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All Journal Jurnal Promkes: The Indonesian Journal of Health Promotion and Health Education KLIK (Kumpulan jurnaL Ilmu Komputer) (e-Journal) Jurnal Teknovasi : Jurnal Teknik dan Inovasi Mesin Otomotif, Komputer, Industri dan Elektronika Paradoks : Jurnal Ilmu Ekonomi OKTAL : Jurnal Ilmu Komputer dan Sains
Syahrul Ramadan
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Aerospace Engineering Agriculture, Biological Sciences & Forestry Astronomy Chemistry Computer Science & IT Electrical & Electronics Engineering Engineering Health Professions Industrial & Manufacturing Engineering Materials Science & Nanotechnology Social Sciences

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MODEL JARINGAN SYARAF TIRUAN DALAM MEMPREDIKSI PENDAPATAN PERKAPITA MASYARAKAT PERKOTAAN PADA GARIS KEMISKINAN BERDASARKAN PROPINSI Solikhun Solikhun; Ahmad Revi; Syahrul Ramadan; Rina Novita Sari
KLIK- KUMPULAN JURNAL ILMU KOMPUTER Vol 5, No 2 (2018)
Publisher : Lambung Mangkurat University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20527/klik.v5i2.136

Abstract

The problem of poverty is one of the fundamental issues that becomes the center of attention of the Government in any country. In an effort to realize the provisions as stipulated in Article 28A of the 1945 Constitution of the State of the Republic of Indonesia which affirms that every person has the right to live and has the right to maintain his life and life, the GOI has established a poverty reduction program as a priority program. The primary target of poverty is mostly in urban areas, because the large number of residents who do transmigration to improve the economy but failed to get results. This study contributes to the government to predict the per capita opinion of urban communities according to the poverty line based on the province in the future. The data used is data from the National Statistics Agency through the website www.bps.go.id. The data is data on per capita income of urban communities on poverty line by province in 2013 semester 2 until 2016 semester 2. Algorithm used in this research is Artificial Neural Network with Backpropogation method. The input variables are data of year 2014 semester (X1), data of 2014 semester 1 (X2), data of 2014 semester 2 (X3), data of 2015 semester 1 (X4), data of 2015 semester 2 ( X5) and data of 2016 semester 1 (X6) with architectural model of training and testing as much as 4 architecture that is 6-2-1, 6-6-1, 6-3-2-1 and 6-2-3-1. The output generated is the best pattern of the ANN architecture. The best architectural model is 6-3-2-1 with epoch 1190, MSE 0,0102524619 and 100% accuracy rate. From this model, the prediction of per capita income of urban community on the poverty line is based on the provinces of each province in Indonesia.Keywords: Income Per Capita, ANN, Backpropogation and PredictionMasalah kemiskinan merupakan salah satu persoalan mendasar yang menjadi pusat perhatian Pemerintah di negara manapun. Dalam Upaya mewujudkan ketentuan sebagaimana ditetapkan Pasal 28A Undang-Undang Dasar Negara Republik Indonesia Tahun 1945 yang menegaskan bahwa setiap orang berhak untuk hidup serta berhak mempertahankan hidup dan kehidupannya, maka Pemerintah Indonesia telah menetapkan program penanggulangan kemiskinan sebagai program prioritas. Sasaran primer kemiskinan mayoritas lebih banyak terdapat di perkotaan, sebab banyaknya para penduduk yang melakukan transmigrasi guna memperbaiki perekonomian namun malah gagal mendapatkan hasil. Penelitian ini memberikan kontribusi bagi pemerintah untuk dapat memprediksi pendapat perkapita masyarakat perkotaan menurut garis kemiskinan berdasarkan propinsi ke depan. Data yang digunakan adalah data dari Badan Statistik Nasional melalui website www.bps.go.id. Data tersebut adalah data pendapatan perkapita masyarakat perkotaan pada garis kemiskinan berdasarkan propinsi tahun 2013 semster 2 sampai dengan tahun 2016 semester 2. Algoritma yang digunakan pada penelitian ini adalah Jaringan Saraf Tiruan dengan metode Backpropogation. Variabel masukan (input) yang digunakan adalah data tahun 2013 semester 2(X1), data tahun 2014 semester 1(X2), data tahun 2014 semester 2(X3), data tahun 2015 semester 1(X4), data tahun 2015 semester 2(X5) dan data tahun 2016 semester 1(X6) dengan model arsitektur pelatihan dan pengujian sebanyak 4 arsitektur yakni 6-2-1, 6-6-1, 6-3-2-1 dan 6-2-3-1. Data target diambil dari data tahun 2016 semster 2. Keluaran yang dihasilkan adalah pola terbaik dari arsitektur JST. Model arsitektur terbaik adalah 6-3-2-1 dengan epoch 1190, MSE 0,0102524619 dan tingkat akurasi 100%. Dari model ini maka dihasilkan prediksi pendapatan perkapita masyarakat perkotaan pada garis kemisikinan berdasarkan propinsi dari masing-masing propinsi di Indonesia.Kata Kunci: Pendapata Perkapita, JST, Backpropogation dan Prediksi
Model Jaringan Syaraf Tiruan Dalam Memprediksi Produksi Susu Segar Di Indonesia Berdasarkan Propinsi Rika Asma Dewi; Rusmansyah Rusmansyah; Syahrul Ramadan; Sundari Retno Andani; Solikhun Solikhun
Jurnal Teknovasi : Jurnal Teknik dan Inovasi Vol 6, No 1 (2019): Teknovasi April 2019
Publisher : LPPM Politeknik LP3I Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55445/teknovasi.v6i1.281

