extreme Programming method was chosen for the development of the web service in this study. This method consists of four stages, namely planning (analysis of what the system needs), design (visualization with Use Case diagrams), coding (using FastAPI Framework), and the last is testing (using BlackBox and JMeter for testing functions and security). The simplicity of this method can support the achievement of the desired results, namely a back-end service in the form of a web service, which can be used by a multi-platform academic information system to exchange data easily and accurately so that errors can be avoided, especially inconsistencies in presenting academic data.
WEB-BASED SANTRI MANAGEMENT AND MONITORING SYSTEM INTEGRATED WITH WHATSAPP Aprillia, Lucita; Agita Rindri, Yang; Agusti Farma, Tri
Jurnal Teknoif Teknik Informatika Institut Teknologi Padang Vol 13 No 2 (2025): TEKNOIF OKTOBER 2025
Publisher : ITP Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21063/jtif.2025.V13.2.117-126

Abstract

The increasing number of students in Islamic boarding schools (pesantren) has made administrative tasks such as recording student violations, achievements, permissions, and health records more complex. Many schools still manage these data manually, resulting in duplication, delayed communication, and inefficient supervision. This study addresses this issue by developing a Web-Based Santri Management and Monitoring System integrated with WhatsApp, aiming to streamline data management and enhance real-time communication between administrators, guardians, and health staff. The system was developed using the Waterfall methodology, which includes requirement analysis, system design, implementation, testing, and maintenance stages. Three main user roles were defined: administrators, guardians, and health staff, each with specific responsibilities. A User Acceptance Test (UAT) was conducted with 32 respondents, including one administrator, 30 guardians, and one health staff. The results showed satisfaction levels of 100% for administrators, 87% for guardians, and 100% for health staff, indicating high user acceptance. These findings suggest that the system effectively addresses the challenges of manual data management, improves administrative efficiency, and strengthens communication through real-time WhatsApp notifications, providing a comprehensive solution for student monitoring and supervision in Islamic boarding schools.
Rethinking Graph-Based Approaches: An Empirical Study of Feature Engineering in Network Intrusion Detection Nwachukwu, Richard
Jurnal Teknoif Teknik Informatika Institut Teknologi Padang Vol 14 No 1 (2026): TEKNOIF APRIL 2026 (In Progress)
Publisher : ITP Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21063/jtif.2026.V14.1.1-10

Abstract

Although graph-based feature engineering has become widely used in network intrusion detection systems (NIDS), there is a severe lack of empirical research on determining whether the addition of network topology features results in a real positive improvement over the operation of the system or it simply adds complexity to the system. Our paper gets into this gap by critically assessing the performance of graph-based methods as compared to conventional statistical features via systematic comparative analysis across several machine learning paradigms. Using the UNSW-NB15 dataset, we employed a graph-theoretic characteristics that included measures of centrality, the community structure identification and the topological analysis, which were compared to traditional traffic-based characteristics. Results revealed a counterintuitive finding where incorporating graph features consistently degraded detection performance across all algorithms, with statistically significant accuracy reductions observed in multiple classifiers. Random Forest experienced modest performance decline, while Support Vector Machines and RBF Networks showed more substantial degradation. Computational analysis also demonstrated that graph feature extraction imposed substantial overhead compared to traditional feature computation, representing approximately nineteen-fold increase in processing time.
Real-Time IoT-Based Solar Power Monitoring System Using Threshold Decision Algorithm and Mobile Push Notifications Rachman, Afif Fathur; Huda, Yasdinul; Parma Dewi, Ika; Kurnia Saputra, Hadi; Effendi, Asnal
Jurnal Teknoif Teknik Informatika Institut Teknologi Padang Vol 14 No 1 (2026): TEKNOIF APRIL 2026 (In Progress)
Publisher : ITP Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21063/jtif.2026.V14.1.11-23

Abstract

The establishment of solar power installations as a renewable energy option necessitates dependable monitoring systems to ensure peak performance. Nonetheless, current monitoring solutions typically emphasize only data visualization, lacking intelligent early warning features, which results in slower fault detection and faster battery deterioration. This research tackles this gap by creating a mobile monitoring system based on the Internet of Things (IoT), where both the threshold-based decision algorithm and notification logic are fully integrated into the mobile application, rather than the IoT hardware. The system employs an ESP8266 microcontroller exclusively for gathering data from a PZEM-017 DC sensor, transmitting raw readings to Firebase Realtime Database. A mobile application built on Flutter fetches data, checks it against user-defined thresholds (voltage, current, power), and produces immediate push notifications with anti-spam delays, audio alerts, and optional Telegram sending. Experimental outcomes from 30 measurement locations and 50 anomaly simulations indicate that the system reaches a voltage measurement error of 1.22% and a current error of 9.90% in comparison to a calibrated multimeter. The typical notification delay is 3.4 seconds, significantly less than the 10-second goal. In contrast to edge-based thresholding (on microcontroller), the mobile-centric method enables users to modify thresholds flexibly through the app without the need for hardware reprogramming, offers more extensive notification options (local pop-up, sound, Telegram), and streamlines IoT device upkeep. The specialized mobile interface provides enhanced customization and data logging features in comparison to standard platforms like Blynk or Telegram-based options.
Alzheimer’s Disease Classification using Lightweight Network MobileNet-V3 Wicaksana Wibowo, Muhammad Sadewa; Kriswantoro, M Cahyo; Purwati, Neni
Jurnal Teknoif Teknik Informatika Institut Teknologi Padang Vol 14 No 1 (2026): TEKNOIF APRIL 2026 (In Progress)
Publisher : ITP Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21063/jtif.2026.V14.1.47-58

