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All Journal EMITTER International Journal of Engineering Technology Jurnal Infomedia El-Mujtama: Jurnal Pengabdian Masyarakat
Isbat Uzzin Nadhori, Isbat Uzzin
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Religion Computer Science & IT Economics, Econometrics & Finance Education Languange, Linguistic, Communication & Media Social Sciences

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Combination Adaptive Traffic Algorithm and Coordinated Sleeping in Wireless Sensor Network Al Rasyid, M. Udin Harun; Aji, Eka Saputra; Nadhori, Isbat Uzzin
EMITTER International Journal of Engineering Technology Vol 2, No 2 (2014)
Publisher : Politeknik Elektronika Negeri Surabaya (PENS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (9680.169 KB)

Abstract

Wireless sensor network (WSN) uses a battery as its primary power source, so that WSN will be limited to battery power for long operations. The WSN should be able to save the energy consumption in order to operate in a long time.WSN has the potential to be the future of wireless communications solutions. WSN are small but has a variety of functions that can help human life. WSN has the wide variety of sensors and can communicate quickly making it easier for people to obtain information accurately and quickly. In this study, we combine adaptive traffic algorithms and coordinated sleeping as power‐efficient WSN solution. We compared the performance of our proposed ideas combination adaptive traffic and coordinated sleeping algorithm with non‐adaptive scheme. From the simulation results, our proposed idea has good‐quality data transmission and more efficient in energy consumption, but it has higher delay than that of non‐adaptive scheme.Keywords:WSN,adaptive traffic,coordinated sleeping,beacon order,superframe order.
Combination Adaptive Traffic Algorithm and Coordinated Sleeping in Wireless Sensor Network Al Rasyid, M. Udin Harun; Aji, Eka Saputra; Nadhori, Isbat Uzzin
EMITTER International Journal of Engineering Technology Vol 2, No 2 (2014)
Publisher : Politeknik Elektronika Negeri Surabaya (PENS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (9680.169 KB) | DOI: 10.24003/emitter.v2i2.23

Abstract

Wireless sensor network (WSN) uses a battery as its primary power source, so that WSN will be limited to battery power for long operations. The WSN should be able to save the energy consumption in order to operate in a long time.WSN has the potential to be the future of wireless communications solutions. WSN are small but has a variety of functions that can help human life. WSN has the wide variety of sensors and can communicate quickly making it easier for people to obtain information accurately and quickly. In this study, we combine adaptive traffic algorithms and coordinated sleeping as power‐efficient WSN solution. We compared the performance of our proposed ideas combination adaptive traffic and coordinated sleeping algorithm with non‐adaptive scheme. From the simulation results, our proposed idea has good‐quality data transmission and more efficient in energy consumption, but it has higher delay than that of non‐adaptive scheme.Keywords:WSN,adaptive traffic,coordinated sleeping,beacon order,superframe order.
Penerapan Algoritma Binning pada Preprocessing Data untuk Meningkatkan Akurasi Klasifikasi Multi-Kelas: Studi Kasus Data SDG Nur Fadhillah, Wiradika; Susetyoko, Ronny; Nadhori, Isbat Uzzin
Jurnal Infomedia: Teknik Informatika, Multimedia, dan Jaringan Vol 10, No 2 (2025): Jurnal Infomedia
Publisher : Politeknik Negeri Lhokseumawe

