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Predicting Graduation Outcomes: Decision Tree Model Enhanced with Genetic Algorithm Rukiastiandari, Sinta; Rohimah, Luthfia; Aprillia, Aprillia; Mutia, Fara
Paradigma - Jurnal Komputer dan Informatika Vol. 26 No. 1 (2024): March 2024 Period
Publisher : LPPM Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/p.v26i1.3165

This research aims to improve the accuracy of predicting student permit results in the digital era by utilizing machine learning techniques. The main focus is the use of a Decision Tree (DT) model optimized with a Genetic Algorithm (GA) to overcome the limitations of accuracy and testing of conventional methods. This research began with collecting student academic data, followed by preprocessing to eliminate incompleteness and organize the data format. The DT model is then built and optimized with GA, which is inspired by biological evolutionary processes to improve feature selection and parameter tuning. The results show a significant increase in prediction accuracy, from 86.19% to 87.68%, and an increase in the Area Under Curve (AUC) value from 0.755% to 0.788%. This research not only proves the effectiveness of GA integration in improving DT models, but also paves the way for the application of evolutionary techniques in educational data analysis and other fields. The main contributions of this research include the development of more accurate prediction models and practical applications in educational contexts, with the hope of assisting educational institutions in making more informed decisions for their students.

Model Hibrida K-Nearest Neighbors Berbasis Genethic Algorithm untuk Prediksi Penyakit Ginjal Kronis Rukiastiandari, Sinta; Rohimah, Luthfia; Aprillia, Aprillia; Chodidjah, Chodidjah; Mutia, Fara
Infotek: Jurnal Informatika dan Teknologi Vol. 8 No. 1 (2025): Infotek : Jurnal Informatika dan Teknologi
Publisher : Fakultas Teknik Universitas Hamzanwadi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29408/jit.v8i1.27918

Chronic Kidney Disease, which is often abbreviated as PGK, is a serious disease that is of major concern to society and the medical world. This disease can cause various serious complications if not treated properly and early. Therefore, accurate prediction of CKD is very important to support early intervention that can slow disease progression, prevent further complications, and increase the patient's chances of recovery. This research aims to increase the accuracy of PGK predictions by developing a hybrid model that combines the K-Nearest Neighbors (KNN) algorithm with optimization using the Genetic Algorithm (GA). In this approach, the KNN algorithm is used to build a prediction model, while GA acts as an optimization tool that improves model performance. The effectiveness of the optimized model is evaluated using key metrics such as accuracy, precision, recall, and area under the curve (AUC). The results show a significant increase in performance, with accuracy increasing by 17.75%, precision increasing by 23.84%, and recall increasing by 5.34%. This research makes an important contribution to the development of data mining technology for clinical applications and opens up opportunities for further improvements in the future in increasing the prediction accuracy of chronic diseases such as CKD

PERSIAPAN PEMERINTAH INDONESIA DALAM MENGHADAPI EMBARGO KELAPA SAWIT SEBAGAI DAMPAK PENERAPAN EUROPEAN UNION DEFORESTATION FREE REGULATION (EUDR) Mutia, Fara; Sutiarnoto, Sutiarnoto; Emia Tarigan, Vita Cita
Sriwijaya Journal of Private Law Volume 1, No.2 : Oktober 2024
Publisher : Fakultas Hukum Universitas Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28946/sjpl.v1i2.3976

