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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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Penentuan Mahasiswa Terbaik Dengan Menggunakan Metode Topsis (Teknik Urutan Preferensi Berdasarkan Kesamaan dengan Solusi Ideal) Ishak, Riswandi; Suryaditya, Rachmat; Nur Khasanah, Siti; Handayani, Popon
Infotek: Jurnal Informatika dan Teknologi Vol. 8 No. 2 (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.v8i2.30601

Abstract

Determining the best students is a crucial process in higher education to provide recognition and motivation to outstanding students. However, manual selection processes are often subjective and time-consuming. To address this issue, this study proposes the application of the TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) method in identifying the best students. TOPSIS was chosen due to its ability to handle multi-criteria decision-making problems by comparing alternatives based on their proximity to the positive ideal solution and distance from the negative ideal solution. This research was conducted on Communication Science students in the Digital Communication Visual class at Bina Sarana Informatika University, utilizing evaluation criteria such as Cumulative Achievement Index (IPK), number of scientific papers, non-academic achievements, and TOEFL scores. The collected data were analyzed using the steps in the TOPSIS method, including normalization of the decision matrix, weighting, calculation of distances to the positive and negative ideal solutions, and computation of preference values for each alternative. The benefit of using TOPSIS is that it considers multiple criteria simultaneously (such as GPA, research, achievements, TOEFL, attendance, etc.), ensuring that assessments are not solely based on a single dominant factor like GPA. The results indicate that Student E achieved the highest preference value of 0.462, ranking them as the top-performing student. The application of the TOPSIS method in this study proved effective in providing objective, efficient, and transparent results in the selection process of outstanding students. Therefore, this method is recommended for implementation in the selection process of outstanding students in higher education institutions
Sistem Rekomendasi Pemilihan Laptop Menggunakan Metode Content-Based Filtering Berbasis Spesifikasi Produk Pratiwi, Niken; Hartanti, Dwi; Arum Sari, Aprilisa
Infotek: Jurnal Informatika dan Teknologi Vol. 8 No. 2 (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.v8i2.30618

Abstract

The advancement of information technology has led to an increasing demand for computing devices, particularly laptops. The wide variety of options based on specifications, brands, and prices often makes it difficult for consumers to choose the device that best suits their needs. Therefore, this study aims to design a laptop recommendation system using the Content-Based Filtering (CBF) approach to provide relevant suggestions based on user preferences. The developed system applies Term Frequency-Inverse Document Frequency (TF-IDF) and Cosine Similarity methods to measure the similarity between key laptop features such as processor type, RAM capacity, storage, and graphics card. Laptop data was obtained through a web scraping process from trusted e-commerce websites and integrated into a web-based platform. Testing results show that the system can automatically generate personalized and highly relevant recommendations. The main contribution of this study is the development of an efficient content-based laptop recommendation system utilizing a combination of TF-IDF and Cosine Similarity techniques. In addition to facilitating faster decision-making in selecting a laptop, the system also demonstrates the practical application of machine learning-based recommendation technologies in the e-commerce sector. This research further provides a foundation for developing similar recommendation systems in other contexts that require content-based personalization approaches.
Integrasi Sistem Informasi Geografis Pada Sistem Pengaduan Masyarakat Berbasis Web Ajitama, Rahmadani; Widyaningsih, Pipin; Nurmalitasari
Infotek: Jurnal Informatika dan Teknologi Vol. 8 No. 2 (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.v8i2.30623

Abstract

Ngabenrejo Village, located in Grobogan Subdistrict, Grobogan Regency, Central Java Province, faces various public issues such as damaged roads, garbage accumulation, flooding, and more. The management of public complaints is still conducted manually, where residents must submit written reports to the village officials. This method often results in unrecorded complaints, difficulty in follow-up, and the risk of reports being overlooked due to the absence of a structured monitoring system. This research aims to design and develop a web-based public complaint system integrated with a Geographic Information System (GIS), referred to in Indonesian as Sistem Informasi Geografis (SIG). The system development method used is prototyping, supported by observation, interviews, and literature studies. The outcome of this research is a web-based complaint system that allows residents to submit complaints online along with the geographical location of the reported issue. Key features include complaint location mapping, email notifications to the complainants, and a dashboard for village officials to manage reports. This system is expected to improve the efficiency of public services and enhance transparency in handling community complaints, as each report is properly recorded, easily monitored, and can be systematically followed up.
Sistem Rekomendasi Resep Masakan Menggunakan Metode Content Based Filtering Berdasarkan Preferensi Pengguna Kurnia Sari, Vena; Hartanti, Dwi; Purwanto, Eko
Infotek: Jurnal Informatika dan Teknologi Vol. 8 No. 2 (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.v8i2.30625

