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All Journal JURNAL TEKNOLOGI DAN OPEN SOURCE Diseminasi : Jurnal Pengabdian kepada Masyarakat International Journal of Advances in Data and Information Systems Journal of Information System and Education Development
Dwipa Junika Putra
Universitas Perintis Indonesia
Computer Science & IT Education Electrical & Electronics Engineering Languange, Linguistic, Communication & Media Other

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Implementation of Fuzzy Logic Using Mamdani Method to Determine The Quantity of Bag Production (Case Study In Roman Indah Padang Bag Factory) Dwipa Junika Putra; Nofriadi Nofriadi; Erlinda Erlinda
JURNAL TEKNOLOGI DAN OPEN SOURCE Vol 5 No 1 (2022): Jurnal Teknologi dan Open Source, June 2022
Publisher : Universitas Islam Kuantan Singingi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36378/jtos.v5i1.2220

Abstract

Roman Indah bag Factory is a bag manufacturing company that receives orders from customers every month. Fuzzy Logic is used to define the production known so far, so that the preferred result can be used as a basis for manager's decision. In the calculation process, Fuzzy Logic Mamdani requires maximum and minimum production data, maximum and minimum demand data, and maximum and minimum inventory data. Fuzzy logic is able to map an input into an output without factor factors. Fuzzy logic is used to create a model of a system that is able to determine the quantity of production. the factors that affect the quantity of production. Fuzzy logic is called the old new logic because the science of modern fuzzy logic and methodological was discovered only a few years ago, in fact the concept of fuzzy logic itself has been in us for a long time. Mamdani method is the most common method when it comes to fuzzy methodology. Mamdani method uses a set of IF-THEN rules derived from experienced operators/experts. The Mamdani model is often known as the Max-Min model. By using Mamdani method in Roman Indah handbag factory can assist in the efficiency of time and labour, because using Mamdani method can calculate the amount of production in the next month, so from the results can be derived consideration material decision by the manager, whether in determining raw materials, promotion, bag model, consumer, HR, etc. so that more company profits.
STRATEGI PERLUASAN PASAR MENGGUNAKAN DIGITAL MARKETING MELALUI PELATIHAN PEMBUATAN TOKO ONLINE DI KOTA BUKITTINGGI Elsa Widia; Dwipa Junika Putra
Diseminasi: Jurnal Pengabdian kepada Masyarakat Vol. 5 No. 1 (2023)
Publisher : Pusat Pengabdian kepada Masyarakat- LPPM Universitas Terbuka

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33830/diseminasiabdimas.v5i1.3449

Abstract

Pandemi Covid-19 telah meninggalkan permasalahan yang besar di seluruh sector perekonomian, terutama para pelaku bisnis. Permasalahan ini juga dirasakan oleh pelaku usaha khususnya Anggota Sanggar Belajar Mandiri di Bukittinggi. Pelaku usaha sanggar ini bergerak di berbagai bidang yang mengalami berbagai kendala pemasaran akibat pandemi. Dalam rangka pengabdian masyarakat kali ini kami akan memberikan pelatihan mengenai peluang berbisnis menggunakan digital dan pendapingan langsung pembuatan toko online. Pelatihan ini diikuti sebanyak 60 anggota sanggar dan berlokasi di Kampus 2 Perintis Indonesia di Bukittingi. Melalui pengabdian ini diharapkan pelaku usaha yang tergabung dalam Sanggar Belajar mandiri dapat menyadari peluang besar dalam bisnis digital. Sehingga mereka dapat memanfaatkan cara tersebut untuk memperluas pemasaran produk mereka. Hasil dari pelatihan ini terlihat dari antusias para pelaku usaha untuk membuat toko online dan mempromosikan produknya. Sebanyak 75 persen anggota telah aktif menggunakan media sosial dan 25% diantaranya telah memiliki media sosial tapi belum dapat mengelola akunnya dengan baik.
Student Identification Based on Patterns of Association For Student Misbehaviour Using Frequent Pattern Growth Algorithms Erlinda Erlinda; Dwipa Junika Putra; Mourend Devegi
JURNAL TEKNOLOGI DAN OPEN SOURCE Vol 6 No 1 (2023): Jurnal Teknologi dan Open Source, June 2023
Publisher : Universitas Islam Kuantan Singingi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36378/jtos.v6i1.3071

