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Traditional association rule analysis is effective at uncovering co-purchase patterns but fails to provide a global structural view of the market, which often results in fragmented and isolated insights. This study proposes a hybrid framework that integrates the Apriori algorithm with a Minimum Spanning Tree (MST) in order to validate and contextualize association rules within a single structural backbone. Transaction data from a retail store are transformed into a weighted, undirected product graph using an inverse-support function, and an MST is then extracted to represent the market backbone, while frequent itemsets and strong rules are obtained using Apriori. Experimental results on 236 multi-item transactions show that the MST backbone comprises 10 products and 9 fundamental links, with 66.67% of these links being confirmed by strong association rules, indicating a substantial coherence between statistical and structural evidence. The proposed model identifies 41 Apriori patterns that can be embedded in the MST and ranks them using a new metric, Structural Distance, which enables the categorization of Core Patterns, Bridge Patterns, and Complex Patterns according to their structural tightness. This hybrid perspective distinguishes dense, strategically meaningful bundles from anomalous but frequent combinations that are structurally peripheral, thereby offering a more holistic and actionable alternative to conventional Market Basket Analysis. The validated framework can support various applications, including store layout optimization, cross-selling strategies, and the design of path-based recommender systems, and it opens avenues for future extensions based on dynamic graphs and Graph Neural Networks.

Tourism is one of the sectors that plays an important role in boosting economic growth through travel activities and destination exploration. Tourists' preferences for nature-based tourism options, such as mountain hiking or beach tourism, are influenced by various factors, ranging from personal experiences and recreational interests to social characteristics. Therefore, a technology-based approach is needed to predict destination choice tendencies more accurately. As artificial intelligence technology develops, deep learning methods have been widely used in classification processes due to their ability to process large amounts of data and recognize complex patterns. In this study, a Multilayer Perceptron (MLP) model is used to classify tourists' preferences between mountain or beach destinations based on a survey dataset. The research stages include data processing, data splitting using a train-test split, model training, and performance evaluation using accuracy, precision, recall, and F1-score. The test results show that the MLP model is capable of achieving an accuracy rate of 99%, confirming that deep learning methods are effective in automatically mapping tourism preference trends. This research is expected to serve as a basis for the development of more personalized travel destination recommendation systems, as well as to support tourism management in formulating targeted promotional strategies.

Given the great benefits of electrical energy, the availability of electrical energy sources is limited. Currently, the availability of electrical energy sources is not able to meet the increasing demand for electricity in Indonesia. The high use of electrical energy in daily life will have a negative impact on the environment. Therefore, to maintain the sustainability of energy sources, it is necessary to pursue strategic steps that can support the provision of electrical energy optimally and affordably, This study aims to find out how much total energy is used by the Energy Consumption Index (IKE) on electrical energy from the influence of electrical power and the length of time of use of electrical energy at SMK Negeri 2 Lubuk Basung, Lubuk Basung District, Agam Regency. This study aims to determine the value of energy consumption used or Energy Consumption Index (IKE) and energy saving opportunities at SMK Negeri 2 Lubuk Basung, Lubuk Basung District, Agam Regency. The results of this study are for the IKE value of the first floor which is 1.71 kWh/m2, for the IKE value of the second floor which is 0.03 kWh/m2, for the IKE value of one building, which is with a value of 1.74 kWh/m2, for the annual IKE of 0.022 kWh/m2/year and for the value of energy-saving opportunities of IDR 651 646/month IDR 7 819 755/year.

Indonesia has extraordinary resources and potential in developing renewable energy sources (RES), but various obstacles must be overcome in implementing RES. The purpose of this study is to analyze the gap in the application of RES. This gap includes energy knowledge, community participation, battery waste management, service quality, regulation, and legal policy. This study uses a mixed-methods approach, by conducting a structured questionnaire in quantitative data collection, while qualitative data collection through special interviews, focused group discussions, and conducting policy regulation analysis. The results show that 62% of people do not understand RES, 28% are involved in project planning, and 74% are unaware of SOP (standard operating procedures) regarding battery waste recycling. The results of the correlation analysis reveal a positive relationship between the level of knowledge and interest in RES (R = 0.56). Also, the developed community-based participation model includes initial involvement, transparency of information, and local incentives. These findings further strengthen the compatibility of the innovation diffusion theory, planned behavior theory, SERVQUAL, and the theory of public interest. This study will make a practical contribution through evidence-based strategies in increasing resilience, especially for policymakers and energy service providers. The impact of the policy aspects includes the need for large reforms, education, public campaigns, and the realization of battery waste management systems. This study also provides an opportunity for further study by expanding the geographical scope and related industrial sectors.

