Abstract:Abstrack: This research aims to improve battery performance and safety on the ECGO2 electric motorcycle by re-assembling the battery system using 18650 lithium cells, Daly BMS 13S/7A battery management system, and XH-M604…
4 module. The configuration used is 13S5P (65 cells), resulting in a total voltage of 48.1 V and a capacity of 14 Ah, or equivalent to 673.4 Wh of energy. Compared to the ECGO2 built-in battery that requires 4-7 hours of charging time, this system is able to speed up charging to ±1.6 hours using a 7 A current charger. Test results using an oscilloscope show that the voltage of the assembled battery is more stable under load than that of a single battery, with minimal ripple. The estimated operating time of an 800 W electric motor using a 673.4 Wh battery is about 50 minutes. To achieve 2 hours of operation, the 13S10P configuration or energy-saving mode (400-500 W) can be used. The system is also more cost-effective at Rp2,678 per Wh compared to the manufacturer's version of Rp4,464 per Wh, as well as improved safety against leakage and overheating.
Keywords: 18650 lithium battery; daly bms; electric motorcycle; fast charging.
Abstrak: Penelitian ini bertujuan untuk meningkatkan performa dan keamanan baterai pada sepeda motor listrik ECGO2 dengan merakit ulang sistem baterai menggunakan sel lithium 18650, sistem manajemen baterai Daly BMS 13S/7A, dan modul XH-M604. Konfigurasi yang digunakan adalah 13S5P (65 sel), menghasilkan tegangan total 48,1 V dan kapasitas 14 Ah, atau setara dengan energi 673,4 Wh. Dibandingkan baterai bawaan ECGO2 yang memerlukan waktu pengisian 4–7 jam, sistem ini mampu mempercepat pengisian menjadi ±1,6 jam menggunakan charger arus 7 A. Hasil pengujian menggunakan osiloskop menunjukkan bahwa tegangan baterai rakitan lebih stabil di bawah beban dibandingkan baterai tunggal, dengan ripple minimal. Estimasi lama pengoperasian motor listrik 800 W menggunakan baterai 673,4 Wh adalah sekitar 50 menit. Untuk mencapai 2 jam pengoperasian, dapat digunakan konfigurasi 13S10P atau mode hemat energi (400–500 W). Sistem ini juga lebih hemat biaya dengan efisiensi harga Rp2.678 per Wh dibandingkan Rp4.464 per Wh versi pabrikan, serta meningkatkan keamanan terhadap kebocoran dan panas berlebih.
Kata kunci: baterai lithium 18650; daly bms; sepeda motor listrik; pengisian daya cepat.
Abstract:Abstract: INET Computer Palembang, as a computer training institution, faces difficulties in understanding participant characteristics due to variations in age, educational background, and chosen course packages. This study…
udy aims to analyze participant criteria and group them based on similarities using the K-Means Clustering algorithm. The data used were historical records of course participants from 2022 to 2025. The research process followed the CRISP-DM stages, starting from data cleaning and transformation, determining the optimal number of clusters using the Elbow Method, to evaluating cluster quality with the Davies-Bouldin Index. The implementation was carried out using Python and the scikit-learn library. The results show that the optimal number of clusters is k=5 with a Sum of Squared Errors (SSE) value of 1064.66 and a Davies-Bouldin Index (DBI) score of 0.820, indicating good cluster quality. The resulting clustering provides a structured profile of participants and demonstrates that K-Means is effective in segmenting course participants. These findings are expected to assist the institution in designing more targeted training programs.
Keywords: clustering; data mining; elbow method; k-means; computer course
Abstract:Abstract: Recommendation systems are becoming increasingly important with the growth of streaming platforms. The purpose of this study is to compare the performance of Content-Based Filtering, Neural Collaborative Filtering,…
ing, and a combination of both in a movie recommendation system. The method used in this study involves retrieving movie details from the TMDB API and ratings from the MovieLens 32M Dataset (2010-2023). Each model's performance is evaluated using evaluation metrics such as RMSE and MAE. The results of this study indicate that Neural Collaborative Filtering achieves the best prediction performance (RMSE = 0.785423, MAE = 0.581262), followed by the hybrid model (RMSE = 0.800863, MAE = 0.660872), while Content-Based Filtering produces low performance and limits the capabilities of the hybrid model. In conclusion, these findings highlight the superiority of latent feature-based models such as NCF that learn directly from user interaction patterns over content-based approaches in the context of modern recommendation systems.
