Article Per Year (5 Year)
p-Index From 2019 - 2024
1.084
P-Index
This Author published in this journals
All Journal International Journal Software Engineering and Computer Science (IJSECS) VIDHEAS: Jurnal Nasional Abdimas Multidisiplin Jurnal Pelita Pengabdian
Edora
Unknown Affiliation
Religion Aerospace Engineering Agriculture, Biological Sciences & Forestry Humanities Astronomy Civil Engineering, Building, Construction & Architecture Computer Science & IT

Published : 7 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 7 Documents
Search

 1 
Grouping Production Goods Requirements Using the K-Means Clustering Method Setiawan, Dani Yuda Dwi; Hadikristanto, Wahyu; Edora
International Journal Software Engineering and Computer Science (IJSECS) Vol. 4 No. 2 (2024): AUGUST 2024
Publisher : Lembaga Komunitas Informasi Teknologi Aceh (KITA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijsecs.v4i2.2863

Abstract

The inventory management of production goods presents several challenges, including difficulties in distinguishing between necessary and unnecessary items, leading to overstocking and manual data processing issues. Additionally, the risk of data loss can impede the data processing workflow. Data testing is conducted to evaluate the accuracy of calculations and the functionality of the applied methods. The objective is to optimize production results and inventory levels in warehouses. The K-means algorithm, known for its simplicity and effectiveness, is utilized to identify clusters within the data. The first cluster (C0) has centroids at (60.33, 70.33) and includes stock data categorized as having no potential. This cluster comprises 35 records. The second cluster (C1) has centroids at (10.94, 7.11) and includes stock data categorized as available, consisting of 15 records. Testing with the RapidMiner Studio application confirms similar insights, with each cluster containing members that are divided into two clusters, each having optimal centroid values of (60.33, 70.33) for Cluster 1 (C0) and (10.94, 7.14) for Cluster 2 (C1), and a Davies-Bouldin Index evaluation score of 0.666.
Estimating Distributor Demand for Fishing Gear Products Using Linear Regression Algorithm Keswanto; Hadikristanto, Wahyu; Edora
International Journal Software Engineering and Computer Science (IJSECS) Vol. 4 No. 2 (2024): AUGUST 2024
Publisher : Lembaga Komunitas Informasi Teknologi Aceh (KITA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijsecs.v4i2.2864

Abstract

Fishing equipment plays a critical role in both recreational and commercial fishing activities across various aquatic environments. The challenge of managing inventory effectively is heightened by the fluctuating demand and the need to avoid overstocking, which can result in increased operational costs. To address this, a linear regression algorithm is utilized to predict demand for fishing products, using relevant independent variables to model the relationship with dependent variables such as monthly sales figures. This predictive model aims to provide actionable insights that can assist businesses in making informed decisions regarding inventory management and distribution strategies. The study employs the RapidMiner Studio application to develop and evaluate the model's performance, with the analysis yielding a Root Mean Square Error (RMSE) of 140.200. This relatively low RMSE value demonstrates the model's accuracy and effectiveness in forecasting demand, suggesting that the algorithm can be a valuable tool for optimizing inventory levels and ensuring product availability while minimizing excess stock.
Predicting Consumer Demand Based on Retail Stock Using the K-Nearest Neighbors Algorithm Putri N.A, Anindya; Hadikristanto, Wahyu; Edora
International Journal Software Engineering and Computer Science (IJSECS) Vol. 4 No. 2 (2024): AUGUST 2024
Publisher : Lembaga Komunitas Informasi Teknologi Aceh (KITA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijsecs.v4i2.2865

