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Infotek : Jurnal Informatika dan Teknologi
Published by Universitas Hamzanwadi
ISSN : 26148773     EISSN : 26148773     DOI : -
Core Subject : Science, Engineering,
Computer Science & IT Control & Systems Engineering Engineering
INFOTEK Jurnal Informatika dan Teknologi Fakultas Teknik Universitas Hamzanwadi selanjutnya disebut Jurnal Infotek (e-ISSN: 2614-8773) merupakan Jurnal yang dikelola oleh Fakultas Teknik Universitas Hamzanwadi yang mempublikasikan artikel ilmiah hasil penelitian atau kajian teoritis (invited authors) dalam bidang (1) keilmuan informatika, (2) Rekayasa Perangkat Lunak, (3) Multimedia, (4) Jaringan Komputer, (5) Data Mining, (6) Image Processing, (7) Komputer Vision, (8) Mikrokontroller, (9) Robotik, (10) IOT yang belum pernah dipublikasikan. Jurnal Infotek diterbitkan oleh Fakultas Teknik Universitas Hamzanwadi dua kali setahun yaitu pada bulan Januari dan Juli. Jurnal Infotek Telah Terindeks pada Google Scholar.
Arjuna Subject : Ilmu Komputer (semua kategori) - Perangkat Lunak
Articles 388 Documents
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Perancangan Aplikasi KWH Meter Dan Sistem Monitoring Konsumsi Listrik Berbasis Internet Of Things Untuk Kamar Kos-Kosan Indra Gunawan; Muhamad Sadali; Hamzan Ahmadi; Jumawal
Infotek: Jurnal Informatika dan Teknologi Vol. 8 No. 1 (2025): Infotek : Jurnal Informatika dan Teknologi
Publisher : Fakultas Teknik Universitas Hamzanwadi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29408/jit.v8i1.28046

Abstract

The use of electrical energy in boarding houses is currently quite important for the residents. However, in its use there are often problems related to fees between boarding house residents which are within 1 KWH Meter, needs between boarding house residents with unequal electricity usage and bill information can be monitored by boarding house owners. Therefore, we need a system that can monitor and calculate the cost of electricity usage in boarding houses in real-time. This research aims to develop a digital KWH meter application design and IoT (Internet of Things) based electrical energy consumption information using ESP8266, PZEM sensors, web server. The results of this research are a KWH prototype that is able to monitor electrical energy consumption in boarding houses in real-time and calculate electricity costs based on the applicable electricity tariffs where the PZEM sensor is used as a tool to measure electrical energy consumption in boarding houses connected to the ESP8266 module to transmit data to the server via WiFi. Then, the data received is processed and presented in the form of values and a dashboard display on the web application in the form of voltage, current and energy data. With this Internet of Things-based electrical energy consumption information application, it is hoped that boarding house residents can monitor electrical energy usage more easily and help in determining payments for the electricity consumption used.
Implementasi Algoritma K-Means Untuk Rekomendasi Pengadaan Buku Ardhianto, Aan; Dwi Hartanti; Joni Maulindar
Infotek: Jurnal Informatika dan Teknologi Vol. 8 No. 1 (2025): Infotek : Jurnal Informatika dan Teknologi
Publisher : Fakultas Teknik Universitas Hamzanwadi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29408/jit.v8i1.28134

