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Infotech: Journal of Technology Information
Published by STMIK Widuri
ISSN : 26205181     EISSN : 24602108     DOI : https://doi.org/10.37365/it
Core Subject : Science,
Computer Science & IT
Jurnal Infotech adalah jurnal ilmiah yang berisi hasil penelitian yang ditulis oleh dosen, peneliti dan praktisi. Jurnal ini diharapkan untuk mengembangkan penelitian dan memberikan kontribusi yang berarti untuk meningkatkan sumber daya penelitian di bidang Teknologi Informasi dan Ilmu Komputer. Infotech diterbitkan oleh Lembaga Penelitian dan Pengabdian Kepada Masyarakat (LPPM) STMIK Widuri dengan akses terbuka. Setiap artikel yang diterbitkan memiliki pengidentifikasi objek digital (DOI). ISSN 2620-5181 (Online) ISSN 2460-2108 (Print)
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 228 Documents
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PERBANDINGAN ALGORITMA UNTUK PREDIKSI SKOR LITERASI MEMBACA SISWA SD DENGAN PEMILIHAN GLM PADA KERANGKA CRISP-DM Hendro Nindito; Maria Brigitta Melodi Santoso; Clara Zefanya Putri Junaidi
Infotech: Journal of Technology Information Vol 12, No 1 (2026): JUNI (In Progress)
Publisher : ISTEK WIDURI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37365/jti.v12i1.587

Abstract

Reading literacy is a fundamental competency that serves as a benchmark for the quality of primary education in Indonesia. The 2022 National Assessment conducted by the Ministry of Education, Culture, Research, and Technology revealed that most primary school students remain in the moderate to low proficiency categories, indicating the urgent need for data-driven strategies to improve literacy outcomes. This study aims to develop a predictive model for primary school students’ reading literacy scores by employing three algorithms: Neural Network (NN), Support Vector Machine (SVM), and Generalized Linear Model (GLM). The analysis followed the CRISP-DM framework, utilizing 2022 National Assessment data that includes school condition variables, availability of facilities, and related literacy indicators. The evaluation results indicate that GLM achieved the best performance, with R² = 0.988, MSE = 0.000322, and MAE = 0.014151, outperforming NN and SVM. This result indicates that the relationships between variables tend to be linear after preprocessing, making GLM more effective under the applied data transformation strategy. The implemented GLM model accurately predicted literacy scores on new data, demonstrating potential for adaptive learning module design and targeted resource allocation. These findings provide practical contributions for schools and policymakers in formulating more effective strategies to enhance reading literacy among primary school students in Indonesia. It is also important to consider that some predictor variables may have inherent relationships with the target variable, which can influence predictive performance.
RANCANG BANGUN SISTEM INFORMASI KONTROL INVENTORI DENGAN METODE SYSTEM DEVELOPMENT LIFE CYCLE (SDLC) Rouli Doharma; Reza Rizki
Infotech: Journal of Technology Information Vol 12, No 1 (2026): JUNI (In Progress)
Publisher : ISTEK WIDURI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37365/jti.v12i1.607

Abstract

PT. XYZ is one of the leading private banks in Indonesia. Having launched its operations in Indonesia in 2019, the bank offers a wide range of banking products and services. PT. XYZ also faces challenges in managing the inventory of goods used in its daily operations. Based on research conducted at PT. XYZ’s headquarters, particularly within the inventory management department, the company frequently encounters difficulties in determining and controlling inventory levels. Therefore, there is a need for an inventory control information system that can assist PT. XYZ in optimizing inventory management using the System Development Life Cycle (SDLC) methodology, which will be primarily implemented within the General Affairs (GA) division at the headquarters. It is hoped that this system will assist users in inventory management and provide accurate, effective, and efficient inventory information, particularly for the GA division at PT. Xyz. The inventory control information system will streamline transaction activities and inventory control. Data collection methods in this study included interviews with sources, literature review, and observation by monitoring the research subject from start to finish. The system developed can generate an inventory control design and information system using the System Development Life Cycle (SDLC) method to calculate inventory levels and provide accurate calculations for the warehouse, as well as build an information system to track inventory levels, safety stock levels, and reorder points. This makes it possible to estimate when to place a reorder.
DIGITAL TWIN DRIVEN SMART CAMPUS DEVELOPMENT: CONCEPTS, CHALLENGES AND OPPORTUNITIES Jusia Amanda Ginting; I Gusti Ngurah Suryantara; Raphael Benedict Manuel
Infotech: Journal of Technology Information Vol 12, No 1 (2026): JUNI (In Progress)
Publisher : ISTEK WIDURI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37365/jti.v12i1.595

