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Perancangan Alat Sistem Keamanan Kendaraan Berbasis SMS dan GPS Elvin Syahrin
Journal Of Informatics And Busisnes Vol. 1 No. 4 (2024): Januari - Maret
Publisher : CV. ITTC INDONESIA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47233/jibs.v1i4.725

Abstract

Motor vehicle theft is currently rampant, making it difficult for owners to recover their lost vehicles and forcing them to be constantly vigilant. Tracking the position of the vehicle during theft is a challenge for vehicle owners. A security system based on SMS and GPS for vehicles allows owners to track the location of their vehicles when theft occurs. They can also control the vehicle's power via SMS. The remote control system utilizes an SMS modem, while location reading utilizes a GPS module. To determine the vehicle's location, simply send an SMS "GET LOCATION". Once the SMS is sent and read by the modem, the modem will reply with the vehicle's location to the sender's SMS number
Sistem Cerdas Rekomendasi Klinik Pratama di Kota Medan Berbasis Data Mining Dengan Metode K-Means Untuk Pasien BPJS dan Umum Dedi Leman; Elvin Syahrin
Jurnal Ilmu Komputer dan Sistem Informasi Vol. 3 No. 3 (2024): September 2024
Publisher : LKP Unity Academy

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70340/jirsi.v3i3.144

Abstract

The growth in the number of clinics in Medan City, along with the increasing population, has triggered a need for more efficient and targeted healthcare services. However, patients often face difficulties in choosing clinics that meet their medical needs, especially BPJS Kesehatan users and general patients. This is due to the lack of information regarding the facilities, service quality, and optimal clinic locations. To address this issue, an Intelligent Clinic Recommendation System is needed to provide clinic suggestions based on patient profiles and needs. This study aims to develop a clinic recommendation system in Medan City using data mining techniques with the K-Means Clustering method. The K-Means method is employed to group clinics based on several important criteria, such as location, types of services, doctor availability, and the clinic's capability to accept BPJS patients as well as general patients. Patient data analyzed includes medical history, distance from the clinic, and service preferences. The results of the study show that the K-Means-based recommendation system can effectively cluster clinics and provide relevant recommendations according to patient profiles. This system not only helps patients choose the right clinic but also improves the efficiency of patient distribution in Klinik Pratama across Medan City. With the implementation of this system, it is expected that access to healthcare services will become more equitable and the quality of services will improve, both for BPJS and general patients.
Peningkatan Kompetensi Teknologi Jaringan Melalui Pelatihan Penggunaan Router TP-Link Pada SMK Swasta Budi Agung Medan Muhammad Reza Fahlevi; Dini Ridha Dwiki Putri; Elvin Syahrin; Aditya Maulana Nst
Jurnal Pengabdian Masyarakat Mandira Cendikia Vol. 4 No. 1 (2025)
Publisher : YAYASAN PENDIDIKAN MANDIRA CENDIKIA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70570/jpkmmc.v4i1.1589

Abstract

Jaringan nirkabel merupakan solusi praktis dalam membangun konektivitas jaringan komputer, mendukung efisiensi akses internet di ruang publik dan institusi. Router TP-Link menjadi perangkat utama untuk mengatur dan mendistribusikan IP Address secara dinamis atau statis melalui teknologi kabel maupun nirkabel. Kegiatan pengabdian ini bertujuan meningkatkan pemahaman dan keterampilan siswa SMK Swasta Budi Agung Medan dalam membangun jaringan nirkabel menggunakan router TP-Link. Metode pelatihan meliputi ceramah, diskusi, dan praktik langsung. Materi mencakup pengenalan jaringan nirkabel, fungsi router TP-Link, dan konfigurasi sebagai wireless access point. Hasilnya, pelatihan ini meningkatkan pengetahuan dasar siswa tentang jaringan nirkabel serta keterampilan teknis dalam konfigurasi router. Kegiatan ini diharapkan dapat mendukung pengembangan kompetensi siswa di bidang teknologi informasi untuk memenuhi kebutuhan dunia industri
Pelatihan Robotika Dasar Untuk Meningkatkan Kompetensi Teknologi Siswa SMK Rahmad Doni; Fetty Ade Putri; Elvin Syahrin; Dwi Rika Uswani
Jurnal Pengabdian Masyarakat Mandira Cendikia Vol. 4 No. 7 (2025)
Publisher : YAYASAN PENDIDIKAN MANDIRA CENDIKIA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70570/jpkmmc.v4i7.1785

Abstract

Perkembangan teknologi di era Revolusi Industri 4.0 menuntut dunia pendidikan, khususnya Sekolah Menengah Kejuruan (SMK) agar dapat membekali siswanya dengan kompetensi yang relevan dengan kebutuhan industri modern saat ini. Salah satu kompetensi yang diperlukan adalah penguasaan dasar dalam bidang robotika dan otomasi. Penelitian ini bertujuan untuk mengkaji efektivitas pelatihan robotika dasar dalam meningkatkan kompetensi teknologi siswa SMK, yang mencakup pengenalan konsep robotika, pengenalan mikrokontroler, serta praktikum perakitan robot sederhana. Hasil menunjukkan adanya peningkatan signifikan pada pemahaman konsep dan keterampilan teknis siswa. Selain itu, pelatihan ini juga meningkatkan minat dan kepercayaan diri siswa terhadap pembelajaran teknologi khususnya dalam bidan robotika dan otomasi. Dapat disimpulkan bahwa pelatihan robotika dasar dinilai efektif dalam meningkatkan kompetensi teknologi siswa SMK
Sistem Deteksi Hama Tanaman Bawang Merah Menggunakan Algoritma K-Means Clustering Muhammad Reza Fahlevi; Dini Ridha Dwiki Putri; Rahmad Doni; Elvin Syahrin; Miftahul Mardiayah
Jurnal Elektronika dan Teknik Informatika Terapan ( JENTIK ) Vol. 3 No. 2 (2025): Juni: Jurnal Elektronika dan Teknik Informatika Terapan (JENTIK)
Publisher : Politeknik Kampar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59061/jentik.v3i2.1135

Abstract

 Farmers often have difficulty detecting pest attacks on shallots early due to limited experience and the use of manual methods that tend to be subjective. To address this issue, this study aims to develop an Android application that can detect pest attacks quickly and accurately using the K-Means Clustering algorithm. This algorithm analyzes five main plant symptoms: leaf color, leaf shape, soil moisture, leaf spots, and plant growth. The research method includes several stages, namely system requirements analysis, application design, implementation using the Java programming language and SQLite database, and testing with a black-box testing approach to ensure application functionality. In the classification process, user data is converted into numeric vectors and the distance is calculated using the Euclidean formula to three cluster centroids: Pest Free, Alert, and Pest Attacked. The application then displays the classification results directly and stores the detection history using RecyclerView. Based on manual calculations of the test data, the centroid of the “Alert” cluster shows the closest distance of 10.10 in the first iteration and gets closer to 5.05 in the second iteration after the centroid is updated. Test results show that the application can accurately classify plant conditions based on symptoms, effectively store and display detection history, and provide an easy-to-use interface that can function offline. Therefore, this application can be a useful tool for farmers in detecting pest attacks on shallots.