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All Journal Sistemasi: Jurnal Sistem Informasi Angkasa: Jurnal Ilmiah Bidang Teknologi JURIKOM (Jurnal Riset Komputer) JURTEKSI Jurdimas (Jurnal Pengabdian Kepada Masyarakat) Royal JOURNAL OF SCIENCE AND SOCIAL RESEARCH JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Building of Informatics, Technology and Science Jurnal Sistem informasi dan informatika (SIMIKA) Jurnal Manajemen Informatika Jayakarta Jutsi: Jurnal Teknologi dan Sistem Informasi J-Com (Journal of Computer) Jurnal Bangun Abdimas Journal of Applied Business and Technology Jurnal Teknologi Ilmu Komputer
Ramdhan, William
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Arts Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Materials Science & Nanotechnology Public Health Social Sciences Other

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Journal : JOURNAL OF SCIENCE AND SOCIAL RESEARCH

 1 
PENERAPAN ALGORITMA K-PROTOTYPES DALAM ANALISIS POTENSI UMKM DI KABUPATEN ASAHAN Ramdhan, William; Nurwati, Nurwati; Santoso, Santoso
JOURNAL OF SCIENCE AND SOCIAL RESEARCH Vol 8, No 3 (2025): August 2025
Publisher : Smart Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54314/jssr.v8i3.3863

Abstract

Abstract: Micro, Small, and Medium Enterprises (MSMEs) in Asahan Regency have very heterogeneous characteristics, both in terms of business sectors, capital size, and income achievement. This study aims to cluster MSMEs using the K-Prototypes algorithm to group business actors into uniform clusters based on numerical and categorical characteristics. The methodology used includes the pre-processing stage, variable transformation, determining the optimal number of clusters using the elbow method, and implementing the K-Prototypes algorithm. The results of the study showed that five main clusters were successfully formed, each showing a different pattern in terms of capital, net income, and dominant business sector. Data visualization and exploration (EDA) also strengthened the understanding of the cluster structure that was formed. The cluster with the highest capital and income is dominated by the medium-scale trade sector, while the cluster with the lowest capital and income is identical to micro MSMEs in the culinary and service sectors. These findings prove that the K-Prototypes algorithm is effective in identifying MSME segmentation in a more structured manner and can be the basis for designing more targeted MSME development strategies. Keyword: UMKM; clustering; K-Prototypes; mixed data; segmentation analysis. Abstrak: Usaha Mikro, Kecil, dan Menengah (UMKM) di Kabupaten Asahan memiliki karakteristik yang sangat heterogen, baik dari sisi sektor usaha, besaran modal, hingga capaian income. Penelitian ini bertujuan untuk melakukan klasterisasi UMKM menggunakan algoritma K-Prototypes guna mengelompokkan pelaku usaha ke dalam klaster-klaster yang seragam berdasarkan karakteristik numerik dan kategorikal. Metodologi yang digunakan mencakup tahap pre-processing, transformasi variabel, penentuan jumlah klaster optimal menggunakan metode elbow, serta implementasi algoritma K-Prototypes. Hasil penelitian menunjukkan bahwa lima klaster utama berhasil dibentuk, masing-masing menunjukkan pola yang berbeda dalam hal modal, income bersih, dan sektor usaha dominan. Visualisasi dan eksplorasi data (EDA) turut memperkuat pemahaman terhadap struktur klaster yang terbentuk. Klaster dengan modal dan income tertinggi didominasi oleh sektor perdagangan skala menengah, sedangkan klaster dengan modal dan income terendah identik dengan UMKM mikro di sektor kuliner dan jasa. Temuan ini membuktikan bahwa algoritma K-Prototypes efektif digunakan untuk mengidentifikasi segmentasi UMKM secara lebih terstruktur dan dapat menjadi dasar dalam merancang strategi pengembangan UMKM yang lebih tepat sasaran. Kata kunci: UMKM; klasterisasi; K-Prototypes; data campuran; analisis segmentasi
OPTIMALISASI CRM BERBASIS AI DALAM E-COMMERCE: ANALISIS PENGARUH TERHADAP LOYALITAS PELANGGAN DENGAN PENDEKATAN SENTIMEN ANALISIS Rahayu, Elly; Ramdhan, William
JOURNAL OF SCIENCE AND SOCIAL RESEARCH Vol 8, No 4 (2025): November 2025
Publisher : Smart Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54314/jssr.v8i4.4005

