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All Journal Buletin Poltanesa Jurnal Pengabdian Masyarakat Bidang Sosial dan Humaniora
Ulfah Nurfadhila
STMIK Widya Cipta Dharma
Agriculture, Biological Sciences & Forestry Computer Science & IT Education Social Sciences

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Digitalisasi Pencatatan Keuangan melalui Pendampingan Aplikasi Money Tracker pada Toko Hawaii Aisyah Fajriantini; Muhamad Amir Ariandi; Ulfah Nurfadhila; Vilianty Rafida
ABDISOSHUM: Jurnal Pengabdian Masyarakat Bidang Sosial dan Humaniora Vol. 5 No. 2 (2026): Juni 2026
Publisher : Yayasan Literasi Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55123/abdisoshum.v5i2.8267

Abstract

This community service activity aims to improve financial literacy and the independence of the manager of Toko Hawaii Alat Jahit Samarinda in conducting digital business financial recording. The main problems faced by the partner include irregular and unstructured recording of income and expenses, as well as the potential mixing of personal and business finances. The activity was carried out using a participatory training approach through initial observation, interviews, financial management education, mentoring in the use of Money Tracker, transaction recording practice, and evaluation of the partner’s ability. Changes were measured using a structured observation sheet with indicators covering understanding of financial recording, income recording, expense recording, transaction categorization, separation of personal and business finances, and the ability to read financial summaries. The results show that the partner began to understand the importance of transaction recording as a basis for business control, started to develop the habit of recording income and expenses, and became more aware of the importance of separating business and personal finances. This activity indicates that MSME financial digitalization requires not only an application but also personal mentoring that can align technology with the partner’s habits and needs.
Classification of Employee Performance Using the K-Nearest Neighbors Method Based on Attendance Data Satria Rodrigo Jody Rosevelt Lumban Tobing; Amelia Yusnita; Ulfah Nurfadhila
Poltanesa Vol 27 No 1 (2026): June 2026
Publisher : P3KM Politeknik Pertanian Negeri Samarinda

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51967/tanesa.v27i1.3783

Abstract

Employee performance assessment is a strategic function in human resource management. However, many companies, including PT. Wijaya Manggala Premier Lestari, still conduct manual evaluations based on limited indicators such as total working days. This study aims to classify employee performance using the K-Nearest Neighbors algorithm based on attendance data from the Mekari Talenta platform. The primary dataset consisted of one hundred twenty two employee records from March 2026, with attendance data from the three preceding months (December 2025 to February 2026) used to verify the consistency of individual attendance patterns. The methodology followed the Cross-Industry Standard Process for Data Mining framework. Eight numerical features were extracted from attendance codes: total small late, total big late, total paid leave, total absence, total unpaid leave, total working day deductions, total working days, and attendance percentage. The K-Nearest Neighbors model was evaluated using five fold stratified cross-validation with K values of 3, 5, and 7. The model with K = 5 achieved the highest performance among the tested K values, with an average accuracy of 89%, precision of 91%, recall of 88%, and F1 score of 89% across all five folds. The confusion matrix confirmed that the model effectively distinguishes between good and poor performers. This research provides a practical, automated classification framework that transforms raw attendance logs into objective performance insights using the Java programming language.
Co-Authors Aisyah Fajriantini Amelia Yusnita Muhamad Amir Ariandi Satria Rodrigo Jody Rosevelt Lumban Tobing