Keywords: content-based filtering; hybrid filtering; movie recommendation; neural collaborative filtering.
Abstrak: Sistem rekomendasi menjadi semakin penting seiring berkembangnya platform streaming. Tujuan dari penelitian ini adalah membandingkan kinerja Content-Based Filtering, Neural Collaborative Filtering dan kombinasi keduanya dalam sistem rekomendasi film. Metode yang digunakan dalam penelitian ini melibatkan pengambilan detail film dari TMDB API dan rating dari dataset MovieLens 32M Dataset (2010-2023). Setiap peforma model dievaluasi dengan menggunakan metrik evaluasi seperti RMSE dan MAE. Hasil dari penelitian ini menunjukkan bahwa Neural Collaborative Filtering mencapai kinerja prediksi terbaik (RMSE = 0.785423, MAE = 0.581262), diikuti oleh model hybrid (RMSE = 0.800863, MAE = 0.660872), sementara Content-Based Filtering menghasilkankan peforma yang rendah dan membatasi kemampuan model hybrid. Kesimpulannya, penelitian ini menyoroti superiotas model berbasis latent feature seperti NCF yang belajar langsung dari pola interaksi pengguna dibandingkan pendekatan berbasis konten dalam konteks sistem rekomendasi modern.
Kata kunci: content-based filtering; hybrid filtering; neural collaborative filtering; rekomendasi film.
Abstract:Abstract: The management of veterinary drug stocks at the Veterinary Clinic Technical Implementation Unit (UPTD) of the North Sumatra Province Plantation and Livestock Service faces obstacles in the form of discrepancies…
between supply and demand, resulting in excess stock and budget waste. Uncertain demand for drugs is a factor that complicates decision-making in stock provision. This study aims to optimize drug stock management using the Mamdani fuzzy logic method, which is capable of handling data uncertainty and modeling information linguistically. Three input variables are used, namely initial stock, demand, and number of visits, with the output being the final stock. The process involves fuzzification, inference based on IF–THEN rules, and defuzzification using the centroid method. The results show that the developed system has a good accuracy level with a MAPE value of 17.52%, which means that this model is effective in providing optimal and efficient drug stock recommendations in a veterinary clinic environment.
Keywords: fuzzy mamdani; optimization; animal drug stock.
Abstract:Giving awards is essential to motivate students; however, selecting outstanding students at the junior high school level is often conducted manually and subjectively, which can lead to unfairness and prolonged processing…
time. This study develops a Decision Support System (DSS) that integrates the Analytical Hierarchy Process (AHP) and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) to support objective and transparent student selection. A quantitative descriptive approach was employed, with data collected through questionnaires, interviews, and documentation at two state junior high schools in Banjarmasin City. Seven assessment criteria were applied: attendance, behavior, uniform neatness, extracurricular participation, academic grades, competition achievements, and disciplinary records. AHP was used to determine the weight of each criterion, while TOPSIS ranked students based on these weights. The web-based system was developed using PHP and MySQL and evaluated using the Technology Acceptance Model (TAM). Results show that academic grades had the highest weight (28.5%), followed by attendance (22.3%) and competition performance (15.2%). The TAM evaluation yielded average scores of 4.32 for Perceived Ease of Use, 4.40 for Perceived Usefulness, 4.15 for Attitudes Towards Use, and 4.28 for Behavioral Intention to Use. The DSS produces accurate rankings, is well-received by users, and offers an efficient, fair, and replicable solution for data-driven educational governance in the digital era.
Abstract:Abstract: The development of information technology encourages businesses to take over digital systems in business operations, even in the sales process. The Point of Sales (POS) system is the leading solution for recording…
ing transactions, managing stock, and creating sales reports efficiently. This study aims to develop a POS application based on a website and make it easier for administrators to manage sales transactions, making them faster and more efficient. This system is made with a structured Agile Development method, requirements, design, development, testing, deployment, and implementation. The framework used is the Laravel framework, with system testing conducted using BlackBox. The test results show that the system is on track and that the efficiency of the transaction and reporting process can be increased. A web-based basis allows users to manage their business more easily in real time because this application is flexible and can be used on various devices.
