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All Journal ELINVO (Electronics, Informatics, and Vocational Education) Moneter : Jurnal Akuntansi dan Keuangan Jurnal Infomedia Jurnal Vokasi Computer Science (CO-SCIENCE) Multidiciplinary Output Research for Actual and International Issue (Morfai Journal) Ekombis Sains: Jurnal Ekonomi, Keuangan dan Bisnis Bulletin of Engineering Science, Technology and Industry
Prihatin, Nanang
Politeknik Negeri Lhokseumawe
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IOT MONITORING WATER NEEDS IN RICE FIELDS Nanang Prihatin; Hari Toha Hidayat; Mursyidah; Hafhis Gustiawan
Bulletin of Engineering Science, Technology and Industry Vol. 2 No. 2 (2024): June
Publisher : PT. Radja Intercontinental Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59733/besti.v2i1.30

Abstract

Water management is a very important role in the success of increasing rice production in fields. This study took a case study on irrigated rice fields. In an effort to improve the quality and efficiency of water management in rice fields, a good monitoring system is also needed. Generally, monitoring has been done manually so far, the interaction between farmers and irrigation officers is still using the telephone, which costs a lot of money. With the IoT (Internet of Things) technology, it can be applied to a monitoring system for managing water needs in rice fields using mobile-based AHP, which is a system that provides notifications in the form of information on water levels and the best humidity values for rice plants in rice fields in real-time and is able to deliver reports via internet transmission media. This study aims to obtain the value of report delivery speed through monitoring applications and to be able to detect water levels and soil moisture in paddy fields using the Analytical Hierarchy Process (AHP) method and sensor accuracy so that the results are as expected. The research data has been obtained by looking at the suitability of soil moisture information in the application with the ETP302 measuring instrument with an accuracy value of 86.12% and the water level in applications with an actual water level of 66.35%. In testing the speed of sending reports an average value of 1.67 s. In the best soil moisture detection test using the AHP method, the suitability value is up to 91.7% and the water level reaches 93.4%. The sensor can also be turned off or on through the monitoring application.
Pelatihan Penyusunan Laporan Keuangan Dana desa (Gampong Mesjid Punteuet Kecamatan Blang Mangat Kota Lhokseumawe) Harianto, Syawal; Prihatin, Nanang; Zulfiar, Edi; Zuarni, Zuarni; Putri, Yetty Tri
Jurnal Vokasi Vol 1, No 1 (2017): April
Publisher : Politeknik Negeri Lhokseumawe

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (465.331 KB) | DOI: 10.30811/vokasi.v1i1.568

Abstract

Dana desa yang diberikan pemerintah pusat bertujuan untuk meningkatkan kesejahteraan masyarakat pedesaan. Untuk itu, penggunaan dana desa harus direncanakan, dilaksanakan dan dilaporkan untuk menilai tingkat keberhasilan program dana desa. Dalam rangka mensukseskan program dana desa ini, tim pelaksana kegiatan aplikasi Ipteks Program Hibah Desa Binaan Politeknik Negeri Lhokseumawe menyelenggarakan “Pelatihan Penyusunan Laporan Keuangan Dana Desa”.Tujuan dari penyelenggraan kegiatan Penerapan Ipteks di Gampong ini untuk, pertamamemberikan pengetahuan yang memadai mengenai pelaporan keuangan Dana Desa. Kedua memberikan pelatihan untuk penyusunan laporan keuangan Dana Desa. Kegiatan pelatihan ini dilaksanakan pada bulan Desember 2016, di Gampong Mesjid Punteuet Kecamatan Blang Mangat Kota Lhokseumawe.Pelatihan diikuti 9 orang peserta, adapun khalayak sasaran peserta terdiri dari Kepala Desa, Sekretaris Desa, Bendahara, Kaur, Kasi, pendamping, dan tenaga administrasi. Adapun pelaksanaan kegiatan pelatihan ini dilakukan dengan menggunakan metode ceramah, tutorial, dan diskusi. Kegiatan pelatihan penyusunan laporan keuangan dana desa bagi perangkat desa di Gampong Mesjid Punteuet berjalan dengan lancar. Semua peserta antusias mengikuti acara hingga selesai dan merasakan manfaat pelatihan untuk meningkatakan akuntabilitas dan transparansi pengunaan dana desa. Peserta pelatihan juga menilai bahwa pelatihan ini penting dan sangat diperlukan bagi perangkat desa. Peserta pelatihan berharap pelatihan serupa dapat dilaksanakan kembali dengan peserta (audience) yang lebih banyak/luas, dan dengan topik lainnya.Kata Kunci: Dana Desa, Laporan Keuangan Dana Desa.
CLASSIFICATION OF MIGRAINE TYPES BASED ON SYMPTOMS USING ARTIFICIAL NEURAL NETWORKS Aulia, Muhammad Kahfi; Prihatin, Nanang
Multidiciplinary Output Research For Actual and International Issue (MORFAI) Vol. 6 No. 2 (2026): Multidiciplinary Output Research For Actual and International Issue
Publisher : RADJA PUBLIKA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5281/zenodo.18811901

Abstract

Migraine is a complex neurological disorder with heterogeneous clinical manifestations, making accurate subtype classification difficult using conventional diagnostic approaches. Diagnostic inaccuracies may result in inappropriate treatment and suboptimal patient outcomes. This study proposes an Artificial Neural Network (ANN) model to classify migraine subtypes based on patient-reported symptoms and clinical characteristics. A publicly available dataset containing 400 instances and 24 features—including demographic data, aura symptoms, neurological and autonomic indicators, genetic history, and disease burden—was utilized. Data preprocessing involved feature standardization, label encoding, and one-hot encoding, followed by an 80:20 split for training and testing. The ANN architecture comprised an input layer with 23 neurons, two hidden layers with 64 and 32 neurons using ReLU activation, and a seven-neuron output layer with softmax activation. The model was trained using the Adam optimizer and categorical cross-entropy loss for 50 epochs. Experimental results showed that the proposed model achieved a training accuracy of 91.56% and a testing accuracy of 93.00%, demonstrating strong generalization performance and effective learning of complex, non-linear symptom patterns. These results indicate that ANN-based classification has significant potential as a clinical decision-support tool for improving migraine subtype diagnosis and enabling more personalized treatment strategies.
Co-Authors Amin, Haris Al Aulia, Muhammad Kahfi Cut Aja Rahmahwati E Elfiana Elfiana Elfiana, Elfiana Elfiana, E Fajri Fajri Filza Humaira Hafhis Gustiawan Halim Zaini Halim Zaini, Halim Hari Toha Hidayat Hari Toha Hidayat Harunsyah, Harunsyah Hasyimi Abdullah Herwinsyah, Reynold Husaini Husaini Intan, Syarifah Keumala Irwan Nurdin Lukman Lukman Maiyurita Maiyurita Muhammad Nasir Muhammad Sami Mukhlisul Muzahid Mursyidah Pardi Pardi Pardi Pardi, Pardi Radhiyatammardhiyyah Radhiyatammardhiyyah Rahmahwati, Cut Aja Rauzana, Rauzana Reza Fauzan Ridwan Ridwan Ridwan, Ridwan Rony, Zahara Tussoleha Rozatul Fitria Safaruddin Sami, Muhammad Satriananda, Satriananda Simbolon, Zulfan Khairil Syawal Harianto, Syawal Utaminingsih, Eka Yetty Tri Putri, Yetty Tri Zuarni, Zuarni Zulfiar, Edi