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Smart Tester Berbasis Mikrokontroler ATMega 328P Sigit Candra Setia
Jusikom : Jurnal Sistem Komputer Musirawas Vol 2 No 1 (2017): Jusikom : Jurnal Sistem Komputer Musirawas JUNI
Publisher : LPPM UNIVERSITAS BINA INSAN

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (647.948 KB) | DOI: 10.32767/jusikom.v2i1.47

Abstract

Abstrak Mikrokontroler kini semakin berkembang pesat dan semakin banyak diminati dalam aplikasi sistem kendali. Bahkan saat ini sudah banyak mikrokontroler yang menjadi yang sudah dalam bentuk modul. Salah satu modul mikrokontroler yang banyak digunakan adalah arduino. Arduino adalah jenis suatu papan yang berisi mikrokontroler. Multimeter yang biasa dijual dipasaran kebanyakan hanya untuk mengukur arus, tegangan, dan resistansi suatu komponen elektronika dan tidak dapat mengukur kutub-kutub dari masing-masing komponen tersebut sehingga harus mempelajari lebih lanjut untuk mengetahui mana saja kutub dari komponen-komponen. Hal ini tentu jadi suatu permasalahan tersendiri bagi yang akan merangkai suatu komponen elektronika. Maka dari itu, sangat dibutuhkan suatu alat ukur yang tidak hanya mengukur besaran arus, tegangan, dan resistansi suatu komponen, tetapi juga dapat mengetahui kutub-kutub dan kaki-kaki seperti komponen dioda dan transistor. Hal ini dapat diwujudkan dengan merancang suatu Smart Tester yang dapat mengukur kaki-kaki komponen elektronika. Dengan menggunakan mikrokontroler. Data hasil pengukuran setiap komponen akan ditampilkan melalui LCD Display.
Strategi Pemberdayaan dan Kesadaran Lingkungan Masyarakat dalam Pengelolaan Bank Sampah Berbasis 3R (Reduce, Reuse, dan Recycle) Menggunakan Google Form Candra Setya, Sigit; Novansyah, Hairil
Jurnal Pengabdian Kepada Masyarakat Vol 2 No 01 (2025): Jurnal Pengabdian Kepada Masyarakat
Publisher : Alihsanpublisher

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Permasalahan pengelolaan sampah di masyarakat masih menjadi tantangan serius yang berdampak terhadap kualitas lingkungan dan kesehatan publik. Rendahnya kesadaran dan partisipasi masyarakat dalam memilah dan mengelola sampah mengakibatkan peningkatan volume sampah yang tidak terkelola dengan baik. Penerapan prinsip 3R (Reduce, Reuse, Recycle) menjadi salah satu pendekatan penting dalam menanggulangi permasalahan ini secara berkelanjutan. Di era digital, pemanfaatan teknologi seperti Google Form dapat berperan strategis dalam mendukung pengelolaan sampah, khususnya dalam proses pendataan dan penyebaran informasi secara efektif. Kegiatan pengabdian ini bertujuan untuk mengidentifikasi cara pemberdayaan masyarakat dalam pengelolaan Bank Sampah berbasis 3R menggunakan Google Form. Kegiatan dilaksanakan di Kelurahan 29 Ilir Kecamatan Ilir Barat Dua Kota Palembang melalui pendekatan sosialisasi, pelatihan, dan pendampingan masyarakat dalam penggunaan teknologi untuk mendukung aktivitas pengelolaan sampah. Hasil dari kegiatan ini menunjukkan bahwa penggunaan Google Form mampu mempermudah proses pencatatan data sampah yang disetorkan oleh warga, meningkatkan keterlibatan masyarakat dalam program Bank Sampah, serta membuka akses informasi lingkungan yang lebih luas. Kegiatan ini memberikan manfaat langsung berupa peningkatan kesadaran lingkungan, pemberdayaan masyarakat dalam pengelolaan sampah rumah tangga, dan peningkatan literasi digital masyarakat dalam konteks keberlanjutan lingkungan. Dengan demikian, strategi ini berkontribusi dalam menciptakan masyarakat yang lebih peduli lingkungan serta mendukung pencapaian tujuan pembangunan berkelanjutan.
Optimizing Insurance Customer Segmentation with C4.5 Decision Tree Algorithm Setya, Sigit Candra; Perangin-angin, Moch. Iswan; Marsono, Marsono; Nasyuha, Asyahri Hadi; Harnaningrum, Lucia Nugraheni
Journal of Information System Research (JOSH) Vol 6 No 4 (2025): July 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josh.v6i4.7358

