Anastasya Latubessy
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Research Subjects
Anastasya Latubessy has a total of 20 co-authors. Here are the top co-authors by number of shared publications:
- Ahmad Jazuli
Universitas Muria Kudus
2 shared publications - Aina Musdholifah
Universitas Gadjah Mada
2 shared publications - Retantyo Wardoyo
Department of Computer Science and Electronics, Faculty of Mathematics and Natural Science, Universitas Gadjah Mada, Yogyakarta 55281
2 shared publications - Rina Fiati
Universitas Muria Kudus
2 shared publications Sri Kusrohmaniah
Universitas Gadjah Mada
2 shared publicationsAditya Riadi
Universitas Muria Kudus Kampus UMK Street Gondang manis 59327 12345 Bae Kudus Central Java Indonesia
1 shared publication
Latest Publications
- Open Access
- 22 July 2025
- Published by Intelligence Science and Technology Press Inc. in Journal of Artificial Intelligence and Technology
Robust Feature Management for Gaming Disorder Classification Using Modified Partial Instance Reduction and Fine-Tune Attribute-Weighted Naïve Bayes
The dynamic nature of the social environment can influence symptom patterns in mental illnesses, thereby affecting their classification. Gaming disorder (GD), recently recognized in ICD-11 by the World Health Organization, is currently identified based on 44 symptoms derived from expert assessments. However, these symptoms may shift as social behaviors evolve, necessitating classification models that remain robust despite changes in dataset attributes. This study proposes a robust model—fine-tuned attribute-weighted Naïve Bayes (FTAWNB) with modified partial instance reduction (mPIR)—to address this issue. Two test scenarios were conducted: the addition of one new attribute and the removal of four attributes from the GD dataset, applied to both the original and updated datasets. The results indicate that FTAWNB with modified PIR enhances classification performance. On the original dataset, accuracy increased by 1.28% (Scenario 1) and 1.4% (Scenario 2). On the updated dataset, the model maintained 99.74% accuracy (Scenario 1) and improved by 1.4% (Scenario 2). These findings demonstrate that the integration of modified PIR improves model stability in dynamic feature environments, thereby contributing to more reliable mental health classification systems.
- 22 July 2025
- Published by Intelligence Science and Technology Press Inc. in Journal of Artificial Intelligence and Technology
Open AccessRobust Feature Management for Gaming Disorder Classification Using Modified Partial Instance Reduction and Fine-Tune Attribute-Weighted Naïve Bayes
The dynamic nature of the social environment can influence symptom patterns in mental illnesses, thereby affecting their classification. Gaming disorder (GD), recently recognized in ICD-11 by the World Health Organization, is currently identified based on 44 symptoms derived from expert assessments. However, these symptoms may shift as social behaviors evolve, necessitating classification models that remain robust despite changes in dataset attributes. This study proposes a robust model—fine-tuned attribute-weighted Naïve Bayes (FTAWNB) with modified partial instance reduction (mPIR)—to address this issue. Two test scenarios were conducted: the addition of one new attribute and the removal of four attributes from the GD dataset, applied to both the original and updated datasets. The results indicate that FTAWNB with modified PIR enhances classification performance. On the original dataset, accuracy increased by 1.28% (Scenario 1) and 1.4% (Scenario 2). On the updated dataset, the model maintained 99.74% accuracy (Scenario 1) and improved by 1.4% (Scenario 2). These findings demonstrate that the integration of modified PIR improves model stability in dynamic feature environments, thereby contributing to more reliable mental health classification systems.
