Publication Search

Waste management remains a critical environmental issue due to the lack of public awareness in separating organic and inorganic waste, resulting in accumulation and environmental pollution This study aims to analyze and evaluate the development of automatic waste sorting systems based on proximity sensors with full-capacity notification using a Systematic Literature Review (SLR) approach.. The proposed system utilizes a combination of sensors, including proximity sensors for material identification and ultrasonic sensors for detecting object presence and bin capacity, integrated with a microcontroller for real-time processing. Additionally, the system is equipped with IoT-based monitoring that allows users to receive notifications when the waste bin reaches its capacity. The research method involves system design, hardware and software integration, and functional testing to evaluate system performance. The results indicate that the system is capable of sorting waste automatically with a high level of accuracy and responsiveness, while also providing real-time monitoring to support waste management operations. The implementation of this system can reduce manual intervention, increase operational efficiency, and promote better waste segregation practices. Furthermore, this study highlights the potential of integrating smart technology into environmental management systems, contributing both theoretically and practically to the development of sustainable waste management solutions.

This research was conducted with the aim of developing an automation system for recording warehouse inventory based on Google Sheets to improve the effectiveness and efficiency of the stocktaking process at the Cresta Management warehouse. This research was based on problems in the semi-manual process that used logbooks and separate files for each group of goods, which caused problems such as data duplication, limited data access, lack of data transparency, and lengthy recapitulation process. This research used the Research and Development method using the ADDIE model (Analyze, Design, Develop, Implement, and Evaluate). Data were collected through observastion, interviews, questionnaires, and documentation. The result of this development is a system consisting of a login page, goods transcation recording, warehouse dashboard, stock reports, stock cards, and PDF report exports. This study also produced evaluation scores regarding the system’s feasibilty: 93,3% from the first media expert, 80% from the second media expert, 73,3% from the material expert, and 91,75% from users through User Acceptance Testing. These evaluation results indicate that the system is feasible for use and implementation in supporting warehouse operations, as it provides real time data updates, improves the efficiency of goods reporting, and enhances warehouse transactions.

This study presents ReflectAI, a web-based system designed to automate the creation of teaching materials tailored to students' learning styles using behavior data from a Learning Management System (LMS). Student digital activity data—such as logins, material access, forum participation, assignment submission, and quiz results—are extracted and processed using a Hierarchical Clustering algorithm to categorize students into three learning styles: visual, auditory, and kinesthetic. Based on the clustering results, the system automatically generates personalized learning modules using generative AI (ChatGPT API), aligned with each student's learning preferences. Employing a data-driven system development approach, the system was tested with data from 230 students in a mathematics course. The results show diverse learning style distributions and relevant, tailored content generation. ReflectAI is designed to reduce teachers’ administrative workload and enhance personalized and adaptive learning. This system contributes to educational transformation through deep, data-driven technology integration.

This study aims to design, implement, and test a prototype that automates three functions, namely watering, fertilizing, and pest control based on Arduino Uno with the ability to directly monitor soil moisture and pH. This system is equipped with four main types of sensors. Soil condition monitoring involves an FC-28 soil moisture sensor and a soil pH sensor, water level measurement involves an HC-SR04 ultrasonic sensor, and pest detection in the plant area involves a RIP sensor. All data obtained from these sensors is then processed by the Arduino Uno microcontroller to automatically activate actuators such as water pumps, liquid fertilizer pumps, buzzers, and DC motors according to soil conditions and plant needs. Prototype testing was conducted on simulated land with various scenarios of moisture, soil pH, and pest activity. The test results revealed that the system was proven to be able to significantly optimize water and fertilizer utilization, as well as reduce pest disturbances that could potentially damage plants.  In addition, this system also displays the operational status directly through an LCD screen, making it easy for users to monitor. The advantage of this system is its multi-function integration in a single device that is cost-effective and easy to operate. In the future, the functionality of this system can be improved through integration with Internet of Things (IoT) technology, enabling remote monitoring and control with greater efficiency. More broadly, this study is expected to support increased production and sustainable agricultural practices in Indonesia.