Isu deforestasi ini mendapat sorotan dari Uni Eropa yang kemudian mengeluarkan kebijakan European Union Deforestation Free Regulation (EUDR) yang mengakibatkan embargo kelapa sawit yang teridentifikasi deforestasi hutan. European Union Deforestation Free Regulation (EUDR) merupakan salah satu upaya dari Uni Eropa dalam mengatasi isu deforestasi hutan. Penerapan EUDR ini mengakibatkan terjadinya embargo terhadap beberapa komoditas yang berpotensi dihasilkan melalui deforestasi hutan. Dengan mengurangi atau menghentikan konsumsi komoditas atau produk yang terkait dengan deforestasi, diharapkan dapat mengurangi dampak negatif terhadap lingkungan, keanekaragaman hayati, dan perubahan iklim. Sebagai salah satu negara produsen kelapa sawit, Indonesia berpotensi mengalami embargo kelapa sawit sebagai dampak penerapan EUDR. Untuk itu, apabila Indonesia mengekspor kelapa sawit ke Uni Eropa, maka harus melewati proses uji tuntas sebagaimana yang telah diatur dalam Pasal (3) Regulation (EU) 2023/1115 of European Union Deforestation Free Regulation (EUDR). Dalam menghadapi EUDR, Pemerintah Indonesia mengeluarkan kebijakan berupa peningkatan sistem ISPO (Indonesian Sustainable Palm Oil).

PERAN KOMITE SEKOLAH DALAM PENGAMBILAN KEBIJAKAN DI SD NEGERI 5 BANDA ACEH Mutia, Fara; Hambali, Hambali; Isa, Muhammad
Jurnal Tunas Bangsa Vol 12 No 1 (2025)
Publisher : Program Studi Pendidikan Guru Sekolah Dasar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46244/tunasbangsa.v12i1.2926

Peran dan fungsi komite sekolah di SD Negeri 5 Banda Aceh masih memiliki kekurangan, terutama dalam pengambilan kebijakan. Penelitian ini bertujuan untuk menganalisis keterlibatan komite sekolah dalam proses pengambilan keputusan dengan pendekatan kualitatif deskriptif. Subjek penelitian mencakup komite sekolah, kepala sekolah, dan 19 guru, dengan teknik pengumpulan data melalui wawancara dan angket, serta analisis menggunakan metode Miles dan Huberman. Hasil penelitian menunjukkan bahwa komite sekolah tidak selalu dilibatkan dalam penentuan kebijakan karena berbagai kendala. Namun, komite tetap berperan penting dalam meningkatkan mutu pendidikan melalui komunikasi, pemantauan, dan pemberian masukan strategis. Dukungan komite terhadap pelaksanaan Kurikulum Merdeka serta kolaborasinya dengan kepala sekolah terbukti meningkatkan kualitas pendidikan, dengan hasil angket menunjukkan skor sangat baik (92,10%). Meskipun keterlibatan komite tidak selalu konsisten, sinergi antara komite sekolah, kepala sekolah, dan Dinas Pendidikan Kota Banda Aceh terbukti efektif dalam mewujudkan tujuan pendidikan yang berkualitas.AbstractThe role and function of the school committee at SD Negeri 5 Banda Aceh still have shortcomings, particularly in policymaking. This study aims to analyze the involvement of the school committee in decision-making processes using a descriptive qualitative approach. The research subjects include the school committee, the principal, and 19 teachers, with data collected through interviews and questionnaires and analyzed using the Miles and Huberman method. The findings indicate that the school committee is not always involved in policy determination due to various constraints. However, the committee still plays a crucial role in improving education quality through communication, monitoring, and providing strategic input. The committee’s support for the implementation of the Kurikulum Merdeka and its collaboration with the principal have proven to enhance education quality, with questionnaire results showing an excellent score (92.10%). Although the committee's involvement is not always consistent, the synergy between the school committee, the principal, and the Banda Aceh City Education Office has been effective in achieving quality education goals.

Predicting Graduation Outcomes: Decision Tree Model Enhanced with Genetic Algorithm Rukiastiandari, Sinta; Rohimah, Luthfia; Aprillia, Aprillia; Mutia, Fara
Paradigma - Jurnal Komputer dan Informatika Vol. 26 No. 1 (2024): March 2024 Period
Publisher : LPPM Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/p.v26i1.3165

