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All Journal JOURNAL OF SCIENCE AND SOCIAL RESEARCH Saber: Jurnal Teknik Informatika, Sains dan Ilmu Komunikasi Jurnal Pengabdian Masyarakat dan Riset Pendidikan
Weny Nur Afdilla Simangunsong
Universitas Asahan
Humanities Computer Science & IT Economics, Econometrics & Finance Education Languange, Linguistic, Communication & Media Mathematics Social Sciences Other

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Implementasi Sistem Lampu Otomatis Berbasis Internet of Things (IOT): Penelitian Weny Nur Afdilla Simangunsong; Dicky Apdillah; Dini Farhatun; Zulfa Ar Rahman
Jurnal Pengabdian Masyarakat dan Riset Pendidikan Vol. 4 No. 3 (2026): Jurnal Pengabdian Masyarakat dan Riset Pendidikan Volume 4 Nomor 3 (Januari 202
Publisher : Lembaga Penelitian dan Pengabdian Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/jerkin.v4i3.5107

Abstract

The use of lighting systems is still commonly controlled manually, which often leads to inefficient electricity consumption, especially when lights remain on while not in use. This study aims to design and implement an automatic lighting control and monitoring system based on the Internet of Things (IoT). The research method applied is an experimental method consisting of system design, implementation, and testing stages. The system is developed using NodeMCU ESP8266 as the main controller, a relay as the actuator, and an LDR sensor to detect ambient light intensity. The test results indicate that the system is capable of controlling lights automatically and manually through a web-based monitoring interface with reliable performance. The implementation of this system reduces dependence on manual operation and improves electrical energy efficiency. Therefore, the proposed IoT-based lighting control and monitoring system can serve as an alternative solution to optimize energy usage in residential and public facilities.
KLASIFIKASI TIPE KACA MENGGUNAKAN METODE K-NEAREST NEIGHBOR Muhammad Azwar Al Ayyub; Weny Nur Afdilla Simangunsong; Dini Farhatun; Emi Dea; Selfina Agustin; Zulfa Ar Rahman; Muhammad Ridho
JOURNAL OF SCIENCE AND SOCIAL RESEARCH Vol. 9 No. 1 (2026): February 2026
Publisher : Smart Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54314/jssr.v9i1.5745

Abstract

Abstract: Glass is a material that is widely used in various fields, such as construction, the automotive industry, and household appliances. Each type of glass has different characteristics based on its chemical composition and production process. Problems arise when the process of identifying glass types is still done manually, which is time-consuming, costly, and prone to error. This study aims to apply the K-Nearest Neighbor (K-NN) method in classifying glass types based on their chemical content attributes. The data in this study was sourced from Kaggle, namely the Glass Identification Dataset. The data used consisted of several chemical features, such as Na, Mg, Al, Si, K, Ca, Ba, and Fe, with seven categories of glass classes. The results showed that the K-NN method was able to classify glass types well and could be an effective solution to assist in the automatic glass identification process. Keyword: Classification, K-Nearest Neighbor, Data Mining, Types of Glass. Abstrak: Kaca merupakan material yang banyak digunakan dalam berbagai bidang, seperti konstruksi, industri otomotif, dan peralatan rumah tangga. Setiap jenis kaca memiliki karakteristik yang berbeda berdasarkan komposisi kimia dan proses produksinya. Permasalahan muncul ketika proses identifikasi jenis kaca masih dilakukan secara manual, sehingga membutuhkan waktu, biaya, dan berpotensi menimbulkan kesalahan. Penelitian ini bertujuan untuk menerapkan metode K-Nearest Neighbor (K-NN) dalam mengklasifikasikan jenis kaca berdasarkan atribut kandungan kimianya. Data dalam penelitian ini bersumber dari Kaggle, yaitu Glass Identification Dataset. Data yang digunakan terdiri dari beberapa fitur kimia, seperti Na, Mg, Al, Si, K, Ca, Ba, dan Fe, dengan tujuh kategori kelas kaca. Hasil penelitian menunjukkan bahwa metode KNN mampu mengklasifikasikan jenis kaca dengan baik dan dapat menjadi solusi yang efektif untuk membantu proses identifikasi kaca secara otomatis. Kata kunci: Klasifikasi, K-Nearest Neighbor, Data Mining, Jenis Kaca.
IMPLEMENTASI SINGLE LAYER PERCEPTRON DALAM KLASIFIKASI KETERSEDIAAN TENAGA KESEHATAN DI PROVINSI SUMATERA UTARA Weny Nur Afdilla Simangunsong; Harmayani Harmayani
JOURNAL OF SCIENCE AND SOCIAL RESEARCH Vol. 9 No. 4 (2026): August 2026 (1)
Publisher : Smart Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54314/jssr.v9i4.7113

