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All Journal E-Bisnis : Jurnal Ilmiah Ekonomi dan Bisnis JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Journal of English Education and Teaching (JEET) alfazuna: Jurnal Pembelajaran Bahasa Arab dan Kebahasaaraban Pelita Eksakta Journal Cerita: Creative Education of Research in Information Technology and Artificial Informatics Jurnal Tekinkom (Teknik Informasi dan Komputer) BERNAS: Jurnal Pengabdian Kepada Masyarakat Coopetition : Jurnal Ilmiah Manajemen Jurnal Administrasi Pendidikan Islam LOSARI: Jurnal Pengabdian Kepada Masyarakat Ma'mal: Jurnal Laboratorium Syariah dan Hukum As-Sidanah : Jurnal Pengabdian Masyarakat Jurnal Kependidikan Islam
Fauzi, Ahmad
Universitas Islam Negeri Sunan Ampel Surabaya
Religion Agriculture, Biological Sciences & Forestry Humanities Biochemistry, Genetics & Molecular Biology Chemistry Computer Science & IT Control & Systems Engineering Dentistry Earth & Planetary Sciences Economics, Econometrics & Finance Education Environmental Science Health Professions Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Neuroscience Nursing Physics Public Health Social Sciences Transportation Veterinary Other

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Training on Making Teaching Materials in The Form of E-modules Based on Guided Discovery Learning for Teachers of Chemical MGMP Pesisir Selatan Oktavia, Budhi; Guspatni, Guspatni; Fauzi, Ahmad
Pelita Eksakta Vol 7 No 2 (2024): Pelita Eksakta, Vol. 7, No. 2
Publisher : Fakultas MIPA Universitas Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/pelitaeksakta/vol7-iss2/251

Abstract

Teachers stated that they wish to be able to produce learning materials and integrate a scientific approach into their implementation and use. Teachers recommend receiving training in the creation of ICT-based teaching materials in order to attain their innovative nature. As a result, we offer training activities to chemistry teachers who are members of the MGMP Chemistry Pesisir Selatan for the creation of teaching materials in the form of e-modules based on Guided Discovery Learning. Teachers will be given information on the main criteria of a teaching material (module), guided discovery learning, e-modules, visual and video editing with computer software, literacy, and other associated ICT skills during this activity.
The Psychology of Saving : How Mindset Impacts Financial Competence Fauzi, Ahmad; Fauziah, Nadiatullah Tsuraya; Rahayu, Sari
Coopetition : Jurnal Ilmiah Manajemen Vol. 15 No. 2 (2024): Coopetition : Jurnal Ilmiah Manajemen
Publisher : Program Studi Magister Manajemen, Institut Manajemen Koperasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32670/coopetition.v15i2.4455

Abstract

This study investigates the dynamics of financial competence among customers and employees of Bank BNI, focusing on the roles of mindset, saving behavior, and financial knowledge. Using a quantitative research design with a sample size of 100 participants selected through random sampling, data were analyzed using Smart PLS for path analysis. The findings reveal significant direct relationships: mindset positively influences both financial knowledge (FK) and financial competence (FC), while saving behavior directly enhances FC. Additionally, indirect effects show that both mindset and saving behavior contribute to FC through their positive impacts on FK. These results highlight the critical importance of psychological factors and proactive financial behaviors in shaping individuals' financial capabilities. For Bank BNI, promoting a positive financial mindset and supporting disciplined saving practices could effectively enhance financial literacy and decision-making among stakeholders. Future research could explore additional variables and interventions to further refine strategies for fostering financial competence across diverse demographic groups.  
Aplikasi Elektronik Kasir Umum E-ku Berbasis Website Metode Spiral Toko Zaynmart Fauzi, Ahmad; Wati, Fanny Fatma; Nurohim, Galih Setiawan
Journal Cerita: Creative Education of Research in Information Technology and Artificial Informatics Vol 10 No 1 (2024): Journal CERITA : Creative Education of Research in Information Technology and Ar
Publisher : UNIVERSITAS RAHARJA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/cerita.v10i1.2990