Abstract

One of the main challenges faced by libraries is determining the procurement of book collections that align with the needs and interests of borrowers. At the Sragen Regency Archives and Library Service, book procurement is often based on intuition or unstructured requests, resulting in many books that are less popular among visitors. This leads to a low number of book borrowings, meaning the library cannot provide optimal services. Based on this issue, the author attempts to cluster the book borrowing data for the year 2023 from the Sragen Regency Archives and Library Service by age group, book categories, number of borrowings, number of titles, and number of copies using data mining techniques with the k-means clustering algorithm. For the initial data processing, the author uses the Min-Max normalization method. After normalization, k-means is calculated with 3 clusters, followed by finding the optimal cluster using the elbow method, silhouette, and gap statistics. The results of the optimal cluster are compared with the results from the Dunn Index method. The research identifies three clusters: Cluster 1 contains book groups with low interest, consisting of 7 categories: General Works, Social Sciences, Language, Pure Sciences, Applied Sciences, Arts and Sports, History and Geography; Cluster 2 contains book groups with moderate interest, consisting of 2 categories: Philosophy and Psychology, Religion; and Cluster 3 contains the book group with the highest interest, consisting of 1 category: Literature
Implementasi Discovery Learning untuk Meningkatkan Kecerdasan Digital Mahasiswa Lathifah, Afra; Kurnia, Ulfa Isni; Hertati, Elvani
Infotek: Jurnal Informatika dan Teknologi Vol. 8 No. 1 (2025): Infotek : Jurnal Informatika dan Teknologi
Publisher : Fakultas Teknik Universitas Hamzanwadi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29408/jit.v8i1.28149

Abstract

The digital era demands students to have comprehensive digital intelligence, including students' ability to access, manage, analyze, and present digital information, alongside a grasp of digital ethics and safety. This research seeks to examine how the Discovery Learning approach influences the enhancement of students' digital intelligence. The study employed a pre-experimental design utilizing a one group pretest-posttest, which included 31 students in their fifth semester from the Faculty of Teacher Training and Education. The results showed a significant increase in students' digital intelligence. Statistical analysis produced a significance probability of p = 0.0000 (p <0.05), an average increase of 25.01%. Through the stages in this model, students are given the opportunity to not be passive in the learning process, so they can have critical thinking skills, problem solving, and digital skills needed in today's digital era. Further research should explore other elements, including lecturer readiness, availability of digital learning resources, and supportive institutional policies
Implementasi Aplikasi Mobile untuk Meningkatkan Keselamatan Turis di Tujuan Wisata Berisiko Tinggi Sulistiyanta, Nur Linda; Ignatius Wahyu Widodo; -, Suyoto
Infotek: Jurnal Informatika dan Teknologi Vol. 8 No. 1 (2025): Infotek : Jurnal Informatika dan Teknologi
Publisher : Fakultas Teknik Universitas Hamzanwadi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29408/jit.v8i1.28192

Abstract

The competitiveness of smart tourism destinations depends on the natural and cultural attractions, infrastructure, and quality of services offered, including security and safety as the main factors in choosing a tourist destination by tourists. The purpose of this study is to determine mobile applications to improve tourist safety in high-risk tourist destinations. This research is a systematic review (Systematic Literature Review). Data is processed and presented in the form of a description. The study results show that a mobile application can be an alternative to improve tourist safety, especially in high-risk tourist destinations. A mobile application can be developed to improve tourist safety, especially in high-risk tourist destinations so that they feel satisfactory service. Satisfactory service can certainly provide a positive experience for tourists. The application can also be developed with the application of artificial intelligence and various features to improve user experience. These services can be in the form of safe transportation route features for tourist destinations such as medical tourism. Mobile applications with real-time features can also make it easier for tourism managers to monitor tourists so that they continue to carry out activities safely. Therefore, the application can also be made specifically to overcome disasters and can be a tool to provide information to tourists, increase their awareness of risks, and improve their preparedness for disasters
Penerapan Algoritma K-Means Untuk Klasterisasi Produktivitas Tanaman Jahe Nayla Salsabila; Karina Aulisari; Hani Zulfia Zahro
Infotek: Jurnal Informatika dan Teknologi Vol. 8 No. 1 (2025): Infotek : Jurnal Informatika dan Teknologi
Publisher : Fakultas Teknik Universitas Hamzanwadi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29408/jit.v8i1.28195

