MODELING OF LABOR MARKET DYNAMICS IN BALIKPAPAN USING THE LOGISTIC GROWTH MODEL
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Population growth and labor force dynamics become important issues in development planning, especially in the buffer zone of the National Capital City (IKN) such as Balikpapan City. This study aims to model the dynamics of labor market in Balikpapan City using Verhulst logistic growth model approach. The data used includes the number of labor force and non-labor force in the period of 2007 to 2023, obtained from the Central Bureau of Statistics of East Kalimantan Province. The modeling process is conducted independently to ensure analytical clarity between labor force and non-labor force groups to obtain a more accurate projection. The results of the analysis show that the average population of the labor force is 289,631 people with a growth rate of 7.17%, while the non-labor force has an average of 156,643 people with a growth rate of 4.44%. Model validation showed a coefficient of determination (R²) of 0.87 for the labor force and 0.88 for the non-labor force, indicating a good model fit. The difference in growth rate reflects the potential improvement of labor market condition in Balikpapan City. The findings of this study are expected to be a reference for the government and policy makers in formulating strategies for improving the quality of human resources and inclusive and sustainable employment planning in the buffer zone of IKN.
Pratiwi CD. Aplikasi Persamaan Diferensial Model Populasi Logistik Untuk Mengestimasi Penduduk Di Kota Balikpapan. AdMathEdu. 2021 Jan 19;10(1):63.
Widiarani S, Priana W, Wahed M. Analisis Sektor Unggulan Perekonomian Kota Balikpapan dan Kota Samarinda. JSA. 2021;2(5):951–63.
Goverment of the Republic of Indonesia. Law Number 3 of 2022 on the National Capital. State Gazette of the Republic of Indonesia; 2022.
Faelassuffa A, Yuliani E. Kajian Tingkat Partisipasi Angkatan Kerja Terhadap Indeks Pembangunan Manusia. JKR. 2022 Jan 18;1(1):49.
Wijaya A, Kasuma J, Tasenţe T, Caisar Darma D. Labor force and economic growth based on demographic pressures, happiness, and human development. JEECAR. 2021 Mar 8;8(1):40–50.
Puspasari S. Pengaruh Partisipasi Angkatan Kerja Terdidik Terhadap Pertumbuhan Ekonomi di Indonesia: Perspektif Modal Manusia. jia. 2019 Dec 28;16(2):194–209.
Soleh M, Sriningsih R. Model Mangsa-Pemangsa dengan Memperhatikan Faktor Internal dan Eksternal. SNTIKI. 2023;245–53.
Salwa SI, Shakira LA, Savitri D. Dinamika Model Mangsa-Pemangsa Lotka Volterra Dengan Adanya Kerja Sama Berburu Pada Pemangsa. Jurnal Riset dan Aplikasi Matematika. 7(2):195–205.
Kurniawan A, Holisin I, Kristanti F. Aplikasi Persamaan Deferensial Biasa Model Eksponensial Dan Logistik Pada Pertumbuhan Penduduk Kota Surabaya. Journal of Mathematics Education, Science and Technology. 2017;2(1):129–41.
Triambak S, Mahapatra DP, Mallick N, Sahoo R. A new logistic growth model applied to COVID-19 fatality data. Epidemics. 2021 Dec;37:100515.
Balakrishnan N. Handbook of the Logistic Distribution. 1st ed. CRC Press; 1991.
Purnama A, Hamidin D. Metode Algoritma Logistic Regression dalam Klasifikasi Email Spam. shift. 2025 Jan 30;5(1):39–47.
Gupta RD, Kundu D. Generalized Logistic Distributions. Journal of Applied Statistical Science. 2010;18(1):51.
Marbun BVS, Amiruddin MNK, Lestari F, Nur Padila W, Lestari L, Al Rasyid MuhH. Proyeksi pertumbuhan penduduk Sulawesi Tenggara dengan menggunakan model eksponensial dan model logistik. J Apl Fis. 2024;20(02):24–30.
Peleg M, Corradini MG, Normand MD. The logistic (Verhulst) model for sigmoid microbial growth curves revisited. Food Research International. 2007 Aug;40(7):808–18.
Karim R, Dey P, Rahman M, Saha SK, Hossain N, Ali MKM. A Study about Forecasting Bangladesh by Using Verhulst Logistic Growth Model and Population Model. 2022;26(1).
Welagedara WADM, Nawarathna LS, Nawarathna RD. Forecasting the Sri Lankan Population with the Gompertz and Verhulst Logistic Growth Models. Sri Lanka Jnl Econ Res. 2019 Dec 1;7(1):1–12.
Aprilia R, Siregar AR, Fernanda FH, Suhendra I, Siregar NS. Analisis Pertumbuhan Mendekati Kapasitas Terhadap Status Gizi Anak dengan Model Logistik. AKSIOMA. 2025 Jan 25;2(1):335–48.
Jain M, Bhati PK, Kataria P, Kumar R. Modelling Logistic Growth Model for COVID-19 Pandemic in India. In: 2020 5th International Conference on Communication and Electronics Systems (ICCES) [Internet]. COIMBATORE, India: IEEE; 2020. p. 784–9. Available from: https://ieeexplore.ieee.org/document/9138049/
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