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All Journal Tech-E Algor Journal of Scientech Research and Development RUBINSTEIN
Rudy Arijanto
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Agriculture, Biological Sciences & Forestry Humanities Computer Science & IT Economics, Econometrics & Finance Education Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Social Sciences Other

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Perancangan Aplikasi Web Dengan Menggunakan Algoritma Apriori Pada Data Mining Untuk Mengetahui Pola Pembelian Konsumen PT Cipta Tunggal Elektronik Freddie Freddie; Yusuf Kurnia; Rudy Arijanto; Yakub -
ALGOR Vol 3 No 1 (2021): High Tech High Value
Publisher : Fakultas Sains dan Teknologi-Universitas Buddhi Dharma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31253/algor.v3i1.640

Abstract

PT. Cipta Tunggal Elektronik merupakan perusahaan yang bergerak dibidang distribusi sound system yang membutuhkan strategi promosi dalam penjualannya. Analisa pola pembelian konsumen dapat membantu perusahaan dalam membentuk paket penjualan agar promosi yang dilakukan tepat sasaran. Proses menganalisa pola pembelian konsumen yang dilakukan secara manual tentu akan membutuhkan waktu dan tenaga yang lebih besar. Oleh karena itu, maka dilakukan penelitian serta perancangan sebuah aplikasi yang dapat mengetahui pola pembelian konsumen dengan metode asosiasi, serta menggunakan apriori sebagai algoritmanya. Oleh karena itu, maka diperlukan sebuah rancangan aplikasi berbasis web dengan algoritma apriori. Hasil dari penelitian ini adalah dibuatnya sebuah aplikasi berbasis web yang dapat melakukan analisa pola pembelian dari data transaksi yang dimasukkan, dengan cara menentukan rentang tanggal pada data yang ingin dianalisa, serta memasukkan nilai minimum support dan minimum confidence yang diinginkan.
RANCANG BANGUN ALAT PENANGGULANGAN KEBOCORAN GAS DAN KEBAKARAN MENGGUNAKAN MIKROKONTROLER ESP8266 Yehova David Rante; Rudy Arijanto
Journal of Scientech Research and Development Vol 6 No 1 (2024): JSRD, June 2024
Publisher : Ikatan Dosen Menulis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56670/jsrd.v6i1.519

Abstract

Tujuan dari penelitian ini adalah untuk memasukkan sensor gas dan api ke dalam sistem pemantauan rumah dan mengirimkan notifikasi ke WhatsApp sebagai reaksi terhadap bahaya yang mungkin terjadi. Penelitian ini menggunakan desain dan pengembangan perangkat keras dan perangkat lunak yang terdiri dari sensor gas, sensor api, water sprayer, dinamo pompa galon, dan modul wifi untuk mengirim pesan melalui aplikasi WhatsApp. Sensor gas mengidentifikasi kebocoran dari tabung gas LPG, sedangkan sensor api mengidentifikasi percikan api yang menyebabkan kebakaran. Kondisi udara di area yang dijaga dipantau secara terus-menerus oleh sistem ini. Modul ESP8266 wifi akan mengirimkan notifikasi chat ke handphone pemilik rumah atau orang yang sudah ditentukan jika sensor mendeteksi gas berlebihan atau tanda-tanda api. Hasil pengujian menunjukkan bahwa sistem ini dapat mendeteksi bahaya gas berlebihan dan kebakaran dengan cepat dan akurat. Selain itu, notifikasi ini dapat dikirimkan segera setelah deteksi bahaya, memungkinkan tindakan cepat. Menggunakan sensor gas dan api untuk memantau dan menjaga rumah dengan notifikasi WhatsApp dapat meningkatkan keamanan dan keselamatan penghuni.
PENGARUH PEMANFAATAN TEKNOLOGI INFORMASI PADA PEDAGANG PASAR LAMA TANGERANG Rudy Arijanto; Jonathan; Rendy Hartono Jesse N.W; Delvien Wiefrand; Jonathan Rio Imanuel Agasi
Tech-E Vol. 9 No. 1 (2025): TECH-E (Technology Electronic)
Publisher : Fakultas Sains dan Teknologi-Universitas Buddhi Dharma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31253/te.v9i1.3216

