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Penelitian ini bertujuan merancang sistem informasi penjualan berbasis web untuk meningkatkan efektivitas pencatatan transaksi pada Toko Bangunan Subur Kaliwungu yang sebelumnya masih dilakukan secara manual. Permasalahan utama yang dihadapi meliputi pencatatan yang tidak efisien, kesulitan pencarian data, serta kurangnya ketepatan dalam laporan keuangan. Metode penelitian yang digunakan adalah kualitatif dengan pendekatan Research and Development (R&D) menggunakan model Prototype. Sistem dikembangkan dengan menerapkan metode akuntansi berbasis Akrual (Accrual Basis) agar laporan keuangan dapat disusun lebih akurat dan real time. Hasil penelitian menunjukkan bahwa sistem ini mampu mencatat transaksi penjualan dan pembelian, mengelola data barang dan pelanggan, serta menyajikan laporan penjualan dan laporan keuangan secara digital. Fitur tambahan seperti histori transaksi, informasi stok barang, serta perhitungan laba rugi juga membantu pemilik toko dalam pengambilan keputusan. Implementasi sistem memberikan dampak positif, di antaranya peningkatan efisiensi, keakuratan data, dan kemudahan monitoring aktivitas penjualan.

Produksi perhiasan emas PT Gemopia Indonesia melibatkan proses bombing, yang membutuhkan keakuratan tinggi untuk memastikan kualitas produk.  Beberapa kelemahan sistem pencatatan yang masih dilakukan secara manual menggunakan Microsoft Excel termasuk keterlambatan laporan, kurangnya keamanan data, dan kesalahan input yang tinggi. Tujuan penelitian ini adalah untuk mengembangkan dan membangun sistem informasi bombing emas berbasis web yang akan mempercepat proses pencatatan, meningkatkan akurasi data, dan memperbaiki alur pelaporan.  Pengembangan sistem ini menggunakan metode Waterfall, yang mencakup tahapan analisis kebutuhan, perancangan sistem menggunakan UML, pengembangan dengan framework Laravel dan database MySQL, dan pengujian dengan metode black box. Hasil pengujian menunjukkan bahwa seluruh fungsi sistem berjalan dengan baik dan sesuai dengan kebutuhan pengguna, dengan fitur seperti perhitungan otomatis, hak akses pengguna bertingkat, verifikasi dan koreksi data produksi, dan pembuatan laporan dalam format PDF. Sistem mampu menerima input, memproses data , dan menghasilkan output yang tepat dan sesuai dengan spesifikasi.Oleh karena itu, sistem ini dinyatakan layak untuk diimplementasikan secara penuh dalam rangka mendukung efisiensi dan transparansi pelaporan produksi di PT Gemopia Indonesia.

This study presents a machine learning approach for predicting the dimensions of microstrip antenna slots based on antenna performance parameters such as frequency, gain, directivity, return loss (S11), radiation efficiency, and VSWR. A two-phase methodology was employed. In the first phase, ten regression algorithms were evaluated, and Random Forest was identified as the most effective model based on Mean Absolute Error (MAE) and R-squared (R²) scores. In the second phase, hyperparameter tuning was conducted using Grid Search to further improve the model’s performance. The optimized Random Forest model demonstrated consistent improvements in predictive accuracy, with R² values increasing across all output variables. These results indicate that the combination of regression-based modeling and systematic hyperparameter tuning is effective for capturing complex relationships in antenna design tasks. The proposed approach offers a promising data-driven alternative for geometric prediction in microstrip antenna development, particularly when analytical models are insufficient.

