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All Journal Jurnal Keperawatan Jiwa (JKJ): Persatuan Perawat Nasional Indonesia Jurnal Teknologi Informasi dan Ilmu Komputer Jurnal Ilmu Keperawatan dan Kebidanan Jurnal Daulat Hukum Jurnal Akta JURNAL PENDIDIKAN TAMBUSAI KOMPUTIKA - Jurnal Sistem Komputer Jurnal Keperawatan Suaka Insan Indonesian Journal of Nursing Research (IJNR) Jurnal Manajemen Asuhan Keperawatan Jurnal Komunikasi Pendidikan Jurnal Ilmiah Kesehatan Ar-Rum Salatiga NURSING UPDATE JURNAL ILMIAH ILMU KEPERAWATAN Adi Husada Nursing Journal Jurnal Peduli Masyarakat Indonesian Journal of Community Health Nursing Jurnal Pendidikan Madrasah Indonesian Journal of Global Health research JIK (Jurnal Ilmu Kebidanan) Jurnal Pengabdian Kepada Masyarakat Ungu ( Abdi Ke Ungu) Trapsila: Jurnal Pendidikan Dasar PROFESSIONAL HEALTH JOURNAL GHIDZA MEDIA JURNAL JIDAN (JURNAL ILMIAH KEBIDANAN) Journal of Language and Health Jurnal Pengabdian Kepada Masyarakat Sisthana Jurnal Pembelajaran Fisika Empowerment Journal Journal of Comprehensive Science Journal of Innovation and Research in Primary Education Jurnal Rumpun Ilmu Kesehatan Jurnal Indonesia Sosial Sains Termometer: Jurnal Ilmiah Ilmu Kesehatan Dan Kedokteran Jurnal Masyarakat Madani Indonesia Diagnosa: Jurnal Ilmu Kesehatan dan Keperawatan Sahabat Sosial: Jurnal Pengabdian Masyarakat Detector: Jurnal Inovasi Riset Ilmu Kesehatan International Journal of Health Sciences Jurnal Pengabdian Perawat Corona: Jurnal Ilmu Kesehatan Umum, Psikolog, Keperawatan dan Kebidanan Protein: Jurnal Ilmu Keperawatan dan Kebidanan Oshada JOURNAL of HEALTH SCIENCE REVIEW Journal of Education and Pedagogy MEDICA (International Medical Scientific Journal) Klinik: Jurnal Ilmiah Kedokteran dan Kesehatan Journal of Health Sciences, Medicine, Biotechnology, and Pharmaceutical Research Jurnal Penelitian Perawat Profesional
Siti Juwariyah
Universitas Telogorejo Semarang
Humanities Astronomy Biochemistry, Genetics & Molecular Biology Chemistry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Immunology & microbiology Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Medicine & Pharmacology Neuroscience Nursing Physics Public Health Social Sciences Veterinary Other

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Parenting Style and Early Childhood Development among Toddlers in Coastal Communities of Semarang, Indonesia Maya Cobalt Angio Septianingtyas; Ellyzabeth Sukmawati; Achmad Solechan; Siti Juwariyah; Danny Putri Sulistyaningrum
MEDICA (International Medical Scientific Journal) Vol. 8 No. 7 (2026): MEDICA (International Medical Scientific Journal)
Publisher : Borneo Scientific Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53770/medica.v8i7.1076