Abstract

In light of the rapid technological advancements today, the utilization of the E-Ku web-based General Electronic Cashier Application remains highly relevant in aiding Micro, Small, and Medium Enterprises (UMKM) in enhancing their daily transaction efficiency. A case study for the implementation of this technology is illustrated through Zaynmart Store. The research approach adopted encompasses an analysis of Zaynmart Store's requirements and the development of web-based software accessible through a variety of devices, including computers, tablets, and smartphones. E-Ku Application empowers UMKM proprietors and their staff to effortlessly record sales transactions, manage inventory, and generate precise financial reports. Research findings underscore that the implementation of E-Ku's web-based General Electronic Cashier Application positively impacts the operational efficiency of Zaynmart Store. The streamlined transaction process facilitates time savings, reduces error potential, and enhances financial record-keeping accuracy for UMKM. Furthermore, E-Ku Application supports store owners in making informed decisions based on the data it provides. Consequently, the E-Ku web-based General Electronic Cashier Application stands as an effective tool for aiding UMKM, such as Zaynmart Store, in managing their day-to-day transactions, improving operational efficiency, and enhancing customer service. The successful implementation of E-Ku highlights the considerable potential of web technology in bolstering the growth and development of UMKM in this digital age.
Rancang Bangun Aplikasi Helpdesk Dilingkungan Institusi Untuk Efisiensi Kinerja User Rahayu, Sri; Supriyanti, Dedeh; Fauzi, Ahmad
Journal Cerita: Creative Education of Research in Information Technology and Artificial Informatics Vol 10 No 2 (2024): Journal CERITA : Creative Education of Research in Information Technology and Ar
Publisher : UNIVERSITAS RAHARJA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/cerita.v10i2.3041

Abstract

The helpdesk section is an officer who fixes all kinds of problems that occur in the office infrastructure, such as damaged computer hardware components and applications that don't work properly. Currently, the process of submitting complaints regarding computer problems is still carried out by meeting directly with the helpdesk department or using an office VoIP telephone. Then the helpdesk will record it in the register of reported problems, then send a team of technicians to repair the computer. When the computer has been repaired, it will be reported back to the helpdesk so that the status of the problem submission data is changed to complete repair. However, the process of submitting complaints is still considered manual and inefficient, so it does not rule out the possibility of obstacles or errors such as duplication of complaint data which occurs due to the large number of reports coming in at once, the data search process is repetitive and takes quite a long time. So it is necessary to build an IT helpdesk system application that uses the PHP programming language which is integrated with the database. This research produces an IT helpdesk system application that functions to make it easier for officers as one of the users in the process of collecting submission data and managing helpdesk data more effectively.
SEGMENTASI PELANGGAN MENGGUNAKAN K-MEANS CLUSTERING DI TOKO RETAIL Achmad, Syifa Latifah; Fauzi, Ahmad; Rahmat, Rahmat; Indra, Jamaludin
Jurnal Tekinkom (Teknik Informasi dan Komputer) Vol 7 No 2 (2024)
Publisher : Politeknik Bisnis Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37600/tekinkom.v7i2.1226

Abstract

Advancements in information technology have transformed various aspects of human life, including the business world. Companies are required to use technology and data effectively to enhance their competitive advantage. One increasingly relevant strategy is Customer Relationship Management (CRM), where customer data is the main focus. Consumer data segmentation is an approach used to group customers based on certain characteristics. In this study, the K-Means Clustering algorithm is applied to consumer data segmentation to improve the marketing strategy of a store. The study begins with the collection of customer data from the Dan+Dan Telukjambe 2 store, followed by Exploratory Data Analysis (EDA) to understand the patterns and characteristics of the data. Preprocessing steps are carried out to ensure the data is ready for use, including removing irrelevant columns, handling missing values, and data transformation. Principal Component Analysis (PCA) is used to reduce data dimensions before applying K-Means Clustering. The Elbow Method and Silhouette Score are used to determine the optimal number of clusters. The study results indicate that the optimal number of clusters is six. Evaluation using the Silhouette Coefficient provides an average coefficient value of 0.66, indicating good clustering quality. Further analysis shows different distributions of age, purchasing power, occupation, and marital status in each cluster, providing deep insights into customer segments. The resulting clusters offer valuable information for developing more effective and targeted marketing strategies
PEMODELAN INSPEKSI PAINTING DEFECT PADA MOBIL MENGGUNAKAN CONVOLUTIONAL NEURAL NETWORK (CNN) Ramadhan, Muchamad Fachrul; Fauzi, Ahmad; Wahiddin, Deden; Rohana, Tatang
Jurnal Tekinkom (Teknik Informasi dan Komputer) Vol 7 No 2 (2024)
Publisher : Politeknik Bisnis Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37600/tekinkom.v7i2.1519

