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All Journal Jurnal Online Mahasiswa (JOM) Bidang Pertanian Mattawang: Jurnal Pengabdian Masyarakat Journal of Applied Data Sciences Jurnal Pengabdian kepada Masyarakat Karya Nyata: Jurnal Pengabdian Kepada Masyarakat
Netti Herawati
Unknown Affiliation
Agriculture, Biological Sciences & Forestry Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Environmental Science Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Public Health Social Sciences Other

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PENAMBAHAN BERBAGAI PERISA DAN BAHAN CAMPURAN TERHADAP PREFERENSI KONSUMEN PADA SOSIS BELUT (Monopterus albus) ', Suntoro; Rossi, Evy; Herawati, Netti
Jurnal Online Mahasiswa (JOM) Bidang Pertanian Vol 2, No 1 (2015): Wisuda February 2015
Publisher : Jurnal Online Mahasiswa (JOM) Bidang Pertanian

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Abstract

The purpose of this study was to determine the effect of a variety of seasioning and seasioning mixed materials to test consumer preferences in eel sausages (Monopterus albus). This research was carried out experiments using nine treatments, which consists of: K1: basic formulation, K2: The addition of carrageenan 1% + 1% barbeque seasioning. (w/w), K3: The addition of carrageenan 1% + 1% curry seasioning. (w/w), K4: The addition of carrot flour 1.5% + 1% barbeque seasioning. (w/w), K5: The addition of flour carrot curry seasioning 1.5% + 1%. (w/w), K6: The addition of egg yolks 2% + barbeque seasioning 1%. (w/w), K7: The addition of 2% egg yolks  + 1% curry seasioning. (w/w), K8: The addition of 1.5% oyster mushrooms + 1% barbeque seasioning. (w/w), and K9: The addition of 1.5% oyster mushroom + 1% curry seasioning. (w/w). Data were analyzed statistically by using a Preference Test Mapping with assistance XL STAT software version 2013. Test hedonic and descriptive analyzed using PCA (Principal Component Analysis). Agglomerative hierarchical clustering (AHC) was used to see all grades of eel sausage. Based on the descriptive analysis using PCA and hedonic analysis using the AHC showed that treatment K2 (addition of 1% carrageenan seasioning barbeque + 1%) and treatment of K4 (addition of carrot flour 1.5% + 1% seasioning barbeque) were expressed panelists who liked their color. Preference Mapping analysis results showed that the treatment K2 (addition of 1% carrageenan + barbeque  seasioning 1%) and treatment of K4 (addition of 1.5% carrot flour + 1% barbeque seasioning) was the best treatment with the ability to be Able to explain the diversity of the data is by 80-100%.   Keywords : Eel, sausage, carrageenan, curry seasioning, barbeque seasioning, AHC,   PCA, Preference Mapping.
Deep Learning untuk Solusi Cerdas: Workshop Penggunaan Aplikasi AI untuk Kehidupan Sehari-Hari Netti Herawati; K Ghazali; Uci Suryani; M Bambang Purwanto
Karya Nyata : Jurnal Pengabdian kepada Masyarakat Vol. 2 No. 2 (2025): Juni : Karya Nyata : Jurnal Pengabdian kepada Masyarakat
Publisher : Lembaga Pengembangan Kinerja Dosen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/karyanyata.v2i2.1329

Abstract

This community service activity is motivated by the rapid development of deep learning and artificial intelligence (AI) which has penetrated various aspects of life. Prasetiya Mandiri Polytechnic held a workshop "Deep Learning for Smart Solutions: Workshop on the Use of AI Applications for Daily Life" to increase AI literacy among students and lecturers. The method of implementing this activity includes the preparation of workshop materials, the implementation of presentation sessions, discussions, and practical exercises, as well as evaluation through questionnaires and observations. The results of the activity showed high enthusiasm of participants and increased understanding of the basic concepts of deep learning and AI applications. The interpretation of the questionnaire data showed a high level of participant satisfaction, with an average score of 4.5 on a scale of 5. The results of the participants' practical exercises also demonstrated their ability to apply AI concepts to create simple applications. This activity succeeded in achieving its goal of improving participants' digital skills and encouraging the application of AI in learning and research at Prasetiya Mandiri Polytechnic. In conclusion, this workshop is effective in improving AI literacy and providing practical experience to participants, and has the potential to be further developed by adding more intensive and diverse practice sessions
Empowering Mothers in Training Active Eating in Children Aged 8-18 Months in Suka Maju Village, Mestong Muara Jambi District : Pemberdayaan Ibu dalam Melatih Makan Aktif pada Anak Usia 8-18 Bulan Di Desa Suka Maju Kecamatan Mestong Muara Jambi Nuraidah; Netti Herawati
Mattawang: Jurnal Pengabdian Masyarakat Vol. 5 No. 3 (2024)
Publisher : Yayasan Ahmar Cendekia Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35877/454RI.mattawang3082

