Penerapan Vector Space Model Dalam Klasifikasi Penilaian Thematic Appeception Test

Usman Nurhasan(1*), Rakhmat Arianto(2), Alwan Ghozi Kurnia(3),

(1) Jurusan Teknologi Informasi, Politeknik Negeri Malang
(2) Jurusan Teknologi Informasi, Politeknik Negeri Malang
(3) Jurusan Teknologi Informasi, Politeknik Negeri Malang
(*) Corresponding Author

Abstract


Psychology is the study of human mental behavior and functions scientifically. In practice, a person's personality can be assessed from psychological tests. One of the psychological tests is the Thematic Apperception Test (TAT). TAT Test is a projective psychological test consisting of various themes presented in the form of an image which is then projected accordingly with the response. The purpose of the TAT is to reveal the dynamics of the subject's personality in the form of encouragement, sediment, complex, and various dominant conflicts. Thematic Apperception Test still uses a card and tape recorder to record Testee's voice. Calculation of results or assessments is still done manually. Errors in the assessment will affect the results, so we need an intelligent information system using the vector space model method based on experience in the field of psychology. A web-based system which can provide personality test results and information about the Thematic Apperception Test. From the test results using 10 stories, it was found that the average precission value was 72.7%, the average recall value was 86.7%, and the average f-measure value was 78.3%.

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References


C. Suwartono, “Alat Tes Psikologi Konteks Indonesia: Tantangan Psikologi di Era MEA,” J. Psikol. Ulayat, vol. 3, no. 1, p. 1, 2017, doi: 10.24854/jpu12016-51.

Kemkes, “Pentingnya Peran Keluarga, Institusi dan Masyarakat Kendalikan Gangguan Kesehatan Jiwa,” 2019.

B. Z. Sulaiman, “Cognitive Behavior Therapy untuk Meningkatkan Perilaku Rutin Minum Obat pada Penderita Skizofrenia,” J. Univ. Muhammadiyah Malang, no. 2002, pp. 19–20, 2016.

R. Sitorus and H. S. Dachlan, “Analisis Pengharuh Frasa Pada Deteksi Emosi Dari Teks Menggunakan Vector Space Model,” vol. 11, no. 1, pp. 41–47, 2017.

Irmawati, “Sistem Temu Kembali Informasi Pada Dokumen Dengan Metode Vector Space Model,” J. Ilm. FIFO, vol. IX, no. 1, pp. 74–80, 2017.

A. Hendini, “Implementasi Vector Space Model Pada Sistem Pencarian Mesin Karaoke,” vol. 6, no. 1, pp. 1–6, 2018.

T. P. Laksono, A. F. Hidayatullah, and C. I. Ratnasari, “Speech to Text of Patient Complaints for Bahasa Indonesia,” Proc. 2018 Int. Conf. Asian Lang. Process. IALP 2018, pp. 79–84, 2019, doi: 10.1109/IALP.2018.8629161.

F. F. Zain and Y. Sibaroni, “Effectiveness of SVM Method by Naïve Bayes Weighting in Movie Review Classification,” Khazanah Inform. J. Ilmu Komput. dan Inform., vol. 5, no. 2, pp. 108–114, 2019, doi: 10.23917/khif.v5i2.7770.

D. H. Wahid and A. SN, “Peringkasan Sentimen Esktraktif di Twitter Menggunakan Hybrid TF-IDF dan Cosine Similarity,” IJCCS (Indonesian J. Comput. Cybern. Syst., vol. 10, no. 2, p. 207, 2016, doi: 10.22146/ijccs.16625.

H. Sujaini, “Performance of Methods in Identifying Similar Languages Based on String to Word Vector,” Khazanah Inform. J. Ilmu Komput. dan Inform., vol. 6, no. 1, pp. 9–14, 2020, doi: 10.23917/khif.v6i1.8199.

R. P. S. Putri and I. Waspada, “Penerapan Algoritma C4.5 pada Aplikasi Prediksi Kelulusan Mahasiswa Prodi Informatika,” Khazanah Inform. J. Ilmu Komput. dan Inform., vol. 4, no. 1, p. 1, 2018, doi: 10.23917/khif.v4i1.5975.

V. J. L. Engel, E. Joshua, and M. M. Engel, “Detection of Cyber Malware Attack Based on Network Traffic Features Using Neural Network,” Khazanah Inform. J. Ilmu Komput. dan Inform., vol. 6, no. 1, pp. 26–32, 2020, doi: 10.23917/khif.v6i1.8869.




DOI: http://dx.doi.org/10.30645/j-sakti.v5i2.356

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