Article Per Year (5 Year)
p-Index From 2021 - 2026
3.189
P-Index
This Author published in this journals
All Journal Elektron Jurnal Ilmiah Jurnal Momentum Indonesian Journal of Electrical Engineering and Informatics (IJEEI) SITEKIN: Jurnal Sains, Teknologi dan Industri JOIV : International Journal on Informatics Visualization Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) INVOTEK: Jurnal Inovasi Vokasional dan Teknologi Jurnal Ilmiah Matrik JURNAL TEKNIK INFORMATIKA DAN SISTEM INFORMASI Jurnal Sisfokom (Sistem Informasi dan Komputer) Jurnal Teknologi Informasi dan Pendidikan Abdi: Jurnal Pengabdian dan Pemberdayaan Masyarakat Jurnal Tekinkom (Teknik Informasi dan Komputer) MOTIVECTION : Journal of Mechanical, Electrical and Industrial Engineering Suluah Bendang: Jurnal Ilmiah Pengabdian Kepada Masyarakat JITSI : Jurnal Ilmiah Teknologi Sistem Informasi Prosiding Seminar Nasional Sisfotek (Sistem Informasi dan Teknologi Informasi) Jurnal Abdimas: Pengabdian dan Pengembangan Masyarakat
Yance Sonatha
Politeknik Negeri Padang
Humanities Automotive Engineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Medicine & Pharmacology Public Health Transportation Other

Published : 35 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 5 Documents
Search
Journal : JOIV : International Journal on Informatics Visualization

 1 
Implementing FAST Method on the Development of Object-Oriented Cooperative Information Systems Meri Azmi; Yance Sonatha; Ervan Asri; - Rasyidah; Dwi Sudarno Putra
JOIV : International Journal on Informatics Visualization Vol 2, No 4-2 (2018): Cyber Security and Information Assurance
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1337.912 KB) | DOI: 10.30630/joiv.2.4-2.189

Abstract

Cooperative is one form of businesses that is widely known as people concern and has a legal entity. In helping its members, the cooperative embraces familial value principle and mutual cooperation for the common social welfare. In carrying out its duties and functions, the cooperative requires an accurate and accountable recording. However, currently there are still many cooperatives performing their recording manually. Therefore, an information systems is needed in assisting the cooperative management in term of this recording. This research developed an object-oriented cooperative information systems using FAST method. Its purpose is to develop a cooperative information systems that can facilitate its  administrators in order to record the data through information systems-based, so the inaccuracy in recording, and loss of important data and archives can be avoided. Its result is a system that has been implemented into a cooperative. Hence, the information systems is developed using Java Programming language and MySQL database. From the system testing results shows that this information systems is capable in processing the accounting data associated with savings and loan transactions automatically, and produce information in the form of managerial and financial reports.
Leveraging Machine Learning to Predict Future Human Development Gsim, Jamal; Zeriab Es-sadek, Mohamed; Sonatha, Yance
JOIV : International Journal on Informatics Visualization Vol 9, No 5 (2025)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/joiv.9.5.2543

Abstract

This study utilizes a rich repository of global development data to forecast the Human Development Index, harnessing the World Bank's World Development Indicators (WDI) database and the United Nations Development Program 's extensive human development metrics as primary data sources. Employing R as the driving force, this research unfolds through a meticulously structured four-phase methodology. The initial phase encompasses data pre-processing tasks, including web scraping, merging, cleansing, and transforming datasets. Subsequently, exploratory data analysis is conducted to unravel correlations and regression patterns among variables, culminating in the creation of refined data frames. The crux of this study revolves around machine learning, where two distinct random forest models are crafted: one for regression and another for classification purposes. Additionally, authentic development indicators are used to predict the Human Development Index accurately. Beyond merely deploying machine learning techniques, this research highlights the importance of adopting a multifaceted approach to assess and address global development challenges. This study not only aims to predict the Human Development Index but also lays a foundation for future research endeavors in this domain. It opens up avenues for exploring novel methodologies and datasets to make more precise and comprehensive predictions of human development indices. The findings of this research are poised to make a significant contribution to understanding the dynamics of global development and devising effective strategies for promoting human well-being worldwide.
GDSS Prototype Model for Supplier Selection at MDM Cooperative Azmi, Meri; Sonatha, Yance; Rahmayuni, Indri; Paboreal Dunque, Kristine Mae; Putra, Dwi Sudarno
JOIV : International Journal on Informatics Visualization Vol 5, No 1 (2021)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30630/joiv.5.1.473

