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Jurnal Informatika: Jurnal Pengembangan IT
Published by Politeknik Harapan Bersama Tegal
ISSN : 24775126     EISSN : 25489356     DOI : https://doi.org/10.30591
Core Subject : Science,
Computer Science & IT
The scope encompasses the Informatics Engineering, Computer Engineering and information Systems., but not limited to, the following scope: 1. Information Systems Information management e-Government E-business and e-Commerce Spatial Information Systems Geographical Information Systems IT Governance and Audits IT Service Management IT Project Management Information System Development Research Methods of Information Systems Software Quality Assurance 2. Computer Engineering Intelligent Systems Network Protocol and Management Robotic Computer Security Information Security and Privacy Information Forensics Network Security Protection Systems 3. Informatics Engineering Software Engineering Soft Computing Data Mining Information Retrieval Multimedia Technology Mobile Computing Artificial Intelligence Games Programming Computer Vision Image Processing, Embedded System Augmented/ Virtual Reality Image Processing Speech Recognition
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 28 Documents
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Search results for , issue "Vol 10, No 2 (2025)" : 28 Documents clear
Manfaat Blockchain pada Sistem Registrasi Tanah: Systematic Literature Review Suratmanto, Bekti; Emanuel, Andi Wahyu Raharjo
Jurnal Informatika: Jurnal Pengembangan IT Vol 10, No 2 (2025)
Publisher : Politeknik Harapan Bersama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30591/jpit.v10i2.6505

Abstract

The robust economic growth in Indonesia in the second quarter of 2023 indicates a projected population increase, leading to higher population density and driving the conversion of agricultural land. Land ownership has become a valuable source of capital, triggering intense competition. Land properties have emerged as valuable assets, emphasizing the importance of land registration as a process for recording ownership rights. The current centralized and manual land registration system faces challenges such as record duplications, unauthorized document reforms, and excessive departmental involvement. These weaknesses can result in pending cases, slow verification processes, and document manipulation.Digital transformation with blockchain technology is proposed as a solution for transparent, efficient, and legally certain land administration. This technology offers decentralized storage, resilience to changes, and peer-to-peer verification in transaction recording. While some countries have successfully implemented blockchain, others have faced failures due to environmental factors, state intervention, socio-political readiness, and institutional factors. In Indonesia, land conflicts have escalated, recording 562 cases from 1988 to July 2023. The lack of capacity and competence in local government human resources, coupled with suboptimal administration, complicates handling and hampers regional revenue. This research proposes a land registration framework with the implementation of blockchain as a solution to land administration issues in Indonesia.
Sistem Otomatisasi Pengendalian Perangkat Listrik Dan Penguncian Pintu Ruangan Menggunakan Komunikasi Bluetooth Rendah Energi Busran, Busran; Ilahi, Riski Pratama; Putra, Eko Kurniawanto; Warman, Indra; Mandarani, Putri
Jurnal Informatika: Jurnal Pengembangan IT Vol 10, No 2 (2025)
Publisher : Politeknik Harapan Bersama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30591/jpit.v10i2.7826

Abstract

This research aims to design and implement an automation system for controlling electrical devices and door locking based on an ESP32 microcontroller with support for Bluetooth Low Energy (BLE) technology. The system was realized in prototype form using the iTag device as a communication medium between the user and the ESP32. The main aim of this system is to increase energy efficiency and room security through automatic control of electrical devices and a door locking mechanism when the room is not in use. Registered iTag devices will be connected to the ESP32 through the BLE pairing process, enabling detection of the user's presence within a 3 meter radius. When a user is detected, the system automatically activates the electrical device and unlocks the door; instead, the device will be disabled and the door locked when the user leaves the area. System testing was carried out to evaluate the BLE signal range and system response to various environmental conditions. Test results show that the system is able to detect iTag devices up to a maximum distance of 12 meters without physical obstacles and 9 meters with wall obstacles. 
Perbandingan Metode KNN dan Naïve Bayes dalam Deteksi Tingkat Stres Berdasarkan Ekspresi Wajah Alamsyah, Malik Fajar; Wijaya, Ardi
Jurnal Informatika: Jurnal Pengembangan IT Vol 10, No 2 (2025)
Publisher : Politeknik Harapan Bersama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30591/jpit.v10i2.8513