Penelitian ini bertujuan untuk mengembangkan sistem pendukung keputusan yang dapat membantu tim Marketing Officer (MO) PT. Alvarel Technology Innovation dalam menentukan status pelanggan secara objektif dan terstruktur. Sistem ini dirancang menggunakan kombinasi metode Analytical Hierarchy Process (AHP) dan Weighted Sum Model (WSM). Metode AHP digunakan untuk menentukan bobot kriteria yang meliputi Potensial Pasar, Urgensi, Finansial, serta Hubungan dan Reputasi, dengan memastikan konsistensi matriks perbandingan berpasangan. Hasil pembobotan kemudian digunakan dalam metode WSM untuk melakukan perhitungan skor total pelanggan dan menyusun pemeringkatan status berdasarkan nilai tertinggi hingga terendah. Data penelitian diperoleh dari catatan internal perusahaan dan wawancara dengan Marketing Officer, dengan jumlah sampel 30 pelanggan. Hasil pengujian menunjukkan bahwa sistem dapat menghasilkan peringkat status pelanggan dalam lima kategori, yaitu potensial, prospek, pending, pasif, dan skip. Temuan utama memperlihatkan bahwa kategori prospek memperoleh skor tertinggi dan menjadi prioritas tindak lanjut. Dengan demikian, sistem pendukung keputusan berbasis AHP–WSM ini mampu mengurangi subjektivitas, meningkatkan efisiensi, serta memberikan rekomendasi yang lebih akurat dan terukur untuk mendukung pengambilan keputusan strategis perusahaan dalam pengelolaan pelanggan.

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.

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.

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.

Kecelakaan lalu lintas di Kabupaten Brebes merupakan masalah kritis karena tingginya frekuensi insiden yang terjadi di wilayah tersebut. Penelitian ini bertujuan untuk menentukan area yang rentan terhadap kecelakaan dengan menggunakan algoritma K-Means Clustering , yang mendukung proses pengambilan keputusan berbasis data. Isu utama yang dieksplorasi dalam penelitian ini adalah bagaimana algoritma K-Means dapat diimplementasikan untuk mengelompokkan zona rawan kecelakaan dan meningkatkan kesadaran masyarakat terhadap keselamatan jalan. Metodologi yang digunakan meliputi pengumpulan data melalui tinjauan pustaka, observasi langsung, dan wawancara, yang dilanjutkan dengan penggunaan algoritma K-Means untuk mengklasifikasikan data kecelakaan berdasarkan jumlah kejadian, korban jiwa, dan cedera. Temuan menunjukkan bahwa algoritma K-Means secara efektif mengelompokkan lokasi rawan kecelakaan ke dalam tiga tingkat risiko yang berbeda: tinggi, sedang, dan rendah. Dengan demikian, informasi yang terklasifikasi ini dapat membantu otoritas terkait dalam meningkatkan langkah-langkah keselamatan lalu lintas dan mengedukasi masyarakat tentang area berisiko tinggi. Hasil penelitian ini diharapkan dapat berkontribusi pada pengembangan kebijakan keselamatan lalu lintas yang lebih terinformasi dan strategis di Kabupaten Brebes.

Penerapan konsep kota cerdas menjadi arah strategis dalam mengelola kompleksitas urbanisasi sekaligus meningkatkan kualitas sumber daya manusia agar lebih adaptif dan kompetitif. Namun, dalam praktiknya, masih ditemukan berbagai permasalahan seperti keterbatasan infrastruktur digital, rendahnya literasi teknologi masyarakat, serta belum optimalnya integrasi teknologi dalam tata kelola kota. Kesenjangan ini dapat menghambat upaya membangun SDM yang berdaya saing tinggi. Studi ini bertujuan untuk menganalisis bagaimana teknologi kecerdasan buatan dapat mendukung transformasi kota cerdas dalam kerangka peningkatan daya saing manusia. Metode yang digunakan adalah pendekatan deskriptif berbasis studi literatur, dengan fokus pada pemetaan peran kecerdasan buatan dalam mendukung pilar smart city: smart governance, smart economy, smart people, smart mobility, smart environment, smart society, dan smart living. Hasil kajian menunjukkan bahwa pemanfaatan kecerdasan buatan mampu mendorong efisiensi layanan publik, memperkuat sistem pendidikan berbasis personalisasi, mendukung analitik data untuk pengambilan keputusan, serta menciptakan ekosistem inovatif yang merangsang pengembangan kompetensi SDM. Selain itu, sinergi antara pemerintah, sektor industri, dan lembaga pendidikan menjadi kunci dalam memastikan bahwa transformasi digital yang dilakukan mampu menjangkau seluruh lapisan masyarakat secara adil dan berkelanjutan. Dengan pemanfaatan kecerdasan buatan secara inklusif dan etis, kota cerdas tidak hanya menjadi solusi teknologi, tetapi juga platform strategis dalam mencetak manusia yang unggul dan siap bersaing dalam era global.

