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All Journal Jurnal Pengabdian kepada Masyarakat Nusantara Enthusiastic : International Journal of Applied Statistics and Data Science MDP Student Conference
Rahmatika, Alfilia Hilda
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Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Electrical & Electronics Engineering Engineering Mathematics Social Sciences

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Pendampingan Diversifikasi Olahan Ikan Gurame untuk Peningkatan Nilai Tambah Hasil Perikanan Desa Tumiyang Banyumas Sumunar, Kurnia Indah; Rahmatika, Alfilia Hilda; Adiyana, Imam
Jurnal Pengabdian kepada Masyarakat Nusantara Vol. 6 No. 4 (2025): Edisi Oktober - Desember
Publisher : Lembaga Dongan Dosen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55338/jpkmn.v6i4.7589

Abstract

Desa Tumiyang Kabupaten Banyumas merupakan salah satu daerah penghasil ikan gurame yang cukup potensial, sehingga keberadaannya menjadi sumber pendapatan utama bagi mayoritas masyarakat setempat. Peluang untuk pengembangan usaha olahan ikan yang lebih bervariasi masih terbuka lebar. Namun berdasarkan wawancara dengan kepala desa, pemanfaatan hasil panen ikan gurame masih terbatas pada penjualan ikan segar sehingga nilai ekonominya belum optimal. Salah satu permasalahan yang dihadapi masyarakat adalah kurangnya pengetahuan dan keterampilan dalam mengolah ikan gurame menjadi produk olahan yang bernilai ekonomi. Selain itu, belum adanya strategi pemasaran yang efektif. Menjawab kebutuhan tersebut, solusi yang ditawarkan adalah berupa pendampingan kepada masyarakat Desa Tumiyang untuk meningkatkan nilai tambah hasil perikanan ikan gurame. Kegiatan pengabdian kepada masyarakat ini bertujuan untuk meningkatkan pengetahuan dan keterampilan masyarakat Desa Tumiyang dalam mengolah ikan gurame menjadi produk olahan bernilai tambah, khususnya kerupuk. Metode kegiatan meliputi penyuluhan tentang pentingnya diversifikasi olahan ikan dan metode pemasaran, selanjutnya pelatihan teknis pembuatan kerupuk gurame, praktik langsung, serta pembimbingan untuk pengemasan produk. Hasil pengabdian ini adalah terjadi peningkatan pengetahuan, keterampilan praktik anggota PKK dan Kelompok Usaha Bersama Desa Tumiyang yaitu dari 63% menjadi 85%. Selain itu, peserta menjadi termotivasi untuk berwirausaha dengan mengembangkan usaha olahan gurame. Dengan demikian, program pendampingan ini membuktikkan inovasi dan diversifikasi olahan ikan dapat menjadi strategi efektif untuk meningkatkan nilai tambah hasil perikanan sekaligus mendorong kemandirian ekonomi masyarakat Desa Tumiyang.
Recommending E-Commerce Platforms for MSMEs: A Sentiment Analysis Approach Adiyana, Imam; Kurniawan, Angga; Rahmatika, Alfilia Hilda; Setiono, Nisrina Hanifa; Gumelar, Satya Fajar
Enthusiastic : International Journal of Applied Statistics and Data Science Volume 5 Issue 2, October 2025
Publisher : Universitas Islam Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20885/enthusiastic.vol5.iss2.art8

Abstract

The rapid growth of e-commerce in Indonesia presents significant opportunities for micro, small, and medium enterprises (MSMEs), yet the diversity of marketplace platforms complicates the selection of an optimal sales channel. This study addressed this challenge by developing a data-driven recommendation system based on sentiment analysis of user reviews. Utilizing a dataset of 80,000 reviews scraped from four major platforms on the Google Play Store (Shopee, Tokopedia, Lazada, and Blibli), two classification approaches were implemented and compared: support vector machine (SVM) and long short-term memory (LSTM). Both models demonstrated a competitive performance, enabling effective sentiment categorization. Furthermore, multinomial logistic regression was employed to analyze the influence of key variables rating, number of likes, and marketplace brand on sentiment outcomes. The analysis revealed that Shopee yielded the highest probability of receiving positive reviews (97.82%) and showed no significant association with negative sentiment. Consequently, this study recommends Shopee as the primary platform for MSMEs to enhance their digital presence and sales performance. The primary contribution lies in integrating machine learning-based sentiment analysis with statistical modelling to generate actionable, evidence-based marketplace recommendations for MSMEs.
Understanding Generation Z’s Mental Health in Relation to Working Hours: A TikTok Sentiment Analysis Approach Putri, Isyiffah Falujjah Anugrah; Rahmatika, Alfilia Hilda; Miranda, Bella Okta Sari; Adiyana, Imam
MDP Student Conference Vol 5 No 1 (2026): The 5th MDP Student Conference 2026
Publisher : Universitas Multi Data Palembang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35957/mdp-sc.v5i1.15335

Abstract

In the digital work environment, long working hours and blurred work-life boundaries have become increasingly common, raising concerns about employees’ mental health, particularly among Generation Z. This study examines how Generation Z perceives working hours and their impact on mental health using social media–based sentiment analysis. Data were collected from 848 TikTok videos posted between 2023 and 2025, consisting of captions and comments related to work-related stress. Sentiment classification was performed using machine learning models, namely Multinomial Naïve Bayes, Support Vector Machine (SVM), and Multilayer Perceptron (MLP). Text representation employed Bag-of-Words and Term Frequency–Inverse Document Frequency (TF-IDF). The results indicate that positive and negative sentiments dominate discussions, reflecting strong emotional responses to working-hour pressure, while neutral sentiment remains difficult to identify. Among the evaluated models, SVM with a radial basis function kernel achieved the best overall performance. These findings highlight the potential of TikTok based sentiment analysis for understanding Generation Z’s mental health in digital work contexts.
Co-Authors Adiyana, Imam Angga Kurniawan Bella Okta Sari Miranda Gumelar, Satya Fajar Putri, Isyiffah Falujjah Anugrah Setiono, Nisrina Hanifa Sumunar, Kurnia Indah