Abstract

Sumenep Regency is one of the regions that produces ginger plants in East Java province, and has become one of the mainstays of the community's economy. However, there are obstacles faced, namely the size of the planting area, erratic weather changes and the lack of modern technology in ginger cultivation which are the main causes in affecting crop yields and product quality. This study aims to implement data mining using a web-based K-Means clustering algorithm to group ginger-producing areas in Sumenep Regency. The data used was 108 data covering the area of harvest areas and the amount of production per sub-district from 2020 to 2023 taken from the official website of the Central Statistics Agency (BPS) of Sumenep Regency. The K-Means algorithm was chosen because of its advantages in efficiently managing large amounts of numerical data, helping to recognize distribution patterns such as harvest area and production amount to produce the right cluster, its relatively simple implementation and easy-to-interpret clustering results. The results of the study show that the Sumenep Regency area can be grouped into 2 clusters based on ginger plant productivity, namely cluster 1 with 104 sub-districts and cluster 2 with 4 sub-districts. This research is expected to help farmers and the government in identifying areas with high and low productivity, optimizing land and resource use, and increasing productivity and income
Klasterisasi Daerah Rawan Bencana Alam Menggunakan Algoritma K-Means Michael Kevin Adinata; Ali Mahmudi; Yosep Agus Pranoto
Infotek: Jurnal Informatika dan Teknologi Vol. 8 No. 1 (2025): Infotek : Jurnal Informatika dan Teknologi
Publisher : Fakultas Teknik Universitas Hamzanwadi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29408/jit.v8i1.28196

Abstract

East Java is a province with high vulnerability to disasters, such as floods, landslides, earthquakes, and strong winds, which have an impact on material losses, casualties, and deterioration of socio-economic conditions, especially in rural areas. The lack of mitigation strategies and resource allocation worsens disaster management. This study aims to classify disaster data using the K-Means algorithm to overcome the limitations of descriptive analysis conducted by BPBD East Java. The data used includes 1125 disaster events with variable disaster frequency, total damage, and the number of casualties per sub-district in East Java districts and cities during 2021-2022, obtained from the official website of the East Java BPBD. The K-Means algorithm was chosen because of its efficiency in managing big data and its flexibility in cluster formation. The results of the study show that in 2021, the region in East Java is divided into three clusters based on the level of disaster risk: Cluster 1 (low risk) with 192 sub-districts, Cluster 2 (medium risk) with 35 sub-districts, and Cluster 3 (high risk) with 10 sub-districts. In 2022, significant changes were seen in Cluster 1, which includes 462 sub-districts, Cluster 2 with 20 sub-districts, and Cluster 3 with 11 sub-districts. The results of this study are expected to support the government's decision-making priorities, especially in disaster management and resource allocation based on risk levels
Implementasi Metode RAD pada Sistem Informasi Manajemen Penelitian, Pengabdian Masyarakat dan Luaran Siska Narulita; Sekarlangit; Ahmad Nugroho; M. Zakki Abdillah
Infotek: Jurnal Informatika dan Teknologi Vol. 8 No. 1 (2025): Infotek : Jurnal Informatika dan Teknologi
Publisher : Fakultas Teknik Universitas Hamzanwadi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29408/jit.v8i1.28232

Abstract

Higher education institutions frequently struggle to manage research, community service, and output data. Manual data and information management is prone to mistakes. It is challenging for leaders and stakeholders to monitor and evaluate performance. This study intends to address these issues by offering a platform that meets the needs of the Community Service Research Institute (LPPM), leaders, and stakeholders. The primary features produced are statistics on research, service, and output data, as well as report generating automation. This study employs RAD to create the system. The system developed has been declared functional based on the results of blackbox testing with equivalent partitions. According to the 91% usability testing estimate, users are pleased with the information system built, and the system is simple to use. This system's specific benefits and potential implications include improved data management efficiency, consolidated data access, accreditation and reporting support, and higher institutional reputation
Implementasi Internet of Things (IoT) Untuk Sistem Pemantauan Kebakaran Dini Dengan Notifikasi Telegram dan Alarm Zaenuar Erfandi; Hartanti, Dwi; Maulindar, Joni
Infotek: Jurnal Informatika dan Teknologi Vol. 8 No. 1 (2025): Infotek : Jurnal Informatika dan Teknologi
Publisher : Fakultas Teknik Universitas Hamzanwadi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29408/jit.v8i1.28248