Abstract

Stress is a feeling in which a person feels under pressure, overwhelmed, and has difficulty in dealing with a problem. Stress can be caused by various factors, such as academic pressure, work, personal problems, or social environment. If not addressed immediately, stress can have adverse effects on an individual's health, such as causing high blood pressure, heart disease, sleep disturbances, and a decreased immune system, which makes a person more vulnerable to various diseases. Therefore, monitoring stress levels is very important to prevent more serious negative impacts. Generally, stress detection is done through consultation with a psychologist, but this method has a subjective nature and requires a lot of time and money. Therefore, this research develops a computer vision-based stress detection system using OpenCV and Dlib, with K-Nearest Neighbors and Naïve Bayes algorithms. The data of 500 samples is divided into 80% training data and 20% test data. Features were extracted, and stress was classified into three levels: low, medium and high. Evaluation using k-fold cross-validation (n_split=10, random_state=42) based on accuracy, precision, recall, and F1-score. The results showed that K-Nearest Neighbors with k=5 excelled with 74% accuracy, 73% precision, 73% recall, and 73% F1-score. Meanwhile, Naïve Bayes only achieved 52% accuracy, 51% precision, 48% recall, and 41% F1-score. This shows that KNN is more effective in stress level classification. However, the accuracy of the model is still limited due to the small amount of training data. Parameter optimization and dataset addition are required to improve the overall system performance.
Analisis Data Warehouse Pada Perpustakaan Universitas XYZ Untuk Efisiensi Manajemen Menggunakan Metode Kimball 4 Langkah Uddin, Badie; Wijayadi, Eneng Mila Lestari; Maharani, Aprilia zahra; Barren, Kailal Wafa Auladal
Jurnal Informatika: Jurnal Pengembangan IT Vol 10, No 2 (2025)
Publisher : Politeknik Harapan Bersama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30591/jpit.v10i2.7323

Abstract

The XYZ University Library faces recurring book losses that affect the efficiency of library collection management. This study aims to develop a data-driven analysis system to identify loss patterns and support decision-making. The proposed solution uses a Data Warehouse approach with the Kimball Four-Step method and the ETL (Extract, Transform, Load) process. This methodology includes business process selection, grain declaration, dimension identification, and fact determination. Library transaction data from 2022 to 2024 was extracted, transformed, and loaded into a MySQL-based warehouse and visualized using Power BI. The analysis revealed that popular book categories, such as novels, were the most frequently lost. The visualization also enabled trend analysis based on time, book types, and user segments. The findings highlight a significant decline in loss cases, from 27 in 2022–2023 to 13 in 2023–2024, suggesting improved monitoring and management. The study demonstrates that the Data Warehouse approach effectively supports historical data analysis and provides accurate insights for sustainable library policy formulation.
HARMONI: Home Automation Module Berbasis Internet of Things dan Deep Learning Juniyanto, Muhammad Ma'sum; Aji, Bernadus Anggo Seno; Kamali, Muhammad Adib
Jurnal Informatika: Jurnal Pengembangan IT Vol 10, No 2 (2025)
Publisher : Politeknik Harapan Bersama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30591/jpit.v10i2.7109

Abstract

Alat listrik yang tidak dimatikan saat tidak digunakan seringkali menyebabkan terjadinya korsleting listrik yang berakibat bencana kebakaran. Selain itu, hal ini juga berpotensi dalam pemborosan penggunaan energi listrik. Orang-orang menyambungkan alat listrik langsung pada sumber listrik melalui stop kontak atau melalui jalur listrik kemudian dihubungkan dengan sakelar, dalam pengoperasiannya. Ini cukup efektif, namun, seringkali dialami kelalaian dalam mematikan atau mencabutnya, sehingga berpotensi membahayakan. Modul otomasi rumah berbasis IoT dan Deep Learning dibuat untuk melakukan digitalisasi dan otomasi sakelar. Terdiri dari mikrokontroler ESP32-S3 dan ESP32 sebagai pengendali sistem, modul relay sebagai sakelar otomatis, modul kamera untuk mendeteksi orang, integrasi Google Home dengan platform Sinric.Pro, website Mowny dengan integrasi protokol HTTPS. Mikrokontroler, modul, relay disusun pada papan-sirkuit-cetak. Website Mowny untuk mengontrol saklar dan monitoring ruangan. Pendeteksian keberadaan orang menggunakan YOLO sebagai pemicu otomasi sakelar. Model deteksi dimuat melalui API untuk diakses pada website. Pengujian sistem meliputi empat skenario untuk menyala-matikan sakelar secara digital dan otomatis, menghasilkan waktu respon sebagai berikut (dalam satuan detik): Google Home (±3,468), Google Assistant (±4,348), website Mowny (±1,042), dan otomasi deteksi objek (±19,375). Modul otomasi ini dapat mengontrol alat listrik dari secara digital dan otomatis, yang berdampak pada kemudahan pengoperasian sakelar ketika mengalami kelalaian mematikan alat listrik
Analisis Pengaruh Luas Area Pertanian Terhadap Prediksi Hasil Pertanian di Kebumen Menggunakan Metode Regresi Linier Ikhsanuddin, Rohmatulloh Muhamad; Rusvinasari, Dian
Jurnal Informatika: Jurnal Pengembangan IT Vol 10, No 2 (2025)
Publisher : Politeknik Harapan Bersama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30591/jpit.v10i2.8471

