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All Journal Abdimas Toddopuli: Jurnal Pengabdian Pada Masyarakat INOVTEK Polbeng - Seri Informatika
Eko Darmanto
Muria Kudus University
Agriculture, Biological Sciences & Forestry Civil Engineering, Building, Construction & Architecture Computer Science & IT Other

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Analisis Penerapan Sistem Informasi Pengarsipan Surat Masuk Pada Bagian Koperasi di Disnakerperinkop dan UKM Kabupaten Kudus Tsirwatun Nisail Khasanah; Eko Darmanto
Abdimas Toddopuli: Jurnal Pengabdian Pada Masyarakat Vol. 7 No. 1 (2025): Volume 7, No 1, Desember 2025
Publisher : Universitas Cokroaminoto Palopo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30605/atjpm.v7i2.7632

Abstract

Pengelolaan surat masuk di Bagian Koperasi di Disnakerperinkop dan UKM Kabupaten Kudus masih dilakukan secara manual sehingga menimbulkan kendala dalam pencatatan, penyimpanan, dan penelusuran arsip. Penelitian ini bertukuan menganalisis penerapan Sistem Informasi Pengarsipan surat masuk untuk meningkatkan efisiensi, ketertiban, dan keteraturan dokumen. Metode yang digunakan meliputi studi literaliteraturervasi lapangan, wawancara, dengan pegawai terkait, serta perancangan system berbasis laravel dan MYSQL. Hasil menunjukkan bahwa system digital memungkinkan pencatatan, penyimpanan, dan penelusuran surat dilakukan lebih cepat dan terstruktur, meminimalkan resiko kehilangan dokumen, serta mempermudah pemantauan status surat secara real-time. Temuan inj sejalan dengan teori digitalisasi administrasi yang menyatakan bahwa system ini memberikan kontribusi signifikan terhadap modernisasiadministrasi, mempermudah pengelolaan surat masuk, dan mendukung proses kerja yang lebih tertata dan professional.
Design and Development of a Make-Up Service Portal in Kudus Regency Using the Customer Satisfaction Index Method Umi Wahidasiana; Eko Darmanto; Arif Setiawan
Journal of Innovation and Technology Polbeng Series on Informatics (INOVTEK Polbeng - Seri Informatika) Vol. 10 No. 3 (2025): November
Publisher : P3M Politeknik Negeri Bengkalis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35314/zga6c449

Abstract

Cosmetology services play an important role in enhancing an individual's self-confidence. In Kudus Regency, many makeup service providers still rely on manual ordering methods, which are prone to recording errors, limited information on service availability, and miscommunication between customers and service providers. This condition hampers operational efficiency and reduces the level of customer satisfaction. This research aims to develop a digital-based make-up service portal to improve service quality and customer satisfaction, which consists of the stages of needs analysis, system design, implementation, testing and maintenance The research method used is qualitative research; data is collected through in-depth interviews with customers, which consists of the stages of needs analysis, system design, implementation, testing, and maintenance. The system developed has main features such as online ordering and service catalogues, as well as CSI-based customer satisfaction evaluations that measure aspects of price, service quality, and user experience. Evaluation using the CSI method shows a customer satisfaction level of 88% with 300 respondents, which indicates that this system is effective in improving user experience and operational efficiency of service providers. In conclusion, the development of this digital-based make-up service portal has succeeded in increasing customer satisfaction and the competitiveness of make-up service providers in Kudus Regency. Further development recommendations are integration with digital payment systems and the use of artificial intelligence technology for more personalized service recommendations.  
Sentiment Analysis of User Reviews for the Locket Widget Application on Google Play Store Using the Naive Bayes Classifier Athia Aisy Bakhita; Arif Setiawan; Eko Darmanto
Journal of Innovation and Technology Polbeng Series on Informatics (INOVTEK Polbeng - Seri Informatika) Vol. 11 No. 3 (2026): August (Inpress)
Publisher : P3M Politeknik Negeri Bengkalis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35314/s90w5308

Abstract

User reviews on the Google Play Store contain valuable opinions that can be utilized to evaluate application quality, including the Locket Widget application. This study aims to classify user review sentiment into positive, neutral, and negative categories using the Naïve Bayes Classifier algorithm with Term Frequency–Inverse Document Frequency (TF-IDF) weighting. The data were collected through web scraping, resulting in 589 user reviews. The dataset then underwent preprocessing, sentiment labeling, TF-IDF weighting, and sentiment classification. The model was evaluated using an 80:20 stratified train–test split. The results showed that the proposed model achieved an accuracy of 76.27%, with a weighted precision of 0.69, weighted recall of 0.76, and weighted F1-score of 0.72. The findings indicate that the combination of TF-IDF and the Naïve Bayes classifier is effective in classifying positive and negative user review sentiments. However, the model was unable to effectively classify the neutral class, resulting in an F1-score of 0.00 for this category. This finding indicates that further improvements are needed to enhance the model's ability to distinguish neutral sentiment from positive and negative classes.
Decision Support System for Furniture Product Recommendation Using Item-Based Collaborative Filtering and Min-Max Normalization KharisatunNisa; Eko Darmanto; Arif Setiawan
Journal of Innovation and Technology Polbeng Series on Informatics (INOVTEK Polbeng - Seri Informatika) Vol. 11 No. 3 (2026): August (Inpress)
Publisher : P3M Politeknik Negeri Bengkalis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35314/j8dchq29

Abstract

The increasing variety of furniture products available in the market makes it difficult for consumers to identify products that best match their preferences. Conventional product selection is often carried out manually, requiring consumers to compare product specifications one by one, which is time-consuming and may lead to less appropriate purchasing decisions. This study proposes a web-based decision support system for furniture product recommendation by integrating the item-based collaborative filtering (IBCF) method with min–max normalization. The recommendation process utilizes historical user ratings to identify similarities among products, while min–max normalization is applied to standardize product attributes, including price, category, material, color, and size, into a comparable scale. To address the cold-start problem for newly added products with insufficient rating data, a content-based similarity mechanism is incorporated into the recommendation process. The system was developed using a dataset consisting of 322 furniture products, 50 consumers, and 1,099 rating transactions. System functionality was evaluated using black-box testing, while user acceptance was assessed through user acceptance testing (UAT) involving ten respondents. The evaluation results show that all primary system functions operated as expected and achieved an overall UAT score of 88.0%, indicating that the proposed system is acceptable and capable of assisting consumers in selecting furniture products based on their preferences. This study contributes by integrating collaborative filtering, multi-attribute normalization, and a content-based cold-start mechanism into a single recommendation framework for furniture product recommendation
Co-Authors Arif Setiawan Athia Aisy Bakhita KharisatunNisa Tsirwatun Nisail Khasanah Umi Wahidasiana