Keywords: agile model;laravel;point of sales; websites
Abstrak: Pengembangan teknologi informasi mendorong bisnis untuk mengambil alih sistem digital dalam operasi bisnis, bahkan dalam proses penjualan. Sistem Point of Sales (POS) adalah solusi utama untuk merekam transaksi, mengelola stok dan membuat laporan penjualan secara efisien. Tujuan dari penelitian ini adalah untuk mengembangan aplikasi POS berdasarkan situs web dan memudahkan administrator dalam mengelola transaksi penjualan, membuatnya lebih cepat dan lebih efisien. Sistem ini dibuat dengan metode Agile Development yang terstruktur, requirement, design, development, testing, deployment, dan implementation serta kerangka kerja yang digunakan yaitu framework Laravel dengan pengujian sistem menggunakan Blackbox. Hasil pengujian menunjukkan bahwa sistem berada di jalur dan bahwa efisiensi proses transaksi dan pelaporan dapat meningkat. Dengan berbasis web memungkinkan pengguna untuk lebih mudah mengelola bisnisnya secara real time, karena aplikasi ini fleksibel melalui berbagai perangkat.
Kata kunci: model agile;laravel;point of sales;website
Abstract:Abstract: The Ministry of Education, Culture, Research, and Technology, has developed guidelines for the Internal Quality Assurance System or known as SPMI, that is being implemented through the Internal Quality Audit (IQA)…
QA) with the PPEPP cycle, namely Determination (P), Implemen-tation (P), Evaluation (E), Control (P), and Improvement (P). Some universities have implemented IQA with system. The problem is that the system does not line well with the PPEPP cycle, which results in unsatisfactory audit results. The purpose of this study is to evaluate how well the university-owned AQI system features in line the PPEPP cycle and to highlight development opportunities. The method used Feature Oriented Domain analysis (FODA) and Acceptance Testing. This study delivered an analysis of IQA system features that consistent with PPEPP. The FODA results were validated by expert and tested with User Acceptance Test (UAT) with 89.98% user response that the system is acceptable. The research contributes to universities' understanding of the features necessary in the AQI system, which has an impact on the perfection of the university AQI system design in accordance with the PPEPP cycle.
Keywords: FODA; IQA system; PPEPP cycle; SPMI
Abstrak: Kementerian Pendidikan, Kebudayaan, Riset, dan Teknologi telah menyusun pedoman Sistem Penjaminan Mutu Internal atau yang dikenal dengan SPMI, yang diimplementasikan melalui Audit Mutu Internal (AMI) dengan siklus PPEPP, yaitu Penetapan (P), Pelaksanaan (P), Evaluasi (E), Pengendalian (P), dan Peningkatan (P). Beberapa perguruan tinggi telah mengimplementasikan AMI dengan sistem. Permasalahannya, sistem tersebut tidak sejalan dengan siklus PPEPP, sehingga hasil audit kurang memuaskan. Tujuan dari penelitian ini adalah untuk mengevaluasi seberapa baik fitur sistem AMI milik perguruan tinggi sejalan dengan siklus PPEPP dan menyoroti peluang pengembangan. Metode yang digunakan adalah analisis Feature Oriented Domain (FODA) dan Acceptance Testing. Penelitian ini menghasilkan analisis fitur sistem AMI yang konsisten dengan PPEPP. Hasil FODA divalidasi oleh ahli dan diuji dengan User Acceptance Test (UAT) dengan 89,98% respon pengguna bahwa sistem dapat diterima. Penelitian ini memberikan kontribusi terhadap pemahaman universitas terhadap fitur-fitur yang diperlukan dalam sistem AMI, yang berdampak pada kesempurnaan desain sistem AMI universitas sesuai dengan siklus PPEPP.
