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All Journal Transmisi: Jurnal Ilmiah Teknik Elektro Jurnal Teknologi Informasi dan Ilmu Komputer Conference SENATIK STT Adisutjipto Yogyakarta Jurdimas (Jurnal Pengabdian Kepada Masyarakat) Royal Jurnal Pengabdian kepada Masyarakat Nusantara Sricommerce: Journal of Sriwijaya Community Services Jurnal Teknik Informatika (JUTIF) PAEDAGOGY : Jurnal Ilmu Pendidikan dan Psikologi Jurnal Karya Abdi Masyarakat Jurnal Masyarakat Madani Indonesia Indonesian Research Journal on Education Jurnal Pendidikan Teknologi Informasi dan Komunikasi International Journal of Contemporary Sciences (IJCS)
Raidah Hanifah
Jurusan Teknik Elektro Fakultas Teknik Universitas Diponegoro Semarang
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Pelatihan Perencanaan Karir Dalam Upaya Meningkatkan Kematangan Karir Pada Siswa Madrasah Aliyah (MA) Syaifussalam, Muhammad Lathief; Wigati, Meilia; Wilantika, Rima; Hanifah, Raidah; Fertha, Fitria
Jurdimas (Jurnal Pengabdian Kepada Masyarakat) Royal Vol. 7 No. 1 (2024): Januari 2024
Publisher : STMIK Royal

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33330/jurdimas.v7i1.2873

Abstract

Madrasah Aliyah (MA) students. The method used in training is through lectures, discussions, assignments, questions and answers. The presenter delivers psychoeducation about careers to open up insight into the benefits and importance of careers for students, self-awareness to increase self-awareness, Johari window to increase knowledge about oneself, set the goals using the SMART method, reveal one's potential through SWOT analysis, and personality analysis through the RIASEC test to determine the suitability of personality with the desired career. Measurements were carried out twice. The first measurement (pre-test) is carried out before implementing the program to determine the initial conditions for student career decision-making. The second measurement (post-test) is carried out after students receive career training. Next, the results of the pre-test and post-test data were statistically analyzed using a paired-sample t-test using SPSS 23.0 for Windows. The results of the PKM activities carried out show that career planning training is able to increase the career maturity of MA students. Students' understanding of themselves will help them determine their career plans in accordance with their interests and talents.Keyword : career maturity; career training; students
Reflections of Self: How Social Media Shapes Teen Body Image Syaifussalam, M. Lathief; Intansari, Fixi; Hanifah, Raidah; Larasati, Bayu Sekar; Wigati, Meilia; Wilantika, Rima
International Journal of Contemporary Sciences (IJCS) Vol. 1 No. 12 (2024): October 2024
Publisher : PT FORMOSA CENDEKIA GLOBAL

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55927/ijcs.v1i12.12041

Abstract

This research explores how advances in information technology, particularly through social media, have transformed communication patterns and influenced teenagers' body image perceptions. Employing a qualitative approach, the study conducted in-depth interviews with three teenage girls aged 17-21 who are active on social media. The findings indicate that many participants experience dissatisfaction with their bodies due to comparisons with prevalent beauty standards. This aligns with social comparison theory, which suggests that individuals often evaluate their appearance by contrasting themselves with others. Social interactions on social media, including comments and likes, also play a significant role in shaping self-confidence. While the pressure to conform to unrealistic beauty ideals is a notable negative effect, some participants reported feeling motivated to pursue healthier lifestyles as a positive outcome. The study highlights the need for effective interventions aimed at educating adolescents about healthy social media use and raising awareness of its potential effects on body image.
Sosialisasi Kesejahteraan Psikologis Lansia untuk Hidup yang Lebih Sehat dan Bermakna Wilantika, Rima; Agustina, Fitria Fertha; Hanifah, Raidah; Wigati, Meilia; Syaifussalam, Muhammad Lathief; Fuadi, Fauzan; Sinatria, Naufal
Jurnal Masyarakat Madani Indonesia Vol. 5 No. 1 (2026): Februari
Publisher : Alesha Media Digital