Information technology is a technology used to manage data, including processing, acquiring, organizing, storing, and manipulating data in various ways to produce high-quality information—namely, information that is relevant, accurate, and timely. This information is used for personal, business, and governmental purposes, serving as strategic information in decision-making. To anticipate changes in weather conditions, particularly rainfall, a valid and accurate report is needed that can be useful for the public. So far, the correlation or relationship between the factors influencing weather conditions—especially rainfall—has not been precisely determined, making it mathematically difficult to create a model that can describe the correlation among all these factors. This is where Artificial Neural Networks (ANN) come into play: to create such models and map out the existing problems purely based on the input data provided. One of the capabilities of neural networks is to make predictions based on previously learned data using the backpropagation method.

Improving the accuracy of emission monitoring in the Continuous Emission Monitoring System (CEMS) is crucial to support compliance with environmental regulations, especially in gas and steam-based power plants (PLTGU). At PT Jawa Satu Power's PLTGU, the purging system on the CEMS sample probe is still performed manually and limited to scheduled preventive maintenance, potentially reducing emission data reliability due to particle contamination. This study aims to design and simulate an automatic purging system based on a Programmable Logic Controller (PLC), taking into account technical parameters such as timer, gas pressure, temperature, and sample flow rate. The system design was carried out through the modeling of automatic control logic using CX-Programmer software, with a protection approach based on real-time conditions and timing. The design results show that the automatic purging system can improve cleaning consistency, reduce the risk of contamination, and enhance the integrity of emission monitoring data. This study is expected to serve as a foundation for developing a more applicable and integrated automated purging system for CEMS in the future.

Pemantauan suhu dan kelembaban secara real-time merupakan kebutuhan penting dalam berbagai bidang, seperti kesehatan, pertanian, industri, dan pengelolaan lingkungan, guna menjaga stabilitas kondisi ruangan dan mencegah kerusakan pada peralatan elektronik. Penelitian ini bertujuan untuk merancang dan membangun sistem monitoring suhu dan kelembaban berbasis mikrokontroler ESP32 dengan sensor DHT22. Sistem dirancang untuk menampilkan data secara langsung melalui layar OLED dan aplikasi Blynk sehingga memungkinkan pemantauan jarak jauh secara real-time. Penelitian ini menggunakan metode eksperimen dengan pengujian pada dua skenario, yaitu ruang tertutup dan area terbuka, dengan titik kendali kelembaban relatif (RH) sebesar 65%. Hasil pengujian menunjukkan bahwa sistem mampu bekerja secara efektif dalam kondisi ruang tertutup, di mana kelembaban meningkat dari 54,5% menjadi 65% RH dalam waktu 10 menit dan kemudian dapat dipertahankan stabil melalui mekanisme kendali otomatis. Namun, pada area terbuka, sistem tidak menunjukkan peningkatan kelembaban yang signifikan karena adanya sirkulasi udara bebas yang mempercepat dispersi uap air. Dengan demikian, dapat disimpulkan bahwa sistem monitoring berbasis ESP32 ini efektif digunakan pada ruang dengan kondisi lingkungan yang terkontrol, serta memiliki potensi untuk dikembangkan lebih lanjut pada aplikasi rumah pintar (smart home) dan sistem industri berbasis Internet of Things (IoT).

Penelitian ini bertujuan untuk menganalisis optimasi parameter Photovoltaic (PV) serta daya keluaran dari pembangkit listrik tenaga surya berbasis Genetic Algorithm. Penelitian ini menggunakan metode pengumpulan data melalui studi literatur, simulasi perangkat lunak, serta pengujian model matematis. Penelitian ini menggunakan pendekatan analisis kuantitatif dan komputasional yang berfokus pada pencarian nilai optimal dari parameter-parameter utama sistem PV, seperti tegangan, arus, dan resistansi. Hasil penelitian menunjukkan bahwa dalam proses optimasi sistem PV, tahapan yang dilakukan meliputi pemodelan karakteristik PV, penyusunan fungsi objektif untuk memaksimalkan daya, penerapan algoritma genetika dalam mencari nilai parameter optimal, serta analisis hasil optimasi. Hasil penelitian memperlihatkan bahwa algoritma genetika mampu meningkatkan efisiensi daya keluaran PV dibandingkan metode konvensional, serta menghasilkan parameter yang lebih sesuai terhadap kondisi iradiasi tertentu. Namun, dalam implementasi metode ini juga ditemukan beberapa kendala, seperti kompleksitas perhitungan dan kebutuhan waktu komputasi yang relatif tinggi. Selain itu, diperlukan penyesuaian lebih lanjut untuk penerapan algoritma ini dalam skala sistem pembangkit yang lebih besar.