Kata kunci: FODA; siklus PPEPP; sistem AMI; SPMI
Abstract:Abstract: The inability to accurately monitor the lifespan of motorcycle batteries can lead to sudden failures, disrupt user activities, and increase maintenance costs. This issue is exacerbated by the absence of a predictive…
ctive system that can assist users and workshops in planning maintenance and managing battery inventory effectively. This study aims to develop a battery lifespan prediction model for motorcycles using the Double Moving Average (DMA) method. The model is built based on historical data from 12 motorcycle units, including usage frequency, duration, terrain conditions, and maintenance habits. Forecasting is conducted through two stages of moving averages followed by trend parameter calculations. Evaluation results show that the model has a high level of accuracy, with MAPE = 0.10, MAD = 1.68, and RMSE = 2.14, indicating very low prediction errors. In addition, DMA is also used to forecast product demand at PT Anugerah Karya Abiwara Kisaran to prevent stock shortages. The system is developed using Visual Studio 2010 and Microsoft Access and has proven effective in supporting maintenance planning and inventory control. With its high accuracy and efficiency, the results of this study provide tangible contributions to decision-making in battery maintenance and inventory management.
Keywords: battery; DMA; motorcycle; prediction.
Abstrak: Ketidakmampuan dalam memantau usia pakai aki sepeda motor secara akurat dapat menyebabkan kerusakan mendadak, mengganggu aktivitas pengguna, serta meningkatkan biaya perawatan. Permasalahan ini diperburuk oleh tidak tersedianya sistem prediktif yang membantu pengguna dan bengkel dalam merencanakan perawatan serta mengelola persediaan aki secara efisien. Penelitian ini bertujuan untuk mengembangkan model prediksi usia pemakaian aki sepeda motor dengan menggunakan metode Double Moving Average (DMA). Model dibangun berdasarkan data historis dari 12 unit sepeda motor yang mencakup frekuensi penggunaan, durasi, kondisi medan dan kebiasaan perawatan. Proses peramalan dilakukan melalui dua tahap perataan bergerak, yang kemudian diikuti dengan perhitungan parameter tren. Hasil evaluasi menunjukkan bahwa model ini memiliki tingkat akurasi yang tinggi, dengan nilai MAPE sebesar 0,10, MAD sebesar 1,68, dan RMSE sebesar 2,14, yang mengindikasikan tingkat kesalahan prediksi yang sangat rendah. Selain itu, metode DMA juga diterapkan untuk meramalkan permintaan produk pada PT Anugerah Karya Abiwara Kisaran guna mencegah terjadinya kekurangan stok. Sistem dikembangkan menggunakan Visual Studio 2010 dan Microsoft Access, serta terbukti efektif dalam mendukung perencanaan perawatan dan pengendalian persediaan. Dengan akurasi dan efisiensi yang tinggi, hasil penelitian ini memberikan kontribusi nyata dalam pengambilan keputusan terkait pemeliharaan aki dan manajemen inventori.
Kata kunci: baterai; DMA; prediksi; sepeda motor.
Abstract:Abstract: In the business world, supplier selection plays a crucial role in ensuring smooth company operations. Suppliers are responsible for providing raw materials with consistent quality, timely delivery, and competitive…
ive prices. The supplier selection process requires evaluation based on various criteria such as product quality, availability, packaging, price, and warranty. Currently, SNM Store places orders by contacting suppliers one by one via telephone to inquire about item availability. This method is time-consuming and may lead to delays in fulfilling item requirements. To address this issue, a Decision Support System (DSS) is needed to assist in efficiently determining the best supplier. One method that can be used in this system is MOORA (Multi-Objective Optimization on the Basis of Ratio Analysis). MOORA is known to be effective in handling multi-criteria decision-making by simultaneously optimizing multiple objectives. This method also reduces subjectivity by assigning weights to each criterion and uses simple and fast calculations to evaluate the available alternatives. The objectives of this research are to identify the key criteria in supplier selection, apply the MOORA method in an efficient and user-friendly evaluation and selection process, and improve the operational efficiency of SNM Store in procurement so that item availability can be ensured in a timely manner.
