Article Per Year (5 Year)
p-Index From 2021 - 2026
3.725
P-Index
This Author published in this journals
All Journal Techno.Com: Jurnal Teknologi Informasi Jurnal Komputer Terapan INOVTEK Polbeng - Seri Informatika Jurnal Informatika Universitas Pamulang JURIKOM (Jurnal Riset Komputer) Jurnal Sistem Komputer dan Informatika (JSON) Madani : Indonesian Journal of Civil Society Journal of Applied Computer Science and Technology (JACOST) Journal of Computer and Information System (J-CIS) Jurnal Pengabdian Kepada Masyarakat Indonesia
Nur, Nahya
Universitas Sulawesi Barat
Agriculture, Biological Sciences & Forestry Humanities Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Engineering Public Health Social Sciences

Published : 24 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 24 Documents
Search

 1   2   3 
Application of Decision Support System for Selection of Residential Criteria using the fuzzy Method in Majene Regency Irianti, Arnita; Quraisy, Muh. Imam; Sulfayanti, Sulfayanti; Nur, Nahya; Ardi, Rahmawati
Jurnal Komputer Terapan Vol 10 No 1 (2024): Jurnal Komputer Terapan
Publisher : Politeknik Caltex Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35143/jkt.v10i1.5870

Abstract

In this digital era, information technology is growing rapidly so that it is used to market various things, including homes. There is a lot of information technology about houses being marketed, but it takes a long time to collect information and compare one house to another. However, some of the housing marketed no longer prioritizes comfort, but rather cheap or economical prices. Due to the fact that sometimes unclear data is needed to solve problems, the fuzzy method is a decision-making approach that uses standard relationships but applies fuzzy set theory to the database. Decision making regarding the selection of comfortable housing criteria according to consumers is carried out using the fuzzy Tahani model approach. The fuzzy holdi technique uses house data that has been processed to produce output in the form of house data that is recommended for customers.
Prediksi Harga Gabah Kering Panen menggunakan Metode Autoregressive Integrated Moving Average Ria, Canda; Wajidi, Farid; Nur, Nahya
Jurnal Sistem Komputer dan Informatika (JSON) Vol. 6 No. 4 (2025): Juni 2025
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/json.v6i4.8614

Abstract

Gabah kering panen (GKP) merupakan komoditas pertanian strategis yang berperan signifikan dalam mendukung ketahanan pangan nasional. Fluktuasi harga gabah yang tidak menentu menjadi tantangan serius bagi petani dalam menentukan harga jual hasil panen. Dalam penelitian ini, harga gabah kering panen diprediksi dengan menggunakan metode   Autoregressive Integrated Moving Average (ARIMA). Data yang digunakan diambil dari data bulanan yang dikumpulkan oleh Badan Pusat Statistik (BPS) dari januari 2010 hingga desember 2024. Proses penelitian meliputi tahap pengumpulan data, pengolahan data, uji stasioneritas menggunakan Augmented Dickey-Fuller (ADF), analisis Autocorrelation Function (ACF) dan Partial Autocorrelation Function (PACF), pemilihan parameter optimal (p, d, q) menggunakan pendekatan grid search, pembangunan model ARIMA, prediksi, dan mengevaluasi performa model. Hasil uji ADF menunjukkan bahwa data menjadi stasioner setelah differencing kedua. Berdasarkan hasil grid search dan nilai Akaike Information Criterion (AIC) yang paling rendah. Dengan nilai AIC, model yang paling cocok adalah ARIMA (1,2,2). Sebesar 2188,98. Evaluasi terhadap nilai Mean Absolute Percentage Error (MAPE) sebesar 8,90%, Root Mean Squared Error (RMSE) sebesar 636,97 dan Mean Squared Error (MSE) sebesar 405731,65. Dari hasil penelitian ini, dapat disimpulkan bahwa model ARIMA cukup andal dan akurat dalam memprediksi harga gabah kering panen.
Pendekatan Backpropagation Artificial Neural Network Untuk Prediksi Kemurnian Madu Tafsir, Andi Muh Ihsanul; Sulfayanti, Sulfayanti; Nur, Nahya
Techno.Com Vol. 24 No. 4 (2025): November 2025
Publisher : LPPM Universitas Dian Nuswantoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62411/tc.v24i4.14855

