Article Per Year (5 Year)
p-Index From 2019 - 2024
0.562
P-Index
This Author published in this journals
All Journal Sinkron : Jurnal dan Penelitian Teknik Informatika Bulletin of Social Informatics Theory and Application Prosiding Seminar Nasional Rekayasa dan Teknologi (TAU SNAR- TEK)
Alim, Syariful
Unknown Affiliation
Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Electrical & Electronics Engineering Social Sciences

Published : 3 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 3 Documents
Search

 1 
Decision Support System for Volunteer Selection for Archipelago Marine Volunteers (Rapala) Using the Profile Matching Method Hozairi; juhairiyah; Makruf , Masdukil; Alim, Syariful
Bulletin of Social Informatics Theory and Application Vol. 8 No. 1 (2024)
Publisher : Association for Scientific Computing Electrical and Engineering

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/businta.v8i1.620

Abstract

This study aims to develop a Decision Support System (DSS) for selecting candidates for Archipelago Sea Rangers Volunteers (RAPALA) using the profile matching method. Bakamla RI, as an institution responsible for maritime security in Indonesian territorial waters, requires prospective RAPALA volunteers who are qualified and have the appropriate competence to protect the archipelago's seas, which are increasingly threatened. In this study, a decision support system was developed that can compare the profiles of prospective volunteers with predetermined criteria. This system aims to improve efficiency and accuracy in the selection process for volunteer candidates, as well as strengthen selection criteria and methods based on appropriate profiles. To create a decision support system, the profile matching method is used. Profiles of prospective volunteers are assessed based on factors such as intelligence, work attitude, behavior, and domicile. This study shows that the RAPALA-1 candidate is ranked first with a score of 4.76, the RAPALA-2 candidate is ranked second with a score of 4.49, and the RAPALA-3 candidate is ranked third with a score of 4.26. It is hoped that with this decision-support system, the selection process for RAPALA volunteer candidates can be carried out more efficiently and objectively. The selected volunteer candidates are expected to have the right skills and motivation to maintain the security and preservation of the archipelago's seas. This will contribute to increasing the security and sustainability of marine resources in Indonesia.
Uncovering Blockchain's Potential for Supply Chain Transparency: Qualitative Study on the Fashion Industry Hindarto, Djarot; Alim, Syariful; Hendrata, Ferial
Sinkron : jurnal dan penelitian teknik informatika Vol. 8 No. 2 (2024): Article Research Volume 8 Issue 2, April 2024
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v8i2.13590

Abstract

With the capacity to increase security and transparency, blockchain technology is being used as an interesting subject of investigation in the fashion industry. This underscores the importance of this current research endeavour. In terms of supply chain transparency, the fashion industry faces considerable barriers, thus requiring new approaches such as blockchain that can address issues such as child labour, unethical payment practices, and environmental impact. Main objective of this research is to identify how blockchain technology can improve transparency, accountability, and compliance with ethical standards. However, knowledge of the specific ways in which blockchain technology can improve transparency in the fashion supply chain, including the drivers and barriers, needs to be improved. The research method is described through a qualitative approach that includes in-depth interviews, participatory observation, and document analysis to collect data from various stakeholders in the industry, including manufacturers, distributors, and consumers. Explanation provides an overview of how the researcher collected and analysed data to achieve the research objectives. Blockchain increases transparency through the provision of verifiable and durable product records and fosters consumer-brand trust. Blockchain facilitates accountability and compliance with environmental and ethical standards, according to key findings. Research detected significant barriers, including exorbitant costs for implementation, limited knowledge of technology, and difficulties in fostering collaboration among relevant parties. Results of this study have far-reaching consequences, providing valuable insights to fashion industry stakeholders on how to overcome barriers to blockchain adoption. Long-term benefits of enhanced supply chain transparency and strategic recommendations ensure a smooth implementation process.
PERAMALAN VOLUME PENJUALAN TABUNG APAR (ALAT PEMADAM API RINGAN ) DENGAN MENGGUNAKAN METODE MONTE CARLO (Studi Kasus : PT Sanindo Perkasa Abadi) Abror, Akhdan; Nurul Hamidah, Mas; Alim, Syariful
Prosiding TAU SNARS-TEK Seminar Nasional Rekayasa dan Teknologi Vol. 4 No. 1 (2024): Prosiding TAU SNARS-TEK Seminar Nasional Rekayasa dan Teknologi 2024
Publisher : Fakultas Teknik dan Teknologi - TANRI ABENG UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47970/snarstek.v2i1.712

Abstract

Forecasting is the art and science of predicting future events. In this research the author uses sales volume forecasting using the Monte Carlo method. This case study is at one PT Sanindo Perkasa Abadi. The problem that is often experienced by PT Sanindo Perkasa Abadi is the excess and shortage or supply of APAR tubes (light fire extinguishers) at certain times which causes reduced income. With these problems, careful planning is needed to be able to estimate the inventory of goods so that it does not result in reduced income for the Company. The method used is Monte Carlo simulation. This method uses a probabilistic approach so that it is able to consider uncertainty. Demand forecasting is carried out for twelve months and uses historical data on actual demand in 2019 and 2022. The calculation results are that for the prediction of the AF11E 3kg fire extinguisher in 2021, the accuracy is 28.67% and the MAE error value = 19.692, the prediction for the AF11E 6kg fire extinguisher in 2020 is accurate. 40.75% and the MAE error value = 10,583, for the prediction year for the 6kg AF11E fire extinguisher in 2021, the accuracy was 47.50% and the MAE error value = 3,833, for the prediction year for the AF31 3kg fire extinguisher in 2020, the accuracy was 48.67% and the MAE error value = 4,750, for the prediction year for the AF31 6kg fire extinguisher in 2019, the accuracy was 47.75% and the MAE error value = 5,583, and for the prediction year for the AF31 6kg fire extinguisher in 2021, the accuracy was 46.83% and the MAE error value = 7,750.
Co-Authors Abror, Akhdan Hendrata, Ferial Hindarto, Djarot Hozairi Juhairiyah Makruf , Masdukil Nurul Hamidah, Mas