Kecap merupakan produk fermentasi kedelai yang berperan penting sebagai bumbu penyedap dalam masakan. Berdasarkan rasa dan kekentalannya, kecap dibedakan menjadi kecap manis dan kecap asin. Penelitian ini bertujuan untuk mengkaji penerapan teknologi filling otomatis sebagai solusi dalam meningkatkan efisiensi proses pengemasan botol kecap pada skala UMKM. Metode yang digunakan adalah deskriptif kualitatif dengan pendekatan studi pustaka. Permintaan pasar yang tinggi terhadap kecap manis mendorong tumbuhnya industri kecil. Namun, UMKM ini menghadapi kendala dalam hal kapasitas produksi dan konsistensi mutu produk. Salah satu proses yang memerlukan waktu lama dan tidak efisien adalah pengemasan manual. Untuk mengatasi permasalahan tersebut, diterapkan solusi teknologi berupa filling machine semi otomatis. Teknologi ini mempercepat proses pengisian botol, mengurangi kehilangan produk akibat tumpahan, serta meningkatkan efisiensi waktu dan tenaga kerja. Meskipun memerlukan investasi awal yang cukup besar dan ketergantungan pada listrik, penggunaan filling machine semi otomatis terbukti efektif dalam meningkatkan efisiensi dan kualitas produksi kecap di skala UMKM.

Traffic congestion is a persistent challenge in urban areas in Indonesia, where increasing vehicle density creates the need for intelligent traffic monitoring systems. This study aims to develop a real-time vehicle parking system using the YOLOv8 object detection model to provide efficient traffic analysis from live CCTV broadcasts and recorded videos. This study uses a quantitative experimental approach with the implementation of the YOLOv8m model using the Ultralytics library in Python, tested on data collected from CCTV cameras A TCS Dishub Medan and additional footage from mobile devices. Vehicles are detected and counted in two directions up (Up) and down (Down) using virtual detection lines on the video frame. The system performance is evaluated by automatic detection counting with manually recorded ground truth data. The results show that on live CCTV broadcasts, the YOLOv8m model achieves an average precision of 98.96%, a recall of 96.59%, and an F1 score of 97.74% for upstream traffic, while for downstream traffic it achieves 100% precision, 95.64% recall, and an F1 score of 97.730/0. On the other hand, on high-quality recorded videos, all performance metrics achieve 100%, indicating perfect detection accuracy. These findings confirm the effectiveness of YOLOv8 in real-time traffic monitoring, but also indicate that video quality and stream stability affect detection performance. In conclusion, the developed system shows strong potential to support smart city traffic management solutions. Future research should focus on performance optimization under low-resolution live streaming conditions to improve accuracy in practical applications.  

This study discusses the design and development of an automatic safety system for a wood cutting machine using Arduino Uno, a PIR (Passive Infrared) sensor, and a servo motor as the main components. The system is designed to automatically stop the movement of the wood cutting machine when human motion is detected around the cutting area, thereby minimizing the risk of work-related accidents. The research method includes hardware design, microcontroller programming, and system response testing using two types of test objects: the human body and a wooden block. The results show that the system operates according to the programmed logic. When the PIR sensor detects human motion, the servo motor stops and the red LED lights up as a danger indicator. In contrast, when no human motion is detected, the servo motor continues to move normally and the green LED remains on as a safe indicator. The system’s average response time is 0.6 seconds, indicating a fast and accurate performance. Therefore, the designed system is considered effective and can serve as a prototype of a simple safety tool to enhance operator safety in wood cutting machines.

Penelitian ini mengembangkan sistem pemantauan berbasis Internet of Things (IoT) untuk mengoptimalkan kinerja Mini PC dan pemeliharaan real-time di CV Permata Gemilang Jaya. Metodologi waterfall diterapkan menggunakanNodeMCU sebagai mikrokontroler utama, dilengkapi dengan sensor DHT22, DS18B20, dan INA219 untuk memantau parameter suhu, CPU, dan memori. Arsitektur sistem mengintegrasikan kerangka kerja Laravel dengan database MySQL, menghasilkan aplikasi web responsif dengan kontrol akses berbasisperan untuk Admin Pusat, Admin Regional, dan Teknisi Cabang. Infrastrukturserver cloud dengan konektivitas GSM cadangan memfasilitasi pemantauanterpusat di wilayah Ciayumajakuning. Desain sistem menggunakan Unified Modeling Language (UML) dengan diagram kasus penggunaan dan diagram aktivitas yang komprehensif. Penerapan sistem pemberitahuan otomatisdengan mekanisme peringatan berbasis ambang batas memungkinkan deteksidini anomali perangkat. Antarmuka yang dioptimalkan untuk selulermeningkatkan aksesibilitas teknisi untuk operasi lapangan. Validasi sistemmenunjukkan strategi pemeliharaan preventif yang sukses dalam mengurangiwaktu henti perangkat dan mengoptimalkan efisiensi operasional infrastrukturteknologi informasi.