Abstract

The problem of drinking fresh milk in Indonesia looks minimal and rarely from children to adults who drink fresh milk, both milk and milk in canned milk. In an effort to realize the provisions as stipulated in the Minister of Health Regulation No. 75 of 2013 informing one's nutritional needs based on age and sex, the Indonesian Government has increased nutritional needs in Indonesia. This research contributes to the government to be able to predict the Production of Fresh Milk in Indonesia by Province. The data used is data from the National Statistics Agency through the website www.bps.go.id. The data is predictive data of fresh milk from 2010 to 2017. The algorithm used in this study is Artificial Neural Networks with the Backpropogation method. The input variables used were data for 2010 (X1), data for 2011 (X2), data for 2012 (X3), data for 2013 (X4), data for 2014 (X5), data for 2015 (X6) and 2016 data (X7) with 4 training and testing architectural models, namely 7-2-1, 7-4-1, 7-16-1 and 7-32-1. Target data is taken from 2017 data. The resulting output is the best pattern of Artificial Neural Network architecture. The best architectural model is 7-4-1 with EPOCH 1042, MSE 0.0095979 and 100% accuracy rate. From this model, the prediction of Fresh Milk Production is based on provinces in Indonesia.
Factors in Rejecting Covid-19 Vaccine in Indonesia: A Systematic Review Indana Zulva, Dewi; Eka Sari, Jayanti Dian; Syahrul Ramadan; Afan Alfayad; Anjali Putri Agustin; Syifaul Lailiyah
Jurnal Promkes: The Indonesian Journal of Health Promotion and Health Education Vol. 12 No. SI1 (2024): Jurnal Promkes: The Indonesian Journal of Health Promotion and Health Educat
Publisher : Universitas Airlangga

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20473/jpk.V12.ISI1.2024.163-173

Abstract

Background: The primary approach to mitigating the Covid-19 epidemic is the implementation of community-wide vaccination initiatives. Nevertheless, a significant obstacle is the widespread refusal to accept the administration of the Covid-19 vaccination. Aims: This study aims to ascertain the determinants behind vaccination hesitancy towards the Covid-19 vaccine in Indonesia. Methods: The research methodology used in this work involves a systematic review approach, specifically using a literature study technique. The literature review used the Google Scholar, Neliti, and Garuda Jurnal databases, focusing on publications published between 2020 and 2021. The literature study search included inclusion criteria encompassing studies involving human subjects, open access availability, and publication in national journals. Results: 38 related publications were identified by the keywords. There were 9 studies subjected to analysis in the final process. Conclusion: The rejection of vaccines in Indonesia can be attributed to various factors, including the prevalence of COVID-19 hoaxes and conspiracies, the level of public knowledge, attitudes, and perceptions towards vaccines, doubts and concerns regarding their efficacy, potential side effects, safety, and compliance with halal standards, as well as the influence of individuals in close relationships.
Pengaruh Corporate Social Responsibility (CSR) Terhadap Kesejahteraan Masyarakat di Desa Leling Kecamatan Tommo Kabupaten Mamuju Syahrul Ramadan; Herman; Yati Heryati
Paradoks : Jurnal Ilmu Ekonomi Vol. 8 No. 4 (2025): Agustus - Oktober
Publisher : Fakultas Ekonomi, Universitas Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57178/paradoks.v8i4.1951

