Application of Data Mining to Determine the Performance of Family Planning Field Officers (PLKB) Using the C4.5 Algorithm

Perdinal Nasution; Mulkan Azhari

doi:10.56211/hanif.v3i1.52

Authors

Perdinal Nasution Universitas Muhammadiyah Sumatera Utara
Mulkan Azhari Universitas Muhammadiyah Sumatera Utara

DOI:

https://doi.org/10.56211/hanif.v3i1.52

Keywords:

Data Mining; C4.5 Algorithm; PLKB Performance (Family Planning Field Officers); Performance Evaluation

Abstract

The effectiveness of family planning programs is closely related to the performance of Family Planning Field Officers (PLKB). Conventional performance evaluation methods often rely on manual assessments, which may lead to subjectivity and inconsistency. To overcome this issue, data mining techniques can be applied to analyze performance data systematically and objectively. This study employs the C4.5 decision tree algorithm to classify and evaluate the performance of PLKB. The dataset used in this research includes several indicators, such as service coverage, counseling frequency, reporting accuracy, and community participation. Prior to model construction, data preprocessing was performed to handle missing values and normalize attributes. The model performance was evaluated using accuracy, precision, recall, and F-measure. The findings indicate that the C4.5 algorithm successfully classified PLKB performance into three categories: high, medium, and low. The model achieved an accuracy of [insert % if available], demonstrating its effectiveness in identifying key determinants of officer performance. Moreover, the decision tree generated interpretable rules that highlight the most influential attributes affecting PLKB performance. The application of data mining using the C4.5 algorithm provides an objective and efficient method for evaluating PLKB performance. This approach not only enhances decision-making for supervision and training but also contributes to the improvement of family planning program implementation. Future research is suggested to compare the C4.5 algorithm with other classification methods to achieve higher accuracy and generalizability.

Downloads

Download data is not yet available.

References

Buku

Indah Purnama Sari. Algoritma dan Pemrograman. Medan: UMSU Press, 2023, pp. 290.

Indah Purnama Sari. Buku Ajar Pemrograman Internet Dasar. Medan: UMSU Press, 2022, pp. 300.

Indah Purnama Sari. Buku Ajar Rekayasa Perangkat Lunak. Medan: UMSU Press, 2021, pp. 228.

Janner Simarmata Arsan Kumala Jaya, Syarifah Fitrah Ramadhani, Niel Ananto, Abdul Karim, Betrisandi, Muhammad Ilham Alhari, Cucut Susanto, Suardinata, Indah Purnama Sari, Edson Yahuda Putra. Komputer dan Masyarakat. Medan: Yayasan Kita Menulis, 2024, pp.162.

Mahdianta Pandia, Indah Purnama Sari, Alexander Wirapraja Fergie Joanda Kaunang, Syarifah Fitrah Ramadhani Stenly Richard Pungus, Sudirman, Suardinata Jimmy Herawan Moedjahedy, Elly Warni, Debby Erce Sondakh. Pengantar Bahasa Pemrograman Python. Medan : Yayasan Kita Menulis, 2024, pp.180

Zelvi Gustiana Arif Dwinanto, Indah Purnama Sari, Janner Simarmata Mahdianta Pandia, Supriadi Syam, Semmy Wellem Taju Fitrah Eka Susilawati, Asmah Akhriana, Rolly Junius Lontaan Fergie Joanda Kaunang. Perkembangan Teknologi Informatika. Medan: Yayasan Kita Menulis, 2024, pp.158

Jurnal

Londa, G. O., Witi, F. L., & Bhae, B. Y. (2022). Sistem Informasi Pendataan Penduduk Desa Detusoko Barat Kecamatan Detusoko Kabupaten Ende Berbasis Web. JURNAL JITEK, II(2). DOI: https://doi.org/10.55606/jitek.v2i2.211

Alghifari, F., & Juardi, D. (2021). Penerapan Data Mining Pada Penjualan Makanan Dan Minuman Menggunakan Metode Algoritma Naïve BayesData Preprocessing. JURNAL ILMIAH INFORMATIKA, 75-81. DOI: https://doi.org/10.33884/jif.v9i02.3755

Amna, S, W., Sudipa, I. I., E. Putra, T. A., Wahidin, A. J., Syukrilla, W. A., . . . Santoso, L. W. (2023). DATA MINING. Sumatera Barat: PT GLOBAL EKSEKUTIF TEKNOLOGI.