Penelitian ini bertujuan untuk merancang dan membuat interface komunikasi data antara Electronic Control Unit (ECU) sepeda motor dengan sistem Android. Masalah yang dihadapi oleh bengkel rumahan seperti Ngoprek Garage Motoshop adalah keterbatasan alat untuk mendeteksi kerusakan ECU secara otomatis. Penelitian ini menggunakan mikrokontroler ESP32 sebagai penghubung antara ECU dan aplikasi Android, yang dirancang menggunakan MIT App Inventor. Sistem ini mampu membaca data kesalahan (Diagnostic Trouble Code/DTC) dari ECU dan menampilkannya secara langsung pada aplikasi Android. Metode penelitian yang digunakan mencakup perancangan perangkat keras dan perangkat lunak, serta pengujian sistem terhadap sepeda motor Honda. Hasil menunjukkan bahwa sistem ini mampu membaca dan menampilkan kode DTC dengan akurasi yang cukup tinggi, meskipun terdapat keterbatasan pada pembacaan parameter data secara real-time. Sistem ini diharapkan menjadi solusi alternatif bagi bengkel kecil dalam melakukan diagnosa awal terhadap kerusakan ECU.

Modern industries require automation to enhance operational efficiency and productivity. This study designs and implements an automatic sorting system based on the Internet of Things (IoT) using a mini conveyor, ESP32 microcontroller, TCS3200 color sensor, servo motor, and the Blynk application. The system is designed to accurately detect object colors, sort objects based on color, and enable remote monitoring and control via mobile devices. Testing results indicate that the system can detect and sort objects with a high level of accuracy, although some errors occur due to changes in lighting conditions. The conveyor speed is consistently recorded at 0.335 m/s, while the system's response time, including color detection, servo movement, and application updates, operates within an optimal range. The Blynk application enhances the flexibility of real-time system control. This study demonstrates that IoT-based sorting systems can serve as an efficient solution to support industrial automation. Further development is recommended to improve color detection accuracy and expand the system's application in more complex industrial scenarios.

Internet of Things (IoT)-based digital transformation has become a major catalyst in improving the efficiency of operational systems in various sectors, including the modern retail industry. One of the common logistics problems found in supermarket environments is the accumulation of unorganized shopping trolleys, which can hinder service flow and increase staff workload. This study presents a design of an IoT-based autonomous smart trolley system and automatic navigation to address these problems in a structured manner. The system design utilizes the integration of ESP32 and Arduino UNO microcontrollers, ultrasonic sensors for distance detection, line sensors for automatic path navigation, and Raspberry Pi modules for visual image processing in location tracking. The system is designed to be able to independently reposition the trolley to a predetermined parking station. Conceptual analysis shows that this system has significant potential in reducing operational costs, increasing labor efficiency, and strengthening customer service automation. Initial evaluation of technical and economic feasibility aspects strengthens the opportunity for widespread system implementation in the future. This design is the first step in developing a smart retail solution based on adaptive technology that is in line with the principles of Society 5.0. Furthermore, the development of this smart trolley system also considers user safety and comfort through additional features such as anti-collision sensors, an early warning system in the event of technical problems, and a manual control option as an alternative in emergency situations. The integration of Internet of Things-based technology also enables real-time monitoring and management systems through a web-based dashboard or mobile application, which can be accessed by supermarket management for operational analysis. Thus, this system not only addresses internal logistics needs but also contributes to improving the overall customer experience.

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).

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.

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.

This research aims to be able to meet the water supply of lettuce plants automatically by using three sensors such as soil moisture, water level, and water discharge. The goal is to provide water needs to plants automatically and regularly. The developed tool uses YL-96 sensor for soil moisture, HC-SR04 for water level and YF-S201 for water discharge. Sensor data is sent to the arduino to be processed using the fuzzy mamdani method so that these three data values affect the movement of the tap servo motor that flows to the lettuce plant. Fuzzy logic here as a decision maker from the value of 3 sensor data and then processed automatically by arduino using fuzzy mamdani to determine how many degrees the servo motor moves. The result is that the Lettuce Plant Water Needs Analysis System Automation Tool is able to maintain the water supply of lettuce plants and soil moisture ideally at 76% with a servo motor movement system success rate of 100%.

