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All Journal JISTECH: Journal of Information Science and Technology JOURNAL OF APPLIED INFORMATICS AND COMPUTING JATI (Jurnal Mahasiswa Teknik Informatika) The Indonesian Journal of Computer Science
Dwi Suhendra, Christian
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Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Energy Engineering

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Implementation of Predicting the Availability of Chicken Eggs on Christmas Day Using Artificial Neural Network Backpropagation Nofianti, Arin; Dwi Suhendra, Christian; Sanglise, Marlinda
The Indonesian Journal of Computer Science Vol. 13 No. 2 (2024): The Indonesian Journal of Computer Science (IJCS)
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v13i2.3800

Abstract

Prediction can be called a science that is used to predict events that are likely to occur in the future based on past events. One of the other prediction methods in circulation is Backpropagation Neural Network. Backpropagation Neural Network (BPNN) is a Neural Network (NN) that is forward in nature and does not have a loop through which signals flow from input neurons to output neurons. This research aims to determine a prediction of egg supply in 2023, especially during Christmas in Manokwari district to meet market and customer needs. By analyzing the availability of egg supplies in the city of Manokwari from January 2018 to December 2022. From the methods used in this research, starting from data collection methods as well as variables and research stages which include the data collection process, data sharing, then training and data testing and validation crosswise, the prediction pattern for the number of egg stocks is 12-16-1, where there are 12 variables in the input layer, then 16 variables in the hidden layer, 1 variable in the output layer, the learning rate value is 0.9 and the value the momentum is 0.1, resulting in a prediction of egg stock in 2023, especially in December, of 131053 eggs. With a MAPE value of 27.4767%. with the results of a feasible prediction model value. With the predicted results, the number of egg stocks in 2023, especially in December (during Christmas celebrations) in Manokwari Regency is 131,053 eggs during December 2023.
Sistem Pakar Cara Mendidik Anak Pelajaran Agama Islam Sesuai Al-Qur'an Menggunakan Metode Forward Chaining Maulidan, Farid; Dwi Suhendra, Christian; Juita, Ratna
Journal of Applied Informatics and Computing Vol. 7 No. 1 (2023): July 2023
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v7i1.5104

Abstract

The Al-Qur'an indirectly provides methods for educating children from an early age, as listed in Al-Ahqaf [46]: 30. The implementation of these educational methods requires an expert, specifically an Islamic religious teacher who can suggest appropriate methods to use. Hence, in this context, there is a need to develop an expert system application that can assist teachers in recommending suitable educational methods to parents or guardians based on the child's behavior input. The "expert-mendidik-islam.com" application is created using the forward chaining method, which is employed for reasoning in the database system through rules derived from interviews with experts. The existing child behaviors and rules can be added through the admin page. To evaluate the application, a Likert model questionnaire was administered to parents or guardians of students at SDN 44 Amban and SDN 48 Inggramui, Manokwari Regency. The questionnaire results consistently scored above 80%, indicating that the users strongly agreed with the questionnaire and the application's effectiveness.
ANALISIS KLASTERISASI PENGGUNA SIM DI KABUPATEN MANOKWARI MENGGUNAKAN ALGORITMA K-MEANS Ratte, Yansi; Dwi Suhendra, Christian; Yertas Baisa, Lorna
JATI (Jurnal Mahasiswa Teknik Informatika) Vol. 9 No. 3 (2025): JATI Vol. 9 No. 3
Publisher : Institut Teknologi Nasional Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36040/jati.v9i3.13784

Abstract

Surat Izin Mengemudi (SIM) merupakan kartu identitas resmi yang harus dimiliki oleh setiap pengendara sepeda motor. Faktanya di Kabupaten Manokwari banyak masyarakat yang tidak memenuhi peraturan tersebut. Akibatnya, kasus pelanggaran lalu lintas semakin tinggi, sehingga untuk mengetahui pola pengguna SIM di perlukan klasterisasi dengan algoritma K-Means menggunakan data peserta uji SIM dengan atribut Umur, Jenis Pekerjaan dan Golongan SIM. Jumlah data sebanyak 1.155. Data tersebut di analisis menggunakan aplikasi Jupyter notebook, dengan menggunakan metode Elbow method di peroleh K=4 dengan nilai error SSE sebesar 48960.67. Nilai K tersebut akan di proses menggunakan algoritma K-Means berdasarkan Umur dan Jenis pekerjaan. Hasilnya Cluster_0 didominasi oleh pelajar/mahasiswa berusia 20 tahun, sementara Cluster_1 mayoritas berusia 25 tahun dan bekerja sebagai wiraswasta. Cluster_2 memiliki rata-rata usia 44 tahun dengan dominasi pekerja ASN, sedangkan Cluster_3 berusia 39 tahun dengan mayoritas bekerja sebagai wiraswasta. Hasil ini dapat digunakan oleh pihak kepolisian untuk menyusun program edukasi dan kebijakan lalu lintas yang lebih efektif guna mengurangi angka pelanggaran lalu lintas di Kabupaten Manokwari
Peningkatan Efisiensi Sistem Sortasi Matang Buah Kopi melalui Optimasi Berbasis Ultrasound dan Logika Fuzzy: Enhanced Efficiency of Coffee Fruit Ripe Sorting System through Ultrasound-based Optimization and Fuzzy Logic El Maidah, Nova; Dwi Suhendra, Christian
JISTECH: Journal of Information Science and Technology Vol 12 No 1 (2023): Vol. 12 No. 1 (2023): April 2023
Publisher : Universitas Papua

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30862/jistech.v12i1.218

Abstract

This research focuses on the development of a coffee fruit sorting system, which is a part of an embedded automation system for coffee processing and storage. The implementation of this system aims to improve and maintain the quality of coffee throughout the production and storage processes. The embedded automation system for coffee processing begins with the coffee fruit sorting system, which is responsible for selecting perfectly ripe and high-quality coffee fruits. Subsequently, the system proceeds with coffee bean production and storage processes. The developed system comprises small-scale subsystems capable of performing various coffee processing tasks. These subsystems can be integrated to form a larger system capable of handling coffee production and storage processes. The research utilizes software technology embedded in the hardware system. The employed software technology is a component of an intelligent control system, which utilizes artificial intelligence as its underlying control mechanism. The maturity classification of coffee fruits is divided into three classes: KM (immature), MM (mature), and MS (fully mature). This classification scheme simplifies the understanding of the sorting process.
Co-Authors El Maidah, Nova Maulidan, Farid Nofianti, Arin Ratna Juita Ratte, Yansi Sanglise, Marlinda Yertas Baisa, Lorna