- Open Access
- 1 March 2025
- Published by Ital Publication in HighTech and Innovation Journal
- Vol. 6 (1) , 67-80
Fine-Tuned Attribute Weighted Naïve Bayes with Modified Partial Instances Reduction for Gaming Disorder Classification
Fine Tuning Attribute Weighted Naïve Bayes (FTAWNB) is a reliable modified Naïve Bayes model. Even though it is able to provide high accuracy on ordinal data, this model is sensitive to outliers. To improve the performance of FTAWNB, this research modified the Partial Instances Reduction (PIR) technique to make the FTAWNB more adaptive to outliers. Nevertheless, in contrast to the original PIR technique, which substitutes missing values for data values deemed outliers, the PIR technique suggested in this study replaces data values deemed outliers using a Naïve Bayes weighting approach. The attribute values from the outlier data are replaced with the highest probability values for the attributes in the actual class. This PIR technique is referred to as modified PIR. The FTAWNB model with modified PIR has been evaluated using the Gaming Disorder dataset. Replacing the four attributes with the least amount of information resulted in accuracy gains of 99.74%, an increase of 1.53% over the FTAWNB model. The experimental result shows that adding the modified PIR technique to the FTAWNB model can handle the outlier in the data, proving it by increasing the performance in terms of accuracy, precision, and recall without pruning the dataset used. Doi: 10.28991/HIJ-2025-06-01-05 Full Text: PDF
- 1 March 2025
- Published by Ital Publication in HighTech and Innovation Journal
- Vol. 6 (1) , 67-80
Open AccessFine-Tuned Attribute Weighted Naïve Bayes with Modified Partial Instances Reduction for Gaming Disorder Classification
Fine Tuning Attribute Weighted Naïve Bayes (FTAWNB) is a reliable modified Naïve Bayes model. Even though it is able to provide high accuracy on ordinal data, this model is sensitive to outliers. To improve the performance of FTAWNB, this research modified the Partial Instances Reduction (PIR) technique to make the FTAWNB more adaptive to outliers. Nevertheless, in contrast to the original PIR technique, which substitutes missing values for data values deemed outliers, the PIR technique suggested in this study replaces data values deemed outliers using a Naïve Bayes weighting approach. The attribute values from the outlier data are replaced with the highest probability values for the attributes in the actual class. This PIR technique is referred to as modified PIR. The FTAWNB model with modified PIR has been evaluated using the Gaming Disorder dataset. Replacing the four attributes with the least amount of information resulted in accuracy gains of 99.74%, an increase of 1.53% over the FTAWNB model. The experimental result shows that adding the modified PIR technique to the FTAWNB model can handle the outlier in the data, proving it by increasing the performance in terms of accuracy, precision, and recall without pruning the dataset used. Doi: 10.28991/HIJ-2025-06-01-05 Full Text: PDF
- Open Access
- 1 June 2024
- Published by Institute of Advanced Engineering and Science in International Journal of Electrical and Computer Engineering (IJECE)
- Vol. 14 (3) , 3277-3286
Fine tuning attribute weighted naïve Bayes model for detecting anxiety disorder levels of online gamers
This research applies the fine tuning attribute weighted naïve Bayes (FTAWNB) model using ordinal data. It is known that in previous research, the FTAWNB model outperformed its competitors on the dataset used. However, the FTAWNB model has not been applied in the mental health domain that uses ordinal data. Therefore, this research used the anxiety gamers dataset to test the fine-tuning attribute weighted Naïve Bayes (FTAWNB) model. Anxiety disorders are mental health disorders that can indicate the emergence of a gaming disorder. Gamers can experience anxiety disorders classified into four classes, namely minimal, mild, moderate, and severe anxiety. Then compare the results by FTAWNB obtained with three other naïve Bayes algorithms, namely Gaussian naïve Bayes, multinomial naïve Bayes, and categorical naïve Bayes, using the same dataset. Model performance is measured based on accuracy, precision, recall, and processing time. The test results show that the FTAWNB outperforms the other three models' accuracy, precision, and recall, with an accuracy value of 99.22%. While the accuracy of Gaussian NB is 91.132%, Categorical is 91.592%, and multinomial naïve Bayes is 61.104%. However, the FTAWNB takes slightly longer than the other three models' processing time. The FTAWNB takes 0.07 seconds to build the model and 0.05 seconds to test the model on training data.