This research aims to improve the accuracy of predicting student permit results in the digital era by utilizing machine learning techniques. The main focus is the use of a Decision Tree (DT) model optimized with a Genetic Algorithm (GA) to overcome the limitations of accuracy and testing of conventional methods. This research began with collecting student academic data, followed by preprocessing to eliminate incompleteness and organize the data format. The DT model is then built and optimized with GA, which is inspired by biological evolutionary processes to improve feature selection and parameter tuning. The results show a significant increase in prediction accuracy, from 86.19% to 87.68%, and an increase in the Area Under Curve (AUC) value from 0.755% to 0.788%. This research not only proves the effectiveness of GA integration in improving DT models, but also paves the way for the application of evolutionary techniques in educational data analysis and other fields. The main contributions of this research include the development of more accurate prediction models and practical applications in educational contexts, with the hope of assisting educational institutions in making more informed decisions for their students.

PREDIKSI STATUS AKADEMIK MAHASISWA BERDASARKAN DATA PEMBAYARAN DENGAN NAIVE BAYES DAN PARTICLE SWARM OPTIMIZATION Rukiastiandari, Sinta; Rohimah, Luthfia; Mutia, Fara; Aprillia; Chodidjah, Chodidjah
Jurnal Informatika dan Rekayasa Elektronik Vol. 8 No. 2 (2025): JIRE November 2025
Publisher : LPPM STMIK Lombok

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36595/jire.v8i2.1756

Pendidikan tinggi di Indonesia menghadapi tantangan dalam pengelolaan pembayaran mahasiswa, di mana keterlambatan dapat berdampak pada status akademik, termasuk risiko cuti atau pengunduran diri. Penelitian ini bertujuan mengembangkan model prediksi status akademik berbasis data pembayaran kuliah dengan metode Naive Bayes (NB) yang dioptimasi menggunakan Particle Swarm Optimization (PSO). Dataset berjumlah 15.697 record mahasiswa yang telah melalui pra-pemrosesan, termasuk penanganan nilai hilang dan pengkodean atribut kategorikal. Hasil menunjukkan bahwa model NB menghasilkan akurasi 98,83%, precision 98,21%, recall 65,09%, dan AUC 0,905. Optimasi dengan PSO meningkatkan recall menjadi 65,13% dan AUC menjadi 0,907, sementara akurasi dan precision tetap stabil. Analisis fitur mengindikasikan bahwa Jenis Kelamin, Jurusan SLTA, dan Kuliah Sambil Bekerja merupakan atribut paling berpengaruh, sedangkan Pekerjaan Ayah relatif kurang signifikan. Temuan ini menegaskan potensi NB-PSO sebagai pendekatan prediktif untuk mendukung pengelolaan administrasi akademik yang lebih efektif.

Enhancing Employee Engagement Through Strategic Human Resource Management in Economics and Management Education Herawaty, Mety Titin; Aprillia; Mutia, Fara; Asmadi, Iwan; Gampu, Seska
Jurnal Sains Sosio Humaniora Vol. 9 No. 2 (2025): Volume 9, Nomor 2 Desember 2025 (In Progress)
Publisher : LPPM Universitas Jambi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22437/jssh.v9i2.50495

This study explores how SHRM enhances employee engagement in higher education, particularly within economics and management education. Using a qualitative library research design and thematic content analysis, the study reviewed scholarly sources published between 2014 and 2024. Literature selection followed explicit inclusion–exclusion criteria, incorporating academic works addressing SHRM, employee engagement, leadership, organizational culture, or HRM in higher education, while excluding non-scholarly publications and studies lacking methodological clarity. The findings show that SHRM strengthens engagement when aligned with institutional strategy, supported by transformational leadership, and embedded within a participatory organizational culture. Four clusters of HR practices competency-based planning, continuous professional development, performance-based rewards, and participatory performance management emerge as key drivers of engagement through their effects on motivation and organizational commitment. Based on these insights, the study proposes a conceptual model explaining how SHRM enhances cognitive, emotional, and behavioral engagement, ultimately improving teaching performance, research productivity, and institutional competitiveness. The results contribute to the limited academic literature on SHRM in higher education and offer practical guidance for universities seeking to build integrated HR strategies. Future empirical research is recommended to validate the proposed model across diverse academic contexts.

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