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All Journal ILKOM Jurnal Ilmiah Simtek : Jurnal Sistem Informasi dan Teknik Komputer Jambura Journal of Electrical and Electronics Engineering Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) Jurnal Restikom : Riset Teknik Informatika dan Komputer Jurnal Minfo Polgan (JMP) Jurnal Nasional Cosphi Jurnal Ilmiah Ilmu Komputer Banthayo Lo Komputer (BALOK) Journal Of Informatics And Busisnes Empiris Jurnal Pengabdian Pada Masyarakat (EJPPM) Jurnal Pengabdian Pada Masyarakat Eldimas
Maryam Hasan
Universitas Ichsan Gorontalo
Agriculture, Biological Sciences & Forestry Humanities Biochemistry, Genetics & Molecular Biology Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Languange, Linguistic, Communication & Media Library & Information Science Mathematics Social Sciences

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Analisis Kualitas Website UMKM Nasional Menggunakan Metode Heuristic Evaluation dan Google Lighthouse Apriyanto Alhamad; Sudirman Melangi; Maryam Hasan; Sitti Nur Avifa Olii; Warid Yunus; Hastuti Dalai
Jurnal Minfo Polgan Vol. 15 No. 2 (2026): Artikel Penelitian
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/jmp.v15i2.16223

Abstract

This study analyzes the quality of SMEsta, a national MSME digital portal, by combining user-based Heuristic Evaluation and Google Lighthouse auditing. The background of the study is the strategic role of public websites in supporting MSME digitalization and the need to evaluate not only interface convenience but also technical readiness on mobile access. The objective is to describe SMEsta usability, identify technical quality gaps, and formulate improvement priorities from both sources of evidence. The research used a quantitative descriptive case-study approach. Users evaluated three pages, namely Home, Export MSME Recommendations, and FAQ, through a Likert questionnaire mapped to Nielsen's ten heuristics, while the same pages were audited through Google Lighthouse mobile configuration. The instrument was validated by experts and showed reliable internal consistency with Cronbach's alpha of 0.910. From 105 responses, 100 valid responses were analyzed. The findings show that SMEsta usability is in the high category, with an overall mean of 4.19 and an index of 79.80. Error prevention obtained the highest mean of 4.32, whereas help users recognize, diagnose, and recover from errors was the lowest with a mean of 3.73. Lighthouse results indicate uneven technical quality, especially performance: the Export MSME Recommendations page scored 56, the Home page scored 36, and the FAQ page scored 23, while SEO reached 100 on all pages. The study concludes that SMEsta is generally usable, but performance optimization and clearer contextual error support should become priority improvements
Penerapan Metode Apriori Pada Transaksi Penjualan Spare Parts Mobil Maryam Hasan; Sudirman S Panna; Siska Udilawati; Almer Hassan Ali
Journal Of Informatics And Busisnes Vol. 3 No. 2 (2025): Juli - September
Publisher : CV. ITTC INDONESIA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47233/jibs.v3i2.3093

Abstract

Until now, commercial vehicle manufacturers continue to innovate their products. One of the manufacturers is PT Nenggapratama Prima Nusantara, engaged in trade and services, namely HINO brand vehicles, spare parts, and services in direct collaboration with PT. Hino Motors Indonesia. The high demand and various types of spare parts certainly drive PT. Nenggapratama Prima Nusantara to maximize existing stock. It aims to ensure that there is no accumulation or shortage of goods. It is important to know the purchasing behavior of customers about which spare parts they buy together. One of the data processing methods usable for this problem is data mining with association analysis using Apriori algorithm. It is a data mining technique that produces rules to determine consumer habits in buying goods simultaneously at once. Based on the results of research using the Apriori method, the largest value (Support x Confidence) is obtained at 0.33. The biggest possibility is that if you buy the Dutro E-4 Fuel Strainer Kit, you will also buy Element Sub Assy Oil with a value of 0.33. Therefore, it can be seen that related spare parts can be arranged simultaneously.
Grouping of Areas Based on Flood Disaster Level Using K-Means Clustering Algorithm Maryam Hasan; Sudirman S. Panna; Abd. Rahmat Karim Haba; Apriyanto Alhamad
Jambura Journal of Electrical and Electronics Engineering Vol 8, No 1 (2026): Januari - Juni 2026
Publisher : Electrical Engineering Department Faculty of Engineering State University of Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37905/jjeee.v8i1.33145