Abstract

Early childhood development remains a major public health concern in Indonesian coastal communities, where socioeconomic vulnerability and suboptimal parenting practices may adversely affect developmental outcomes. This study examined the association between parenting styles and early childhood development among toddlers in coastal communities of Semarang, Indonesia, using a convergent mixed-methods design. A total of 371 mothers with children aged 12–59 months were selected through stratified random sampling from nine coastal villages within the Bandarharjo Primary Health Center catchment area. Quantitative data were collected using the Parenting Styles and Dimensions Questionnaire and the Indonesian Pre-Screening Developmental Questionnaire, while qualitative data were obtained through in-depth interviews with mothers, health cadres, midwives, and community leaders. Quantitative data were analyzed using descriptive statistics, Chi-square tests, and logistic regression, whereas qualitative data were analyzed thematically. Democratic parenting was the predominant parenting style (57.7%), and 72.0% of toddlers demonstrated age-appropriate development. Parenting style was significantly associated with child development (p < 0.001; Cramer's V = 0.27). Logistic regression showed that democratic parenting was associated with better developmental outcomes (OR = 2.94; 95% CI: 1.61–5.37; p < 0.001). Qualitative findings revealed that fragmented caregiving, parental workload, limited developmental literacy, and reliance on digital devices as caregiving substitutes influenced parenting practices and child development. These findings highlight the importance of promoting democratic parenting while addressing socioeconomic and contextual barriers to improve developmental outcomes among children in vulnerable coastal communities.
Deteksi Backdoor Berdasarkan Static Code Analysis Dan Software Component Analysis Juniawan, Fransiskus Panca; Sylfania, Dwi Yuny; Hulvi, Alfajri; Juwariyah, Siti
Jurnal Teknologi Informasi dan Ilmu Komputer Vol 13 No 4: Agustus 2026
Publisher : Fakultas Ilmu Komputer, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25126/jtiik.134