Digital transformation in government bureaucracy has become a strategic step to improve efficiency, accountability, and transparency, including in the management of regional legal products. In the Regional Secretariat of Tegal Regency, the process of submitting legal products is still done manually, which causes inefficiencies, delays, and a lack of document traceability. To address these issues, a web-based legal product submission application has been developed with document tracking features. This research uses the Waterfall system development method, and implements a FIFO (First In First Out) queuing system in the submission process, along with Role-Based Access Control (RBAC) for managing user access rights. The goal of this system is to create a faster, more transparent, and digitally documented application process. The implementation results show that the application is able to systematically and integratively manage the flow of submissions, corrections, verification, and the ratification of legal products. Features such as a Login page with CAPTCHA, analysis dashboards, tracking, and monthly reports enhance the monitoring and security functions of the system. This application can be an effective solution in supporting the digitization of regional legal bureaucracy, as well as providing ease and efficiency for regional officials in preparing and submitting drafts of legal products digitally.

Infeksi Saluran Pernapasan Akut (ISPA) merupakan masalah kesehatan utama di Kabupaten Tegal, terutama menyerang anak-anak dan lansia, dengan 25.273 kasus tercatat pada Januari–Juni 2025. Faktor seperti kepadatan penduduk, polusi udara, dan sanitasi buruk mempersulit analisis konvensional dalam mengidentifikasi wilayah berisiko tinggi. Penelitian ini bertujuan mengembangkan Sistem Informasi Geografis (SIG) berbasis web untuk memetakan dan memantau kasus ISPA secara akurat menggunakan pendekatan spasial. Metode Waterfall digunakan dalam pengembangan sistem, meliputi analisis kebutuhan, perancangan, implementasi, pengujian, dan pemeliharaan. Data spasial (koordinat lokasi) dan non-spasial (usia, jenis kelamin, jumlah kasus) dikumpulkan dari Dinas Kesehatan dan dianalisis menggunakan teknik kepadatan titik dan klaster untuk mengidentifikasi pola sebaran. Sistem ini dibangun dengan framework Laravel sebagai backend dan Leaflet.js untuk visualisasi peta interaktif. Hasilnya, SIG ini mampu memvisualisasikan sebaran kasus ISPA per kecamatan, mendukung Dinas Kesehatan dalam mengalokasikan sumber daya medis secara efisien dan mengidentifikasi wilayah prioritas seperti Dukuhwaru dan Tarub. Bagi masyarakat, sistem ini meningkatkan akses informasi digital, mendorong kesadaran pencegahan, dan mendukung edukasi kesehatan. Sistem ini terbukti efektif sebagai alat strategis untuk pengambilan keputusan berbasis data, mempercepat respons terhadap ISPA, dan menjadi fondasi untuk pengembangan SIG dalam memantau penyakit lain di masa depan.