The growing demand for affordable transportation has significantly expanded the used car market. This study aims to develop optimal sales strategies by analyzing seller types and vehicle categories through exploratory data analysis and linear regression techniques. Using a cleaned public dataset of over 150,000 used car listings in Germany, key variables such as registration year, mileage, vehicle type, and seller type were examined. Results indicate that individual sellers dominate the market, although dealers set higher and more stable prices. SUVs and limousines typically hold higher market value. The linear regression model achieved an R-squared value of 0.34, suggesting that registration year and mileage account for 34% of the price variance. These findings offer practical insights for stakeholders in the used car business to tailor pricing strategies based on vehicle attributes and seller classification

This research aims to analyze the impact of a new coil winding design in 3-phase induction motor on effiiciency, with the objective of creating a new 3-phase induction motor with improved performance. The research was conducted in the Electric Power System Laboratority, Department of Electrical Engineering, Padang Institute of Technology, and focuses solely on efficiency and its relationship to motor output power. The study involved redesigning the coils of a conventional 3-phase induction motor into a 6-phase coil design without altering the motor’s position, followed by testing both motors and comparing the efficiency of the conventional 3-phase induction motor with that of the redesigned 6-phase motor using the asymmetrical double methode. The result show that the efficiency of the 6-phase coil-designed motor increased compared to the conventional 3-phase induction motor.   importance of maintaining data security and implementing AI strategically to provide optimal benefits for consumers and business development.

This study aims to analyze the sentiment of iPhone product reviews fromAmazon using the BERT (Bidirectional Encoder Representations from Transformers) model to classify reviews as either positive or negative. The dataset, sourced from Kaggle, includes text reviews and star ratings, where high ratings indicate positive sentiment and low ratings indicate negative sentiment. After text preprocessing steps, including data cleaning, tokenization, and sentiment labeling, the BERT model was fine-tuned for sentiment classification, with the data split into training, validation, and test sets. Evaluation results demonstrate that the BERT model achieves a high classification accuracy, with an accuracy rate of 93.9% and a balanced F1 score between precision and recall. Confusion matrix evaluation also indicates that the model consistently identifies both positive and negative sentiments. This study shows that Transformer-based models like BERT are highly effective in understanding customer opinions in e-commerce, with broad application potential for data-driven decision-making in marketing strategies and product development.

This study examines the role of Artificial Intelligence (AI) in marketing strategy through a Systematic Literature Review (SLR) approach. AI has shown a transformative impact by outperforming traditional methods, especially in optimizing big data-based marketing strategies. With the ability to analyze consumer behavior in depth, AI enables businesses to personalize marketing efforts and improve user experiences more efficiently and responsively. However, challenges such as data privacy, high initial investment, and reliance on data quality remain major concerns that must be addressed. This study also evaluates the effectiveness of using AI across marketing channels, which shows significant differences in their impact on business strategy. In addition, the integration of AI-based fitness equipment is considered to have a major contribution in increasing consumer satisfaction while driving online business growth. The results of this study provide valuable insights into the effective implementation of AI, as well as highlight the importance of maintaining data security and implementing AI strategically to provide optimal benefits for consumers and business development.

The combination of activities carried out by humans and technology is related to administrative systems that create information from organized work processes. PT. Farmhouse Production in the administration of data management is carried out with the help of Microsoft Excel and documents are written, and copied in the traditional way which results in the accumulation of accumulated paper resulting in complexity and difficulty in finding the required documents. Therefore, a balance of human resources, database, hardware, software, and a new strategy is needed to overcome the problems that can burden the company by realizing a website that is easy to apply so that any file is found quickly by paying attention to supervision, control, and methodical organization using PIESCES analysis as a method used to detect deficiencies and weakness in the old system. With this analysis, the new system is the right support in managing data that is collected in an orderly manner and stored neatly in large storage without being randomized and the work is more strategic because the information generated is valuable to the recipient or leader.