Abstract

Food is a fundamental human need that plays a crucial role in supporting health. For housewives, cooking is a daily routine in preparing nutritious meals for their families. In the digital era, technology simplifies recipe searching, but the abundance of available recipes often makes it difficult for users to find ones that match their available ingredients. To address this issue, this study develops a recipe recommendation system based on content-based filtering. The dataset was collected from cookpad.com and includes recipe names, ingredients, cooking duration, and cooking instructions. The system is designed using a content-based filtering approach and cosine similarity to measure the relevance between user input and existing recipe data. Users simply input ingredients, seasonings, or types of dishes they have, and the system provides relevant recommendations. Testing results show that the system can accurately identify and recommend recipes based on keywords, including specific cases such as "Soto Ayam Bening." The recommendations generated are reasonably accurate and assist users in selecting the most suitable recipes according to their needs. This system is expected to offer a practical solution for users in determining appropriate meal choices based on the ingredients available at home
Sistem Peminjaman Alat Laboratorium Berbasis RFID dan IoT di Fakultas Kedokteran Gigi UMS Mulyanto, Hari; Maulindar, Joni; Lestari, Wiji
Infotek: Jurnal Informatika dan Teknologi Vol. 8 No. 2 (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.v8i2.30631

Abstract

Laboratories play a crucial role in supporting academic activities at health education institutions. However, inventory management at the Laboratory of the Faculty of Dentistry, Universitas Muhammadiyah Surakarta (UMS), is still conducted manually, leading to recording errors, service delays, and difficulties in real-time equipment monitoring. These issues hinder students from accessing information about the availability and location of equipment needed during practical sessions. This study aims to develop a laboratory equipment loan administration system using Radio Frequency Identification (RFID) technology integrated with the Internet of Things (IoT). The system was developed using the prototyping method, utilizing the ESP8266 and RFID RC522 sensor as the main components to support automated, contactless identification of equipment. The developed system is capable of digitally recording and monitoring the borrowing and returning of equipment in a structured and real-time manner. Testing results show that the system functions properly and meets user needs, although it has a limitation in RFID reading distance, with a maximum range of only 3 cm. This constraint presents a challenge for field implementation. Overall, the system has proven to improve efficiency, accuracy, and transparency in laboratory inventory management and supports the digitalization of technology-based equipment loan processes.
Implementasi Logika Fuzzy Mamdani Dalam Klasifikasi Kategori Berat Badan Berbasis IMT Ambon, Matelda Yunanta; Lili, Juniver Veronika; Bandhaso, Victor; Wati, Masna; Septiarini, Anindita
Infotek: Jurnal Informatika dan Teknologi Vol. 8 No. 2 (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.v8i2.30637

Abstract

Body Mass Index (BMI) is a common method used to classify body weight based on the ratio of weight to height. However, its accuracy is often questioned because it does not account for age and gender, which also influence body composition. This study implements the Mamdani fuzzy logic approach to classify body weight based on BMI while considering age and gender. The system utilizes fuzzy membership functions to dynamically determine categories such as Underweight, Normal, Overweight, and Obese, and is developed using the Python programming language with interactive visualizations. Testing results show that the system can provide more adaptive and personalized classifications. Defuzzification values, such as 59.48 for a BMI of 24.22, indicate a classification consistent with WHO standards—namely, the Normal category. The system also demonstrates that classification results may vary for the same BMI when age or gender differs, as illustrated in multi-demographic visualizations. The centroid defuzzification method produces stable and representative outputs. Evaluation results show high accuracy, consistency in rule base, and an ability to handle data uncertainty. Thus, this system serves as a more flexible alternative to conventional methods in body weight classification.
Evaluasi Kebergunaan Aplikasi Soeselo Online Menggunakan Metode System Usability Scale (SUS), Sauro-Lewis CGS, dan Adjective Rating Haries Anom Susetyo Aji Nugroho
Infotek: Jurnal Informatika dan Teknologi Vol. 8 No. 2 (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.v8i2.30680

Abstract

The development of information technology in the health sector encourages hospitals to adopt application-based registration systems to improve service efficiency. RSUD dr. Soeselo Tegal Regency developed the Soeselo Online application as a solution to reduce physical queues. However, the low rating and many user complaints on the Play Store indicate potential usability problems. This study aims to evaluate the usability of the Soeselo Online application from the user's perspective. The evaluation was conducted using the Usability Testing approach using System Usability Scale (SUS), Completion Rate, Sauro-Lewis Curved Grading Scale (CGS), and Adjective Rating methods. A total of 25 respondents participated in this study. The results of the analysis show that the application has an effectiveness rate of 97.6% which falls into the “Good” category, as well as an average SUS score of 70.3 which falls into the “B” category on the CGS and “Ok” on the Adjective Rating. This finding shows that although the application is quite effective to use, there are aspects of usability that need to be improved to achieve an optimal level of user satisfaction. The results of this study are expected to be the basis of recommendations for further development of the Soeselo Online application in order to improve the quality and user satisfaction of the application, as well as for the hospital in optimizing digital-based services.
Optimalisasi Prediksi Dalam Kelulusan Berbasis Deep Learning: Perbandingan Kinerja Multi-Layer Perceptron dan Deep Neural Network Dewi, Yumi Novita; Iqbal, Muhammad; Lisnawanty; Maisyaroh; Suhardjono
Infotek: Jurnal Informatika dan Teknologi Vol. 8 No. 2 (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.v8i2.30756

