Article Per Year (5 Year)
p-Index From 2021 - 2026
9.928
P-Index
This Author published in this journals
All Journal Katalogis Indonesian Journal of Forestry Research JAM : Jurnal Aplikasi Manajemen Majalah Kulit, Karet, dan Plastik JURNAL ILMIAH PENDIDIKAN FISIKA AL BIRUNI Jurnal Pembelajaran Berpikir Matematika Jurnal Manajemen Dan Kewirausahaan Jurnal Dinamika Pengabdian (JDP) JURNAL PENDIDIKAN FISIKA Sistemasi: Jurnal Sistem Informasi Resona : Jurnal Ilmiah Pengabdian Masyarakat Southeast Asian Journal of Islamic Education Syntax Literate: Jurnal Ilmiah Indonesia Varia Justicia Al-Iktisab: Journal of Islamic Economic Law JOURNAL EQUITABLE Jurnal Sosial Humaniora IKRA-ITH ABDIMAS JURTEKSI Jurdimas (Jurnal Pengabdian Kepada Masyarakat) Royal JOURNAL OF SCIENCE AND SOCIAL RESEARCH JURNAL PANGAN Kosmik Hukum EDUMATIC: Jurnal Pendidikan Informatika Jurnal Justitia : Jurnal Ilmu Hukum dan Humaniora Building of Informatics, Technology and Science AS-SIYASAH: Jurnal Ilmu Sosial Dan Ilmu Politik Jurnal Manajemen dan Bisnis Jayakarta Jurnal Warna : Pendidikan dan Pembelajaran Anak Usia Dini Community Development Journal: Jurnal Pengabdian Masyarakat Journal of Food Technology and Agroindustry Idealis : Indonesia Journal Information System Community Empowerment Borobudur Law Review International Journal of Business, Law, and Education Jutsi: Jurnal Teknologi dan Sistem Informasi Jurnal Teknisi J-Com (Journal of Computer) Anoa : Jurnal Pengabdian Masyarakat Sosial, Politik, Budaya, Hukum. Ekonomi Jurnal Pengabdian Masyarakat Ilmu Terapan (JPMIT) Society: Jurnal Pengabdian Masyarakat Sultan Idris Journal of Psychology and Education el-Buhuth: Borneo Journal of Islamic Studies Borobudur Journal on Legal Services JOMPA ABDI: Jurnal Pengabdian Masyarakat Prosiding University Research Colloquium Jurnal Pemberdayaan Sosial dan Teknologi Masyarakat Journal of Management and Administration Provision Jurnal Indonesia Sosial Sains International Journal of Multidisciplinary Sciences and Arts BOCAH: Borneo Early Childhood Education and Humanity Journal JAMU : Jurnal Abdi Masyarakat UMUS Journal of Technology and Food Processing (JTFP) Journal Of Computer Science And Technology Journal Markcount Finance Media Akuntansi Perpajakan Socio-Economic and Humanistic Aspects for Township and Industry Jurnal Riset Multidisiplin dan Inovasi Teknologi Journal of Management and Innovation Entrepreneurship (JMIE) Transnational Business Law Journal Jurnal Edukatif E-Amal: Jurnal Pengabdian Kepada Masyarakat INOVASI: Jurnal Ekonomi, Keuangan, dan Manajemen Journal Development Manecos Fortunate Business Review
Nurwati Nurwati
FKM UNHAS
Religion Agriculture, Biological Sciences & Forestry Arts Humanities Astronomy Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Immunology & microbiology Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Medicine & Pharmacology Neuroscience Nursing Physics Public Health Social Sciences Transportation Other

Published : 101 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 3 Documents
Search
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
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.
