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All Journal Jurnal Simetris Bulletin of Electrical Engineering and Informatics Telematika : Jurnal Informatika dan Teknologi Informasi Jurnas Nasional Teknologi dan Sistem Informasi Computatio : Journal of Computer Science and Information Systems JRSI (Jurnal Rekayasa Sistem dan Industri) JURNAL REKAYASA TEKNOLOGI INFORMASI Innovation in Research of Informatics (INNOVATICS) Jurnal Pengabdian Siliwangi Jati Emas (Jurnal Aplikasi Teknik dan Pengabdian Masyarakat) International Journal of Applied Sciences and Smart Technologies
Heni Sulastri
Program Studi Informatika, Fakultas Teknik, Universitas Siliwangi
Agriculture, Biological Sciences & Forestry Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Public Health Social Sciences Other

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ITGbM PELATIHAN APLIKASI PENDUKUNG KEPTUSAN PEMILIHAN CALON PESERTA LOMBA OLIMPIADE OLAHRAGA SISWA NASIONAL TINGKAT SEKOLAH DASAR Neng Ika Kurniati; Heni Sulastri
Jurnal Pengabdian Siliwangi Vol 5, No 1 (2019)
Publisher : LPPM Univeristas Siliwangi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37058/jsppm.v5i1.572

Abstract

Salah satu program pemerintah dalam meningkatkan kualitas sumber daya manusia adalah dengan menyelenggarakan Olimpiade Olahraga Siswa Nasional (O2SN). Tujuan dilaksanakan Olimpiade Olahraga Siswa Nasional (O2SN) ini yaitu memfasilitasi dan memotivasi para siswa yang mempunyai bakat di cabang olahraga, sehingga para siswa dapat meningkatkan skill dan kemampuan mereka sesuai dengan bidang yang dimiliki. Pemilihan siswa-siswi yang mengikuti lomba olimpiade biasanya dilakukan oleh guru ataupun kepala sekolah di Sekolah Dasar dengan cara manual melaui test dan mempertimbangkan nilai olahraga siswa, sehingga membutuhkan waktu yang sangat lama, karena menyeleksi satu persatu siswa terlebih dahulu, disamping itu masih bisa terjadi kesalahan dalam pengolahan data yang digunakan pada tahap seleksi pemilihan siswa, oleh karna itu perlu dibuat Aplikasi pendukung keputusan yang diharapkan membantu pengambil keputusan dalam menentukan siswa-siswi yang paling tepat dalam mengikuti lomba Olimpiade Olahraga Siswa Nasional (O2SN) untuk mewakili tingkat nasional, dengan menerapkan metode Simple Additive Weighting (SAW) sebagai pengambilan keputusan. Adanya aplikasi pendukung keputusan pemilihan calon peserta lomba Olimpiade Olahraga Siswa Nasional (O2SN) ini lebih cepat dan mengurangi kesalahan dalam pengambilan keputusan. Kata kunci : Olimpiade Olahraga Siswa Nasional (O2SN); Aplikasi Pendukung Keputusan; Simple Additive Weighting (SAW).
Improving the Performance of Posyandu Cadres with SIPPOS: Posyandu Service Information System in the Sangkali Tamansari Community Health Center Area Tasikmalaya City: Peningkatan Kinerja Kader Posyandu dengan SIPPOS: Sistem Informasi Pelayanan Posyandu di Wilayah Puskesmas Sangkali Tamansari Kota Tasikmalaya Heni Sulastri; Siti Yuliyanti; Neng Ika Kurniati; Muhammad Al-Husaini; Hen Hen Lukmana
JATI EMAS (Jurnal Aplikasi Teknik dan Pengabdian Masyarakat) Vol. 10 No. 1 (2026): Jati Emas (Jurnal Aplikasi Teknik dan Pengabdian Masyarakat)
Publisher : DPD Jatim Perkumpulan Dosen Indonesia Semesta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36339/je.v10i1.480

Abstract

Posyandu cadres have a strategic role in the promotion and prevention of public health services at the primary level. However, many cadres rely on manual recording systems that are less efficient. This community service focuses on training, mentoring, and monitoring the implementation of the system with the aim of improving the performance of Posyandu cadres through the implementation of SIPPOS (Posyandu Service Information System). SIPPOS is an information system to assist Posyandu cadres in managing health service data more quickly. Community service activities include SIPPOS socialization to cadres and health center officers, including training on system usage and technical assistance. Evaluation of the effectiveness of SIPPOS use in routine Posyandu activities, and program sustainability in order to expand the benefits of the community service reach. This community service is expected to significantly improve Posyandu cadres in mastery of information technology and the accuracy of service data recording.
Principal Component Analysis-Driven Feature Reduction for Predicting Coffee Quality Using a Machine Learning Approach Siti Yuliyanti; Heni Sulastri; Sakifah
International Journal of Applied Sciences and Smart Technologies Vol. 8 No. 1 (2026): Volume 08, Issue 1, June 2026
Publisher : Faculty of Science and Technology, Universitas Sanata Dharma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24071/pmjkr989

Abstract

Coffee quality assessment using a machine learning approach faces major challenges, including high data dimensionality and redundancy between features. Therefore, PCA is proposed as a feature reduction technique to improve the efficiency and accuracy of coffee quality prediction models. The research phase began with data acquisition, data cleaning, feature engineering, explanatory data analysis, testing the normalization of coffee parameter profiles, implementing PCA on Random Forest and XGBoost models, and then evaluating model performance. Model evaluation using MAE and MAPE showed that Random Forest provided more precise predictions than XGBoost, particularly when applying PCA. This resulted in a 39% performance increase for Random Forest from 0.11903 to 0.08542 and an 8% increase for XGBoost, shifting the score from 0.12511 to 0.11570. Prediction visualization reinforced the consistency and precision of the Random Forest model, regardless of whether PCA was used. The findings of this study highlight the importance of feature cleaning and engineering, and the role of PCA in improving the precision of coffee quality predictions. The use of the Random Forest model with PCA is recommended as an efficient method for modeling the quality of Arabica coffee, taking into account sensory and environmental factors.
Co-Authors Acep Irham Gufroni Alam Rahmatulloh Anindita Septiarini, Anindita Euis Nur Fitriani Dewi Gilang Saeful Anwar Hairah, Ummul Hen Hen Lukmana Husen Husen Husni Mubarok Iwan Sutrisman Mohammad Rizal Ramli Muhammad Al-Husaini Muhammad Anwari Nanda Adi Pamungkas Neng Ika Kurniati Neng Ika Kurniati Nur Widiyasono Puspitasari, Novianti Rianto, Rianto Sakifah Siti Yuliyanti Syifa Sefia Iasha Tejawati, Andi