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All Journal Golden Ratio of Community Services and Dedication Jurnal of Information Technology and Society (JITS) Jurnal Akademik Pengabdian Masyarakat Jurnal Publikasi Ilmu Komputer dan Multimedia
Tamriesfatno, Sigrid
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Humanities Computer Science & IT Economics, Econometrics & Finance Education Industrial & Manufacturing Engineering Social Sciences

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Empowering Communities through Financial Literacy Initiatives for SME Development Awaluddin, Sri Prilmayanti; Paula, Eka Wijaya; Tamriesfatno, Sigrid; Adijah S, Andi Adijah S; Khair, Andi Ummul
Golden Ratio of Community Services and Dedication Vol. 5 No. 2 (2025): May - October
Publisher : Manunggal Halim Jaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52970/grcsd.v5i2.589

Abstract

Financial literacy initiatives are crucial in empowering communities for small and medium-sized enterprise (SME) development. This qualitative literature review explores the landscape of financial literacy programs targeting SMEs, their effectiveness, and the contextual factors influencing their outcomes. The research methodology systematically selects peer-reviewed articles, books, and reports published between 2012 and 2022, utilizing databases such as PubMed, Google Scholar, Web of Science, and Scopus. Data collection entails thorough reading and analysis of selected sources, followed by iterative coding to identify key themes and insights. The findings reveal a diverse range of financial literacy interventions, including workshops, training seminars, and online resources, tailored to address the specific needs of SME owners and entrepreneurs. Cultural, socio-economic, and institutional contexts significantly influence the design and implementation of these programs, highlighting the importance of contextual sensitivity. Participation in financial education programs positively impacts SMEs' financial knowledge, decision-making abilities, and business performance, leading to improved access to financing and sustainable growth. However, challenges such as resource constraints and low financial awareness hinder the scalability and effectiveness of these initiatives. Leveraging technology and innovative delivery methods, such as digital platforms and social media, holds promise in expanding the reach and impact of financial literacy programs, particularly in underserved communities. This review underscores the importance of continued investment in financial education to unlock the full potential of SMEs as drivers of economic prosperity and social progress.
Clustering Aktivitas Olahraga Siswa untuk Evaluasi Kesehatan Fisik Tamriesfatno, Sigrid; Muh. Ikhwan Mardin; La Ode Muh. Armadi AM; Husna Saleh; Sarni Alex Sandra
Jurnal Teknologi Informasi dan Masyarakat Vol 3 No 1 (2025): Journal of Information Technology and Society (JITS)
Publisher : Universitas Muhammadiyah Bangka Belitung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35438/jits.v3i1.1419

Abstract

Sufficient and regular physical activity plays an important role in supporting students' physical, mental, and social health. However, variations in exercise habits necessitate a more objective evaluation of students' physical activity levels. This study aims to categorize students' sports activities based on duration and distance using the K-Means algorithm, in order to evaluate exercise patterns and provide relevant information for the development of physical fitness coaching programs. Data were collected from 30 students and analyzed using an unsupervised learning approach. The clustering results formed three main clusters: (1) students with low activity, short duration, and high BMI values; (2) students with moderate activity, ideal duration, and normal BMI values; and (3) students with very high activity, long duration, and consistently healthy BMI values. These findings indicate that clustering methods are effective in identifying groups of students based on their exercise habits and can serve as a foundation for fitness improvement strategies. Keywords: Physical Activity, K-Means Clustering, Exercise Habits
Pembentukan Kelompok Belajar Efektif Berbasis Algoritma Clustering untuk Meningkatkan Kualitas Pembelajaran di SD Negeri Ganrang Jawa II Muhammad Ikhwan Mardin; Sigrid Tamriesfatno; La Ode Muh. Armadi AM; Sarwono Sarwono; Muhamad Irwin Syawal; Riska Kherani; Muhammad As'ad; Sarni Alex Sandra
JURNAL AKADEMIK PENGABDIAN MASYARAKAT Vol. 4 No. 1 (2026): Januari
Publisher : CV. KAMPUS AKADEMIK PUBLISING