Abstract

Fire is a serious threat that can cause major losses, both material and non-material. This research aims to develop an Internet of Things (IoT) based fire monitoring system at the Tangen District Office to detect fires early. This system uses smoke, temperature and fire sensors integrated with a NodeMCU microcontroller to process data in real-time. Data from sensors is analyzed to detect signs of fire, and notifications are sent instantly via the Telegram application and accompanied by alarm activation. Tests show that the system has a detection accuracy rate of up to 95% in detecting various types of fire media, such as wood, paper and plastic, with an effective sensor distance of up to 20 cm. This system is able to reduce response time by up to 70% compared to conventional methods, increasing the readiness of officers in handling fires. It is hoped that the results of this research can minimize the risk and impact of fire, as well as significantly increase building safety
Rancang Bangun Sistem TOEFL Untuk Analisis Kelemahan Peserta Dengan Penerapan Algoritma K-Means Clustering Nabella, Arika Risma Nabella; Hani Zulfia Zahro’; Yosep Agus Pranoto
Infotek: Jurnal Informatika dan Teknologi Vol. 8 No. 1 (2025): Infotek : Jurnal Informatika dan Teknologi
Publisher : Fakultas Teknik Universitas Hamzanwadi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29408/jit.v8i1.28260

Abstract

English proficiency is a critical skill across various sectors, particularly in educational and professional contexts. The TOEFL test assesses English language skills, covering aspects such as Reading, Listening, Speaking, and Writing. However, TOEFL results often only provide a total score without detailed insights into participants' weaknesses. To address this, this study utilizes the K-Means Clustering algorithm for its simplicity, efficiency in processing multidimensional data, and ability to produce statistically meaningful groupings. The research aims to identify the weaknesses of TOEFL participants at the Language Laboratory of ITN Malang. The dataset comprises scores from 520 students across Reading, Structure and Written Expression, and Listening sections. This method classifies participants into three primary clusters: Reading Boosters (C1), Grammar Builders (C2), and Listening Improvers (C3). The clustering process involves randomly selecting initial centroids, calculating distances using the Euclidean Distance formula, and iterating until cluster stability is achieved. The analysis results show that 36.54% of participants fall into C1, 41.35% into C2, and 22.21% into C3. The implementation of this algorithm offers valuable insights for developing more effective learning programs.
Pengembangan Sistem untuk Deteksi dan Identifikasi Lokasi Kecelakaan pada Lansia sebagai Bentuk Peningkatan Keselamatan berbasis Internet of Things (IoT) Mandala Putra, Hadian; 'Alimuddin; Suhartini; Wahyu Rizki
Infotek: Jurnal Informatika dan Teknologi Vol. 8 No. 1 (2025): Infotek : Jurnal Informatika dan Teknologi
Publisher : Fakultas Teknik Universitas Hamzanwadi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29408/jit.v8i1.28263

Abstract

fainting, which can be fatal to their health and quality of life. The elderly population in Indonesia continues to increase, creating an urgent need for technological solutions to effectively monitor their health conditions. This study aims to design and develop an Internet of Things (IoT)-based accident detection and identification system for the elderly. The system utilizes several sensors, including an accelerometer, pulse sensor, and GPS, to monitor the physical conditions of the elderly and track their location in real-time. The research method employed is the Research and Development (R&D) method. Testing was conducted on a non-elderly subject by simulating falls with several scenarios, repeated multiple times. When the sensors detect an accident, the system automatically sends notifications to the user’s or the elderly family’s smartphone, enabling quick actions that can prevent further impacts. The results showed that the system achieved a detection accuracy rate of 91% in identifying falls and weak pulse conditions out of 30 test trials

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