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30811/jim.v10i2.7165

Abstract

Klasifikasi data memainkan peran esensial dalam analisis data, terutama untuk data Sustainable Development Goals (SDGs) yang seringkali memiliki karakteristik kompleks seperti nilai hilang dan distribusi tidak seimbang, sehingga memerlukan tahap preprocessing yang efektif. Penelitian ini bertujuan untuk mengevaluasi secara komprehensif efektivitas tiga teknik binning, yaitu Fixed Binning, Random Binning, dan KNN Binning, dalam meningkatkan akurasi klasifikasi multikelas pada data SDGs. Teknik binning ini diimplementasikan dan diuji menggunakan tiga algoritma klasifikasi utama, yaitu Random Forest, Logistic Regression, dan Multilayer Perceptron (MLP). Penelitian ini menggunakan dua dataset yang merepresentasikan data SDGs, yaitu data pembangunan berkelanjutan dan ketahanan pangan. Dataset tersebut adalah dataset UKT dengan 2.137 entri dan dataset Ketahanan pangan dengan 514 entri. KNN Binning dipilih karena kemampuannya mengelompokkan data berdasarkan kedekatan antar instans, adaptif terhadap distribusi data yang kompleks. Hasil penelitian secara konsisten menunjukkan bahwa KNN Binning memberikan peningkatan akurasi tertinggi. Secara spesifik, kombinasi KNN Binning dengan Random Forest menghasilkan akurasi 92.25% pada dataset UKT dan 73.79% pada dataset Ketahanan pangan. Lebih lanjut, kombinasi ini juga menunjukkan peningkatan pada metrik presisi, recall, dan F1 score. Temuan ini menggarisbawahi superioritas KNN Binning dalam menangani data SDGs yang beragam dan tidak merata, sehingga memberikan kontribusi penting bagi pengembangan teknik preprocessing yang lebih akurat, andal, dan dapat meningkatkan performa model klasifikasi secara keseluruhan untuk analisis data SDGs.
Implementasi Aplikasi Chatbot Informasi Pelayanan Kelurahan Keputih, Surabaya Edelani, Renovita; Satriyanto, Edi; Nadhori, Isbat Uzzin; Susetyoko, Ronny; Barakbah, Aliridho; Karlita, Tita; Muliawati, Tri Hadiah; Fadliana, Alfi; Maulana, Wahyu Ikbal; Insani, Fawzan; Fauzi Nafi'Ubadah, Kriza; Haikal Yuniarta Krisgianto, Ricko; Saputra, Muhammad Krisnanda Vilovan; Ridho, Bistiana Syafina; Ni'Ma, Najma Akmalina; Damayanti, Anita; Febrianto, Ardiansyah Indra; Alde, Muhammad Riski
El-Mujtama: Jurnal Pengabdian Masyarakat  Vol. 5 No. 2 (2025): El-Mujtama: Jurnal Pengabdian Masyarakat
Publisher : Intitut Agama Islam Nasional Laa Roiba Bogor

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47467/elmujtama.v5i2.6272

Abstract

In today's era of digital transformation, the government, particularly Kelurahan Keputih, is aware of the community's need for information regarding the management of kependudukan and non-kependudukan documents. Given their busy lifestyles, residents require a medium to access information related to these matters. This service information is needed to improve bureaucratic efficiency, accelerate information access, and reduce the burden of manual administrative work. Therefore, researchers have developed an AI-based Intelligent Chatbot application using Large Language Modeling (LLM) technology to assist both employees and residents of Kelurahan Keputih in obtaining information related to the management of kependudukan and non-kependudukan services. The implementation of this Chatbot utilizes the Hugging Face library and the LangChain model, one of the Llama models developed by Meta. This Kelurahan Keputih Service Information Chatbot application is named "BambuBot". This application benefits the residents of Keputih by providing them with interactive, comprehensive, and easily accessible information regarding services for managing kependudukan and non-kependudukan documents, as well as platforms for processing these documents.
Co-Authors Alde, Muhammad Riski Alfi Fadliana Ali Ridho Barakbah ANITA DAMAYANTI Edelani, Renovita Edi Satriyanto Eka Saputra Aji, Eka Saputra Fauzi Nafi'Ubadah, Kriza Febrianto, Ardiansyah Indra Haikal Yuniarta Krisgianto, Ricko Insani, Fawzan M Udin Harun Al Rasyid, M Udin Harun Maulana, Wahyu Ikbal Ni'Ma, Najma Akmalina Nur Fadhillah, Wiradika Ridho, Bistiana Syafina Saputra, Muhammad Krisnanda Vilovan Susetyoko, Ronny Tita Karlita Tri Hadiah Muliawati, Tri Hadiah