Abstract

Kebumen as an agricultural area whose people mostly play a role in agriculture has an important role in the southern part of Java. The size of the agricultural area will affect agricultural results, especially rice yields. Large agricultural areas will be beneficial for the community in their role as well as food self-sufficiency programs so that dependence on foreign agricultural production is reduced. However, agricultural conditions have not been managed maximally. It is hoped that agricultural yield predictions can help the government in making decisions on the management of agricultural areas in Kebumen. The linear regression method is one of the methods in data mining for data forecasting that relies on historical data so it requires agricultural yield data for the period from 2013 to 2019. The prediction process uses data on the area of the harvest which will influence the harvest in tons. Previous research shows that the linear regression method produces very small error values so it is very suitable for use in prediction cases. The aim of this research is to determine the predicted influence of harvested land area on the amount of harvest in Kebumen as analysis material. The stages in the linear regression method are determining the intercept and coefficient values with the a value of -317.231 and the b value of 6.0123, determining the regression equation to determine predictions, calculating the difference in predicted data, calculating the error value using MAPE with a result of 5,60%.
Transformasi Digital Sistem Kehadiran untuk Budaya Hybrid Work dengan TOGAF Framework Mareta, Arvin; Yohannis, Alfa
Jurnal Informatika: Jurnal Pengembangan IT Vol 10, No 2 (2025)
Publisher : Politeknik Harapan Bersama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30591/jpit.v10i2.8335

Abstract

Since the end of the COVID-19 pandemic in 2023, hybrid work or work from anywhere (WFA) methods have become increasingly popular. While this work culture offers flexibility, it also poses challenges for companies in monitoring employee attendance. This study proposes the implementation of the TOGAF Framework to design an attendance management system that supports a hybrid work culture. The design process begins with a preliminary phase to identify user needs and the limitations of traditional systems. The system is designed using TOGAF ADM (Architecture Development Method), covering phases such as Architecture Vision, Business Architecture, Information System Architecture, and Technology Architecture. Technologies such as IoT, GPS, facial recognition, and mobile applications are employed to ensure system flexibility and accuracy. Testing is conducted in two stages: Blackbox Testing to verify functionality against specifications, and User Acceptance Testing (UAT) to evaluate system usability in real-world conditions. The test results show that the system meets all specifications, improves operational efficiency by up to 40%, and ensures the security and accuracy of attendance data. The system is also designed for integration with other modules, such as payroll and HRIS, to support strategic decision-making. This approach provides an effective and adaptive solution for monitoring employee attendance, whether working remotely or in the office, and enhances productivity in modern work environments.
Optimalisasi Portofolio Saham Syariah Berbasis Prediksi Menggunakan Long Short-Term Memory (LSTM) Nurmawati, Erna; Abyasa, Rayhan; Putra, Raditya Amanta
Jurnal Informatika: Jurnal Pengembangan IT Vol 10, No 2 (2025)
Publisher : Politeknik Harapan Bersama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30591/jpit.v10i2.8421

Abstract

Saham merupakan salah satu jenis investasi aset finansial yang berpotensi untuk memberikan tingkat imbal balik yang tinggi sehingga menjadi salah satu instrument investasi yang popular. Salah satu jenis saham yang popular di Indonesia adalah saham syariah yang didukung kuat dengan ajaran agama islam (shariah compliant). Saham syariah mempunyai kinerja yang baik jika dibandingkan dengan saham konvensional ketika terjadi krisis keuangan ditandai dengan risiko indeks yang lebih kecil. Investor saham selalu menginginkan hasil timbal balik yang maksimal dengan risiko seminimal mungkin. Keinginan tersebut dapat tercapai dengan menyeleksi saham dengan return terbesar lalu melakukan optimalisasi pada potofolio saham. Salah satu metode seleksi saham yang dapat dilakukan adalah dengan memprediksi harga saham dengan menggunakan model LSTM pada indeks JII. Saham dengan return terbesar sesuai dengan hasil prediksi akan dimasukkan ke dalam satu portofolio yang akan dioptimalisasi dengan metode Mean-Variance (MV) dan Equal Weight (EW) yang akan diambil metode terbaik. Sebagai pembanding, portofolio dengan saham yang dipilih secara acak akan dibentuk dan dibandingkan hasilnya. Hasil penelitian menunjukkan portofolio yang dibentuk dengan menggunakan prediksi model LSTM dan metode optimalisasi MV memiliki keseimbangan dalam nilai mean return bulanan, standar deviasi bulanan, sharpe ratio bulanan, serta simulasi investasi sepanjang tahun 2023.

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