Diabetes Mellitus merupakan salah satu penyakit kronis yang jumlah penderitanya terus bertambah setiap tahunnya, termasuk di wilayah Puskesmas Brebes. Banyaknya pasien dengan kondisi klinis yang beragam mendorong perlunya suatu metode untuk mengelompokkan pasien berdasarkan tingkat keparahannya. Penelitian ini bertujuan untuk menerapkan algoritma K-Means dalam proses pengelompokan pasien Diabetes Mellitus dengan menggunakan beberapa parameter klinis, yaitu Gula Darah Puasa (GDP), kadar HbA1c, Kolesterol Total (CHOL), serta tekanan darah sistolik dan diastolik. Pendekatan yang digunakan dalam penelitian ini adalah deskriptif kuantitatif dengan metode data mining berbasis algoritma K-Means. Data yang digunakan diperoleh dari rekam medis Puskesmas Brebes. Proses klasterisasi menghasilkan tiga kelompok, yaitu kategori risiko rendah, sedang, dan tinggi. Hasil penelitian menunjukkan bahwa algoritma K-Means mampu melakukan pengelompokan data pasien secara akurat sesuai tingkat keparahan. Hasil tersebut kemudian divisualisasikan melalui sistem berbasis web yang bertujuan untuk mempermudah pihak puskesmas dalam menganalisis kondisi pasien serta mendukung pengambilan keputusan medis yang lebih efektif.

Mental health is a crucial aspect of modern life, with stress and anxiety being among the most common and impactful psychological disorders. This research proposes a stress and anxiety monitoring system based on the Internet of Things (IoT), integrating biometric sensors and Deep Neural Networks (DNN) for early detection and in-depth analysis. The system is designed using MAX30102 (heart rate and SpO₂), GSR (Galvanic Skin Response), and DS18B20 (body temperature) sensors, managed by an ESP32 microcontroller and communicating through the MQTT protocol. Physiological data is collected in real-time, formatted in JSON, and transmitted to both Android and web-based applications for visualization. The DNN model is developed using the TensorFlow framework with a layered architecture and ReLU activation functions to classify four mental states: relaxed, calm, anxious, and highly stressed. The training dataset comprises both primary and secondary data, including the WESAD dataset. Model performance is evaluated through k-fold cross-validation, showing high accuracy and strong generalization capabilities. The results indicate that the integration of sensor technology and deep learning significantly improves the effectiveness of stress and anxiety detection compared to traditional methods. This system demonstrates great potential for the development of AI-based wearable devices for autonomous, real-time, and adaptive mental health monitoring.

The coffee farming sector in Gunungmanik Village, Indonesia, plays a significant role in the local economy. However, the monitoring and management of coffee crops remain largely manual and conventional, making it difficult for farmers to respond quickly to environmental threats such as drought, pests, or sudden temperature shifts. This research presents the development of iotgm.id, a web-based monitoring system integrated with Internet of Things (IoT) devices designed to provide real-time environmental data for coffee plantations. The system measures key parameters including temperature, soil moisture, and motion detection (as a proxy for pest activity), and delivers this data via a user-friendly web interface. It also features digital farm record management, real-time alerts for abnormal conditions, and data visualization through interactive dashboards. Field testing with local farmers showed that the system improves decision-making, speeds up responses to environmental changes, and reduces the need for direct field visits. Unlike earlier systems that often required technical expertise or focused on single parameters, this system offers multi-parameter monitoring and is accessible to farmers without advanced digital literacy. The system bridges the gap between sophisticated agricultural technologies and practical field-level application. It contributes to the adoption of precision agriculture in rural areas, offering a scalable model for broader implementation in similar contexts

The Message Queue Telementary Transport (MQTT) protocol is able to adjust the sending and receiving of messages to monitor in accordance with the user's preferences because the sending and receiving of messages is topic based on a specified topic, making it necessary to routinely monitor the condition of patients who have been diagnosed with heart problems from a distance. With the aim to perform a Quality of Service (QoS) analysis with throughput, delay, and packet loss parameters using Unshielded Twisted Pair internet transmission media (UTP) and Wireless, the goal of this research is to design and implement (MQTT) a heart rate monitoring device with an EKG module as a sensor and ESP32 as a microcontroller. On the Ubidots website, EKG signals are transmitted over the internet and shown in real time. QoS analysis is performed using the Wireshark application. Data was collected on two scenarios at intervals of 30 minutes, 1 hour, 2 hours, 5 hours, 8 hours, 12 hours, 18 hours, and 23 hours. The throughput, latency, and packet loss metrics used in this study's results cause different value variations; these are influenced by the weather, internet bandwidth, computer, and router specifications. According to testing, the tool is portable and has a 3000mAh battery, but it has the restriction that it can only be used with reliable internet and bandwidth.

