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All Journal E-Jurnal Matematika Jurnal Mahasiswa Statistik Natural B JOIV : International Journal on Informatics Visualization Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer BAREKENG: Jurnal Ilmu Matematika dan Terapan
Ni Wayan Surya Wardhani
Prodi Statistika Jurusan Matematika FMIPA Universitas Brawijaya
Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Mathematics Mechanical Engineering Physics Transportation

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Improved Fuzzy Possibilistic C-Means using Artificial Bee Colony for Clustering New Student’s Financial Capability to Determine Tuition Level Satriyanto, Edi; Surya Wardhani, Ni Wayan; Anam, Syaiful; Mahmudy, Wayan Firdaus
JOIV : International Journal on Informatics Visualization Vol 8, No 4 (2024)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/joiv.8.4.3087

Abstract

Outliers in the dataset will affect the quality of the cluster, so a good clustering method is needed. Based on the Mahalanobis distance method, it is known that the research dataset has outliers. Clustering methods that are often used for this type of data are Fuzzy C-means (FCM), Possibilistic C-means (PCM), and Fuzzy Possibilistic C-means (FPCM). This study aims to develop a clustering method that is more robust to outliers by using the Artificial Bee Colony (ABC) algorithm to minimize the objective function of FPCM. This study produces a new algorithm called Artificial Bee Colony Fuzzy Possibilistic C-Means (ABCFPCM) so that the resulting clusters are not easily trapped in the local optimum. This study also provides cluster centroid initialization using K-Means++ to improve cluster quality. ABCFPCM performs best because it significantly increases the Silhouette value and the Between Sum Squares (BSS) and Total Sum Squares (TSS) ratio. ABCFPCM performance provides the best cluster quality of 72.16% based on the BSS/TSS ratio, FPCM of 70.71%, and FCM K-Means++ of 68.14%. K-Means++ in the cluster method does not affect cluster performance except for FCM, where cluster quality is slightly increased. The centroid results of 8 clusters as the best performance of ABCFPCM are used to determine the tuition rate level. The impact of this study is to improve the quality of FPCM performance because it is no longer trapped in a local optimum at the cluster centroid.
META-REGRESSION OF SOCIOECONOMIC FACTORS AND THE PREVALENCE OF PHYSICAL DISORDERS IN HYPERTENSIVE PATIENTS Rahmi, Nur Silviyah; Astutik, Suci; Surya Wardhani, Ni Wayan; Maharani, Adinda Gita; Fakhrunnisa, Atmadani Rahayu; Khatimah, Husnul; Aulia, Silvia Intan
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 19 No 4 (2025): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol19iss4pp2275-2286

Abstract

Hypertension is a common degenerative disease with a high mortality rate and a significant impact on quality of life and productivity. Education level plays a crucial role in understanding and managing hypertension, where higher education levels can contribute to reducing the risk of hypertension. This study utilized meta-analysis and meta-regression to explore the relationship between education level and hypertension prevalence. Secondary data from eight previous studies conducted between 2015 and 2023 were analyzed. Heterogeneity analysis was performed to determine the appropriate meta-analysis model, with a random-effect model selected based on the test results. Of the eight studies analyzed, five showed a negative odds ratio, indicating that individuals with higher education levels have a lower likelihood of developing hypertension compared to those with lower education levels. The heterogeneity test showed significant variability among the studies (I2 = 91.38%). The random-effect model estimated a combined effect size with an ln odds ratio of -0.1777 and a 95% confidence interval of -0.3228 to -0.0326. These findings suggest that higher education levels are associated with a lower risk of hypertension. This underscores the importance of improving access to quality education as part of public health strategies to reduce the incidence of hypertension and enhance overall community well-being.
Co-Authors Ahmad Afif Supianto Amelia, Okky Ariska Aulia, Silvia Intan Danang Ariyanto Dianiati, Aldila Nur Edi Satriyanto Eka Saraswati Fakhrunnisa, Atmadani Rahayu Fariz, Yustian Al Fitrianty, Delbra Andhini Henny Pramoedyo Henny Pramoedyo Hidayati, Azizah Husnul Khatimah Ismi, Septi Nurul Kusdarwati, Heni Kusumastuti, Prawitra Loekito Adi Soehono Luthfatul Amaliana Maharani, Adinda Gita Meilianawati, Putri Mitakda, Maria Benadetha Mitakda, Maria Bernadetha Nugraheni, Listia Nugroho, Waego Hadi Pramana, Gilang Putra Prasetyo, Teguh Putri, Frida Aridiana Rahma Fitriani Rahmi, Nur Silviyah Ramadani, Betty Wulansari Ramdan, Bayu Muhamad Ria Rosilawati Rosa Nur Madinah Saputra, Yoyok Yuni Solimun, Solimun Suci Astutik Sumarminingsih, Eni Syaiful Anam Theresia Mitakda, Maria Bernadetha UMU SA’ADAH Wayan Firdaus Mahmudy Yusrina Nur Dianati