Abstract

Di era transformasi digital yang pesat, perangkat lunak telah menjadi komponen penting di berbagai sektor. Namun, di lain sisi perangkat lunak juga semakin menjadi sasaran ancaman keamanan siber. Salah satu ancaman yang paling mengkhawatirkan adalah backdoor, yaitu kerentanan tersembunyi yang disisipkan secara tidak sah ke dalam perangkat lunak sehingga memungkinkan akses tanpa izin dengan menghindari mekanisme keamanan tradisional. Penelitian ini bertujuan mengembangkan metode deteksi backdoor yang lebih akurat dan komprehensif melalui integrasi Static Code Analysis dan Software Component Analysis. Representasi fitur dilakukan menggunakan Term Frequency–Inverse Document Frequency (TF-IDF), kemudian digunakan sebagai masukan bagi beberapa algoritma Machine Learning dan Deep Learning, yaitu Logistic Regression, K-Nearest Neighbor (KNN), Random Forest, Decision Tree, Gradient Boosting, XGBoost, LightGBM, AdaBoost, Multi-Layer Perceptron (MLP), dan Long Short-Term Memory (LSTM). Dataset penelitian terdiri atas 128 sampel source code, yang mencakup 60 sampel backdoor dan 68 sampel benign, dikumpulkan dari repositori publik serta dikurasi secara manual untuk menjamin kualitas dan relevansinya. Hasil eksperimen menunjukkan bahwa XGBoost dan KNN memperoleh akurasi tertinggi sebesar 96,15%, diikuti oleh MLP, LSTM, dan AdaBoost dengan akurasi 92,31%. Temuan ini menunjukkan bahwa integrasi analisis statis, inspeksi kerentanan berbasis komponen, dan teknik Machine Learning mampu meningkatkan efektivitas deteksi backdoor. Selain itu, pendekatan yang diusulkan berpotensi mendukung implementasi deteksi backdoor secara otomatis pada pipeline DevSecOps untuk meningkatkan keamanan perangkat lunak sebelum tahap deployment.   Abstract In the era of rapid digital transformation, software has become a critical component across various sectors. However, it has also become an increasingly attractive target for cybersecurity threats. One of the most concerning threats is the backdoor, a hidden vulnerability that is illicitly inserted into software, enabling unauthorized access while bypassing traditional security mechanisms. This study aims to develop a more accurate and comprehensive backdoor detection method by integrating Static Code Analysis and Software Component Analysis. Feature representation is performed using Term Frequency–Inverse Document Frequency (TF-IDF), and the resulting feature vectors are used as input for several Machine Learning and Deep Learning algorithms, including Logistic Regression, K-Nearest Neighbor (KNN), Random Forest, Decision Tree, Gradient Boosting, XGBoost, LightGBM, AdaBoost, Multi-Layer Perceptron (MLP), and Long Short-Term Memory (LSTM). The dataset consists of 128 source code samples, comprising 60 backdoor and 68 benign samples, collected from public repositories and manually curated to ensure data quality and relevance. Experimental results demonstrate that XGBoost and KNN achieve the highest classification accuracy of 96.15%, followed by MLP, LSTM, and AdaBoost with an accuracy of 92.31%. These findings indicate that integrating static code analysis, component-based vulnerability inspection, and machine learning techniques can significantly improve the effectiveness of backdoor detection. Furthermore, the proposed approach has the potential to support automated backdoor detection within DevSecOps pipelines, thereby enhancing software security before deployment.
Co-Authors Achmad Solechan Albertus Ata Maran Albina Bare Telan, Albina Bare Ananda, Restu Ardiansyah, Dicko Putra Arfilian, Nisa Asti Nuraeni Auliya Sina Mugna azizah, sofia Desy Aprima Deviyanti, Mutia Rahma Dewi Sekar Arum Dito Anurogo, Dito Durotun Nafisah Dwi Novri Spriatiningrum Dwi Yuny Sylfania Ellyzabeth Sukmawati Emilia Puspitasari Fatkul Anam Fitri Juliasari Gianinda Wening Saraswanty Hellen Febriyanti Hesty Tri Kurniasari Hulvi, Alfajri Indra Nur Azizah Isnanto, Burham I’ien Noer’aini Juniawan, Fransiskus Panca Kristina Maharani Kusrini Kysara, Amanda Ayu Diva Laura Khattrine Lutfiana Putri Febriyanti Machfudin, Amanda Afriyani Mamat Supriyono Mamat Supriyono Maya Cobalt Angio Melania Putri Devitasari Mianti Nurrizky Miss Nafisah Moh. Anshori Aris Widya Muhamad Ridwan Muhammad Romli dan Suprihatin Andes Ismayana Muniatur Rohmaniyah Munsharif Abdul Chalim N.H, M Firmansyah Nabilla Qoni Maharani Nabilla Qoni Maharani Ni Wayan Dewi Maharani Niva Juliana Noer'aini, I'ien Noviyanti, Laura Khattrine Nursinah, A. Ovikariani Ovikariani Panca Juniawan, Fransiskus Pannyiwi, Rahmat permatasari, yana Prita Adisty Handayani Putra, Muhammad Ricky Perdana Qomariyah Qomariyah Qoni Maharani, Nabilla Rasyid, Djusmadi Resa Nirmala Jona Retno Setyawati Riduan, Nor Rizqi Agung Pratiwi Robert Marco, Robert RUSMIYATI Rusmiyati RUSMIYATI Rusmiyati Rusmiyati, Rusmiyati Safridha Kemala Putri Sarah Nur Tri Andini Sarah Nur Tri Andini Saraswanty, Gianinda Wening Sasongko, Hendrik Probo Satria Eureka Nurseskasatmata Sembiring, Endam Apulina Br Sembiring, Rinawati Septianingtyas, Maya Siti Nafisah Siti Sufaidah Sovianti, Vivi Suciwati - Suciwati -, Suciwati Sudarti . Sudiartini, Rini Sulfiani, Sulfiani Sulistyaningrum, Danny Putri Susi Susanti Sutejo, Mianti Nurrizky Sutrisno Adi Prayitno Swanny Trikajanti Widyaatmadja Syarief, Syarifah Wahyuni Al Trapsilo Prihandono tyas, ade UAP, sulastri UAP, tamiati Ulvi Chamidah Umi Solekah Utari Utari Utari Utari Wiranti, Bhakti Yhurike Diah Pitaloka Yuanta, Friendha yulianingsih, wulan Yuny Sylfania, Dwi Zudatul Diana Zuriani Rizki