Abstract

Abstract: The equitable availability of health workers is an essential factor in improving the quality of healthcare services. The unequal distribution of nurses across regencies and cities in North Sumatra Province has created the need for an approach capable of identifying the level of health workforce availability quickly and objectively. This study aims to implement the Single Layer Perceptron model to classify the level of health workforce availability based on the number of nurses, population, and public health centers. The study utilized secondary data obtained from the North Sumatra Provincial Health Office for the period of 2019–2024. Prior to the training process, the data were normalized using the Min-Max Normalization method and divided into 80% training data and 20% testing data. The training process employed a learning rate of 0.1, a maximum of 3,000 epochs, and an error tolerance of 0.01. The proposed model classified the data into two categories, namely low and high, and was implemented in a web-based application that supports data training, prediction, and classification result evaluation. The results demonstrate that the Single Layer Perceptron model is capable of recognizing patterns in health workforce availability and performing classification effectively, thereby supporting decision-making processes related to the equitable distribution of health workers in North Sumatra Province. Furthermore, the developed system facilitates data management and provides computerized classification results efficiently. Keywords: Single Layer Perceptron, Classification, Artificial Neural Network, Health Workforce, North Sumatra Province.   Abstrak: Ketersediaan tenaga kesehatan yang merata merupakan faktor penting dalam meningkatkan kualitas pelayanan kesehatan. Ketimpangan distribusi tenaga perawat antar kabupaten/kota di Provinsi Sumatera Utara menyebabkan perlunya suatu pendekatan yang mampu mengidentifikasi tingkat ketersediaan tenaga kesehatan secara cepat dan objektif. Penelitian ini bertujuan mengimplementasikan model Single Layer Perceptron untuk mengklasifikasikan tingkat ketersediaan tenaga kesehatan berdasarkan data jumlah perawat, jumlah penduduk, dan jumlah puskesmas. Data yang digunakan merupakan data sekunder dari Dinas Kesehatan Provinsi Sumatera Utara periode 2019–2024. Sebelum proses pelatihan, data dinormalisasi menggunakan metode Min-Max Normalization, kemudian dibagi menjadi 80% data latih dan 20% data uji. Proses pelatihan menggunakan learning rate sebesar 0,1, maksimum epoch sebanyak 3000, serta error tolerance sebesar 0,01. Model menghasilkan klasifikasi ke dalam dua kategori, yaitu rendah dan tinggi, serta diimplementasikan dalam aplikasi berbasis web yang mendukung proses pelatihan, prediksi, dan evaluasi hasil klasifikasi. Hasil penelitian menunjukkan bahwa Single Layer Perceptron mampu mengenali pola ketersediaan tenaga kesehatan dan memberikan hasil klasifikasi secara efektif sehingga dapat mendukung proses pengambilan keputusan dalam pemerataan tenaga kesehatan di Provinsi Sumatera Utara. Implementasi sistem yang dikembangkan juga mempermudah pengelolaan data dan penyajian informasi klasifikasi secara terkomputerisasi. Kata Kunci: Single Layer Perceptron, klasifikasi, jaringan saraf tiruan, tenaga kesehatan, Provinsi Sumatera Utara.
Rancang Bangun Sistem Informasi Website Desa Aekkorsik untuk Meningkatkan Aksesibilitas dan Layanan Digital Masyarakat Ramadhani Fitri Panjaitan; Weny Nur Afdilla Simangunsong; Zulfa Ar Rahman; Khairul Saleh
SABER : Jurnal Teknik Informatika, Sains dan Ilmu Komunikasi Vol. 3 No. 4 (2025): Oktober: Jurnal Teknik Informatika, Sains dan Ilmu Komunikasi
Publisher : STIKes Ibnu Sina Ajibarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59841/saber.v3i4.3314

Abstract

the village level. Aek Korsik Village, located in Aek Ledong Subdistrict, Asahan Regency, does not yet have an official website as an information medium or a platform for digital public services. This condition limits the community’s access to village information and keeps administrative services in a conventional, manual system. Through the Community Service Program (Kuliah Kerja Nyata/KKN) Group 5, Faculty of Engineering, Universitas Asahan, a web-based information system was designed and developed for Aek Korsik Village with the aim of improving information accessibility, village government transparency, and the efficiency of digital services for the community. The system development process involved field observations, interviews with village officials, needs analysis, user interface design, implementation, and website testing. The developed village website provides key features such as village profile, news and announcements, online administrative services, and information on village potential. The implementation results show that the website serves as an effective communication medium, facilitates community access to information, and supports transparency in public services. This study also recommends further development, such as mobile application integration and enhanced system security, to ensure the sustainability of digital services in Aek Korsik Village
Co-Authors Dicky Apdillah Dini Farhatun Emi Dea Harmayani Khairul Saleh Muhammad Azwar Al Ayyub Muhammad Ridho Ramadhani Fitri Panjaitan Selfina Agustin Zulfa Ar Rahman