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IMPLEMENTATION OF SUPPLY CHAIN MANAGEMENT IN MANAGING VEHICLE SPARE PARTS USING CODEIGNITER FRAMEWORK Nurdian, Risky Agung; Zamakhsyari, Fardan; Amrozi, Yusuf
Jurnal AKSI (Akuntansi dan Sistem Informasi) Vol 5, No 1 (2020)
Publisher : Politeknik Negeri Madiun

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (517.562 KB) | DOI: 10.32486/aksi.v5i1.448

Abstract

Company Z is a business entity engaged in the distribution of motorcycle parts in partnership with local shops in the supply chain. The process of recording parts distribution services, service returns and report services is still done manually. So this process is quite vulnerable to data loss that has been recorded. Therefore, a more effective and efficient recording system is needed. The system will be designed using the concept of Supply Chain Management which includes the process of purchasing goods, selling goods, managing suppliers, returning goods and managing reports. In this study the authors used a descriptive qualitative research method with interview, observation and document collection data collection techniques. The system is designed using a codeigniter framework and uses a MySQL database. The system that has been designed can provide solutions in recording the purchase, sales, management, product returns, and report management services that have been carried out based on the website so that it becomes more effective and efficient.
Enhance User Interface to Deaf E-Learning Based on User Centered Design Fardan Zamakhsyari; Achmad Teguh Wibowo; Mohammad Khusnu Milad
MATICS: Jurnal Ilmu Komputer dan Teknologi Informasi (Journal of Computer Science and Information Technology) Vol 14, No 2 (2022): MATICS
Publisher : Department of Informatics Engineering

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18860/mat.v14i2.17703

Abstract

Abstract—The cognitive learning approach through visual media is a characteristic of learning for deaf students because these students can receive learning more quickly. However, this method became an obstacle when this process was online conducted because of the effect of the Covid-19 pandemic. Based on the explanation, a need for media learning based on interactive media can help students in the studying process. This research focuses on developing learning media using User Center Design (UCD) method to a center for the development system. In this research, we develop a user interface (UI) for deaf students, especially in the Putra Asih inclusive school in the city of Kediri, Indonesia. The evaluation of this research using ISO-9241 shows the effectiveness of using the application obtained 87,15%, effectiveness of the user interface design obtained 80,05%, and user satisfaction obtained 71,18% where all parameters make sense and acceptable based on a response from the users.
Comparison of KNN and Random Forest Algorithms on E-Commerce Service Chatbot Zamakhsyari, Fardan; Makayasa, Bagas Adi; Hamami, R. Abudullah; Akbar, Muhammad Tulus; Cahyono, Andi; Amirullah, Amirullah; Hisyamuddin, Muhammad Zida; Siregar, Maria Ulfah
JISKA (Jurnal Informatika Sunan Kalijaga) Vol. 10 No. 1 (2025): January 2025
Publisher : UIN Sunan Kalijaga Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14421/jiska.2025.10.1.100-109

Abstract

Technology has a profound influence on our lives, with the expansion of e-commerce being a significant outcome that warrants attention. Given the prevalence of smartphones equipped with messaging apps and fast networks, people often utilize these platforms to communicate with sellers, offering a convenient way for sellers to engage efficiently with a diverse customer base. Recognizing this trend, there is a need for digital transformation of services to improve operational efficiency. Thus, this study aimed to compare the efficiency of classification algorithms in e-commerce service chatbots. The researcher employed machine learning techniques, specifically KNN and Random Forest algorithms, in this case. To assess the feasibility of the application, the chatbot results will be tested using the confusion matrix method to determine accuracy. From this study, it was found that the KNN method, combined with calculating word weight using TF-IDF, produces an accuracy value of 71.4%, thus confirming its feasibility.
A Systematic Literature Review of Design Thinking Approach for User Interface Design Zamakhsyari, Fardan; Fatwanto, Agung
JOIV : International Journal on Informatics Visualization Vol 7, No 4 (2023)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/joiv.7.4.1615