- 1 June 2024
- Published by Institute of Advanced Engineering and Science in International Journal of Electrical and Computer Engineering (IJECE)
- Vol. 14 (3) , 3277-3286
Open AccessFine tuning attribute weighted naïve Bayes model for detecting anxiety disorder levels of online gamers
This research applies the fine tuning attribute weighted naïve Bayes (FTAWNB) model using ordinal data. It is known that in previous research, the FTAWNB model outperformed its competitors on the dataset used. However, the FTAWNB model has not been applied in the mental health domain that uses ordinal data. Therefore, this research used the anxiety gamers dataset to test the fine-tuning attribute weighted Naïve Bayes (FTAWNB) model. Anxiety disorders are mental health disorders that can indicate the emergence of a gaming disorder. Gamers can experience anxiety disorders classified into four classes, namely minimal, mild, moderate, and severe anxiety. Then compare the results by FTAWNB obtained with three other naïve Bayes algorithms, namely Gaussian naïve Bayes, multinomial naïve Bayes, and categorical naïve Bayes, using the same dataset. Model performance is measured based on accuracy, precision, recall, and processing time. The test results show that the FTAWNB outperforms the other three models' accuracy, precision, and recall, with an accuracy value of 99.22%. While the accuracy of Gaussian NB is 91.132%, Categorical is 91.592%, and multinomial naïve Bayes is 61.104%. However, the FTAWNB takes slightly longer than the other three models' processing time. The FTAWNB takes 0.07 seconds to build the model and 0.05 seconds to test the model on training data.
- Open Access
- 13 December 2023
- Published by Universitas Muria Kudus in Jurnal Dialektika Informatika (Detika)
- Vol. 4 (1) , 26-32
APLIKASI STUDIO MUSIK BERBASIS QR CODE DI OMT MUSIK STUDIO
APLIKASI STUDIO MUSIK BERBASIS QR CODE DI OMT MUSIK STUDIO
- 13 December 2023
- Published by Universitas Muria Kudus in Jurnal Dialektika Informatika (Detika)
- Vol. 4 (1) , 26-32
Open AccessAPLIKASI STUDIO MUSIK BERBASIS QR CODE DI OMT MUSIK STUDIO
APLIKASI STUDIO MUSIK BERBASIS QR CODE DI OMT MUSIK STUDIO
- Open Access
- 30 December 2021
- Published by Universitas Muria Kudus in Indonesian Journal of Technology, Informatics and Science (IJTIS)
- Vol. 3 (1) , 36-41
ANALISA USER ACCEPTANCE TESTING TERHADAP SISTEM INFORMASI PENGELOLAAN BEDAH RUMAH DI DINAS PERUMAHAN RAKYAT DAN KAWASAN PERMUKIMAN KABUPATEN JEPARA
Abstrak Bedah rumah atau Bantuan Stimulan Perumahan Swadaya (BSPS) merupakan salah satu program pemerintah untuk memperbaiki rumah penduduk yang kurang layak untuk dihuni. Pada pelaksanaannya, proses pendataan dan Penyeleksian rumah masyarakat yang berhak menerima bantuan ini sering kali membutuhkan ketelitian yang tinggi sehingga memerlukan waktu yang cukup lama agar bantuan menjadi tepat sasaran. Sistem informasi yang terintegrasi menjadi solusi untuk mengatasi permasalahan yang dapat mempermudah pekerjaan dan mempersingkat waktu Selain itu, sistem juga dapat melakukan pengelompokan dan penyeleksian