Abstract

Insurance companies rely on premium payments as their primary source of revenue. However, economic instability often causes delays in premium payments, impacting revenue recording. This study applies the C4.5 Decision Tree algorithm to classify insurance customers based on premium amount, age, income, and claim history, thereby improving product recommendations. The research utilizes data mining techniques to analyze customer attributes and generate decision rules for optimal insurance product selection. The findings indicate that customers with a premium of IDR 500,000 are best suited for PRUMed Cover (PMC), while those with IDR 1,000,000 are recommended PRUCritical Benefit 88 (PCB88). For customers with IDR 750,000, additional factors such as age and income level influence the recommended insurance type. The entropy and information gain calculations identify premium amount as the most significant attribute for decision-making, followed by age, income, and claim history. By implementing this method, insurance companies can enhance customer segmentation, streamline product selection, and optimize marketing strategies. The transparent and interpretable decision tree structure ensures regulatory compliance while improving customer satisfaction. Future research should explore additional variables, such as behavioral data and regional trends, and compare C4.5 with other classification algorithms like Random Forest or Support Vector Machines (SVM) to enhance accuracy and scalability.
Implementasi Sistem Hotspot Menggunakan Mikrotik Dan Captive Portal Sebagai Media Penunjang Aktivitas Belajar Hairil Novansyah; Sigit Candra Setya
BETRIK Vol. 16 No. 02 (2025): Jurnal Ilmiah BETRIK : Besemah Teknologi Informasi dan Komputer
Publisher : PPPM Institut Teknologi Pagar Alam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36050/4er7dd06

Abstract

The need for internet access on campus is increasing, particularly for searching and utilizing information to support the teaching and learning process. At the Pagar Alam Institute of Technology, the current hotspot network is limited to certain rooms, such as the STAFF, LPPM, BAAK, and Multimedia Laboratory, making it difficult for all students to access it equally. This situation results in limited access to information and hinders the learning process. This research aims to design and implement a dedicated student hotspot network to expand internet access on campus. The PPDIOO (Prepare, Planning, Design, Implement, Operate, Optimize) method is used, supported by Unified Modeling Language (UML)-based system modeling tools, such as use case diagrams and activity diagrams. The Queue Tree method is used to manage and distribute bandwidth. The result of this research is a hotspot network accessible to students on campus, with a bandwidth of 512 Kbps per user. This network supports various learning activities, such as browsing, access to the SPADA and SISTA systems, and other online learning services like YouTube This implementation is expected to support the academic process and improve the quality of learning at the Pagar Alam Institute of Technology.
Rancang Bangun Robot Line Follower Berbasis Arduino sebagai Media Edukasi pada Mata Kuliah Robotika Hairil Novansyah; Sigit Candra Setya; Efan
BETRIK Vol. 16 No. 03 (2025): Jurnal Ilmiah BETRIK : Besemah Teknologi Informasi dan Komputer
Publisher : PPPM Institut Teknologi Pagar Alam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36050/fn8vav65

Abstract

Information technology is currently growing rapidly, one of which is the use of a robot. This researcher aims to design and build a Line Follower robot as a demonstration medium in robotics courses at the Pagar Alam High School of Technology. Researchers make a robot for demonstration media in robotics courses, because in this course the conventional media still uses power points and a video. Therefore, it is necessary to make a tool for conventional media as a teaching aid in robotics courses. by utilizing a microcontroller, Motor Drive, PIR Sensor and DC Motor, to make a Line Follower robot. The method used in this research is the Rapid Application Development (RAD) system developer method. The stages used are Requirement planning, design workshop, Build The System and Implementation. The devices that the researchers use include the ATmega328 microcontroller, motor drive, DC motor, and infrared sensor. To obtain data in this study, researchers used data collection techniques including observation, interviews and literature study. From the results of the tests that have been carried out by researchers for line follower cars, researchers have succeeded in making and running a line follower car and this car will be shaped like an offroad car that runs automatically following the trajectory guide line. Based on the results of the pre-test, the average score was 35.9% and the post-test score was 90.9% in the high category. Based on the results of these tests, it can improve student learning systems before and after there is a tool as a medium of democracy in robotics courses.
Prediksi Cryptocurrency Berbasis LSTM Menggunakan Multi Modal Indikator Trading(Studi: Ethereum dan Solana) Arya; Yogi Isro' Mukti; Alfis Arif; -, Sigit Candra Setya
BETRIK Vol. 17 No. 01 (2026): Jurnal Ilmiah BETRIK : Besemah Teknologi Informasi dan Komputer
Publisher : PPPM Institut Teknologi Pagar Alam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36050/83kqq228

Abstract

The dynamic development of the cryptocurrency market causes digital asset prices to experience high volatility, making it difficult for investors to accurately predict price movements. Therefore, an analytical method is needed to model price movement patterns in time series data. This study aims to develop a cryptocurrency price prediction model for Ethereum and Solana using the Long Short-Term Memory (LSTM) method with a multi-modal trading indicator approach. The dataset used consists of historical price data including open, high, low, close, trading volume, and technical indicators such as Exponential Moving Average (EMA), Relative Strength Index (RSI), and Bollinger Bands. The research process follows the CRISP-DM methodology, which includes business understanding, data understanding, data preparation, modelling, evaluation, and deployment stages. The data were processed through normalization and time series windowing, with a training and testing data split of 80:20. The evaluation results using Root Mean Square Error (RMSE) and Mean Absolute Percentage Error (MAPE) indicate that the model has good predictive performance. The Ethereum model produced an RMSE value of 129.08 and a MAPE of 3.26%, while the Solana model produced an RMSE of 8.30 and a MAPE of 3.63%. The developed model was also implemented in a Streamlit-based dashboard to visualize prediction results interactively, helping users monitor and analyze cryptocurrency price movements.