Abstrak  - Coal handling system berfungsi menangani pekerjaan mulai dari pembongkaran batu bara dari kapal/tongkang (unloading area) yang dipindahkan ke conveyor - conveyor, penimbunan/penyimpanan di stock area, ataupun pengisian ke bunker yang digunakan untuk pembakaran di boiler. Dalam proses pembongkaran tersebut tidak boleh terjadi penyumbatan / plugging terutama pada chute conveyor, maka dari itu diperlukan sensor proteksi untuk mencegah hal tersebut. Sensor lama yang digunakan yaitu berjenis Tilt Switch yang selama pemakaian tidak efektif karena banyak masalah sehingga dilakukan pemeliharaan, akibatnya dilakukan penggantian menggunakan sensor berjenis MBD (Microwave Beam Detector). Dari analisa setelah penggantian menggunakan sensor MBD, permasalahan penyumbatan chute berkurang dapat dilihat dari frekuensi pemeliharaan yang semakin berkurang.

Peningkatan transaksi dalam platform e-commerce seperti Shopee menuntut adanya sistem prediksi status pesanan yang akurat, guna mengoptimalkan pelayanan dan mengurangi pembatalan maupun keterlambatan pengiriman. Penelitian ini bertujuan membangun model klasifikasi status pesanan (selesai atau batal) pada toko Stuftech.Id menggunakan algoritma C4.5. Data yang digunakan merupakan transaksi pesanan mencakup metode pembayaran, kategori wilayah pengiriman, dan ongkos kirim. Proses klasifikasi dilakukan menggunakan RapidMiner dengan tahapan preprocessing, pembangunan decision tree, dan evaluasi model. Hasil analisis menunjukkan bahwa atribut “Kategori Pulau” memiliki nilai gain tertinggi sehingga dipilih sebagai node akar. Model yang dibentuk menghasilkan akurasi sebesar 86%, dengan recall 100% untuk pesanan selesai namun hanya 6,67% untuk pesanan batal. Temuan ini mengindikasikan bahwa algoritma C4.5 efektif dalam memprediksi pesanan yang berhasil, namun perlu peningkatan dalam mendeteksi potensi pembatalan. Implementasi model ini dapat membantu pelaku usaha dalam mengambil keputusan operasional secara proaktif.

Terrestrial digital television transmitter stations are the main facilities in the transmission of digital television broadcasts to the public. The quality of the transmitted signal is expected to reach the Central Java-1 service area well so as to provide optimal and reliable quality of digital television broadcast performance according to the needs of the community, but currently, complaints about signal problems such as service coverage and reception quality still occur a lot, coverage and signal quality received by community-owned television transmitters cannot be separated from the influence of the quality performance of digital television transmission stations. The purpose of this research is to analyse the coverage performance of digital television services of digital television transmitter stations using the K-Means Clustering Method, identify areas with the best signal coverage and group areas based on the level of signal performance. The data used includes field strength parameters collected through field measurements at 25 service area location points, topography factors and transmitter distance were found to be the main causes of signal quality differences. Data analysis shows that the K-Means Clustering method effectively clusters areas with signal reception quality categories of very good cluster 3 areas, good cluster 8 areas, fair cluster 5 areas and poor cluster 9 areas. The results of this study can be recommended in the evaluation and optimisation of tele-transmitting station networks.

