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All Journal International Journal of Electrical and Computer Engineering IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Jurnal Simetris Jurnal Sains dan Teknologi Prosiding SNATIF Jurnal Teknologi Informasi dan Ilmu Komputer Jurnal Informatika Upgris Jurnal Teknologi dan Sistem Komputer Bianglala Informatika : Jurnal Komputer dan Informatika Akademi Bina Sarana Informatika Yogyakarta Indonesian Journal of Electrical Engineering and Computer Science Indonesian Journal of Technology, Informatics and Science (IJTIS) Jurnal Dialektika Informatika (Detika) Muria Jurnal Layanan Masyarakat
Anastasya Latubessy
Universitas Muria Kudus
Humanities Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Engineering Environmental Science Industrial & Manufacturing Engineering Mechanical Engineering Social Sciences

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Fine tuning attribute weighted naïve Bayes model for detecting anxiety disorder levels of online gamers Latubessy, Anastasya; Wardoyo, Retantyo; Musdholifah, Aina; Kusrohmaniah, Sri
International Journal of Electrical and Computer Engineering (IJECE) Vol 14, No 3: June 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v14i3.pp3277-3286

Abstract

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.
Penerapan Intelligent Geographic Information System untuk Deteksi Kecanduan Game Latubessy, Anastasya; Jazuli, Ahmad; Fiati, Rina
Jurnal Teknologi Informasi dan Ilmu Komputer Vol 7 No 6: Desember 2020
Publisher : Fakultas Ilmu Komputer, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25126/jtiik.2020722185

Abstract

Segala sesuatu yang berlebihan dapat menimbulkan efek kecanduan. Hal yang sama juga berlaku untuk game. Game dapat memberikan efek adiksi yang mengakibatkan pemainnya ketagihan. Pemain game tidak mengenal batas usia. Anak-anak bahkan anak usia dini sudah bermain game dengan menggunakan gadget, sebagai akibat dari perkembangan teknologi saat ini. Kecanduan game dapat berdampak negatif pada anak usia dini. Penelitian terdahulu menunjukkan adanya hubungan korelasi negatif antara kecanduan game dengan proses pembelajaran. Meninjau hal tersebut, maka orang tua perlu waspada terhadap pola permainan game anak. Penelitian terdahulu menghasilkan aplikasi untuk mendeteksi tingkat kecanduan game anak dengan menggunakan salah satu metode dalam sistem pakar yaitu backward chaining untuk identifikasi gejala kecanduan game. Penelitian saat ini mengkombinasi teknologi pakar pada aplikasi sebelumnya dengan teknologi Geographic Information System untuk mendeteksi kecanduan game anak dan memetakan persebarannya di wilayah Indonesia bagian timur, barat dan tengah. Penelitian ini menggunakan metode perancangan sistem waterfall, yang dimulai dari identifikasi masalah, analisa masalah, perancangan sistem, implementasi dan pengujian sistem. Sehingga menghasilkan aplikasi yang diberi nama IGIS-Decandu(Intelligent Geographic Information System Deteksi Kecanduan Game) yang dapat digunakan untuk mengetahui tingkat persebaran kecanduan game anak Indonesia. Hasil uji coba untuk pengujian identifikasi kecanduan game antara sistem IGIS-Decandu dan ujicoba manual memperoleh nilai Kappa sebesar 1.0. Berdasarkan  pengujian tersebut, dapat disimpulkan bahwa sistem IGIS-Decandu siap untuk digunakan secara umum, karena proses identifikasi kecanduan game valid dengan nilai keeratan kesepakatan antara pengujian sistem dan manual adalah 1.00 yang berarti “Sangat Kuat”. AbstractAnything that is excessive can have an addictive effect. The same thing applies to games. Games can have an addictive effect that results in players being addicted. Gamers don't know the age limit. Children and even young children are already playing games using gadgets, as a result of current technological developments. Game addiction can have a negative impact on early childhood. Previous research has shown a negative correlation between game addiction and the learning process. Reviewing this, parents need to be aware of the pattern of children's game play. Previous research has made an application to detect the level of addiction to children's by using one method in the expert system that is backward chaining to identify the symptoms of game addiction. Current research combines expert technology in previous applications with Geographic Information System technology to detect children's gaming addictions and map their distribution in eastern, western and central Indonesia. This study uses a waterfall system design method, which start from identification, problem analysis, design system, implementation system and testing system to produce an application called IGIS-Decandu (Intelligent Geographic Information System for Game Addiction Detection) that can be used to determine the level of distribution of Indonesian children's game addiction. The results of trials for testing the game addiction identification between the IGIS-Decandu system and manual testing obtained a Kappa value of 1.0. Based on these tests, it can be concluded that the IGIS-Decandu system is ready for general use, because the process of identifying game addiction is valid with the value of the agreement between the system and manual testing being 1.00 which means "Very Strong"
PENERAPAN MODEL MULTI LAYER PERCEPTRON UNTUK KLASIFIKASI TINGKAT GANGGUAN KECEMASAN Latubessy, Anastasya
Jurnal Dialektika Informatika (Detika) Vol 6, No 1 (2025): Jurnal Dialektika Informatika(Detika) Vol.6 No.1 Desember 2025
Publisher : Universitas Muria Kudus

