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All Journal Jurnal Online Mahasiswa (JOM) Bidang Ilmu Sosial dan Ilmu Politik J-SAKTI (Jurnal Sains Komputer dan Informatika) JURTEKSI JOISIE (Journal Of Information Systems And Informatics Engineering) JATI (Jurnal Mahasiswa Teknik Informatika) TIN: TERAPAN INFORMATIKA NUSANTARA Jurnal Manajemen Informatika Jayakarta J-SAKTI (Jurnal Sains Komputer dan Informatika) Edu Sociata : Jurnal Pendidikan Sosiologi Journal of Artificial Intelligence and Engineering Applications (JAIEA) Jurnal Pengabdian Pada Masyarakat METHABDI Majalah Ilmiah METHODA
Safii, M.
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Analysis of Decreased Public Awareness in the Application of Health Protocols with the C4.5 . Algorithm Arfika, Retno; Safii, M.
Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 1 No. 1 (2021): October 2021
Publisher : Yayasan Kita Menulis

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (427.989 KB) | DOI: 10.59934/jaiea.v1i1.56

Abstract

The purpose of this study is to determine the dominant factors that affect the decline in public awarenesson the application of health protocols using the C4.5 Algorithm. Sources of data used in this study obtained by conducting observations and interviews. The variables used include (1) Employment, (2) Environment, (3) Sanctions and (4) Concern. The research test process uses RapidMiner software to create a decision tree. The results obtained 6 rules with 4 rules decreasing status and 2 rules increasing status. The level of accuracy obtained is 100%. The results of this study are expected to be input for the surrounding community to better understand the importance of implementing health protocols at this time, so that they can help the Government to succeed in the health protocol awareness program in inhibiting the spread of Covid-19 in Indonesia.
PERANCANGAN ABSENSI QR CODE MAHASISWA BERBASIS WEBSITE PADA STIKOM TUNAS BANGSA PEMATANG SIANTAR MENGGUNAKAN METODE AGILE Rafai, Muhammad; Solikhun, Solikhun; Safii, M.
Jurnal Manajamen Informatika Jayakarta Vol 4 No 1 (2024): JMI Jayakarta (February 2024) Seleksi Paper SENATIKA-4 (October 2023)
Publisher : Sekolah Tinggi Manajemen Informatika dan Komputer Jayakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52362/jmijayakarta.v4i1.1303

Abstract

This research discusses the implementation of a web-based attendance system that utilizes QR scanner technology to record individual attendance, especially in an educational environment. The report also highlights the primary benefits of this approach, such as process efficiency, data accuracy, and real-time information access. The web-based attendance system using QR scanner technology not only enhances administrative effectiveness but also provides a more modern and interactive experience for individuals who need to be accounted for. This helps reduce the risk of errors in manual attendance recording and provides faster and more accurate access to attendance data. In this research, the author used various methods to collect data, including observation and a literature review. The author relied on various online documentation sources as data references for this report. The documents used by the author included several Scopus-indexed journals, e-books, and various digital news pages from the past 5 years. For the development method of this website, the author employed the Agile methodology. Agile is one of the models of the Software Development Life Cycle (SDLC). The results of this research, which combine QR codes and web access, make this attendance system a relevant and innovative solution for efficient attendance management.
ALGORITMA K-MEANS DALAM PENGELOMPOKAN SURAT KELUAR DI KANTOR KEMENTERIAN AGAMA KOTA PEMATANG SIANTAR Nasution, Mhd Aditia; Safii, M.
Jurnal Manajamen Informatika Jayakarta Vol 4 No 1 (2024): JMI Jayakarta (February 2024) Seleksi Paper SENATIKA-4 (October 2023)
Publisher : Sekolah Tinggi Manajemen Informatika dan Komputer Jayakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52362/jmijayakarta.v4i1.1304