Andarista, R. R., & Jananto, A. (2022). Penerapan Data Mining Algoritma C4.5 Untuk Klasifikasi Hasil Pengujian Kendaraan Bermotor. Jurnal TEKNO KOMPAK, XVI(2), 29-43. DOI: https://doi.org/10.33365/jtk.v16i2.1525

Astuti, I. P. (2019). Algoritma Apriori Untuk Menemukan Hubungan Antara Jurusan Sekolah Dengan Tingkat Kelulusan Mahasiswa. JURNAL TEKNIK INFORMATIKA, 69-78. DOI: https://doi.org/10.15408/jti.v12i1.10525

Bachtiar, L., & Mahradianur. (2023). Analisis Data Mining Menggunakan Metode Algoritma C4.5 Menentukan Penerima Bantuan Langsung Tunai. JURNAL INFORMATIKA, X(1), 28-36. DOI: https://doi.org/10.31294/inf.v10i1.15115

Budiman, I., Saori, S., Anwar, R. N., Fitriani, & Yuga, M. (2021). Analisis Pengendalian Mutu Di Bidang Industri Makanan (Studi Kasus: UMKM Mochi Kaswari Lampion Kota Sukabumi). Jurnal Inovasi Penelitian, X(1).

Hidayah, A. Z., & Rozi, A. F. (2021). Penerapan Data Mining Dalam Menentukan Kinerja Karyawan Terbaik Dengan Menggunakan Metode Algoritma C4.5 ( Studi Kasus : Universitas Mercu Buana Yogyakarta ). JURNAL INFORMATION SYSTEM & ARTIFICIAL INTELLIGENCE, I(2), 117-127.

Juni Arta, I. K., Indrawan, G., & Dantes, G. R. (2019). Data Mining Rekomendasi Calon Mahasiswa Berprestasi Di STMIK Denpasar Menggunakan Metode Technique For Others Reference By Similarity To Ideal Solution. Jurnal Ilmu Komputer Indonesia (JIKI), 11-21.

Sari, I.P., Hariani, P.P., Al-Khowarizmi, A., Ramadhani, F., Sulaiman, O.K., Satria, A, & Manurung, A.A. (2024). CLUSTERING HIV/AIDS DISEASE USING K-MEANS CLUSTERING ALGORITHM. Proceeding International Seminar on Islamic Studies 5 (1), 1668-1676

Mardi, Y. (2019). Data Mining : Klasifikasi Menggunakan Algoritma C4.5. Data Mining : Klasifikasi Menggunakan Algoritma C4.5, 213-219. DOI: https://doi.org/10.22202/ei.2016.v2i2.1465

Sari, I.P., Ramadhani, F., Satria, A., & Sulaiman, O.K. Leukocoria Identification: A 5-Fold Cross Validation CNN and Adaboost Hybrid Approach. 2023 6th International Seminar on Research of Information Technology and Intelligent Systems (ISRITI), 486-491 DOI: https://doi.org/10.1109/ISRITI60336.2023.10467242

Manurung, A.A., Nasution, M.D., & Sari, I.P. (2023). Implementation of Fuzzy K-Nearest Neighbor Method in Dengue Disease Classification. 2023 11th International Conference on Cyber and IT Service Management (CITSM), 1-4 DOI: https://doi.org/10.1109/CITSM60085.2023.10455306

Sari, I.P., Ramadhani, F., Satria, A., & Apdilah, D. (2023). Implementasi Pengolahan Citra Digital dalam Pengenalan Wajah menggunakan Algoritma PCA dan Viola Jones. Hello World Jurnal Ilmu Komputer 2 (3), 146-157 DOI: https://doi.org/10.56211/helloworld.v2i3.346

Sari, I.P., Al-Khowarizmi, A, Sulaiman, O.K., & Apdilah, D. (2023). Implementation of Data Classification Using K-Means Algorithm in Clustering Stunting Cases. Journal of Computer Science, Information Technology and Telecommunication Engineering 4 (2), 402-412 DOI: https://doi.org/10.30596/jcositte.v4i2.15765

Sulaiman, O.K & Batubara, I.H. (2021). Implementation Data Mining For Level Analysis Traffic Violation By Algorithm Association Rule. Al'adzkiya International of Computer Science and Information Technology (AIoCSIT) Journal 2 (2), 128-135

Sari, I.P., Batubara, I.H., & Al-Khowarizmi, A. (2021). Sensitivity Of Obtaining Errors In The Combination Of Fuzzy And Neural Networks For Conducting Student Assessment On E-Learning. International Journal of Economic, Technology and Social Sciences (Injects) 2 (1), 331-338 DOI: https://doi.org/10.53695/injects.v2i1.412

Sari, I.P., Al-Khowarizmi, A., & Batubara, I.H. (2021). Cluster Analysis Using K-Means Algorithm and Fuzzy C-Means Clustering For Grouping Students' Abilities In Online Learning Process. Journal of Computer Science, Information Technology and Telecommunication Engineering 2 (1), 139-144

Apdilah, D., & Sari, I.P. (2021). Optimization Of The Fuzzy C-Means Cluster Center For Credit Data Grouping Using Genetic Algorithms. Al'adzkiya International of Computer Science and Information Technology (AIoCSIT) Journal 2 (2), 156-163