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24176/detika.v6i1.15968

Abstract

Gangguan kecemasan rentan dialami oleh semua orang. Tanpa disadari seseorang dapat mengalami gangguan kecemasan, yang dapat berdampak negatif dalam menjalani kehidupannya. Deteksi dini dapat dilakukan dengan menggunakan alat ukur GAD-7 (General Anxiety Disorder-7). Alat ukur manual ini dapat dikembangkan menggunakan model machine learning untuk klasifikasi gangguan kecemasan menggunakan empat tingkat gangguan kecemasan (minimal anxiety, mild anxiety, moderate anxiety, severe anxiety). Penelitian ini menggunakan salah satu model machine learning handal yaitu Multi-Layer Perceptron (MLP) untuk klasfikasi tingkat gangguan kecemasan. Hasil menunjukkan model MLP mampu memberikan performa terbaik dengan akurasi 99,95% pada 13.464 data yang digunakan. Namun waktu komputasi yang dibutuhkan model MLP lebih lama dibandingkan benchmark model yang digunakan sebagai pembanding dalam penelitian ini.
Co-Authors - Mustabsyiroh - Mustabsyiroh A.A. Ketut Agung Cahyawan W Ade Eka Pratama Ade Eka Pratama, Ade Eka Ahmad Ashari Ahmad Jazuli Ahmad Jazuli Aina Musdholifah Alif Catur Murti, Alif Catur Arief Susanto Bayu Adianto Bik, Zidli Auna Daud Parabang Dewa Caniaghi Esti Wijayanti Esti Wijayanti, Esti Farid Eka Dharma Farid Eka Dharma, Farid Eka Fundhi Fanju Hafili Fundhi Fanju Hafili, Fundhi Fanju Hakim, M. Malik Laelly Hidayah Anggraini Laelly Hidayah Anggraini, Laelly Hidayah Lelly Hidayah Anggraini Lelly Hidayah Anggraini Lelly Hidayah Anggraini Lia Musfiroh M. Malik Hakim Miftha Ainul Chamida Moh Dahlan Moh Dahlan Mohammad Dahlan, Mohammad Muhammad Abdullah Muthik Muhammad Afandi Muhammad Afandi Muhammad Haidar Ali Muhammad Rifa'i Mukhamad Nurkamid Mukhamad Nurkamid Putri, Agustina Wahyu Rahma R. Yusroni Ratih Nindyasari Retantyo Wardoyo Rina Fiati Rizki Akbar Rizky Sari Mei Maharani Rizky Sari Mei Maharani, Rizky Sari Rizkysari Mei Maharani Rizkysari Meimaharani Siti Helmyati Sri Kusrohmaniah, Sri Tri Listyorini Wiwit Agus Triyanto Yusroni, R.