Abstract

The Province of Gorontalo is highly vulnerable to flood disasters due to its geographical conditions, high rainfall, and uncontrolled land-use changes. This study aims to apply the K-Means Clustering algorithm to classify regions based on flood impact levels to support disaster mitigation and decision-making processes by the National Search and Rescue Agency (BNPP) Gorontalo. The dataset comprises 405 disaster incident records obtained from related institutions, including the number of affected, injured, deceased, and missing individuals. The analysis process involves data collection, preprocessing, distance calculation using the Euclidean Distance method, and the formation of two clusters based on impact levels. The iteration process stopped at the second iteration, indicating that a stable (convergent) condition had been achieved. The results revealed that Cluster 1 (C1) includes areas significantly affected by floods such as Imana, Iloheluma, and Tudi villages, while Cluster 2 (C2) represents unaffected areas like Wapalo, Ilomata, Motihelumo, and others. The implementation of the K-Means algorithm proved effective in identifying disaster-prone regions objectively and data-driven, thus supporting more efficient disaster response planning.
Aspect-Based Sentiment Analysis (ABSA) of Ventela Shoe Reviews on TikTok Shop Using Fine-Tuned IndoBERT Fitrawansyah Butas; Amiruddin Bengnga; Maryam Hasan; Rezqiwati Ishak; Rofiq Harun; Andi Kamaruddin
Jambura Journal of Electrical and Electronics Engineering Vol 8, No 2 (2026): Juli - Desember 2026
Publisher : Electrical Engineering Department Faculty of Engineering State University of Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37905/jjeee.v8i2.39805

Abstract

The massive volume of consumer reviews on the social commerce platform TikTok Shop makes it difficult for local shoe brands such as Ventela to understand consumer perception in a structured manner, while Indonesian-language Aspect-Based Sentiment Analysis (ABSA) studies on this platform remain very limited. This study aims to apply fine-tuned IndoBERT for aspect-based sentiment classification and to measure consumer perception of four product aspects, namely Comfort, Design, Durability, and Price. Using a computational experiment approach, 1,000 reviews were collected, automatically annotated using a lexicon-based method with negation handling, restructured into 706 review-aspect pairs and divided using an 80:20 stratified split, and used to train and compare three models: TF-IDF with Logistic Regression, TF-IDF with Linear SVM, and fine-tuned IndoBERT. Testing on 142 test samples shows that fine-tuned IndoBERT is superior, achieving an Accuracy of 0.8521 and an F1-Macro of 0.7813 and surpassing both baselines on four of five primary metrics. Analysis of 706 review-aspect pairs identifies Design (75.6% positive) and Price (71.8% positive) as the main strengths, while Comfort (32.7% negative) and Durability (30.8% negative) emerge as improvement areas related to sizing and the quality of adhesive and stitching. This study enriches Indonesian ABSA literature in the social commerce domain and delivers a ready-to-use web-based simulator built with Gradio to facilitate periodic consumer-perception monitoring for data-driven decision-making processes.
Co-Authors Abd. Rahmat Karim Haba Almer Hassan Ali Amiruddin Bengnga Andi Kamaruddin Apriyanto Alhamad Bahrin Bahrin Betrisandi, Betrisandi Fitrawansyah Butas Gaffar, Gaffar Hastuti Dalai Husdi Irma Surya Kumala Idris Ismail S Manto Juriko Abdussamad Mahmud, Mohamad An Nafli Muhammad Erdiansyah Muhammad Faisal Pelangi, Kartika Candra Ramadhani, Syarifah Fitrah Rezqiwati Ishak Rifdah Rofifah Faruk Abdullah Rofiq Harun Salihi, Irvan Siska Udilawati Siti Azizah Tondako Sitti Nur Avifa Olii Sudirman Melangi Sudirman S. Panna Swastiani Dunggio Syahrir Abdussamad Warid Yunus Yulianti Lasena Zulfrianto Yusrin Lamasigi