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All Journal Jurnal Tekinkom (Teknik Informasi dan Komputer) Jurnal Minfo Polgan (JMP) Jurnal Sistem Informasi Triguna Dharma (JURSI TGD) Journal of Computer Science and Research
Syahputri, Maulisa
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Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Library & Information Science Mathematics Social Sciences

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ANALISIS BUSINESS INTELEGENSI PENGARUH KECERDASAN EMOSIONAL TERHADAP KINERJA KARYAWAN ALGORITMA REGRESI LINIER Sitorus, Zulham; Syahputri, Maulisa; Nainggolan, Andreas Ghanneson; Sibarani, Dina Marsauli; Nahampun, Natalia; Putra, Khairil
Jurnal Tekinkom (Teknik Informasi dan Komputer) Vol 7 No 2 (2024)
Publisher : Politeknik Bisnis Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37600/tekinkom.v7i2.1215

Abstract

Prima Indonesia University is a leading private university in the city of Medan, operating in the education sector which applies Business Intelligence to its management system. This research was conducted using the Linear Regression Algorithm to measure the influence of Emotional Intelligence on Employee Performance at Prima Indonesia University, totaling 212 data. The data used in this research is employee performance history data for the last 5 years. Next, the Linear Regression Algorithm is applied to the processed dataset. The research results will later show that the Linear Regression Algorithm is able to produce quite accurate measurements. The results of this research can show how much emotional intelligence influences an employee's performance. Thus, the Linear Regression Algorithm can be a solution in evaluating the influence of Emotional Intelligence on Employee Performance, and can provide long-term recommendations for increasing the productivity of Employee Performance at Prima Indonesia University.
Classification Of Pistachio Varieties Using Machine Learning Algorithms Siahaan, Andysah Putera Utama; Iqbal, Muhammad; Dika, Dika; Syahputri, Maulisa
Jurnal Minfo Polgan Vol. 14 No. 1 (2025): Artikel Penelitian
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/jmp.v14i1.15088

Abstract

The accurate classification of pistachio varieties plays a crucial role in ensuring quality control, enhancing traceability, and improving market segmentation in the agricultural sector. This study explores the application of various machine learning algorithms—including Decision Tree, Random Forest, XGBoost, Support Vector Classifier (SVC), k-Nearest Neighbors (KNN), and Logistic Regression—for the classification of pistachio types based on morphological features. A publicly available dataset containing measurements such as kernel length, shell width, and aspect ratio was used to train and evaluate the models. The results demonstrated that ensemble methods like XGBoost and Random Forest consistently outperformed other algorithms, achieving accuracy scores of 0.86 and 0.85, respectively, with high Area Under the Curve (AUC) values in the Receiver Operating Characteristic (ROC) analysis. Furthermore, hyperparameter tuning improved model performance across the board. These findings indicate the potential of machine learning as a reliable tool for automating pistachio variety classification and supporting decision-making in agricultural practices. Future research may involve real-time classification using image-based features and integration into precision agriculture systems.
Analisis Algoritma Certainty Factor dalam Menentukan Pembagian Warisan Hukum Perdata Menggunakan Metode RDR Muhammad Syahputra Novelan; Syahputri, Maulisa; Rido Favorit Saronitehe Waruwu; Sella Monika Br Tarigan; Heri Eko Rahmadi Putra
Jurnal Sistem Informasi Triguna Dharma (JURSI TGD) Vol. 4 No. 4 (2025): EDISI JULI 2025
Publisher : STMIK Triguna Dharma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53513/jursi.v4i4.11482

Abstract

Dalam surah Al-Jasiyah ayat 18 dijelaskan mengenai prosedur atau hukum yang telah ditetapkan Allah bagi hamba-Nya untuk diikuti, baik yang berkaitan dengan aqidah, ibadah, akhlak, maupun muamalah. Di antara hukum yang harus dipenuhi adalah hukum waris. Warisan dikenal dengan istilah ‘faraid’, yaitu bentuk peraturan yang mengatur pemindahan hak milik seseorang yang telah meninggal kepada ahli warisnya agar dapat digunakan untuk meningkatkan kesejahteraan dan mengubah kehidupan mereka yang ditinggalkan. Dalam proses pembagian warisan juga menggunakan perhitungan yang akurat dan adil guna menghindari potensi konflik di antara ahli waris. Selain hukum waris Islam, terdapat pula hukum waris yang diadopsi dari negara-negara Barat, yaitu hukum waris sipil. Hukum perdata menjelaskan bagian-bagian yang diperoleh berdasarkan pembagian kelompok. Dari penelitian yang dilakukan menggunakan algoritma Certainty Factor (CF) dan metode Ripple Down Rules untuk mendapatkan pembagian warisan kelompok pertama dengan nilai CF sebesar 0,424.
The Best Caregiver at SOS Children’s Villages Using a Decision Support System Muhammad Iqbal; Syahputri, Maulisa
Journal of Computer Science and Research (JoCoSiR) Vol. 3 No. 1 (2025): Jan: Computer Science
Publisher : Asosiasi Perguruan Tinggi Informatika dan Ilmu Komputer (APTIKOM) Provinsi Sumatera Utara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.65126/jocosir.v3i1.67

Abstract

This study focuses on the development and implementation of a Decision Support System (DSS) designed to determine the best caregiver at SOS Children’s Villages. The main objective is to enhance efficiency and objectivity in the decision-making process related to caregiver performance evaluation. The research methodology includes collecting caregiver performance data, analyzing organizational needs, and applying an appropriate decision-making model. The DSS developed in this study utilizes Artificial Intelligence (AI) techniques to process and analyze performance data, generate performance scores, and identify the best caregiver based on predetermined criteria. The results show that the implementation of the DSS improves the objectivity of performance evaluations and provides significant support in the decision-making process. With this system, the organization is expected to better identify and optimize the potential of each caregiver, thereby increasing productivity and strengthening the competitiveness of SOS Children’s Villages in Medan. The collected data is processed and evaluated using the Simple Additive Weighting (SAW) method. The results are presented in the form of rankings and scores for each caregiver, facilitating a more accurate and transparent decision-making process. This study is expected to contribute positively to improving the efficiency and effectiveness of human resource management at SOS Children’s Villages.
Co-Authors Andysah Putera Utama Siahaan Dika, Dika Heri Eko Rahmadi Putra Muhammad Iqbal Muhammad Iqbal Muhammad Syahputra Novelan Nahampun, Natalia Nainggolan, Andreas Ghanneson Putra, Khairil Rido Favorit Saronitehe Waruwu Sella Monika Br Tarigan Sibarani, Dina Marsauli Sitorus, Zulham