Due to the busy activities outside the home, some people do not have time or forget to water their plants, so when they return home they find that the plants have died from drought. Therefore, to overcome this problem by conducting research using Internet of Things technology. The aim of this research is to design an automatic watering tool to overcome manual watering and support learning. This prototype uses a NodeMCU ESP8266 as the main controller, a soil moisture sensor is used to read soil moisture.  Soil moisture sensors are used to detect soil moisture. If the soil humidity is below the minimum limit, the watering process will be active and the watering process will be active if the NodeMCU ESP8266 receives commands from the smartphone.

This service presents the results of activities carried out at PT PLN (Persero) Aceh Distribution Unit, focusing on designing a web-based automatic certificate generation system using the System Development Life Cycle (SDLC) method. The main goal of the development of this system is to improve efficiency and effectiveness in the process of creating certificates that were previously done manually. Through the needs analysis, it was found that the current manual system resulted in delays and errors in the management of certificate data. The SDLC method was chosen to ensure that system development is carried out in a structured manner, from needs analysis to system maintenance.

Proses budidaya jamur tiram sangat tergantung dengan kestabilan pada kondisi lingkungan, terutama suhu ruangan dan kelembapan yang harus di perhatikan oleh para petani.  Hal ini menjadi permasalahan ketika proses pemantauan dan pengendalian lingkungan secara manual dilakukan, membutuhkan tenaga yang kuat dan waktu yang cukup besar. Penelitian ini bertujuan Mendesain rancangan sistem monitoring dan kendali suhu ruangan budidaya jamur tiram secara otomatis dan jarak jauh berbasis teknologi Internet of Things (IoT) untuk para petani. Dalam proses sistem ini penelitian ini memanfaatkan sensor suhu dan kelembapan DHT11 sebagai input, mikrokontroler Arduino Uno sebagai pemroses data, dan modul ESP8266 sebagai pengirim data nirkabel ke aplikasi Android berbasis Blynk.  Adapun metode dalam penelitia ini digunakan pengembangan yang digunakan adalah Software Development Life Cycle (SDLC) model waterfall, dan menganalisis kebutuhan, perancangan sistem, implementasi, pengujian, hingga pemeliharaan. Hasil pengujian menunjukkan bahwa sistem mampu membaca suhu dan mengaktifkan blower (kipas) secara otomatis ketika suhu melebihi ambang batas, serta menampilkan data suhu dan status kipas secara real-time melalui aplikasi Blynk. Dengan adanya sistem ini, pemantauan dan pengendalian lingkungan budidaya jamur dapat dilakukan lebih efisien dan fleksibel dan mendukung produktivitas budidaya secara optimal.

In the digital economy era, financial transparency has become a critical aspect for the sustainability and credibility of Micro, Small, and Medium Enterprises (MSMEs). Despite their substantial contribution to employment and economic growth, many MSMEs in Indonesia still rely on manual accounting systems, which limit the accuracy and traceability of financial reporting. This study aims to empirically examine the effect of cloud-based accounting automation on financial transparency among Indonesian MSMEs. Using a mixed-methods approach, the research collected quantitative data from 120 MSME respondents in Jakarta and West Java through structured questionnaires and qualitative data from six key informants through semi-structured interviews. The quantitative data were analyzed using simple linear regression, resulting in a coefficient of determination (R²) of 0.513 and a beta coefficient of 0.598 (p = 0.000), indicating a strong and significant influence of accounting automation on financial transparency. Qualitative findings also revealed improvements in real-time access, reporting accuracy, and transaction traceability. The study confirms that cloud-based digital accounting systems enhance financial transparency by enabling automated integration, audit trails, and timely reporting. These findings contribute to the literature on digital transformation in MSMEs and offer practical implications for policymakers, financial institutions, and software providers to accelerate technology adoption and improve financial governance in the MSME sector.

Water is an essential resource for every household. Typically, household water distribution systems rely on PVC pipes and faucets. Despite this, water leakage remains a frequent issue, occurring in both pipes and taps. This study aims to design an Arduino-based automatic faucet control system capable of detecting leaks in water pipes, with the goal of conserving water and improving usage efficiency. The system employs a pressure sensor to monitor water pressure within the pipe, an ultrasonic sensor to detect user presence at the tap, and a solenoid valve to automatically shut off the water supply in the event of a leak. Testing and design outcomes indicate that the system functions effectively. The solenoid valve successfully closes the water flow automatically when a leak is detected. However, the current system lacks a notification feature to alert users when a leak occurs. Future developments should consider integrating a notification mechanism to inform users promptly about any detected leaks.