Abstract

This high level of nutritional problems is an important problem that needs to be followed up, so that the impact of nutritional problems does not interfere with growth and development. Suka Maju Village has 15 malnourished babies and 59 undernourished babies, in 2022. This can result in stunting. In order for children's growth and development to run well, children must eat enough. One of the methods recommended by WHO-UNICEF is active/responsive feeding techniques. The aim of community service is to increase mothers' knowledge and skills in actively feeding their children. The target of community service is 20 mothers and 5 cadres. This activity was carried out in Suka Maju village, Mestong District, Muaro Jambi Regency. The method of this activity is socialization of materials and education/demonstration of how to wash hands and actively feed children. After the socialization activities were carried out, there was an increase in mother's knowledge before with an average of 4.9 and after an average of 9.06 socialization of 4.15. There was an increase in cadre knowledge with an average of 6.4 before and after 9.8. Increased by 3.4. And there was an increase in maternal skills before with a mean of 4.4 and after a mean of 12.9 an increase of 8.5. There was an increase in average cadre skills before 8.8 and after 14.0. Increased by 5.2. The conclusion is that there has been an increase in the knowledge and skills of mothers. With the help of partners, monitoring and sustainability needs to be done so that mothers can provide food and get children used to being independent in eating.
PENGUATAN KEMAMPUAN PETANI MELALUI BIMBINGAN TEKNIS DAN SEKOLAH LAPANG BUDIDAYA ORGANIK KOMODITAS TANAMAN HORTIKULTURA DI POKDARWIS PAINGAN, KABUPATEN PADANG PARIAMAN Silvia Permata Sari; Dini Hervani; Muhsanati, Muhsanati; Ricky Akbar; Lakry Matlaf Putra; Zaini, Zaini; Netti Herawati; Fachrizky Erdi Prawira; Hafiz Reyhan; Shelvi Anggraini; Muhammad Farid Rizki; Irsya Dunas; Yura, David
J-ABDI: Jurnal Pengabdian kepada Masyarakat Vol. 5 No. 4: September 2025
Publisher : Bajang Institute

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Abstract

Pengabdian kepada masyarakat ini bertujuan untuk meningkatkan kemampuan petani dalam mengelola pertanian organik, khususnya pada komoditas kacang tanah, jagung manis, dan cabai. Kegiatan ini dilaksanakan di Nagari Guguak Kuranji Hilir, Kec. Sungai Limau, Kab. Padang Pariaman dari bulan Mei sampai Agustus 2025, dengan melibatkan 45 orang peserta yang terdiri dari petani lokal dan anggota PokDarwis Paingan. Kegiatan ini berupa bimbingan teknis dan sekolah lapang yang berfokus pada teknik budidaya organik yang ramah lingkungan. Hasil dari kegiatan ini menunjukkan bahwa peserta memiliki pemahaman yang lebih baik tentang pertanian organik dan dapat mengaplikasikan ilmu yang diperoleh dalam praktik pertanian mereka sehari-hari
Adaptive k-Nearest Neighbor Learning for Robust Modal Regression on Multimodal and Heavy-Tailed Data Sutarman Sutarman; Netti Herawati; Adli Abdillah Nababan
Journal of Applied Data Sciences Vol 7, No 2: May 2026
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v7i2.1221

Abstract

Modal regression has attracted increasing attention as an alternative to mean-based regression, particularly in settings characterized by heteroscedasticity, multimodal conditional distributions, and heavy-tailed noise. In such scenarios, estimators based on central tendency may yield predictions that fall in low-density regions of the response space. This paper proposes an adaptive k-nearest neighbor framework for modal regression that integrates entropy-guided neighborhood selection with nonparametric mode estimation, including MeanShift clustering and one-dimensional kernel density estimation. The proposed approach adjusts neighborhood size based on local uncertainty, allowing the regression model to adapt to variations in data density without relying on a globally fixed parameter. Extensive experiments on simulated datasets and real-world benchmarks demonstrate that adaptive modal regression methods generally reduce or stabilize prediction errors relative to fixed-k modal regression and classical kNN mean and median estimators, particularly under heteroscedastic and multimodal conditions, although the magnitude of improvement varies across scenarios. Statistical tests confirm significant differences in most experimental settings, with practical gains ranging from incremental to substantial depending on data complexity. In addition to accuracy, computational behavior is explicitly examined. The findings show a trade-off between computational cost and predictive robustness: entropy-guided adaptive modal regression requires additional runtime due to neighborhood adaptation and density estimation, but this overhead increases proportionally with sample size and remains manageable for medium-sized datasets. Based on these results, adaptive modal regression provides a useful and flexible alternative for regression tasks involving complex and heterogeneous data distributions where robustness is prioritized over minimal computation time.
Co-Authors ', Suntoro Adli Abdillah Nababan Akbar, Ricky Dini Hervani Fachrizky Erdi Prawira Hafiz Reyhan Irsya Dunas K Ghazali Lakry Matlaf Putra M Bambang Purwanto Muhammad Farid Rizki MUHSANATI, MUHSANATI Nuraidah Rossi, Evy Shelvi Anggraini Silvia Permata Sari Sutarman Sutarman Uci Suryani Yura, David Zaini Zaini