terhadap keadaan rumah dari masyarakat miskin lalu dirangkingkan untuk prioritas dalam mendapatkan program bantuan bedah rumah. Penelitian ini menggunakan contract acceptance testing pada pengujian user acceptance dengan 2 jenis skala pembobotan dan 9 poin pertanyaan. Pengujian telah dilakukan dengan mengakumulasi persentase dari setiap pertanyaan dan menghasilkan 86,2% dengan kriteria sangat sesuai dan sangat mudah. Kata kunci: Bedah rumah, Sistem Informasi, Metode Waterfall
- 30 December 2021
- Published by Universitas Muria Kudus in Indonesian Journal of Technology, Informatics and Science (IJTIS)
- Vol. 3 (1) , 36-41
Open AccessANALISA USER ACCEPTANCE TESTING TERHADAP SISTEM INFORMASI PENGELOLAAN BEDAH RUMAH DI DINAS PERUMAHAN RAKYAT DAN KAWASAN PERMUKIMAN KABUPATEN JEPARA
Abstrak Bedah rumah atau Bantuan Stimulan Perumahan Swadaya (BSPS) merupakan salah satu program pemerintah untuk memperbaiki rumah penduduk yang kurang layak untuk dihuni. Pada pelaksanaannya, proses pendataan dan Penyeleksian rumah masyarakat yang berhak menerima bantuan ini sering kali membutuhkan ketelitian yang tinggi sehingga memerlukan waktu yang cukup lama agar bantuan menjadi tepat sasaran. Sistem informasi yang terintegrasi menjadi solusi untuk mengatasi permasalahan yang dapat mempermudah pekerjaan dan mempersingkat waktu Selain itu, sistem juga dapat melakukan pengelompokan dan penyeleksian terhadap keadaan rumah dari masyarakat miskin lalu dirangkingkan untuk prioritas dalam mendapatkan program bantuan bedah rumah. Penelitian ini menggunakan contract acceptance testing pada pengujian user acceptance dengan 2 jenis skala pembobotan dan 9 poin pertanyaan. Pengujian telah dilakukan dengan mengakumulasi persentase dari setiap pertanyaan dan menghasilkan 86,2% dengan kriteria sangat sesuai dan sangat mudah. Kata kunci: Bedah rumah, Sistem Informasi, Metode Waterfall
- Open Access
- 30 June 2021
- Published by Universitas Muria Kudus in Indonesian Journal of Technology, Informatics and Science (IJTIS)
- Vol. 2 (2) , 71-74
PENGUJIAN SISTEM INFORMASI PELAYANAN PUBLIK KEPOLISIAN RESOR KABUPATEN KUDUS
Pelayanan publik adalah kegiatan atau rangkaian kegiatan dalam rangka pemenuhan kebutuhan pelayanan sesuai dengan peraturan perundang- undangan bagi setiap warga negara dan penduduk atas barang, jasa, dan/atau pelayanan administratif yang disediakan oleh penyelenggara pelayanan publik. Kepolisian merupakan salah satu instansi yang diberi amanah dalam melakukan pelayanan publik. Pelayanan publik yang baik membutuhkan sarana yang tepat. Diera perkembangan teknologi saat ini, kepolisian ingin mengadopsi teknologi digital untuk membantu proses pelayanan publik. Salah satu teknologi yang dapat membantu adalah Sistem Informasi. Oleh sebab itu, dalam penelitian kerja sama antara Program Studi Teknik Informatika denga Kepolisian Resor Kudus yang tertuang dalam perjanjian kerjasama, maka dibuatkan sebuah Sistem Informasi terpadu yang dapat digunaka untuk proses pelayanan informasi. Dengan harapan proses pelayanan publik di kepolisian resor kudus dapat dilaksakan dengan lebih baik.