Abstract

Predicting on-time graduation is one of the significant challenges in education, aiming to model the factors influencing academic success. This study aims to compare the performance of two Deep Learning algorithms, namely Deep Neural Networks (DNN) and Multi-Layer Perceptron (MLP), in predicting on-time graduation. The methodology used involves evaluating both algorithms with various performance metrics, including Recall, Accuracy, Precision, AUC, MCC, and Cohen Kappa. The results show that DNN performs better in terms of Recall (0.9766), indicating its ability to capture most of the students who graduate on time, although its AUC (0.8625) and Precision (0.8803) are lower compared to MLP. On the other hand, MLP excels in Accuracy (0.8812) and Precision (0.9037), providing more stable results for MCC and Cohen Kappa, demonstrating a better balance in predicting students who graduate on time and those who do not. Overall, while DNN is more sensitive in capturing students who graduate on time, MLP performs better in terms of balance between accuracy and minimizing prediction errors. This study suggests using MLP if the primary priority is accuracy and prediction stability, while DNN is more suitable when the main focus is capturing as many students as possible who graduate on time.
Penerapan Model CRISP-DM Untuk Klasifikasi Tumor Otak Menggunakan Algoritma CNN Sulaiman, Hamdun; Yuliani, Yuri; Yanto; Al Farobi, Ibnu; Panggalih, Kukuh
Infotek: Jurnal Informatika dan Teknologi Vol. 8 No. 2 (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.v8i2.31014

Abstract

In general, a tumor is an abnormal tissue growth in the body that occurs due to uncontrolled cell division. Tumors can be benign (non-cancerous) or malignant (cancerous). Benign tumors tend to grow locally without spreading to other tissues, while malignant tumors can invade surrounding tissues and spread to other parts of the body through the bloodstream. A brain tumor is a mass or growth of abnormal tissue in or around the brain. Specifically, brain tumors can be primary (originating from the brain cells themselves or surrounding tissues, such as the meninges, pituitary gland, or cranial nerves) or secondary (metastasis from cancer originating from other parts of the body). The main problem today is that brain tumors have many types, therefore research on the classification of brain tumor types is very valuable today. In order to improve accuracy and also speed up the diagnosis process. The results of this study, brain tumor image data classification has been carried out using the CNN Algorithm method with the CRISP-DM data mining technique. The dataset consists of 3,554 datasets, but from the results of testing this algorithm has good performance with an accuracy of 98% with Evaluation and validation using the Confusion Matrix test parameters. and successfully classified human brains affected by tumors and those not affected by tumors, in addition to being able to classify 3 different types of tumors, namely glioma, meningioma, and pituitary.
Implementasi Internet Of Things (IOT) Untuk Monitoring Kualitas Tanah Tanaman Herbal Dengan Integrasi QR Code Gunawan, Indra; Sadali, Muhamad; Ahmadi, Hamzan; Wijaya, Lalu Kerta; Ermawati, Siti
Infotek: Jurnal Informatika dan Teknologi Vol. 8 No. 2 (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.v8i2.31101

Abstract

In everyday life, the utilization of herbal plants is still relatively low, due to ignorance of the types and benefits of herbal plants and many plants that wither or die. The factors of plant fertility such as soil moisture and soil temperature. Therefore, this research aims to create an alternative prototype for monitoring the soil quality of herbal plants by utilizing IoT (Internet of Things) technology with the integration of a QR Code as a marker of herbal plant identity at each monitoring location. The research method used is Research and Development (R&D). This research uses ESP32 as a microcontroller to drive electronic devices and soil PH sensors, soil moisture, soil temperature and air temperature and humidity connected to IoT devices. Soil quality data, such as moisture, temperature, and pH levels are collected in realtime and converted into QR codes. This data is then sent to the server for processing and analysis, providing useful information for plant owners to effectively manage soil quality. The results showed that the soil pH, soil moisture, soil temperature and air temperature and humidity measuring instruments can work well and have an accuracy rate of 90% and the data is successfully displayed to the webserver.

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