Abstract

Student infractions are incidents often committed by students who break the rules at school. This naturally worries school authorities and overwhelms them with student misbehavior. Student rule-breaking is a common problem that can interfere with a safe and orderly learning environment. The more students break the rules, the greater the impact on several aspects, including student achievement, discipline, suboptimal teaching and learning activities, and students' social lives outside of school. Identifying students who are prone to rule violations can help school officials implement more effective prevention programs. Data mining is a process of extracting information from large data sets to discover patterns and relationships hidden within them. This study aims to identify frequent student infractions using the Frequent Pattern Growth algorithm. The Frequent Pattern Growth (FP -growth) algorithm is used to generate frequent itemsets that are then used in the association rules process. The association rules process aims to find rules or relationships between violations based on the discovered Frequent Itemsets. This process is influenced by predefined minimum support and minimum confidence values. A Minimum Support value of 30% and a Minimum Confidence value of 50% are used to obtain rules with a sufficiently high confidence level. It is expected that the identification results from this study will provide a better understanding of the types of violations commonly committed by students in school. This information can be used by school officials to develop more effective prevention strategies and focus on.
Enhancing Soil-Transmitted Helminth Detection in Microscopic Images Using the Chain Code for Object Feature Extraction Rio Andika Malik; Marta Riri Frimadani; Dwipa Junika Putra
International Journal of Advances in Data and Information Systems Vol. 4 No. 2 (2023): October 2023 - International Journal of Advances in Data and Information System
Publisher : Indonesian Scientific Journal

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25008/ijadis.v4i2.1305

Abstract

Soil-Transmitted Helminth (STH) infections are a grave global health issue, which involves particularly in countries that are developing with insufficient sanitation and limited access to healthcare. With better intestinal helminth egg detection technology, health facilities in areas with limited resources can identify and treat these infections more promptly. It is necessary to create a strong framework and an effective method to solve this challenge. The outcomes of this study could assist in parasite infection discovery and public health. Chain code-based feature extraction strategy can also be the foundation for the development of comparable approaches for diagnosing various parasitic diseases. Overall, the neural network design used in this study makes the model that is produced a good model that assigns well to never-before-seen data. The significance of image processing technologies in the medical field is shown by this study.
Pengukuran Tingkat Kepuasan Mahasiswa Terhadap Pelayanan di Kantin Kampus Menggunakan Algoritma K-means Clusterring Hasnah Vithon Carelsa; Rio Andika Malik; Dwipa Junika Putra
Journal of Information System and Education Development Vol. 1 No. 3 (2023): Journal of Information System and Education Development
Publisher : Manna wa Salwa Foundation (Yayasan Manna wa Salwa)

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

Abstract

The K-means Clustering algorithm technique is being used in this study to gauge how satisfied students in the Universitas Perintis Indonesia Digital Business programme are with the cafeteria's offerings. The study focuses on customer service characteristics such meal quality, cost, speed of service, cleanliness, and comfort in the cafeteria setting. The goal of the research is to provide deeper insights into student expectations and preferences for cafeteria services by utilising K-means to uncover distinct satisfaction patterns among student groups. When used to measure student satisfaction with cafeteria services, the K-means Clustering method is successful at identifying groups of students who have similar patterns of satisfaction. Some student groups score food quality and cleanliness favourably, according to the clustering data, while other groups may be more critical. In light of the preferences of each student group, cafeteria management can use this data to develop more specialised plans for improving services. The study also shows that using the K-means Clustering method to evaluate customer satisfaction offers a potentially advantageous strategy for enhancing service quality across a variety of service sectors.
Co-Authors Elsa Widia Erlinda Erlinda Erlinda Erlinda Hasnah Vithon Carelsa Marta Riri Frimadani Mourend Devegi Nofriadi Nofriadi Rio Andika Malik