Abstract

Madu merupakan produk alami yang kemurniannya menjadi indikator utama kualitas dan keasliannya. Penelitian ini bertujuan untuk memprediksi tingkat kemurnian madu menggunakan algoritma Artificial Neural Network (ANN) dengan metode Backpropagation. Dataset terdiri dari 247.903 data dengan 10 atribut madu yang digunakan sebagai variabel input, sedangkan tingkat kemurnian madu dijadikan sebagai target output. Tahapan penelitian meliputi pra-pemrosesan data, pelatihan model, serta evaluasi hasil prediksi. Setelah melalui tahap pra-pemrosesan, jumlah fitur input bertambah menjadi 27. Pada proses eksperimen, dilakukan pengujian beberapa variasi arsitektur (27-14-14-1, 27-27-27-1, 27-54-54-1), fungsi aktivasi (ReLU, sigmoid biner, sigmoid bipolar), learning rate (0,01, 0,1, 0,5), dan jumlah epoch (1000, 1500, 2000) untuk memperoleh konfigurasi terbaik. Hasil optimal diperoleh pada arsitektur jaringan 27-54-54-1 dengan fungsi aktivasi ReLU, learning rate 0,5, dan jumlah epoch sebanyak 2000. Konfigurasi tersebut menghasilkan kinerja prediksi dengan nilai Mean Squared Error (MSE) 0,000542, R-squared (R²) sebesar 0,972010, dan Mean Absolute Percentage Error (MAPE) 1,26%. Hasil ini membuktikan bahwa algoritma Backpropagation Artificial Neural Network dapat digunakan secara efektif dalam memprediksi tingkat kemurnian madu. Kata Kunci - Artificial Neural Network, Backpropagation, Prediksi, Kemurnian Madu
Pemanfaatan Sistem Informasi Edukasi Mitigasi Bencana pada KSR PMI Unit Markas Majene Nahya Nur; Farid Wajidi; Ade Mulawarman; Muh. Adrian; Rifky Gunawan
Jurnal Pengabdian kepada Masyarakat Indonesia (JPKMI) Vol. 2 No. 3 (2022): Desember : Jurnal Pengabdian Kepada Masyarakat Indonesia (JPKMI)
Publisher : Pusat Riset dan Inovasi Nasional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/jpkmi.v2i3.726

Abstract

The availability of information related to disasters is one of the efforts so that the public better understands the actions that must be taken to minimize the risks that occur. However, the availability of this information, especially in the Majene Regency area, is currently still quite minimal. In fact, Majene is one of the areas with a fairly high Disaster Risk Index. This activity embraces the Voluntary Corps (KSR) PMI Majene Headquarters Unit as a partner considering that KSR is one of the organizations engaged in the humanitarian field and actively participates in disaster management. The activities carried out include the use of a disaster education information system by providing training to KSR members in managing the system and creating disaster education content. The results of the activities obtained show an increase in the ability of KSR members in terms of management and content creation using Canva and hopes that the disaster education information system that has been built can continue to be used for the dissemination of disaster information.
Co-Authors -, Ika Nurul Fadhillah Ade Mulawarman Agus Zainal Arifin Alifia Puspaningrum Ardi, Rahmawati Arfiah, Sitti Arnita Irianti Asmawati Asnan Cirua, A. Amirul Aulia, Novita Dian Megah Sari Dian Megah Sari Faharuddin Situju, Sulfayanti Farid Wajidi Fitriani Fitriani Halal, Nursan Heliawaty Hamrul Heliawaty Hamrul, Heliawaty Heri, Adi Iin Aisyah Khofifah Indra Indra Indra Indra Iqram, Muh. Irianti, Arnita Ismaun Muh. Adrian Muh. Adrian mustafa, mukhdar Nur Syahra Nurdina Rasjid Nurul Inayah Putri, Haerya Quraisy, Muh. Imam Rasjid, Nurdina Rensa, Erma Ria, Canda Rian, Andrian Rifky Gunawan Rifky Gunawan Riza, Ozzy Secio Situju, Sulfayanti Sugiarto Cokrowibowo Sulfayanti Sulfayanti Sulfayanti, Sulfayanti Syarkia Yunus Tafsir, Andi Muh Ihsanul wahyuni wahyuni rahman Wildayani Wildayani