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59025/qbfmj730

Abstract

Lansia cenderung mengalami berbagai masalah. Misalnya, kondisi fisik yang lemah seperti kemampuan melihat, mendengar, berjalan, dan kondisi kesehatan yang menurun sehingga mereka rentan terhadap penyakit . Situasi ekonomi semakin terancam, terutama jika ada masalah kesehatan, sehingga lansia harus menyesuaikan gaya hidup yang mereka jalani. Lansia juga mengalami beberapa masalah psikologis yang memengaruhi kesejahteraan psikologis mereka di usia lanjut. pengabdian masyarakat di lembaga kesejahteraan sosial Amanah Bunda yaitu sosialisasi kesejahteraan psikologis lansia. Tujuan pengabdian masyarakat ini yaitu memberikan pemahaman tentang kesejahteraan psikologis pada lansia. Hasil evaluasi setelah disampaikan materi kesejahteraan psikologis hasilnya menunjukan bahwa secara keseluruhan lansia di lembaga kesejahteraan sosial Amanah Bunda sudah mengetahui tentang pentingnya kesejahteraan psikologis.
Preventing Data Leakage in Classification via Integrated Machine Learning Pipelines: Preprocessing, Feature Transformation, and Hyperparameter Tuning Ichwani, Arief; Kesuma, Rahman Indra; Setiawan, Andika; Wicaksono, Imam Eko; Hanifah, Raidah
Jurnal Teknik Informatika (Jutif) Vol. 7 No. 1 (2026): JUTIF Volume 7, Number 1, February 2026
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2026.7.1.5490

Abstract

Data leakage in machine learning classification often leads to overfitting, inflated performance estimates, and poor reproducibility, which can undermine the reliability of deployed models and incur industrial losses. This paper addresses the leakage problem by proposing an integrated machine learning pipeline that strictly isolates training and evaluation processes across preprocessing, feature transformation, and model optimization stages. Experiments are conducted on the Titanic passenger survival dataset, where exploratory data analysis identifies data quality issues, followed by stratified train-test splitting to preserve class distribution. All preprocessing steps, including missing value imputation, categorical encoding, and feature scaling, are applied exclusively to the training data using a ColumnTransformer embedded within a unified Pipeline. A K-Nearest Neighbors (KNN) classifier is employed, with hyperparameters optimized via GridSearchCV and 3-fold cross-validation. Experimental results show that a baseline model without leakage control achieves only 72.62% test accuracy and exhibits a substantial overfitting gap. In contrast, the proposed pipeline-based approach improves generalization, achieving 78.21% test accuracy with an optimal configuration of k = 29 and Manhattan distance while significantly reducing overfitting. The main contribution of this work is the formulation of a reproducible, leakage-aware pipeline guideline that ensures unbiased evaluation and reliable generalization in classification tasks, providing practical methodological insights for both academic research and real-world machine learning applications.
Co-Authors Andika Setiawan, Andika Ardiyansah, Muhammad Ariyanti, Okta Nuria Darmayanti, Dini Fertha, Fitria Fitria Fertha Agustina Fixi Intansari Fuadi, Fauzan Haq, Muhammad Shodikul Husain, Andi Musthafa Ichwani, Arief Ilham Firman Ashari Larasati, Bayu Sekar Lathief Syaifussalam, Muhammad Lestari, Sastri Ayu Missasi, Vallahatullah Muhammad Lathief Syaifussalam Naufal Sinatria Nurhasanah, Isye Susana Pilopa, Okta Pilopa, Okta Praseptiawan, Mugi R. Rizal Isnanto Rahman Indra Kesuma Ramdani, Ahmad Luky Ramdani, Ahmad Luky Sawitri, Riska Agi Syaifussalam, M. Lathief Ufaira, Rifda Alda Untoro, Meida Cahyo Wafa Zahiroh, Nadiyah Wicaksono, Imam Eko Wigati, Meilia Wilantika, Rima Yuli Christyono Yunira, Eka Nur'azmi