Abstract

Penelitian ini bertujuan untuk menganalisis pengaruh Corporate Social Responsibility (CSR) PT. Manakarra Unggul Lestari terhadap kesejahteraan masyarakat di Desa Leling, Kecamatan Tommo, Kabupaten Mamuju, serta mengukur tingkat korelasi antara pelaksanaan CSR dengan kesejahteraan masyarakat di wilayah tersebut. Jenis penelitian yang digunakan adalah penelitian deskriptif dengan metode pengumpulan data melalui observasi, wawancara, kuesioner, dan dokumentasi. Analisis data dilakukan menggunakan regresi linear sederhana dengan uji validitas, uji reliabilitas, uji t (parsial), dan uji koefisien determinasi. Hasil penelitian menunjukkan bahwa variabel CSR berpengaruh signifikan terhadap kesejahteraan masyarakat, dengan nilai signifikansi sebesar 0,038 (< 0,05). Selain itu, hasil analisis korelasi menunjukkan bahwa CSR memiliki hubungan positif terhadap kesejahteraan masyarakat dengan nilai korelasi sebesar 23,2%. Temuan ini mengindikasikan bahwa program CSR PT. Manakarra Unggul Lestari berkontribusi dalam meningkatkan kesejahteraan masyarakat di Desa Leling, meskipun pengaruhnya masih dalam kategori rendah.
Pengujian Black Box pada Aplikasi Absensi Karyawan Berbasis Web dengan Teknik Equivalence Partitions Ilham Ramdhani; Risky Tuah Sinaga; Syahrul Ramadan; Wahyu Diansyah; Aries Saifudin
OKTAL : Jurnal Ilmu Komputer dan Sains Vol 2 No 06 (2023): OKTAL : Jurnal Ilmu Komputer Dan Sains
Publisher : CV. Multi Kreasi Media

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

In the application system there are some bugs or errors in the making. Therefore it is necessary to test the application so that it runs properly and checks whether a program is running properly. The application aims to evaluate whether a software is functioning as it should or there are still some program errors that must be corrected so that the quality of the software is said to be good. The methods that are used for testing include Blackbox testing which is often used by testers to study whether the program is synchronized or not. In this article the software that will be studied uses Blackbox Testing to test a web-based attendance application system at PT Sigma Cipta Utama. There are several methods in Blackbox Testing, one of which is using the Equivalence Partitions technique, which means testing based on input in each form in the Petgram mobile software, where there are the required results and the actual results together with successful or failed conclusions. Each input presentation will be tested and grouped according to its use, whether it is valid or invalid. So it is hoped that using this test is the quality of the software produced according to the expected functions, and can provide profits for the company.
Analisa Perbandingan Metode SAW, WP dan TOPSIS Dalam Sistem Pendukung Keputusan Pada Kasus Pemilihan Manajer Ilham Ramdani; Syahrul Ramadan; Risky Tuah Sinaga; Wahyu Diansyah; Robby Jordan
OKTAL : Jurnal Ilmu Komputer dan Sains Vol 2 No 08 (2023): OKTAL : Jurnal Ilmu Komputer Dan Sains
Publisher : CV. Multi Kreasi Media

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Abstract

In making a decision, it is necessary to have the right consideration so that you don't regret making a decision.If a wrong step in making a decision will certainly be fatal for the person who made the decision.Therefore we need a system that can analyze a decision.Decision support systems are one of the sciences of information systems that are intended as a tool for decision making.Decision support systems are designed to offer decision makers different options for completing tasks.Decision support systems incorporate computational capabilities into interactive services to users by processing or manipulating data using certain structured models or rules to produce various decisions in decision-making situations.There are several methods analyzed in decision making systems such as simple additive weighting (SAW), product weight (WP), Technique for Order Preference by Similarity to Ideal Solution (TOPSIS).
Co-Authors Afan Alfayad Ahmad Revi Anjali Putri Agustin Aries Saifudin Herman Ilham Ramdani Ilham Ramdhani Indana Zulva, Dewi Jayanti Dian Eka Sari, Jayanti Dian Rika Asma Dewi Rina Novita Sari Risky Tuah Sinaga Robby Jordan Rusmansyah Rusmansyah Solikhun Solikhun Solikhun Solikhun Sundari Retno Andani Syifaul Lailiyah, Syifaul Wahyu Diansyah Yati Heryati