Keywords: decision support system ; MOORA; supplier
Abstrak: Dalam dunia bisnis, pemilihan supplier memegang peranan penting dalam memastikan kelancaran operasional perusahaan. Supplier bertanggung jawab menyediakan bahan baku dengan kualitas konsisten, pengiriman tepat waktu, dan harga kompetitif. Proses seleksi supplier memerlukan evaluasi terhadap berbagai kriteria seperti kualitas produk, ketersediaan, pengemasan, harga, dan garansi. Toko SNM saat ini melakukan pemesanan dengan menghubungi supplier satu per satu melalui telepon untuk menanyakan ketersediaan barang. Metode ini memakan waktu dan dapat menyebabkan keterlambatan dalam pemenuhan kebutuhan barang. Untuk mengatasi hal tersebut, diperlukan sistem pendukung keputusan (Decision Support System) yang dapat membantu dalam menentukan supplier terbaik secara efisien. Salah satu metode yang dapat digunakan dalam sistem ini adalah MOORA (Multi-Objective Optimization on the Basis of Ratio Analysis). MOORA dikenal efektif dalam menangani keputusan multi-kriteria dengan mengoptimalkan berbagai tujuan secara bersamaan. Metode ini juga mengurangi subjektivitas melalui pemberian bobot pada tiap kriteria dan menggunakan perhitungan yang sederhana serta cepat dalam mengevaluasi alternatif yang tersedia. adapun tujuan dari penelitian ini adalah untuk mengidentifikasi kriteria-kriteria penting dalam pemilihan supplier, menerapkan metode MOORA dalam proses evaluasi dan seleksi yang efisien dan mudah digunakan, serta meningkatkan efisiensi operasional Toko SNM dalam hal pengadaan barang agar ketersediaan barang dapat terjamin tepat waktu.
Kata kunci: MOORA; sistem penunjang keputusan; supplier;
Abstract:Abstract: This study aims to develop a Deep Learning-based Traffic Flow Detector to automatically and accurately observe traffic flow. Conventional traffic observation is often conducted manually or via CCTV, but it is prone…
rone to human error and difficult to use for real-time trend analysis. In this study, the YOLOv4 method is used to detect four types of vehicles (cars, motorcycles, buses, trucks). To continuously track vehicle movement and address occlusion issues, the Deep SORT algorithm is implemented. The YOLOv4 model used is a pre-trained model and was tested on seven CCTV video recordings obtained from the official website of the Pekanbaru City Transportation Department. The system was implemented on a limited device, the Nvidia Jetson Nano, as a simulation of direct CCTV integration. Test results showed a highest precision of 98%, but the maximum accuracy achieved was only 26%. This low accuracy is influenced by several factors, including video resolution, detection model quality, and lighting conditions. Nevertheless, the system demonstrates potential to support future traffic management and engineering decisions but still requires further optimization, including improving video resolution and quality, retraining the model with a more representative local dataset, using lighter and more accurate detection models, and optimizing the tracking algorithm.
Keywords: deep learning; deepsort; NVIDIA Jetson NANO; traffic flow; YOLOv4
Abstrak: Penelitian ini bertujuan mengembangkan Traffic Flow Detector berbasis Deep Learning untuk mengobservasi arus lalu lintas secara otomatis dan akurat. Observasi lalu lintas konvensional sering dilakukan secara manual atau melalui CCTV, namun rentan terhadap human error dan sulit digunakan untuk menganalisis tren secara real-time. Pada penelitian ini digunakan metode YOLOv4 untuk mendeteksi empat jenis kendaraan (mobil, motor, bus, truk). Untuk melacak pergerakan kendaraan secara berkelanjutan dan mengatasi masalah occlusion, digunakan algoritma Deep SORT. Model YOLOv4 yang digunakan merupakan pre-trained model dan diujikan pada tujuh rekaman video CCTV yang diambil dari situs resmi Dinas Perhubungan Kota Pekanbaru. Sistem ini diimplementasikan pada perangkat terbatas Nvidia Jetson Nano sebagai simulasi penerapan langsung pada CCTV. Hasil pengujian menunjukkan presisi tertinggi mencapai 98%, namun akurasi tertingginya hanya sebesar 26%. Rendahnya akurasi dipengaruhi oleh beberapa faktor seperti resolusi video, kualitas model deteksi, serta kondisi pencahayaan. Meski demikian, sistem ini menunjukkan potensi untuk membantu pengambilan keputusan dalam manajemen dan rekayasa lalu lintas di masa depan, namun masih membutuhkan optimasi lebih lanjut, seperti peningkatan kualitas video input, pelatihan ulang model dengan dataset lokal, penggunaan model deteksi yang lebih ringan dan akurat serta pengoptimalan algoritma pelacakan.
Kata kunci: deep learning deepsort; Nvidia Jetson Nano; traffic flow; YOLOv4