Abstract

MDM is a trade cooperative business unit that supplies healthy food options for consumers around the Andalas University campus. So far, the selection of suppliers that provide supply goods to the stores is only based on the trust between both parties, which is the principle of mutual acquaintance and kinship. The problems that may arise from a process like this are the lack of the right supplier, unavailability of goods, relatively higher product prices, late delivery, and low-quality goods. Therefore, we need a GDSS that is capable of overcoming these problems. This GDSS helps in decision-making by determining the right supplier for each of the stores owned by the MDM Cooperative. The methods used are AHP, TOPSIS, and BORDA, involving six criteria and five tested alternatives. The AHP method is used to obtain the weight of each criterion taken from the pairwise comparison matrix. The TOPSIS method is used to determine which suppliers get priority for supply goods. Combining the AHP and TOPSIS methods can reduce the weaknesses of the TOPSIS itself by giving subjective weights. The use of the BORDA method can provide maximum results in selecting this supplier. This GDSS also involves three decision-making bodies: the head of the cooperative, the deputy, and the treasurer. The results of this prototype can show the best alternative selected based on the ranking method.
A Web-based Group Decision Support System for Retail Product Sales a Case Study on Padang, Indonesia Azmi, Meri; Satria, Deni; Mulya, Farhan Rinsky; Sonatha, Yance; Putra, Dwi Sudarno
JOIV : International Journal on Informatics Visualization Vol 7, No 3 (2023)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30630/joiv.7.3.1331

Abstract

The industrial sector's growth has led to an increase in the number of industrial products available in the market. However, this has made it more challenging for retail merchants to choose which items to sell due to the overwhelming number of options. The seller must carefully consider various factors such as the type, quality, and probability of selling the goods to turn a profit. This research proposes a group decision support system to assist retail sellers in selecting the products to sell. The system is designed to process various information on comparing retail products against specific criteria, enabling sellers to make quick and accurate decisions. To achieve optimal results, this study combines three methods in the decision-making calculation process: Fuzzy Logic, EDAS, and Borda methods. The Fuzzy Logic method is used to assign a value to an unclear criterion, followed by the EDAS method ranking process, and ending with the combination of the decision-making results using the Borda method. The group decision support system is web-based and has been proven to provide effective solutions for retail business actors to increase sales and reduce losses. By using this system, retail sellers can make informed decisions about their products, enabling them to optimize their profits and reduce their risks. In conclusion, the increase in the number of industrial products has created challenges for retail merchants, but this research proposes a solution in the form of a group decision support system. Combining Fuzzy Logic, EDAS, and Borda methods results in an effective decision-making process that allows retail sellers to make informed decisions and achieve their business goals.
Group Decision Support System Using AHP, Topsis and Borda Methods for Loan Determination in Cooperatives Sonatha, Yance; Azmi, Meri; Rahmayuni, Indri
JOIV : International Journal on Informatics Visualization Vol 5, No 4 (2021)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30630/joiv.5.4.640

Abstract

Cooperatives are one of the business units which purpose is to help the economy of small and medium-sized communities. One of the cooperatives in the city of Padang, West Sumatra, Indonesia is KPN Kapur Warna. The routine business unit managed by KPN Kapur Warna is for savings and loans. So far, the savings and loan process is still done manually, including determining the eligibility of members to receive loans. Determination of the eligibility of members is carried out less objectively, by only looking at the profile of participants in general and the decision-making process is only carried out by one person, namely the chairman of the cooperative. The process that has been carried out so far has often resulted in wrong targets, namely providing loans to members who are not appropriate, resulting in bad credit or delays in paying monthly installments of participants. Therefore, we need a group decision support system that can help solve the above problems. In this study, a group decision support system was made using the AHP, TOPSIS and BORDA methods using five main criteria. The AHP method is used to determine the priority value for each criterion and the TOPSIS method is used to rank each alternative. Each decision maker performs the same process with the two methods, and then voting is carried out using the BORDA method of combining assessments for different decision makers. This study succeeded in providing a reference in determining the eligibility of which members are entitled to receive loans from cooperatives, with results that are more subjective and can help cooperatives in their work efficiently.
Co-Authors Alde Alanda, Alde Aldo Erianda Aldo Erianda, Aldo Andres Saputra Cipto Prabowo Damayanti, Elok Deni Satria Dwi Sudarno Putra Dwiny Meidelfi Ervan Asri Fazrol Rozi, Fazrol Fitri Nova Fitri, Redhatul Gsim, Jamal Gusman, Taufik Hidra Amnur Humaira, Humaira Indra Zandi Indri Rahmayuni Indri Rahmayuni Indri Rahmayuni Iswandi Saputra Kirana, Salsabila Okta Lastri Fatika Sari Meri Azmi Meri Azmi Meri Azmi Meri Azmi Meri Azmi Mulya, Farhan Rinsky Mutia Rahmi Dewi Nurhayati - Nurhayati - Nurhayati Nurhayati Nurhayati Nurhayati Paboreal Dunque, Kristine Mae Putri, Dinda Meivianti Dwi Rasyidah Rasyidah Rasyidah, - Rendhika Aditya Rika Idmayanti Rita Afyenni Rita Afyenni Safira Putri Nabila Sistri Indah Purnama Indah Purnama Siti Sa'adiyah Tri Lestari Yogi Febrian Wibawa Yuli Purnama Sari Zeriab Es-sadek, Mohamed