Abstract

The management of outgoing letters within the Office of the Ministry of Religious Affairs in Pematang Siantar City is a crucial aspect of its operations. In an effort to enhance the efficiency and effectiveness of outgoing letter management, this research introduces the implementation of the K-Means Algorithm as one of the solutions. The objective of this research is to evaluate the impact of using the K-Means Algorithm in grouping outgoing letters. The results of the research indicate that the K-Means Algorithm has significantly aided in the process of grouping outgoing letters by identifying relevant patterns and characteristics. Grouping outgoing letters based on specific attribute similarities has allowed for improved letter distribution efficiency and a better understanding of sending patterns. Furthermore, the potential for further development in terms of integration with an electronic letter management system is evident. Therefore, this research demonstrates that the K-Means Algorithm has the potential to enhance outgoing letter management within the Office of the Ministry of Religious Affairs in Pematang Siantar City and can be considered a valuable tool in improving operational efficiency and publicservice.
PENERAPAN ALGORITMA BACKPROPOGATION DALAM PREDIKSI JUMLAH PENDUDUK DI PROVINSI SUMATERA UTARA Napitupulu, Pretty Natalia; Safii, M.
Jurnal Manajamen Informatika Jayakarta Vol 4 No 1 (2024): JMI Jayakarta (February 2024) Seleksi Paper SENATIKA-4 (October 2023)
Publisher : Sekolah Tinggi Manajemen Informatika dan Komputer Jayakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52362/jmijayakarta.v4i1.1300

Abstract

Total Population is the total number of individuals living in an area or country at any given time.country at any given time. However, a large population has several negative effects of social instability, poverty, reduced quality of life, and increased unemployment.quality of life, and increased unemployment. This research discusses the application of the Backpropagation algorithm in predicting population in the province of North Sumatra province. The purpose of this research is to make predictions that can help local governments in development planning and more effective management of resources more effectively. The Backpropagation method is used in training of the artificial neural network model using historical data on the population population and the factors that influence the growth. The results of experimental results show that the resulting model is able to provide fairly accurate predictions with an acceptable error rate. This paper presents the results of research that aims to apply the Backpropagation algorithm in an effort to predict population in North Sumatra province from 2013-2022 using Microsoft Excel and Matlab version 2011b for data processing and analysis. version 2011b for data processing and analysis. The architecture uses three models, namely: 4-5-1, 4-10-1, 4-15-1. The most accurate architecture model is 3-15-1 model which has a Mean Squared Error (MSE) of 0.00000034 and 100% accuracy rate with time 00:05 at epoch 92.
ANALISA TINGKAT KEPUASAN REKANAN PADA CV KARYA ABSHOR PEMATANG SIANTAR MENGGUNAKAN ALGORITMA C4.5 Ardilla, Ririn; Andani, Sundari Retno; Safii, M.
Jurnal Manajamen Informatika Jayakarta Vol 4 No 1 (2024): JMI Jayakarta (February 2024) Seleksi Paper SENATIKA-4 (October 2023)
Publisher : Sekolah Tinggi Manajemen Informatika dan Komputer Jayakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52362/jmijayakarta.v4i1.1307