ANALISIS MODEL KLASIFIKASI DENGAN OPTIMASI PARTICLE SWARM OPTIMIZATION DALAM KLASIFIKASI STATUS GIZI ANAK Nurwati, Nurwati; Nofitri, Rika; Selvi, Diana
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.v8i4.4247

Abstract

Abstract: Nutritional status represents a state of equilibrium in the form of specific variables or the manifestation of nutrition in the form of specific variables. Optimal nutritional status is achieved when there is a balance between nutrient intake and nutrient requirements. Malnutrition not only affects an individual's physical health but also negatively impacts their overall development and well-being. However, data warehouses related to child nutritional status in Asahan Regency from various community health centers (Puskesmas) have not been optimally utilized to generate valuable information. Therefore, the purpose of this study was to analyze child nutrition datasets using a machine learning-based classification model that can predict children's nutritional status early. The classification model was chosen because of its ability to group data or objects based on specific classes, making it suitable for future data prediction. Based on the results, it can be concluded that optimizing the toddler nutritional status classification model using the Particle Swarm Optimization (PSO) method and cross-validation was able to identify the best model, namely the Decision Tree, with an accuracy of 37.50%. Although the overall accuracy of all models was still relatively low. This indicates the need for further data processing, such as data balancing, selecting more relevant features, and further parameter tuning to improve classification performance. Keywords: Classification; Particle_Swarm Optimization; Cross Validation, Nutritional Status Abstrak: Status gizi adalah representasi dari keadaan keseimbangan dalam bentuk variabel tertentu atau manifestasi nutrisi dalam bentuk variabel tertentu, di mana status gizi optimal dicapai ketika terjadi keseimbangan antara asupan dan kebutuhan zat gizi. Gizi buruk tidak hanya memengaruhi kesehatan fisik individu, tetapi juga berdampak negatif pada perkembangan dan kesejahteraan mereka secara keseluruhan. Akan tetapi, gudang data yang terkait status gizi anak di Kabupaten Asahan dari berbagai puskesmas belum dimanfaatkan dengan optimal untuk menghasilkan informasi yang berharga. Oleh karena itu, tujuan dari penelitian ini adalah untuk menganalisis dataset gizi anak menggunakan model klasifikasi berbasis machine learning yang dapat memprediksi status gizi anak secara dini. Model klasifikasi dipilih karena kemampuannya dalam mengelompokkan data atau objek berdasarkan kelas tertentu, sehingga cocok untuk prediksi data di masa depan. Berdasarkan hasil penelitian, dapat disimpulkan bahwa optimasi model klasifikasi status gizi balita menggunakan metode Particle Swarm Optimization (PSO) dan cross validation mampu mengidentifikasi model terbaik, yaitu Decision Tree dengan akurasi 37,50%, meskipun secara umum tingkat akurasi seluruh model masih relatif rendah. Hal ini menunjukkan perlunya pengolahan data lebih lanjut, seperti balancing data, pemilihan fitur yang lebih relevan, maupun tuning parameter lanjutan untuk meningkatkan performa klasifikasi. Kata kunci: Klasifikasi; Particle Swarm Optimization; Cross Validation, Status Gizi 