Abstract

This study aims to examine the development and implementation of digital twin technology in supporting smart campus ecosystems through a Systematic Literature Review approach. The study focuses on identifying technological trends, implementation opportunities, and various challenges that arise in the adoption of digital twin systems within higher education environments. The SLR method was conducted using the PRISMA framework to ensure a transparent and systematic article selection process. A total of 765 initial articles were identified from various academic databases with a publication range from 2015 to 2025. After undergoing the screening and selection process, 36 relevant articles were obtained for further analysis. The results show that digital twin technology has significant potential in supporting smart campus management through real-time monitoring of campus infrastructure, predictive maintenance of facilities, energy management optimization, and data-driven decision-making in university operations. In addition, this review also identifies several challenges in implementing digital twin systems, including data integration complexity, cybersecurity risks, high infrastructure investment requirements, and organizational readiness in facing digital transformation.
REKOMENDASI APLIKASI PEMBELIAN EMAS DIGITAL BERBASIS ANALISIS SENTIMEN MENGGUNAKAN MODEL TRANSFORMER BERT Rhisa Adika Putri; Jessicania Windari
Infotech: Journal of Technology Information Vol 12, No 1 (2026): JUNI (In Progress)
Publisher : ISTEK WIDURI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37365/jti.v12i1.604

Abstract

The development of digital gold-based financial services in Indonesia has shown significant growth; however, the quality of user experience remains a critical factor in ensuring long-term application usage. Although thousands of user reviews are available across various digital platforms, this information has not been fully utilized as a foundation for service improvement. This study aims to conduct an in-depth analysis of user sentiment and generate application development recommendations based on real user perceptions and experiences. The methodology includes collecting a large number of user reviews, performing text preprocessing, and applying sentiment classification using several machine learning models. IndoBERT demonstrated the best performance with an accuracy of 0.88, precision of 0.84, recall of 0.88, and F1-score of 0.86 based on 7,113 test data, indicating strong capability in identifying positive and negative sentiment, although neutral sentiment remains challenging. The analysis reveals that positive sentiment is associated with the ease of investing in gold, intuitive interface design, and overall user convenience. Conversely, negative sentiment is predominantly linked to technical issues such as transaction errors, login disruptions, slow authentication, and system instability. The WordCloud visualization also highlights the dominance of terms such as error, login, and verification. Based on these sentiment patterns, the study proposes several priority recommendations, including enhancing system stability, optimizing authentication mechanisms, refining transaction flows, and strengthening customer support. This study provides a structured mapping of user issues that can serve as a strategic foundation for developing more reliable, secure, and user-aligned digital gold financial applications.
SISTEM PENDUKUNG KEPUTUSAN PEMILIHAN KARYAWAN TERBAIK MENGGUNAKAN METODE TOPSIS Rafli Abadi Ikhwan; Arafat Febriandirza
Infotech: Journal of Technology Information Vol 12, No 1 (2026): JUNI (In Progress)
Publisher : ISTEK WIDURI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37365/jti.v12i1.588