Abstract

Technological progress is reshaping traditional markets, bringing improvements in speed, convenience, and reach to day-to-day trading. Digital payment platforms such as QRIS and All Payment along with e-commerce channels allow merchants to process transactions more quickly and give customers flexible, cash-free options. Although these innovations promise greater operational efficiency, widespread uptake remains uneven. Two persistent hurdles are low digital literacy and anxieties over data security, issues that often breed resistance and mistrust among stallholders. Findings from surveys and in-depth interviews suggest that tailor-made education and hands-on training are pivotal in changing perceptions. By demonstrating practical advantages like simplified bookkeeping, real-time sales tracking, and broader customer access training sessions help traders see technology as an ally rather than a threat. Equally important is the coordinated support of local governments, market management bodies, and technology vendors. Their collaboration can produce policies that lower adoption costs, provide subsidies for devices, and establish on-site help desks to address technical problems swiftly. Such institutional backing both incentivizes merchants and accelerates the diffusion of digital tools throughout the market ecosystem. Furthermore, guaranteeing reliable internet connectivity and user-friendly interfaces reduces friction in daily use, reinforcing trader confidence. Early adopters already report smoother workflows, faster customer turnover, and better record-keeping accuracy. These outcomes highlight the need for a multifaceted strategy combining capacity-building, stakeholder engagement, and infrastructure enhancement to modernize traditional commerce while safeguarding its cultural vibrancy and social relevance.
Web-Based Car Sales Prediction System Using the ARIMA (Autoregressive Integrated Moving Average) Model for Optimizing Automotive Marketing Strategies Kurnia, Yusuf; Yakub; Rudy Arijanto; Winson Layanda; Dwi Putra, Dicky Surya
RUBINSTEIN Vol. 4 No. 1 (2025): RUBINSTEIN (juRnal mUltidisiplin BIsNis Sains TEknologI & humaNiora)
Publisher : LP3kM Buddhi Dharma University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31253/rubin.v4i1.4039

Abstract

This study aims to develop a web-based car sales prediction system using the ARIMA (Autoregressive Integrated Moving Average) model to support the optimization of marketing strategies in the automotive sector. With the rapid growth of the automotive industry in Indonesia, companies, particularly car showrooms, face the challenge of accurately forecasting vehicle demand. Therefore, an ARIMA-based prediction system can assist in estimating future sales based on historical data, thereby improving stock management, distribution, and marketing strategies. The system was developed using five years of historical sales data and implemented the ARIMA model to forecast car sales for upcoming periods. It was built with the Python programming language, employing Flask for the backend and HTML, CSS, and JavaScript for the frontend. The prediction results are presented in the form of interactive graphs, enabling users to make data-driven decisions more effectively. System evaluation was carried out by measuring prediction accuracy using MAPE (Mean Absolute Percentage Error) and RMSE (Root Mean Square Error) metrics. The testing results indicate that the ARIMA model can generate predictions with a high level of accuracy, assisting showrooms in planning stock and promotional activities more efficiently. Furthermore, the system is equipped with a responsive user interface, making it easily accessible via mobile devices. This research contributes to the utilization of technology in sales planning, particularly in the automotive sector, by enabling more precise, efficient, and data-driven decision-making.
Co-Authors Delvien Wiefrand Dwi Putra, Dicky Surya Freddie Freddie Jonathan Jonathan Rio Imanuel Agasi Rendy Hartono Jesse N.W Winson Layanda Yakub Yakub - Yehova David Rante Yusuf Kurnia Yusuf Kurnia, Yusuf