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61722/japm.v4i1.8926

Abstract

This community service program aims to form effective student learning groups based on clustering algorithms to improve the quality of learning at SD Negeri Ganrang Jawa II. The main problem faced by teachers is the difficulty in dividing students into learning groups evenly based on academic ability, as well as students’ tendency to choose their own friends when working in groups. These conditions result in unbalanced and less effective learning groups. To address this problem, the K-Means Clustering algorithm is applied to group students based on academic scores, so that each group consists of students with high, medium, and low abilities. The service method includes collecting student academic data, implementing the clustering algorithm, and assisting teachers in applying the learning groups. The results show that the distribution of learning groups becomes more balanced, student interaction increases, and the learning process runs more effectively. Therefore, the application of clustering algorithms can serve as an innovative solution to support collaborative learning strategies in elementary schools.
Penerapan Metode Clustering dengan Algoritma K-Means untuk Pengelompokkan Data Sekolah Menengah di Kabupaten Muna Barat Sigrid Tamriesfatno; Riska Kherani; Sarwono Sarwono
Jurnal Publikasi Ilmu Komputer dan Multimedia Vol. 4 No. 2 (2025): Mei: Jurnal Publikasi Ilmu Komputer dan Multimedia
Publisher : Pusat Riset dan Inovasi Nasional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/jupikom.v4i2.4180

Abstract

Improving the quality of education requires a comprehensive understanding of the conditions and characteristics of each educational institution. West Muna Regency has various secondary schools with diverse profiles and challenges. Until now, school grouping has often been done manually, which does not always accurately reflect the overall characteristics of the data. This study aims to cluster secondary schools in West Muna Regency using the K-Means algorithm as a clustering method to identify hidden patterns in school data, such as the number of students, teachers, staff, facilities, and location. The research method involves several stages, including data collection, method analysis, software implementation, and cluster testing. The clustering results produced three school clusters with different characteristics. Cluster 1 consists of schools with the most complete resources, Cluster 2 includes the largest number of schools with varying resources, and Cluster 3 represents schools with moderate conditions. These findings are expected to serve as a basis for formulating more targeted educational policies, ensuring equitable distribution of resources, and improving the quality of education in West Muna Regency.
Implementasi Algoritma Naive Bayes untuk Sistem Pendukung Keputusan Penerima Bantuan Pendidikan Chandra Wisnu Nugroho; Sigrid Tamriesfatno; Sulkifli Sulkifli
Jurnal Publikasi Ilmu Komputer dan Multimedia Vol. 4 No. 1 (2025): Januari: Jurnal Publikasi Ilmu Komputer dan Multimedia
Publisher : Pusat Riset dan Inovasi Nasional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/jupikom.v4i1.4276

Abstract

Education plays a crucial role in shaping excellent human resources, which are the main foundation of national development. However, economic limitations remain a significant barrier for some students in accessing proper education. To address this issue, the government has implemented various educational assistance programs. SMKN 9 Bulukumba, as one of the vocational high schools, also faces challenges in selecting scholarship recipients efficiently, objectively, and transparently. This study aims to develop a decision support system based on the Naive Bayes Classifier algorithm to assist the selection process of educational aid recipients. Naive Bayes is a simple yet effective probabilistic classification algorithm that performs well on small to medium-sized datasets. This research employs a data mining approach to build a classification model based on several attributes, such as type of residence, means of transportation, and parents’ income. The results of testing on 10 student data samples showed that 6 students were classified as eligible for assistance, while 4 were not. The dominant factors determining eligibility were the low income of the father and the absence of income from the mother. Interestingly, all students using public transportation were not classified as aid recipients, indicating that transportation is not always a primary indicator of eligibility. Keywords: Education, Data Mining, Naive Bayes, Classification
Perancangan Sistem Keamanan Pintu Toko Berbasis Internet Of Things (Studi Kasus : Toko Chantika Shoes) Alman Arapa; Sigrid Tamriesfatno; Sarliadin Sarliadin; Sarwono Sarwono; Ahmad Musawir
Jurnal Publikasi Ilmu Komputer dan Multimedia Vol. 5 No. 1 (2026): Januari: Jurnal Publikasi Ilmu Komputer dan Multimedia
Publisher : Pusat Riset dan Inovasi Nasional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/jupikom.v5i1.6589