The food security program involving chili cultivation in Pentur Village is hindered by inefficiencies in water use and suboptimal plant growth, primarily due to traditional irrigation methods that fail to consistently maintain ideal soil moisture and temperature. This issue is exacerbated by unpredictable environmental shifts, such as fluctuating weather patterns, and a lack of precise irrigation control stemming from technological limitations. To address this, a system for monitoring and regulating chili plant irrigation using IoT technology was developed. This system employs humidity and temperature sensors connected to an IoT platform like Blynk, enabling real-time observation of plant and environmental conditions. Data on soil moisture, air temperature, and humidity are stored in a database, and irrigation is automated based on soil moisture levels. The goal is to enhance water efficiency, minimize risks associated with over or under-watering due to environmental variations, and improve both yield and quality of the chili crop. This IoT-based system aims to simplify chili plant management for Pentur Village farmers and significantly boost agricultural output.

The digital revolution has transformed retail industry into a new era full of opportunities through e-commerce but also presenting challenges in online furniture sales. Due to their inability to precisely measure and see furniture in their spaces, many customers are hesitant to make purchases. Augmented Reality (AR) offers solutions through realistic visualizations, but it’s costly and has a lot of accessibility problems. WebAR solves these issues by delivering AR features directly on mobile browsers without requiring additional apps. This study investigates the impact of WebAR innovation on e-commerce furniture by examining the roles of interactivity (IN), vividness (VI), augmentation (AU), customization (CT), and ease of access (EA) on purchase intention (PI), mediated by spatial presence (SP), decision comfort (DC), and satisfaction (SF). Using the Stimulus-Organism-Response (SOR) model, data from 100 respondents were analyzed with the PLS-SEM algorithm using SmartPLS 4.0. The findings tell us that WebAR significantly enhances consumers’s shopping experience and ultimately boosts purchase intention.

SMA Negeri 1 Baturiti merupakan salah satu instansi pendidikan di bawah naungan Dinas Pendidikan Kabupaten Tabanan yang memiliki berbagai aset penunjang kegiatan belajar mengajar. Proses pelaporan aset selama ini masih dilakukan secara manual menggunakan Microsoft Word, sehingga kurang efisien dan sering mengalami keterlambatan dalam pelaporan kepada Dinas Pendidikan. Untuk mengatasi permasalahan tersebut, dirancang dan dibangun sistem dengan judul Optimalisasi Pengelolaan Inventaris Sekolah Melalui Sistem Inventory Berbasis Web di SMA N 1 Baturiti. Sistem ini dikembangkan menggunakan bahasa pemrograman PHP dan database MySQL, serta dilengkapi fitur pencetakan laporan dengan PHP Word dan PHP Excel. Sistem ini mempermudah proses input data aset dan menghasilkan laporan yang lebih cepat, akurat, dan terstruktur. Dengan adanya sistem ini, diharapkan pelaporan aset sekolah kepada Dinas Pendidikan dapat dilakukan secara lebih tepat waktu dan efisien.

The increasing need for electrical energy in Indonesia encourages the development of new renewable energy (EBT), including hydroelectric power plants (PLTA) as an environmentally friendly solution. This research was conducted at the Mentawa Dam, West Toili District, Banggai Regency, Central Sulawesi, to analyze the potential of water energy that can be utilized as a source of micro-hydro power plants (PLTMH). This dam currently functions as irrigation and a tourist attraction, but has significant potential to generate sustainable electrical energy. The research methods include measuring water discharge using the float method, measuring the height of the water fall (head) with an altimeter and GPS, and analyzing the potential for electrical power using the formula P = η ⋅ ρ ⋅ g ⋅ Q ⋅ H. The measurement results show an average water discharge of 3.01 m³ / s and a water fall (head) of 6.56 meters. With a turbine efficiency of 80%, the potential electrical power that can be generated reaches 154.76 kW. This study recommends the use of Kaplan turbines in Mentawa Dam, which are ideal for large discharge conditions and low to medium heads, and can adapt to discharge fluctuations, making it an optimal choice to maximize energy potential. This research is expected to provide sustainable energy solutions for the people of Toili Barat District and support the development of the tourism sector.