Abstract

The user interface is an influential element in software applications. A well-designed user interface will potentially increase the usability of software applications. Therefore, user interface designers should deliberate when considering which approach and method to implement for designing user interfaces. Design thinking is currently a widely followed approach in user interface design practices. Hence, this study aimed to explore research trends and current practices of design thinking approach for user interface design. This study employed a systematic literature review following the Kitchenham method. This study found 39 articles deemed relevant to the design thinking approach. In general, our study found five common stages broadly mentioned in the articles, i.e., empathize, define, ideate, prototype, and test. The most widely practiced method during those five stages is interview, user persona, brainstorming, user interface, and usability testing. However, there is no consensus on what kind of stage(s) and which method(s) should be employed when following the design thinking approach for user interface design. Therefore, it will depend on the designer's decision in choosing which stage(s) and their related method(s) will be employed.
A Systematic Literature Review of BERT-based Models for Natural Language Processing Tasks Agung Fatwanto; Fardan Zamakhsyari; Rebbecah Ndungi
JURNAL INFOTEL Vol 16 No 4 (2024): November 2024
Publisher : LPPM INSTITUT TEKNOLOGI TELKOM PURWOKERTO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20895/infotel.v16i4.1206

Abstract

Research area in natural language processing (NLP) domain has made major advances in recent years. The Bidirectional Encoder Representations from Transformers (BERT) and its derivative models have been at the vanguard, gaining notice for their exceptional performance across a variety of NLP applications. As a response to this context, hence, this study aims to conduct a systematic literature review on current research in BERT-based models in order to describe their characteristic variations on three frequently demanded natural language processing (NLP) tasks, i.e. text classification, question answering, and text summarization. This study employed a systematic literature review method as prescribed by Kitchenham. We collected 4,120 papers from publications indexed by Scopus and Google Scholar from which 42 complied to our defined review criteria and finally chosen for further analysis. Our review came up with three conclusions. First, in order to select appropriate models for particular NLP tasks, three primary concerns should be considered: i) the type of NLP problem to be resolved (i.e. NLP task to be served), ii) the specific domain to be handled (such as financial, medical, law/legal or others), and iii) the intended language to be applied (such as English or others). Second, learning rate, batch size, and the type of optimizer were the three most considered hyperparameters to be properly arranged in model training. Third, the most widely used metrics for text classification tasks were F1-score, accuracy, precision, and sensitivity (recall), while question answering, and text summarization tasks were mostly used the Exact Match and ROUGE respectively.
Sentiment Analysis of YouTube Comments for the Jumbo Movie Trailer Using IndoBERT Zamakhsyari, Fardan; Suhana, Rizka; Ramadhani, Irfan; Priyo Santoso, Dwi
Smart Techno (Smart Technology, Informatics and Technopreneurship) Vol. 8 No. 1 (2026)
Publisher : Primakara University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59356/smart-techno.v8i1.198

Abstract

The film industry in Indonesia has experienced significant growth, from cinematography to animation. Along with this growth, public opinion has also varied, from assessments of the storyline to the production process. To assess public sentiment on social media, a system is needed that can accommodate this process. This study aims to analyse public sentiment towards the trailer for the animated film ‘Jumbo,’ which was released on the YouTube platform. Using an NLP approach, two fine-tuned IndoBERT models were compared: ‘Aardiiiiy/indobertweet-base-Indonesian-sentiment-analysis’ and ‘rikidharmawan/finetuning-sentiment-model-indobertweet-v2’. The data to be processed was obtained from 1,468 YouTube comments through a crawling process using the YouTube API. The data was then analysed using both models to classify the comments into positive, neutral, and negative sentiments. Evaluation was conducted using a confusion matrix with accuracy, precision, recall, and F1-score metrics. The evaluation results show that ‘Aardiiiiy/indobertweet-base-Indonesian-sentiment-analysis’ is superior, with an accuracy of 57.2% and a higher average F1-score compared to ‘rikidharmawan/finetuning-sentiment-model-indobertweet-v2,’ which has an accuracy of 51.3%. This research contributes to the selection of sentiment analysis models for Indonesian-language data, particularly in the domains of social media and the film industry.