Abstract

In the workplace, selecting the best employee is a crucial part of maintaining motivation, productivity, and fostering a healthy work culture. However, this process is often subjective, slow, and inefficient when carried out manually. Therefore, this research aims to develop a Decision Support System (DSS) for selecting the best employee using the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method at Kopi Gram company. The TOPSIS method was chosen for its ability to evaluate alternatives based on their proximity to the ideal positive solution and distance from the ideal negative solution. The system considers multiple criteria, including Teamwork, Responsibility, Attendance, Customer Satisfaction, and Loyalty. The system was developed as a web-based application using PHP as the programming language and MySQL as the database. The implementation results show that the TOPSIS method can provide more objective, transparent, and efficient employee rankings compared to manual methods. This system is expected to assist management in making more accurate decisions and enhance employee trust in the assessment process.
SISTEM OPTIMASISASI PERUMAHAN BERBASIS SMART HOME UNTUK MENGHEMAT ENERGI LISTRIK Buang Abdullah; Asep Suryadi
Infotech: Journal of Technology Information Vol 12, No 1 (2026): JUNI (In Progress)
Publisher : ISTEK WIDURI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37365/jti.v12i1.610

Abstract

Electrical energy waste in the residential sector is often caused by conventional electrical systems that rely on manual control without real-time monitoring, as identified in Purna Bakti Housing with weekly token costs reaching IDR 100,000. This research aims to design and implement a Smart Home-Based Housing Optimization System to save electrical energy through an Internet of Things (IoT) approach. The system is built using the ESP32-S3 microcontroller as the control center, the ZMPT101B sensor for monitoring power consumption, and relay modules as device control actuators. A control algorithm based on if-else logic and scheduling is implemented to automate device operation based on load and time. The research method uses Research and Development (R&D) with the ADDIE model, covering the stages of analysis, design, development, implementation, and evaluation. Test results show that the system can monitor energy consumption in real-time, send notifications via Telegram Bot, and control devices automatically. The system proves effective in identifying waste patterns and reducing energy consumption, thereby potentially lowering monthly electricity costs. Thus, the developed system can be a practical and affordable solution for improving energy efficiency in residential environments.
IMPLEMENTASI ALGORITHMA CONVOLUTIONAL NEURAL NETWORK (CNN) PADA SOFTWARE PENDETEKSI TUMOR OTAK BERDASARKAN MAGNETIC RESONANCE IMAGE (MRI) Akhmad Rizal Dzikrillah; Fadhlina Shifa Hanum; Fadhillah Al Ghifari; Pancatatva Hesti Gunawan
Infotech: Journal of Technology Information Vol 12, No 1 (2026): JUNI (In Progress)
Publisher : ISTEK WIDURI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37365/jti.v12i1.594

Abstract

A brain tumor is an abnormal growth of brain cells that occurs in or around the brain and can be life-threatening. A common technique used to diagnose a brain tumor is through the analysis of MRI images of the patient's brain by a radiologist. Deep learning technology can be used to generate a classification model for the presence of a brain tumor based on a dataset of Magnetic Resonance Images (MRIs) of patients in a hospital. This study aims to create software that can diagnose the presence of a brain tumor based on a patient's MRI images. The software implements a classification model using a Convolutional Neural Network (CNN) algorithm. The CNN classification model has an accuracy of up to 0.96 with a precision of 1.00, a recall of 0.92, and an F1-Score of 0.96 for the MRI category diagnosed with a tumor and with a precision of 0.92, a recall of 1.00, and an F1-Score of 0.96 for the MRI category diagnosed with a non-tumor. The model also does not experience overfitting based on epoch evaluation. The results of the diagnosis of the presence of brain tumors by the software always showed agreement with the results of the radiology expert's diagnosis in all research samples.
SISTEM PAKAR DIAGNOSIS PENYAKIT PADA KUCING MENGGUNAKAN METODE FORWARD CHAINING BERBASIS ANDROID Raihan Fasya; Karno Diantoro; Samroh Samroh; Ahmad Soderi; Ilham Aditya Chandra
Infotech: Journal of Technology Information Vol 12, No 1 (2026): JUNI (In Progress)
Publisher : ISTEK WIDURI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37365/jti.v12i1.602