- 30 June 2021
- Published by Universitas Muria Kudus in Indonesian Journal of Technology, Informatics and Science (IJTIS)
- Vol. 2 (2) , 71-74
Open AccessPENGUJIAN SISTEM INFORMASI PELAYANAN PUBLIK KEPOLISIAN RESOR KABUPATEN KUDUS
Pelayanan publik adalah kegiatan atau rangkaian kegiatan dalam rangka pemenuhan kebutuhan pelayanan sesuai dengan peraturan perundang- undangan bagi setiap warga negara dan penduduk atas barang, jasa, dan/atau pelayanan administratif yang disediakan oleh penyelenggara pelayanan publik. Kepolisian merupakan salah satu instansi yang diberi amanah dalam melakukan pelayanan publik. Pelayanan publik yang baik membutuhkan sarana yang tepat. Diera perkembangan teknologi saat ini, kepolisian ingin mengadopsi teknologi digital untuk membantu proses pelayanan publik. Salah satu teknologi yang dapat membantu adalah Sistem Informasi. Oleh sebab itu, dalam penelitian kerja sama antara Program Studi Teknik Informatika denga Kepolisian Resor Kudus yang tertuang dalam perjanjian kerjasama, maka dibuatkan sebuah Sistem Informasi terpadu yang dapat digunaka untuk proses pelayanan informasi. Dengan harapan proses pelayanan publik di kepolisian resor kudus dapat dilaksakan dengan lebih baik.
- Open Access
- 1 February 2021
- Published by IOP Publishing in Journal of Physics: Conference Series
- Vol. 1779 (1) , 012085
Statistical Analysis Relationship Between Behavior of Millenial Parents With Game Addictions in Children
Game addiction has been declared as one of the mental disorders by WHO. According to research conducted by first author in previous studies stated that there is a negative correlation between the learning process of children with game addiction. This causes anxiety for parents. Today, technology that is developing rapidly is one of the challenges for parents, especially millennial parents. On the other hand, millennial parents also often use gadgets or play games on these gadgets. The parenting style applied by millennial parents to children can also affect children’s growth and development. Indirectly the child will follow what the parents do. The current research, analyzes the relationship between millennial parents’ care for game addiction in children. This study consisted of two variables, namely the millennial parent’s behavior and game addiction, each of which has aspects that are translated into a questionnaire. This study uses a qualitative approach. The method of correlation test analysis using Pearson Product Moment with the help of SPSS. The study concluded that, there was a relationship between behavior of millennial parents and game addiction in children. The relationship that occurs is a significant positive correlation where, the higher the behavior style of millennial parents, the higher the game addiction in children. With the correlation coefficient between the parental millennial behavior and game addiction in children amounting to 0.366 with sig. = 0.023 (p <0.05).
- 1 February 2021
- Published by IOP Publishing in Journal of Physics: Conference Series
- Vol. 1779 (1) , 012085
Open AccessStatistical Analysis Relationship Between Behavior of Millenial Parents With Game Addictions in Children
Game addiction has been declared as one of the mental disorders by WHO. According to research conducted by first author in previous studies stated that there is a negative correlation between the learning process of children with game addiction. This causes anxiety for parents. Today, technology that is developing rapidly is one of the challenges for parents, especially millennial parents. On the other hand, millennial parents also often use gadgets or play games on these gadgets. The parenting style applied by millennial parents to children can also affect children’s growth and development. Indirectly the child will follow what the parents do. The current research, analyzes the relationship between millennial parents’ care for game addiction in children. This study consisted of two variables, namely the millennial parent’s behavior and game addiction, each of which has aspects that are translated into a questionnaire. This study uses a qualitative approach. The method of correlation test analysis using Pearson Product Moment with the help of SPSS. The study concluded that, there was a relationship between behavior of millennial parents and game addiction in children. The relationship that occurs is a significant positive correlation where, the higher the behavior style of millennial parents, the higher the game addiction in children. With the correlation coefficient between the parental millennial behavior and game addiction in children amounting to 0.366 with sig. = 0.023 (p <0.05).
