Ahmad Mulia Ali, Basthoh (2015) Pemetaan Sebaran Mutu Pendidikan Dasar Menggunakan Metode Self-Organizing Maps. Masters thesis, Institut Teknologi Sepuluh Nopember.
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Abstract
Salah satu program percepatan pembangunan oleh pemerintah adalah
melakukan pemerataan dalam peningkatan mutu pendidikan disemua wilayah
NKRI. Salah satu tahapan dalam melakukan program tersebut adalah dengan
melakukan pemetaan mutu pendidikan melalui sekolah. Pemetaan mutu
pendidikan melalui sekolah diharapkan bisa memberi gambaran kondisi
dilapangan mutu pendidikan yang sebenarnya kepada penyelenggara pendidikan.
Dengan adanya pemetaan mutu pendidikan diharapkan bisa menghasilkan
evaluasi, kebijakan, dan rekomendasi, serta program perencanaan yang berguna
untuk peningkatan mutu pendidikan berikutnya. Saat ini pemetaan masih
menggunakan cara konvensional. Sehingga diperlukan metode yang dapat
mengolah data untuk melakukan pemetaan secara cepat, efektif dan efisien. Pada
penelitian ini mencoba menggunakan metode clustering Self-Organizing Maps
(SOM) untuk melakukan pengelompokan dan pemetaan dengan mengolah data
nilai mutu sekolah berdasarkan enam Standar Nasional Pendidikan. Data penilaian
yang digunakan adalah nilai standar kompetensi lulusan, nilai standar isi, nilai
standar proses, nilai standar penilaian, nilai standar pendidik dan tenaga
kependidikan, dan nilai standar pengelolaan. Proses pemetaan diawali dengan
penormalan data, kemudian data tersebut dijadikan sebagai input pada metode
yang digunakan. Hasil dari penelitian ini menunjukkan bahwa secara rata-rata
mutu pendidikan sekolah dasar ada di kategori sangat diharapkan Standar
Nasional Pendidikan karena dari 6 pengelompokan 5 pengelompokan unggul di
kategori mutu yang sangat diharapkan Standar Nasional Pendidikan. Sedangkan
mutu pendidikan kategori mutu memenui Standar Nasional Pendidikan ada di
parameter Standar Kompetensi Lulusan. Dari hasil pengujian analisa clustering
dengan menggunakan validitas Davies-Bouldin Index (DBI) diperoleh informasi
bahwa clustering pada pengujian 6 variabel Standar Nasional Pendidikan sudah
bagus.
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One of the accelerated development program by the government is doing
equalization in improving the quality of education in all the Homeland. One of the
stages in the conduct of the program is to do with the quality of education through
school mapping. Mapping the quality of education through the school is expected
to give a picture of the actual field of education quality to education providers.
With the mapping of the quality of education is expected to produce an
evaluation, policies, and recommendations as well as useful for planning
programs to improve the quality of education next. Currently still using
conventional mapping. So, we need a method that can process data for mapping
quickly, effectively and efficiently. In this study tried to use the clustering method
Self-Organizing Maps (SOM) to perform grouping and mapping the data
processing school quality score based on six National Education Standards.
Assessment data used is the value of competency standards, the value of content
standards, a standard process value, the default value assessment, the default value
of educators and education personnel, and value management standards. The
mapping process begins with normalization of the data, then the data is used as
input to the method used. The results of this study showed that the average quality
of primary school education in the category is expected because of the National
Standards 6 5 grouping grouping excel in the category of quality that is expected
of National Education Standards. While the quality of education quality category
memenui National Education Standards in parameter Competency Standards.
From the test results of clustering analysis using the Davies-Bouldin validity
Index (DBI) obtained information that clustering on 6 test variable National
Education Standards are good.
| Item Type: | Thesis (Masters) |
|---|---|
| Additional Information: | RTE 621.367 8 Bas p |
| Uncontrolled Keywords: | mapping of education, school quality, School Self-Evaluation, unsupervised neural networks, self-organizing maps. |
| Subjects: | T Technology > TK Electrical engineering. Electronics Nuclear engineering T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK5105 Data Transmission Systems |
| Divisions: | Faculty of Industrial Technology > Electrical Engineering > 20101-(S2) Master Thesis |
| Depositing User: | Mr. Fandika aqsa |
| Date Deposited: | 14 Jun 2017 02:23 |
| Last Modified: | 15 Jun 2017 02:13 |
| URI: | http://repository.its.ac.id/id/eprint/41649 |
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