Abstract

The purpose of this study is to analyze the relationship between the application of AI in CRM and customer loyalty. The results of sentiment analysis through Web Scraping are used to strengthen the interpretation of the results, not as a mediator or can be called triangulation or enrichment data. The population of this study were active e-commerce customers with a sample of 384 respondents obtained through purposive sampling techniques. Data analysts used the SEM-PLS and NLP approaches for sentiment classification. The study's results indicate that AI-based CRM has a positive and significant impact on customer loyalty. This is indicated by the T-statistic value of 29,415 > 1.96. The conceptual model is also very good, as evidenced by the SRMR value of 0.054> 0.050 and the NFI value of 0.907. Sentiment analysis collected through social media X from 3,213 tweets with the keyword skincare resulted in 74% neutral opinions, 13.7%, and 12.3% negative. Furthermore, the classification results of 7 aspects of positive and negative opinions such as aftersales, delivery, experience, order, packaging, product, and unknown, from positive opinions the largest percentage is in the experience (customer experience) 43.2% while for negative opinions the largest percentage is also in the experience aspect of 45.8%. This data is important for business owners to make improvements and improvements to create customer satisfaction. 45.8% of bad customer experiences will, if not followed up, make customers switch to other stores.
ANALISIS DATA EKSPLORATORI DAN CLUSTERING K-MODES UNTUK PEMETAAN STATUS GIZI BALITA PADA KASUS STUNTING DI KABUPATEN ASAHAN Ramdhan, William; Nurwati, Nurwati; Rahayu, Elly
JOURNAL OF SCIENCE AND SOCIAL RESEARCH Vol 8, No 4 (2025): November 2025
Publisher : Smart Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54314/jssr.v8i4.4192

Abstract

Stunting is a chronic nutritional problem that impacts children's physical growth and development and is a public health challenge in Indonesia. This study integrates Exploratory Data Analysis (EDA) and K-Modes Clustering to map the nutritional status of toddlers in stunting cases in Asahan Regency. EDA was used to explore data distribution, identify relationships between nutritional status indicators, and identify risk factor patterns, while K-Modes was used to group toddlers based on shared categorical characteristics. The dataset used included sociodemographic variables (gender, age category, parental education and occupation) and nutritional status indicators (weight/age, height/age, weight/height). The analysis results showed a moderate positive correlation between weight/age and height/age (0.32) and a strong negative correlation between weight/age and weight/height (-0.50), indicating a link between stunting and wasting. The application of K-Modes resulted in three main clusters: Cluster 0, dominated by female toddlers with normal nutritional status but low parental education; Cluster 1 consists of infant girls with low weight for age and short height for age, despite most parents having a high school education; Cluster 2 contains infant boys with very low weight for age and very short height for age, and relatively low maternal education. The profile of each cluster was analyzed to identify dominant characteristics relevant for intervention. This integrative approach demonstrates that the combination of EDA and K-Modes is able to provide a comprehensive picture of variations in toddler nutritional status, thus serving as a basis for planning more targeted promotive and stunting prevention strategies at the regional level.
Co-Authors Akmal Akmal Alfina, Chalista Amalia Amalia Amalia, Laily Rizky Annissa, Nur Tiara Ayu Safitri Chaniago, Arif Syarifuddin Deny Jollyta dermawan, ari Erick Santoso Farenza, Dinda Novri Gustin, Sela Ida Ayu Putu Sri Widnyani Ihsan, Mhd. Ihsan Ishan, Mhd Johan Johan Kartika, Juli Kifti, Wan Mariatul Laksamana, Aditia Mariatul Kifti, Wan Marpaung, Darmiyanti Maulana Marpaung, Teguh Gilang Monalisa, Nency Widya Nabila, Inaya Nadia Nadia Nofriadi Nofriadi Nursia, Akris Nursia Nurwati Nurwati Parini Prihandoko Prihandoko Purwanti, Teti Rahayu, Elly Rahmadhani, Dhea Safitri, Lisda sahren, sahren SANTOSO SANTOSO Septian, ashley Xyaniena Sri Amelia, Sri Sudarmin Sudarmin Susilo, Widya Amanda Syahputra, Abdul Karim Syaputra, Abdul Karim Tiara, Adinda Yusda, Riki Andri Zein, Jihan Raihan