- Open Access
- 15 December 2019
- Published by Universitas Muria Kudus in Indonesian Journal of Technology, Informatics and Science (IJTIS)
- Vol. 1 (1) , 1-4
PEMODELAN SAW DALAM PENENTUAN PENERIMAAN KARYAWAN DI GBI KUDUS
Penerimaan pegawai baru adalah hal yang penting bagi perusahaan untuk memperoleh calon pegawai baru dalam menduduki suatu jabatan. Pada sebagian perusahaan, proses penerimaan pegawai baru masih belum dilakukan secara profesional. Hal ini terjadi karena tidak ada model standar yang sistematis untuk menilai kelayakan calon pegawai baru. Aplikasi sistem pendukung keputusan penerimaan pegawai baru yang dibangun menggunakan metode Simple Additive Weighting (SAW). Metode ini dipilih karena dapat menentukan nilai bobot untuk setiap atribut, kemudian dilanjutkan dengan proses perankingan yang akan menyeleksi alternatif terbaik dari sejumlah alternatif, dalam hal ini alternatif yang dimaksud adalah yang berhak diterima sebagai pegawai baru berdasarkan kriteria-kriteria yang ditentukan. Berdasarkan hasil pengujian, sistem yang dibangun dapat mempermudah dan mempercepat proses penyeleksian penerimaan pegawai baru dan membantu manajer divisi Sumber Daya Manusia (SDM) dalam pengambilan keputusan untuk menentukan pegawai baru di suatu perusahaan.
- 15 December 2019
- Published by Universitas Muria Kudus in Indonesian Journal of Technology, Informatics and Science (IJTIS)
- Vol. 1 (1) , 1-4
Open AccessPEMODELAN SAW DALAM PENENTUAN PENERIMAAN KARYAWAN DI GBI KUDUS
Penerimaan pegawai baru adalah hal yang penting bagi perusahaan untuk memperoleh calon pegawai baru dalam menduduki suatu jabatan. Pada sebagian perusahaan, proses penerimaan pegawai baru masih belum dilakukan secara profesional. Hal ini terjadi karena tidak ada model standar yang sistematis untuk menilai kelayakan calon pegawai baru. Aplikasi sistem pendukung keputusan penerimaan pegawai baru yang dibangun menggunakan metode Simple Additive Weighting (SAW). Metode ini dipilih karena dapat menentukan nilai bobot untuk setiap atribut, kemudian dilanjutkan dengan proses perankingan yang akan menyeleksi alternatif terbaik dari sejumlah alternatif, dalam hal ini alternatif yang dimaksud adalah yang berhak diterima sebagai pegawai baru berdasarkan kriteria-kriteria yang ditentukan. Berdasarkan hasil pengujian, sistem yang dibangun dapat mempermudah dan mempercepat proses penyeleksian penerimaan pegawai baru dan membantu manajer divisi Sumber Daya Manusia (SDM) dalam pengambilan keputusan untuk menentukan pegawai baru di suatu perusahaan.
- 14 June 2018
- Published by Science Publishing Corporation in International Journal of Engineering & Technology
- Vol. 7 (3) , 1791
Web application to measure level of addictive game
Game becomes very popular within all ages. The intensity of someone playing games can influence the behavior of that person. World Health Organization (WHO) is classifying gaming disorder as an addictive behavior disorder. According to psychologists, there are six types of game addiction behavior, such as, Salience, Euphoria, Conflict, Tolerance, Withdrawal, and the last is Relapse and Reinstatement. A person is said to be addicted to the game if it meets at least three of the six types of behavior that exist. The six types of game addiction behavior then modeled using backward chaining algorithm. After that, the model was implemented into the system. Thus this research re-sult a web application to identify game addiction. Now we can measure how many people are affected using this web application.
- 14 June 2018
- Published by Science Publishing Corporation in International Journal of Engineering & Technology
- Vol. 7 (3) , 1791
Web application to measure level of addictive game
Game becomes very popular within all ages. The intensity of someone playing games can influence the behavior of that person. World Health Organization (WHO) is classifying gaming disorder as an addictive behavior disorder. According to psychologists, there are six types of game addiction behavior, such as, Salience, Euphoria, Conflict, Tolerance, Withdrawal, and the last is Relapse and Reinstatement. A person is said to be addicted to the game if it meets at least three of the six types of behavior that exist. The six types of game addiction behavior then modeled using backward chaining algorithm. After that, the model was implemented into the system. Thus this research re-sult a web application to identify game addiction. Now we can measure how many people are affected using this web application.