Co-Authors ABDILLAH RAMADHAN Abdul Gani Abdul Razak Adhisyah, Siti Vickie Dina Maulaya Adi Rizfal Efriadi, Adi Rizfal Adiwijaya, Achmad Jaka Santos Adya Hermawati Afiana, Nisa Dewi Ahmad Riyadi Ajahra, Fatimah Akbar, Muh. Alfarizi, Rizky Putri Alidin, La Ode Asfahyadin Amri, Muhammad Al Anugrah, Citra Apriandani, Babby Apriany, Vivi Awasinombu, Aidin Hudani Bahar, Harmiaty Bambang Tjatur Iswanto, Bambang Tjatur Bambang Wiyono, Bambang Basri Basri Berliani, Ainun br sinambela, salsabilah ramadani Budiharto Budiharto Buyung Sarita Cahyani, Indah Tri Cahyani, Nopita Indah Chanafi, Muhammad Cusyana, Silvi Reni Cusyana Dakum, Dakum Dalimunthe, Ruri Ashari Deskiana, Intan Dewi ANGGRAENI Dewi, Sri Puspita Djaya, Subhan Effendi, Indah Syalsabilla Eko Jokolelono Endaryo, Dimas Bagas Endeh Suhartini fadila, nurlailatul Febriyani, Nadia Febryawan, Aldy Fera, Melly Ferdiansyah, Malik FIKRI HAIKAL Fitri Larasati, Mustika Fitriwati Djam’an Fredinan Yulianda Ghifari, Ghazi Al Gundari, Putri Habib, Yahya Abdul Handoyo, Wuri Harbeng Masni, Harbeng Haris, Nadhifa Abdul Harjoprawiro, La Hasanah, Acunta Uswatun Havita, Deandra Najwa Hayati, Norlina Heni Hendrawati Heniyatun Herman Saputra, Rifki Herman Saputra, Rifki Husin Husin Husin, Husin Husna, Lenny Hutabarat, Zuhri Saputra Hutapea, Tiofani Br. I Made Antara Ilyanawati, R. Yuniar Anisa Indra Indra Istia, Inka Condro Ity Rukiyah Iwan Setiadi Johny Krisnan, Johny Khotamir Rusli, Radif Kifti, Wan Mariatul Kinanti, Ajeng Zahra Kusumah, Akhmad Hadi Kusumah, Surya La Ode Bahana Adam Larasati, Ika Arum Larasati, Mustika Fitri Latupapua, Conchita V Lestari, Cetryn Ayu Diah Lestari, Mariska Dwi Liandini, Sevya M. Rendi Aridhayandi Maharani, Dewi Mahpial, Dheo Junia Mahrani, Sri Wiyati Mangilep, Muhammad Ady Agung Martaleni - Meitri, Jeanet Silky Mochammad Imron Awalludin Montundu, Yusuf MUFTI MUFTI, MUFTI Muhammad Irkham Firdaus Muhammad Sudia Mujahidah Mujahidah Murdjani Kamaluddin, Murdjani Muthia Dewi Narassati, Maulida Nasution, Ulfa Oktaviani Nia Syafrila, Wirfa Ningrum, Mawar Puspitha Ningsih, Ade Irma Suriya Nofitri, Rika Novanda, Della Sagita Noviasari, Dilli Trisna Nugraha, Rahmat Nurul Prima Nur Alim Djalil Nur lina Nurayini, Soleha Nurhaliza, Rizky Nurhasanah Nurhasanah Nurlita , Febri Nurqamar, Insani Fitri Pamungkas, Aldo Satriyo Pandiangan, Anjani Putri Belawati Pariabti Palloan Pebriani, Elvi Penny Setyowati, Penny Pianti, Uut Okta Prasja, Teguh Rama Pratama, Grevind Putra, Singgih Adhi Putri, Anggia Sekar Putri, Rima Melani Putri, Riska Ananda Rachman, Muhammad Sultan Al Viqri Rahayu, Elly Rahmadani, Cindy Rahmadani, Nurul Rahman Nur Ibnu, Adi Rahmawati, Rahmawati ramadani, Novita Ramdhan, William Ramlawati Ramlawati Randi, Mohamma Jusuf Rasnawati, Rasnawati Rina Rina Ritawaty, Noor Rizki Utami, A’Allya Rizqiyah, Jazirotur Roestamy, Martin Rohminatin, Rohminatin Safitri, Rahmah Salman Samir, Salman Salsabila Rizki, Diva Salsabila, Adinda Samsir Samsir Samsir Samsir, Samsir SANTOSO SANTOSO Santoso, R. Tri Priyono Budi Saputra, Endra Saputri, Rischa Indah Sari Risnawati, Ayu Sari, Padia Nadila Selvi, Diana Sena, Maulana Dwi Sinarwaty Sunarjo Soraya, Elly Sri Nadilah, Sri Supriadi, Sendi Susanti, Riski Susilawati, Susilawati Syafnur, Afdhal Syahfitri, Novianti Syamsul Bahri Tahir, Febryansyah Umairoh, Siti Umar Wirahadi Kusuma, Umar Wirahadi Utami, Dinda Fransiska Valeria , Maciejewski Vanisa Meifari Wahyuniati Hamid Widodo Widodo Yudi Santoso, Yudi Yulia Kurniaty Yuliana, Eni Yulita, Kintan Yunika Purwanti Yusda, Riki Andri Yusuf Yusuf