Abstract

Door security is a vital aspect in ensuring safety and protecting assets, particularly in commercial buildings such as retail stores that are vulnerable to unauthorized access outside operating hours. Along with the rapid advancement of digital technology, security systems are required to go beyond conventional mechanisms by providing remote monitoring and control capabilities. This study aims to design an Internet of Things (IoT)–based door security system as a solution to enhance security at Chantika Shoes Store. The research adopts a system design method that includes requirements analysis, hardware design, software design, and system workflow development. The proposed system utilizes IoT devices and sensors to detect door activity and transmit real-time information to users via an internet network. Through the integration of hardware and software components, the system enables continuous monitoring of door conditions, instant notification delivery in the event of unauthorized access, and remote control of the door locking mechanism using a mobile application. This approach allows store owners to respond quickly to potential security threats and improves efficiency compared to conventional security systems. The designed system is expected to serve as a reference for developing more effective and efficient IoT-based door security solutions that meet the security requirements of retail businesses in the modern technological era
Penerapan Algoritma C4.5 dalam Memprediksi Minat Siswa SMKS Unggulan Wakatobi untuk Melanjutkan Pendidikan Tinggi Tamriesfatno, Sigrid; Muhammad Ikhwan Mardin; La Ode Muh. Armadi. AM; M. Noor Fuad; Muhammad As'ad
Jurnal Publikasi Ilmu Komputer dan Multimedia Vol. 4 No. 1 (2025): Januari: Jurnal Publikasi Ilmu Komputer dan Multimedia
Publisher : Pusat Riset dan Inovasi Nasional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/jupikom.v4i1.6776

Abstract

Minat siswa Sekolah Menengah Kejuruan (SMK) untuk melanjutkan pendidikan ke jenjang perguruan tinggi dipengaruhi oleh berbagai faktor kompleks, mulai dari kondisi ekonomi hingga latar belakang personal. Penelitian ini bertujuan untuk memprediksi minat siswa SMKS Unggulan Wakatobi dalam melanjutkan pendidikan tinggi guna memberikan dasar evaluasi bagi pihak sekolah dalam menyusun strategi bimbingan konseling. Metode yang digunakan dalam penelitian ini adalah Data Mining dengan menerapkan algoritma C4.5 untuk membentuk pohon keputusan (decision tree) sebagai model klasifikasi. Data yang dianalisis mencakup variabel kemampuan ekonomi orang tua dan jenis kelamin siswa. Hasil penelitian menunjukkan bahwa algoritma C4.5 berhasil memetakan pola minat siswa, di mana faktor kemampuan ekonomi orang tua menjadi atribut akar (root node) atau penentu utama. Temuan spesifik menunjukkan bahwa siswa dengan kemampuan ekonomi rendah justru memiliki kecenderungan tinggi untuk melanjutkan pendidikan. Sementara pada kategori ekonomi sedang dan tinggi, jenis kelamin menjadi faktor penentu akhir, di mana siswa perempuan cenderung berminat melanjutkan studi, sedangkan siswa laki-laki cenderung tidak. Model ini diharapkan dapat menjadi instrumen bagi SMKS Unggulan Wakatobi dalam meningkatkan angka lulusan yang menempuh pendidikan tinggi demi penguatan kualitas sumber daya manusia di daerah Wakatobi.
Co-Authors - Sri Prilmayanti Awaluddin, - Adijah S, Andi Adijah S ahmad musawir Alman Arapa Andi Ummul Khair Chandra Wisnu Nugroho Husna Saleh La Ode Muh. Armadi AM La Ode Muh. Armadi. AM M. Noor Fuad Muhamad Irwin Syawal Muhammad As'ad Muhammad Ikhwan Mardin Muhammad Ikhwan Mardin Paula Eka Wijaya Riska Kherani Sarliadin Sarliadin Sarni Alex Sandra Sarwono Sarwono Sulkifli Sulkifli