Abstract

Inefficient stock management, such as improper stock management, will result in excess or shortage of goods. Excess stock can cause high storage costs and the risk of unsold goods. Predict consumer needs based on stock. Analyze inefficient stock to improve shortages. One effective method for making this prediction is using the K-Nearest Neighbors (K-NN) algorithm. The K-NN algorithm is a simple but powerful machine-learning technique that can be used for classification and regression. The model scenario results show 24 objects in the Low-needs group and 14 in the High-needs group. Evaluation and performance testing using the Rapid Miner tool can also produce a relevant picture of the modelled scenario. The model implemented using the K-NN algorithm has an Accuracy value of 97.50% with a Standard Deviation of +/- 750%, then a Precision value of 100%, and a Recall value of 950%. By measuring model performance with cross-validation, the resulting accuracy has a standard deviation value, which aims to see the distance between the average accuracy and the accuracy of each experiment (iteration)
Peningkatan Keahlian Jaringan Internet Siswa SMK Merah Putih untuk Menghadapi Era Industri 4.0 Turmud Zy, Ahmad; Edora; Ghofir, Abdul
VIDHEAS: Jurnal Nasional Abdimas Multidisiplin Vol. 2 No. 1 (2024): Juni 2024
Publisher : VINICHO MEDIA PUBLISINDO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61946/vidheas.v2i1.61

Abstract

Kemajuan pesat Revolusi Industri 4.0 menuntut pengembangan keterampilan baru yang kompleks berbasis teknologi canggih. Untuk menghadapi tantangan ini, SMK Merah Putih meningkatkan keterampilan jaringan internet siswanya melalui program pembelajaran terpadu. Program ini bertujuan untuk memberikan pemahaman mendalam dan keterampilan praktis dalam jaringan komputer, yang sangat penting di dunia digital dan terhubung saat ini. Guru menerima pelatihan untuk meningkatkan kemampuan mereka mengajar menggunakan teknologi jaringan terbaru, dan kurikulum diperbarui untuk mencerminkan kebutuhan industri. Hasil program menunjukkan peningkatan signifikan dalam kompetensi siswa, yang dibuktikan dengan kemampuan mereka menerapkan keterampilan jaringan internet dalam proyek nyata. Evaluasi menunjukkan bahwa 85% siswa merasa lebih siap memasuki dunia kerja dengan keterampilan yang telah mereka peroleh. Integrasi teknologi jaringan internet ke dalam kurikulum terbukti efektif dalam meningkatkan daya saing siswa dan mempersiapkan mereka menghadapi tantangan masa depan.
Penggunaan Teknologi Artificial Intelligence Dalam Penulisan Buku Danny, Muhtajuddin; Rilvani, Elkin; Edora; Mulyana, Iwan
VIDHEAS: Jurnal Nasional Abdimas Multidisiplin Vol. 2 No. 1 (2024): Juni 2024
Publisher : VINICHO MEDIA PUBLISINDO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61946/vidheas.v2i1.77

Abstract

Training on the use of Artificial Intelligence (AI) technology in book writing is a response to the rapid development of information and communication technology which has influenced various aspects of life, including the publishing and writing industry. AI technology has developed rapidly and shown its potential in various fields, including data analysis, natural language processing (NLP), and machine learning (Machine Learning). AI algorithms can generate text, analyze writing style, and provide relevant recommendations for writers. AI can help writers in various stages of the writing process, from brainstorming ideas, creating initial drafts, to editing. Tools like GPT-4 can generate paragraphs or chapters based on specific instructions, which helps speed up the writing process and overcome creative barriers. The use of AI can improve the quality of writing by providing suggestions for editing and improvement. AI can also ensure consistency in writing style and use of terminology, which is especially important in writing technical books or series. In the digital era, speed and quality of content production are key factors in competition. Authors and publishers who are able to utilize AI technology can have a competitive advantage by producing books faster and with better quality.
Implementasi Sistem Informasi Pedidikan dan Latihan (SIDIKLAT) pada Instalasi Diklat RSUD dr. Chasbullah Abdulmadjid Kota Bekasi Sanudin; Hadikristanto, Wahyu; Firmansyah, Andri; Edora; Purwanto
VIDHEAS: Jurnal Nasional Abdimas Multidisiplin Vol. 2 No. 2 (2024): Desember 2024
Publisher : VINICHO MEDIA PUBLISINDO