Pemetaan wilayah wilayah pemasaran menjadi salah satu alat yang dapat digunakan untuk menggambarkan suatu kegiatan usaha untuk mengetahui sasaran yang tepat dalam pelaksanaannya di wilayah kerja tertentu. Penelitian ini mencoba merancang pemetaan wilayah pemasaran, diharapkan dengan penelitian ini dapat meningkatkan rencana strategis pemasaran yang tepat sasaran. Sehingga dapat membantu manajemen Dealer X cabang demak dalam menentukan kebijakan pemasarannya. Dalam pemetaan ini menggunakan software QGis untuk pemetaan. Hasil dari penelitian ini adalah peta keluaran yang dapat digunakan sebagai bahan pertimbangan bagian pemasaran untuk memetakan wilayah pemasaran yang ada di wilayah yang ditentukan.

Information technology is a technology used to process data, including processing, obtaining, compiling, storing, manipulating data in various ways to produce relevant, accurate and timely information, which is used for personal, business and government purposes and is strategic information for decision making, in recording fixed assets for example, must be managed properly because the need for the data is frequent intensity, the number of items is not small so it is impossible to memorize, the calculation of depreciation of fixed assets of a company needs to be done at the end of every year because it will affect the book value and depreciation expense on the balance sheet and depreciation expense on fixed assets on the income statement. This depreciation calculation can also be used as a reference in the allocation to purchase new assets if the existing fixed assets can no longer be used. Obstacles in preparing depreciation reports if not resolved immediately will have a bad impact on schools, for example being late in submitting annual tax reports due to the long preparation of depreciation reports will result in schools being fined for being late in reporting the annual corporate tax return. With the accounting information system for depreciation of fixed assets, it is expected that it will facilitate officers in managing fixed asset data and depreciation reports. The new system that will be designed is web-based, so that it can be accessed at any time by interested parties and makes coordination time more effective.

Indonesia terkenal sebagai negara agraris karena memiliki sumber daya alam melimpah yang didukung dengan tanah subur sehingga masyarakatnya mayoritas bermatapencaharian sebagai petani. Salah satu hasil pertanian yang berkontribusi terhadap kemiskinan di Indonesia yaitu beras. Beras dengan mudah dapat ditemukan di pasar baik pasar tradisional maupun pasar modern, namun ditengah pandemi virus corona (COVID-19) sekarang ini membuat orang merasa takut untuk pergi ke pasar karena pasar merupakan salah satu klaster terbesar penularan covid-19. Salah satu inovasi teknologi yang telah banyak digunakan dalam dunia perniagaan yaitu vending machine (VM). VM merupakan sebuah mesin penjualan otomatis yang biasanya terdapat di tempat ramai dan strategis. Hal ini yang mendasari untuk pembuatan simulasi VM beras dan diharapkan dapat menjadi salah satu solusi pemutus penyebaran dan penularan covid-19. Simulasi VM beras ini dapat melakukan penjualan otomatis beras dengan masukkan berupa uang kertas atau dengan e-money dan keluarannya berupa struk bukti pembelian beras dan 5 jenis beras. Metode yang digunakan yaitu Finite State Automata (FSA) jenis Non-deterministic Finite State Automata (NFA) yang didefinisikan lima tupel, dengan rumus: M = (Q, Σ, δ, S, F). NFA dipilih karena dapat menjelaskan konsep kerja secara rinci sehingga mudah dipahami dan hasil dari FSA dapat dibuat konsep logika sederhana untuk implementasi.

As an old educational institution, SMK Ma'arif NU 1 Ajibarang is growing rapidly, however it has not implemented Information Systems and Information Technology optimally in its business processes and does not yet have an Information Systems strategic planning portfolio. This is deemed necessary in making a strategic information system, in order to provide superiority in business competition. Information system strategic planning is one of the keys in implementing information systems and information technology in business activities. Strategic planning in this study uses themethod Ward and Peppard to compile an information system strategic plan at SMK Ma'aif NU 1 Ajibarang and AHP to determine the application roadmap. The results of this analysis define the information system strategic planning company in the form of an information system business strategy, information system management strategy and information technology, information system strategy, information system recommendations, future applications and implementation plans.