Abstract

This research was conducted at PT Amazon Pet Indo, a company specializing in pet care and supplies, particularly for cats. The issue addressed is the public’s lack of knowledge regarding cat diseases, including types of diseases, symptoms, and treatment methods. Additionally, there is currently no expert system application available to help cat owners perform initial diagnoses on their own. As a solution, an Android-based expert system application for diagnosing cat diseases was developed using the Java programming language with the Forward Chaining inference method. This method works by matching the symptoms selected by the user with a knowledge base of rules embedded in the system. The application is designed to help users recognize symptoms, identify possible diseases, and obtain information on prevention and initial treatment. Based on black-box testing results, the application is capable of providing diagnostic results consistent with the symptoms entered in the consultation menu and runs smoothly on Android devices. This application can help users obtain information quickly and accurately, enabling them to take appropriate preventive measures and provide initial treatment.
PERANCANGAN SINGLE AXIS SOLAR TRACKING TERINTEGRASI IoT GUNA MENINGKATKAN KAPASITAS PANEL SURYA Rosalina Rosalina; Tole Sutikno; Abdul Fadlil
Infotech: Journal of Technology Information Vol 12, No 1 (2026): JUNI (In Progress)
Publisher : ISTEK WIDURI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37365/jti.v12i1.589

Abstract

The global energy crisis is a complex phenomenon involving an imbalance between increasingly limited energy supplies and ever-rising demand, driven by geopolitical dynamics, shifts in the energy market, and the challenges of transitioning to renewable energy sources. In a country as vast as Indonesia, the potential for developing renewable energy such as solar, hydro, wind, and geothermal energy is significant. This potential presents an opportunity for Indonesia’s resilience in the national energy sector. Utilizing solar energy through solar panels requires an optimized system to maximize the generated electrical power. This research aims to design an IoT-integrated single-axis solar tracking system using an ESP32 microcontroller to enhance the capacity of solar panels. The research methodology includes designing an algorithm to control the rotation angle of the solar tracker using an LDR sensor to determine the intensity of the sun’s electromagnetic waves and to drive the servo motor so that the panel is perpendicular to the sunlight. Solar panel temperature monitoring is performed using a MAX6675 sensor. For real-time current and voltage measurements, an INA219 sensor is used. The results of the solar panel data, processed adaptively by a control algorithm based on sensor data, are displayed on the LCD screen and transmitted to the Blynk IoT platform. The research findings indicate that the maximum power capacity recorded on the Blynk monitoring app was 1.75 watts at 12:00 PM, when solar intensity was at its peak. After 12:00 PM, power generation began to decline in tandem with the decrease in sunlight intensity in the afternoon. The data on power generation from this single-axis solar tracking system indicates that the use of this algorithm is capable of increasing the power absorbed by the solar panels and optimizing the use of solar energy.
ANALISIS KEPUASAN MAHASISWA TERHADAP LAYANAN PENDIDIKAN MENGGUNAKAN METODE SERVICE QUALITY Utari Sekar Putri; Dieni Mulyasari
Infotech: Journal of Technology Information Vol 12, No 1 (2026): JUNI (In Progress)
Publisher : ISTEK WIDURI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37365/jti.v12i1.612

Abstract

Improving the quality of higher education services is a key factor in supporting students’ academic success and achieving learning standards aligned with Outcome-Based Education (OBE). This study aims to analyze students’ satisfaction levels with educational services, including administrative services, academic facilities, and teaching quality, using the Service Quality (ServQual) method. Research data were obtained through the distribution of questionnaires to active students to measure the level of expectations and perceptions regarding the services received. The analysis was conducted by calculating the gap between perceptions and expectations in each ServQual dimension, namely Tangibles, Reliability, Responsiveness, Assurance, and Empathy. The research results indicate that the majority of students fall into the “satisfied” category regarding the educational services provided. The combined percentage of ‘Satisfied’ and “Very Satisfied” categories reached 92.32%, while the dissatisfaction rate was only 1.67%. Nevertheless, the gap analysis results indicate that there are several aspects that still require attention, particularly in the dimensions of Responsiveness (service responsiveness) and Tangibles (physical evidence/supporting facilities), which show relatively higher gap values compared to the other dimensions. These findings indicate that the ServQual method is effective for comprehensively evaluating the quality of educational services and identifying areas for improvement. The research results are expected to serve as a basis for program administrators and educational institutions in formulating strategic policies aimed at continuously improving service quality and student satisfaction.

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