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

Abstract

This training activity was conducted to enhance the capacity of the staff at the Education and Training Unit (Diklat) of RSUD dr. Chasbullah Abdulmadjid, Kota Bekasi, in operating and implementing the Education and Training Information System (SIDIKLAT). The training was designed to provide an in-depth understanding of the features and functions of SIDIKLAT that support the management of education and training at the hospital. The methods used included presentations, live demonstrations, and system simulations by the participants. During the training, participants were actively engaged in each session to ensure optimal technical and operational mastery. Evaluations showed that the training successfully improved the participants' competence in using SIDIKLAT and increased awareness of the importance of technology integration in education and training management. It is expected that after this training, the Diklat staff will effectively implement SIDIKLAT in their daily activities, thereby supporting the improvement of the quality and efficiency of education and training services at RSUD dr. Chasbullah Abdulmadjid.
Sosialisasi Rancangan SNI ISO 15397 Komunikasi Sifat Kertas, kepada sivitas akademika Politeknik Negeri Media Kreatif RAHARDJO, sugeng; Gema Sukmawati Suryadi; wiyanto; siti rahayu; edora
Jurnal Pelita Pengabdian Vol. 2 No. 2 (2024): Juli 2024
Publisher : DPPM Universitas Pelita Bangsa

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

Abstract

Badan Standarisasi Nasional Atau BSN adalah lembaga di bawah BRIN, Badan Riset Nasional. Salah satu tugas BSN adalah menyusun Standarisasi Nasional Indonesia, mengacu kepada Standarisasi Internasional (ISO, International Standarization Organization) yang bermarkas di Swiss. Di Indonesia ISO tersebut di alih bahaskan oleh ISO Komtek 37-01, yaitu suatu komisi teknik tentang standarisasi percetakan dan pengemasan, saat ini memiliki 11 anggota tetap, dan 3 observer. Salah satu Observer dari Universitas Pelita Bangsa (sdr. Sugeng Budi Rahardjo, ST.MM) dan dua observer lainnya yaitu dari Polimedia, Depok (Ibu Gema, S.Pd, M.Si) Beberapa SNI yang sudah di keluarkan yaitu : SNI ISO 12643-5:2010, RSNI ISO 15397:2014 RSNI ISO 2836:2021 RSNI ISO 3664:2009;RSNI ISO 12643-3:2010 RSNI ISO 20654:2017. Dan menjadi kewajiban bagi Anggota Komtek dan Narasumber untuk melakukan Sosialisasi kepada Stake Holder terkait Teknik Grafika seperti : Pengusaha Percetakan dan Kemasan, Suplier bahan baku percetakan dan Kemasan, Perusahaan Permesinan dan Bengkel Percetakan dan Kemasan, Dosen dan Mahasiswa Teknologi Grafika dan Packaging, Perusahaan Supporting Percetakan dan Kemasan, seperti perusahaan Software, Perusahaan Supply Chain, Vendor dan Supplier Percetakan dan Kemasan. Pada Kesempatan ini Pengabdian dilaksanakan kepada Dosen dan Mahasiswa Teknologi Grafika Politeknik Negeri Media yang sudah di laksanakan pada tanggal 14 Juni 2024 di Gedung C, Teknik Grafika, Politeknik Negeri Media Kreatif Depok, yang di hadiri oleh sejumlah mahasiswa dan Dosen Teknik Grafika. Kegiatan ini sejalan dengan peran dari Badan Standarisasi Nasional Indonesia yaitu mensosialisasikan hasil rancangan SNI Grafika kepada Insan Grafika sehingga diharapkan kegiatan ini memberikan dampak bagi pertumbuhan kualitas pengetahuan grafika, yang pada akhirnya dapat meningkatkan kompetitifnes dan kompetensi Percetakan dan Kemasan di Indonesia.
Co-Authors Abdul Ghofir Andri Firmansyah Elkin Rilvani Gema Sukmawati Suryadi Iwan Mulyana Keswanto Muhtajuddin Danny Purwanto Putri N.A, Anindya Rahardjo, Sugeng Sanudin Setiawan, Dani Yuda Dwi Siti Rahayu Turmud Zy, Ahmad Wahyu Hadikristanto Wiyanto