Abstract

Quality control is an important process carried out at the last stage of the production process, this activity is carried out by checking a product. Painting defects on cars are a problem that must be considered in the car production process at car companies. The perfection of a product is important to increase the level of customer satisfaction. These checking activities are still carried out manually with human power, which can still cause defective products to be missed in a production process that occurs as a result of human error. The use of artificial intelligence can be used to detect image and video objects, used to overcome the problem of human error in carrying out checks. Convolutional Neural Networks (CNN) is an algorithm that can be used in product defect inspection, image recognition, and image classification. The study focuses on modeling the inspection and detection of painting defects in cars using CNN, emphasizing the importance of quality control in ensuring product quality. The CNN model is trained with image data of normal car paint and defective car paint, and evaluated using a confusion matrix for optimal parameters. The results show quite high accuracy in detecting car paint defects of 98% with the help of the ResNet50 transfer learning CNN architecture.
Penerapan Algoritma Random Forest Untuk Menentukan Kualitas Anggur Merah Supriyadi, Riki; Gata, Windu; Maulidah, Nurlaelatul; Fauzi, Ahmad
E-Bisnis : Jurnal Ilmiah Ekonomi dan Bisnis Vol 13 No 2 (2020): Jurnal Ilmiah Ekonomi dan Bisnis
Publisher : LPPM Universitas Sains dan Teknologi Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/e-bisnis.v13i2.247

Abstract

Abstract In this study that was used as the object of research in classifying red wine based on the quality influenced by each red wine or red wine based on the content of each type of wine, from each attribute containing the composition in the wine seen which attributes most affect the quality of red wine, so that it will be known ingridents that can improve the quality of the wine, in this study was carried out by the application of Machine learning by comparing three algorithms of mining data that is , Decission Tree, Random Forest and Support Vector Machine (SVM), from the results of research that has been done by comparing the three algorithms, Random Forest produced the best accuracy among other algorithms that have been tested. Random Forest with accuracy results of 0.7468 makes this algorithm best used to classify the quality of red wine. And in the second order Decission Tree with accuracy results of 0.7031, while Support Vector Machine (SVM) get an accuracy result of 0.65. So in the research that has been done to classify the quality of red wine based on its composition Random Forest becomes the best algorithm to use..
Co-Authors Abdul Haris Achmad, Syifa Latifah Alfiarany Choirun Nisa Alissa Qotrunnada Rohmah Anggita, Sharazita Dyah Budhi Oktavia Dianita Nur Auliya Fauziah, Nadiatullah Tsuraya Febrina Zakiya Daroja Galih Setiawan Nurohim Gata, Windu Guspatni Guspatni Heeba Alya Ronan Indra, Jamaludin Irma Setya Ningsih Lubab, Ahmad Miftahul Ainiyah Muhammad Sholahudin Ayyubi Nisa’ Cholida, Aliffian Nurlaelatul Maulidah Nurlita Nindya Putri Qibtiyah, Siti Rahayu, Sari Rahmat Rahmat Ramadhan, Muchamad Fachrul Riki Supriyadi Rista Dwi Jayanti Rizka Safriyani Rizky Luthfiandari Rizky Rahmawati, Hanifa Rohana, Tatang Shifa Shalsabila Siti Asmiyah SRI RAHAYU Supriyanti, Dedeh Upik Khoirul Abidin Vina Afrina Fitri Wahiddin, Deden Wati, Fanny Fatma Windhi Candra