Abstract

CV Karya Abshor Pematang Siantar is a company engaged in the procurement of goods and services, where this company can meet consumer needs such as operational support equipment, photocopy printing, contractors, leveransir, distributors and suppliers. There are many goods and services procurement businesses that offer various promos, prizes, and at low prices. If the customer is not satisfied with it, all will be in vain. The purpose of this study is to help CV owners. Karya Abshor knows the benchmark for partner satisfaction to be able to compete with other partner companies. Researchers will analyze partner satisfaction with attributes of service, performance, speed, convenience, cooperation, and satisfaction. By utilizing data mining techniques from the three tests that have been carried out on the partner satisfaction dataset distributed to 73 partners, it can be predicted using the C4.5 algorithm (decision tree) with an accuracy result of 95.45% with the help of the RapidMiner 8.1 tool. With these results, it can be used to measure the level of partner satisfaction with the procurement company CV Karya Abshor.[1] The author suggests that this research can be developed again using other methods and algorithms to get a comparison of results and steps to use them. And it's best to use more data and attributes to produce more accurate rules and be able to compare the classification process.
PENERAPAN METODE REGRESI LINEAR SEDERHANA DALAM MEMPREDIKSI TANDAN BUAH SEGAR MASUK DI PKS DOLOK ILIR Rizki, Fahrizal; Irawan, Eka; Safii, M.
Jurnal Manajamen Informatika Jayakarta Vol 4 No 1 (2024): JMI Jayakarta (February 2024) Seleksi Paper SENATIKA-4 (October 2023)
Publisher : Sekolah Tinggi Manajemen Informatika dan Komputer Jayakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52362/jmijayakarta.v4i1.1301

Abstract

Oil palm is a very important crop in the agricultural sector today. This is because oil palm is the country's largest foreign exchange earner as well as a driver of the people's economy and plays a role in employment. Dolok Ilir Palm Oil Mill is one of the business units of PT Perkebunan Nusantara 4 which is engaged in the palm oil sector. As a plantation that has a palm oil processing plant, PKS Dolok Ilir also processes palm oil from other PTPN IV plantation units. Fresh fruit bunches entering the Dolok Ilir PKS are still difficult to predict. The high number of incoming Fresh Fruit Bunches and limited processing capacity causes some fruits cannot be processed on the same day, this will have an impact on reducing the quality of Fresh Fruit Bunches (FFB) and the quality of Crude Palm Oil (CPO). From these problems, an algorithm is needed to predict incoming Fresh Fruit Bunches (FFB) at the Dolok Ilir PKS.
ANALYSIS OF THE BACKPROPAGATION ALGORITHM IN PREDICTING WATER VOLUME OF PDAM TIRTAULI PEMATANG SIANTAR CITY Ramadani, Saputra; Wanto, Anjar; Safii, M.
JURTEKSI (jurnal Teknologi dan Sistem Informasi) Vol. 10 No. 2 (2024): Maret 2024
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat (LPPM) STMIK Royal Kisaran