Abstract

Alzheimer’s disease is a major public health concern characterized by progressive cognitive decline due to irreversible neuronal damage. Alzheimer’s disease represents a major global health concern in the twenty-first century. Although magnetic resonance imaging (MRI) is widely used for early diagnosis, manual interpretation is time-consuming and subject to variability. This study proposes an automated classification system based on the lightweight MobileNetV3 architecture to improve diagnostic efficiency. The model leverages depthwise separable convolutions to reduce computational complexity while maintaining high performance. MobileNetV3 models is then evaluated using appropriate metrics to assess the effectiveness of the proposed classification approach. Data augmentation techniques, including random rotation and flipping, are applied to enhance model generalization.  Experimental results demonstrate that the MobileNetV3 Small model achieves superior performance, with an accuracy and F1-score of approximately 0.94, compared to 0.90 for the MobileNetV3 Large model. These findings indicate that the compact architecture provides better efficiency and reliability for Alzheimer’s disease classification. The proposed approach is suitable for deployment in resource-constrained medical environments.
Classification of Daily Rainfall Using XGBoost with SMOTE in The Special Region of Yogyakarta Mulia Ramadani, Ayyesa Azzahra; Wijayanto, Danur
Jurnal Teknoif Teknik Informatika Institut Teknologi Padang Vol 14 No 1 (2026): TEKNOIF APRIL 2026 (In Progress)
Publisher : ITP Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21063/jtif.2026.V14.1.59-67

Abstract

Rainfall is a meteorological parameter that influences various sectors, such as agriculture, water resource management, and disaster mitigation; however, the process of classifying it still faces challenges, particularly due to imbalanced data across categories. This study aims to evaluate the performance of the XGBoost algorithm in classifying daily rainfall in the Special Region of Yogyakarta using NASA POWER data from 2000 to 2025, with input variables including air temperature, relative humidity, wind speed, and surface pressure. The evaluation was conducted using accuracy, precision, recall, and F1-score metrics to provide a more comprehensive overview of the model’s performance. The results indicate that the model achieved an accuracy of 0.82 and performed well in identifying light rain, and began to identify moderate rain, although not yet optimally; however, its performance remains limited for higher-intensity rain classes. This suggests that imbalanced data distribution remains a primary factor affecting model performance, making data quality and balance critical considerations in the development of rainfall classification models.
Analysis of Vegetation Changes in Siak Regency's Oil Palm Plantations Nurrahma, Elvira; Supriatna, Faiza Aulia; Sari, Inggit Lolita; roza, Emilia; Ramza, Harry
Jurnal Teknoif Teknik Informatika Institut Teknologi Padang Vol 14 No 1 (2026): TEKNOIF APRIL 2026 (In Progress)
Publisher : ITP Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21063/jtif.2026.V14.1.24-46

Abstract

Land cover change driven by the expansion of oil palm plantations has become a critical environmental issue in Siak Regency, Riau Province, necessitating periodic vegetation monitoring for sustainable land management. This study aimed to integrate Google Earth Engine and Quantum Geographic Information System to analyze vegetation changes in oil palm plantations using Sentinel-2 imagery from the 2022 to 2024 period. The methods involved processing Sentinel-2 Level-2A imagery through cloud masking, generating annual median-based composites, and calculating vegetation indices, including the Normalized Difference Vegetation Index, Enhanced Vegetation Index, and Soil Adjusted Vegetation Index. These indices were classified into several density classes to map land cover conditions, while changes in oil palm and non-oil palm areas were identified annually. All image processing stages were performed on a cloud computing platform, and the results were exported for spatial visualization and further analysis. The findings indicated that Siak Regency remained predominantly characterized by moderate to dense vegetation, particularly in the central and eastern regions. However, annual vegetation dynamics were detected in the western region, which was dominated by residential and industrial activities. In Koto Gasib District, there was a measurable increase in non-oil palm classes and expanding land cover changes over time. Overall, the integration of cloud-based processing and desktop geographic information systems proved effective in producing accurate spatial information for multitemporal analysis to support land use planning and oil palm plantation management in Siak Regency.

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