- Open Access
- 1 April 2018
- Published by Universitas Muria Kudus in Simetris: Jurnal Teknik Mesin, Elektro dan Ilmu Komputer
- Vol. 9 (1) , 205-210
MODEL DDST(DENVER DEVELOPMENT SCREENING TEST) UNTUK MONITORING PERKEMBANGAN ANAK BERBASIS EXPERT SYSTEM
Pertumbuhan dan perkembangan anak atau biasanya disebut tumbuh kembang anak menjadi perhatian bagi setiap orang tua. Pertumbuhan lebih melihat pada perubahan fisik, proses bertambahnya ukuran tubuh dengan adanya pembesaran sel-sel tubuh. Sedangkan perkembangan itu sendiri merupakan hasil dari proses tingkat kematangan seorang anak. Menjadi harapan setiap orang tua agar tumbuh kembang anaknya dapat berjalan dengan baik. Pada kasus-kasus tertentu seorang anak dapat memiliki perilaku penyimpangan dalam perkembangannya. Orang tua harus dapat menyadari pola penyimpangan tersebut lebih dini. Namun, tidak semua orang tua mengetahui ciri-ciri penyimpangan perkembangan anak. Salah satu tes yang dapat digunakan untuk mengukur perkembangan anak yaitu, DDST(Denver Development Screening Test). Dengan menggunakan 121 jenis tugas perkembangan yang terbagi atas empat sektor yaitu, personal social, fine motor adaptive, bahasa dan grass motor. Tes yang masih bersifat manual ini kemudian dimodelkan dengan menggunakan salah satu metode pemodelan expert system yaitu backward chaining. Dari hasil akhir penelitian ini adalah sebuah model yang dapat digunakan untuk menunjukkan perkembangan seorang anak.
- 1 April 2018
- Published by Universitas Muria Kudus in Simetris: Jurnal Teknik Mesin, Elektro dan Ilmu Komputer
- Vol. 9 (1) , 205-210
Open AccessMODEL DDST(DENVER DEVELOPMENT SCREENING TEST) UNTUK MONITORING PERKEMBANGAN ANAK BERBASIS EXPERT SYSTEM
Pertumbuhan dan perkembangan anak atau biasanya disebut tumbuh kembang anak menjadi perhatian bagi setiap orang tua. Pertumbuhan lebih melihat pada perubahan fisik, proses bertambahnya ukuran tubuh dengan adanya pembesaran sel-sel tubuh. Sedangkan perkembangan itu sendiri merupakan hasil dari proses tingkat kematangan seorang anak. Menjadi harapan setiap orang tua agar tumbuh kembang anaknya dapat berjalan dengan baik. Pada kasus-kasus tertentu seorang anak dapat memiliki perilaku penyimpangan dalam perkembangannya. Orang tua harus dapat menyadari pola penyimpangan tersebut lebih dini. Namun, tidak semua orang tua mengetahui ciri-ciri penyimpangan perkembangan anak. Salah satu tes yang dapat digunakan untuk mengukur perkembangan anak yaitu, DDST(Denver Development Screening Test). Dengan menggunakan 121 jenis tugas perkembangan yang terbagi atas empat sektor yaitu, personal social, fine motor adaptive, bahasa dan grass motor. Tes yang masih bersifat manual ini kemudian dimodelkan dengan menggunakan salah satu metode pemodelan expert system yaitu backward chaining. Dari hasil akhir penelitian ini adalah sebuah model yang dapat digunakan untuk menunjukkan perkembangan seorang anak.