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33330/jurteksi.v10i2.2893

Abstract

Abstract: Increasing living standards cause an increase in the need for drinking water. However, current water supply estimates are still not optimal, with water production sometimes being more or less than requirements. To estimate the amount of water, an appropriate method is needed. The method used in this research is the back propagation algorithm artificial neural network method. When developing forecasts, past data is necessary to produce accurate results. This research aims to develop a predictive model that can estimate the volume of water that will be used by PDAM Tirtauli in the future. It is hoped that this predictive model can help PDAMs in planning more efficient water supply management and can reduce the potential for water supply shortages in the future. This research uses water distribution data for the 2015-2022 period. Training data starts in 2015-2021, testing data starts in 2016-2022. In this research, results were obtained using the Matlab R2011a application. In this research, the 5 architectures used are architecture 6-53-1, 6-58-1, 6-61-1, 6-81-1, 6-87-1. Based on these five architectures, the best architecture was obtained, namely architecture 6-87-1 with a root mean square error test value of 0.00010031 and an accuracy of 92%. The results achieved in 2023 are the total water volume of PDAM Tirtauli Pematangsiantar of 189,610,426.                                                                                            Keywords: backpropagation; distribution; PDAM; prediction; water   Abstrak: Meningkatnya taraf hidup menyebabkan meningkatnya kebutuhan akan air minum. Namun, perkiraan pasokan air saat ini masih belum optimal, dengan produksi air kadang-kadang lebih atau kurang dari kebutuhan. Untuk memperkirakan jumlah air diperlukan suatu metode yang sesuai. Metode yang digunakan dalam penelitian ini adalah metode jaringan syaraf tiruan algoritma back propagation. Saat mengembangkan perkiraan, data masa lalu diperlukan untuk menghasilkan hasil yang akurat. Penelitian ini bertujuan untuk mengembangkan model prediktif yang dapat memperkirakan volume air yang akan digunakan oleh PDAM Tirtauli di masa mendatang. Model prediktif ini diharapkan dapat membantu PDAM dalam perencanaan pengelolaan pasokan air yang lebih efisien dan dapat mengurangi potensi kekurangan pasokan air pada masa yang akan datang. Penelitian ini menggunakan data sebaran air periode 2015-2022. Data pelatihan dimulai pada tahun 2015-2021, data pengujian dimulai pada tahun 2016-2022. Pada penelitian ini diperoleh hasil dengan menggunakan aplikasi Matlab R2011a. Pada penelitian ini 5 arsitektur yang digunakan adalah arsitektur 6-53-1, 6-58-1, 6-61-1, 6-81-1, 6-87-1. Berdasarkan kelima arsitektur tersebut diperoleh arsitektur terbaik yaitu arsitektur 6-87-1 dengan nilai uji root mean square error sebesar 0,00010031 dan mendapatkan akurasi sebesar 92%. Hasil yang dicapai pada tahun 2023 adalah total volume air PDAM Tirtauli Pematangsiantar sebesar 189.610.426. Kata Kunci: air; backpropagation; distribusi; PDAM; prediksi 
Pelatihan Mengenal dan Mengoptimalkan Prompt GPT untuk Pembelajaran Digital di SMK PAB 8 Sampali Alfina, Ommi; Syahputri, Nita; Lahilote, Abqoriy Hisan; Rustam, Muhammad Taufiq; Safii, M.
Jurnal Pengabdian Pada Masyarakat METHABDI Vol 5 No 1 (2025): Jurnal Pengabdian Pada Masyarakat METHABDI
Publisher : Universitas Methodist Indonesia

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

Abstract

The training program titled "Introduction and Optimization of GPT Prompts for Digital Learning at SMK PAB 8 Sampali" was conducted as an effort to enhance digital literacy and technological skills among teachers and students. In the era of Education 4.0, artificial intelligence (AI) technology, particularly Generative Pre-trained Transformer (GPT), holds great potential to support teaching and learning processes, including generating exam questions, summarizing materials, and planning lessons. This training aimed to provide basic understanding of GPT concepts and practical skills in crafting effective prompts for various educational purposes. The implementation method employed hands-on practice and real-life case studies within the SMK environment. The results showed an improvement in teachers' and students' abilities to utilize AI technologies, as well as increased awareness of the importance of ethical and creative use of technology in digital education. Through this training, SMK PAB 8 Sampali is expected to become a pioneer in the application of AI in vocational secondary schools in Medan.
Co-Authors Alfina, Ommi Ardilla, Ririn Arfika, Retno Belli Nasution Butarbutar, Ehrlich F.T Cut Irna Liyana Dewi, Rafiqa Eka Irawan Fitri Anggraini, Fitri Hambali, Humaidi Hartama, Dedy Irfan Sudahri Damanik Kartina, Anggriani Dwi Khusnul Khatimah Kiswara, Qodrat Lahilote, Abqoriy Hisan Lubis, Nur Azizah Muhammad Ridwan Lubis Napitupulu, Pretty Natalia Nasution, Mhd Aditia Puspita, Dahlia Rafai, Muhammad Ramadani, Saputra Rawinda Fitrotul Mualafina, Rawinda Fitrotul Renaldi Renaldi Rizki, Fahrizal RUSTAM, MUHAMMAD TAUFIQ Sari, Andini Fadila Sari, Feby Widya Siallagan, Sri Anita SIREGAR, ELIDA TUTI Solikhun Solikhun, Solikhun Suhendro, Dedi Sundari Retno Andani Syahputri, Nita Syaputri, Vera Trisno, Agus Wanto, Anjar