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All Journal Jurnal Aplikasi Bisnis dan Manajemen (JABM) E-Journal Jurnal Pengabdian kepada Masyarakat Nusantara Jurnal Abdi Masyarakat Indonesia Enthusiastic : International Journal of Applied Statistics and Data Science Prosiding Seminar Nasional Teknologi Informasi dan Bisnis MDP Student Conference
Alfilia Hilda Rahmatika
Universitas Telkom
Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Mathematics Mechanical Engineering Physics Public Health 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.
Leveraging Market Basket Analysis to Develop Sales Strategies for MSMEs: a Case Study of Los in Between Satya Fajar Gumelar; Ega Adrianto; Alfilia Hilda Rahmatika
Jurnal Aplikasi Bisnis dan Manajemen Vol. 12 No. 2 (2026): JABM, Vol. 12 No. 2, May 2026
Publisher : School of Business, Bogor Agricultural University (SB-IPB)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17358/jabm.12.2.385

Abstract

Background: Micro, Small, and Medium Enterprises (MSMEs) a cornerstone of Indonesia’s economic, contributing approximately 61% to the national GDP (Haryo Limanseto, 2022). However, MSMEs, particularly in the competitive Food and Beverage (F&B) sector, face persistent challenges including limited access to capital, technological adoption gaps, and volatile consumer preferences (Badan Pusat Statistik, 2023). These factors make revenue stability a critical issue. Purpose:  Through a case study of LOS In Between, this research aims to: (1) demonstrate the application of MBA in a resource-constrained, offline MSME setting; (2) identify product associations to inform bundling and upselling strategies for the business; and (3) propose a replicable analytical approach that can be adapted by other small-scale F&B businesses to enhance sales performance. This study aims to analyze consumer purchasing patterns through Market Basket Analysis (MBA) and to provide actionable data-driven strategies to improve sales performance and competitiveness in MSMEs. Design/methodology/approach: This study applies Market Basket Analysis using the Apriori algorithm to transactional data from LOS In Between (January–June 2025). Association rules derived from support, confidence, and lift metrics were translated into practical sales strategies—including bundling, upselling, and cross selling. Findings/Result: The analysis revealed that STM functions as an anchor product frequently purchased with items such as SJ and WF, making it ideal for strategic bundling. Products with weaker associations, such as CMM, were considered more suitable for upselling promotions. The findings show that even MSMEs with modest transaction volumes can leverage simple data analytics to uncover purchasing patterns, optimize sales, and enhance customer experience. Conclusion: MBA provides a practical and scalable analytical tool for MSMEs to design evidence-based sales strategies. By leveraging transaction data, MSMEs can increase revenue, strengthen customer engagement, and sustain competitiveness in dynamic market environments.Originality/value (State of the art): This study addresses the gap by adapting Market Basket Analysis to a micro-scale F&B, LOS In Between. Its novelty lies not only in applying MBA to this constrained setting but also in proposing a practical methodology that converts association rules into actionable strategies like bundling and upselling, designed for periodic re-mining to track preference shifts. The research also outlines how MBA can be integrated with lightweight decision frameworks suitable for MSMEs, providing localized evidence from Indonesia’s F&B sector.  Keywords:   market basket analysis, sales strategies, msmes, apriori, purchase patterns
Understanding Generation Z’s Mental Health in Relation to Working Hours: A TikTok Sentiment Analysis Approach Isyiffah Falujjah Anugrah Putri; Alfilia Hilda Rahmatika; Bella Okta Sari Miranda; Imam Adiyana
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.
Perbandingan Kinerja SVM dan Zara Zevira Wulandari; Isyiffah Falujjah Anugrah Putri; Jihan Nur Kencana Siwi; Bella Okta Sari Miranda; Alfilia Hilda Rahmatika
Prosiding Seminar Nasional Teknologi Informasi dan Bisnis Prosiding Seminar Nasional Teknologi Informasi dan Bisnis (SENATIB) 2026
Publisher : Fakultas Ilmu Komputer Universitas Duta Bangsa Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Dominasi Shopee di pasar e-commerce Indonesia punya konsekuensi langsung, yakni ulasan penggunanya di Google Play Store menumpuk terlalu cepat untuk dibaca dan dikategorikan satu per satu. Penelitian ini menguji apakah SVM atau MLP lebih cocok menjalankan Aspect-Based Sentiment Analysis (ABSA) terhadap 290.338 ulasan Shopee yang terkumpul sepanjang 2025. Teksnya dibersihkan, dilabeli ke lima aspek layanan, lalu diubah jadi representasi TF-IDF sebelum dataset dibagi 80:20 untuk pelatihan dan pengujian. Ada lima model yang dibandingkan dengan empat kernel SVM (Linear, Polynomial, RBF, Sigmoid) dan satu MLP. Sigmoid unggul tipis dengan akurasi 79,9%, diikuti RBF (79,2%), Linear (78,0%), Polynomial (76,4%), dan MLP di posisi terakhir dengan 75,56%. Satu masalah yang sama muncul di kelima model, yakni sentimen netral paling sulit dikenali, kerap tertukar dengan positif atau negatif, dan ini terlihat konsisten di seluruh confusion matrix. Hasilnya cukup jelas, SVM, khususnya kernel Sigmoid, lebih unggul untuk ABSA pada ulasan Shopee dibanding MLP. Adapun dari sisi sentimen itu sendiri, opini pengguna terhadap aplikasi ini didominasi kesan positif.
Pelatihan dan Pendampingan Literasi Keuangan serta Penguatan Motivasi Usaha bagi Anggota TP-PKK Desa Tumiyang, Kecamatan Kebasen, Kabupaten Banyumas, Jawa Tengah Kurnia Indah Sumunar; Alfilia Hilda Rahmatika; Imam Adiyana
Jurnal Abdi Masyarakat Indonesia Vol 6 No 4 (2026): JAMSI - Juli 2026
Publisher : CV Firmos

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54082/jamsi.3003

Abstract

Kegiatan pengabdian kepada masyarakat ini bertujuan meningkatkan literasi keuangan dan motivasi kewirausahaan anggota TP-PKK Desa Tumiyang sebagai tindak lanjut program sebelumnya yang telah meningkatkan keterampilan teknis produksi. Hasil evaluasi dan wawancara lanjutan menunjukkan bahwa sebagian anggota masih ragu memulai usaha secara mandiri, kurang percaya diri dalam mempromosikan produk, belum melakukan pencatatan keuangan secara rutin, serta masih mencampurkan keuangan usaha dengan keuangan rumah tangga sehingga tidak dapat menghitung keuntungan secara akurat. Program ini melibatkan 35 peserta melalui metode penyuluhan, pelatihan praktik, dan monitoring berkelanjutan. Penyuluhan difokuskan pada pemahaman dasar pemisahan keuangan usaha dan rumah tangga, pencatatan transaksi sederhana, penyusunan laporan laba rugi, serta pembentukan mindset wirausaha. Pelatihan dilakukan dengan pendekatan learning by doing, di mana peserta mempraktikkan langsung pencatatan keuangan menggunakan buku kas sederhana, menghitung laba usaha berdasarkan data riil, serta membuat materi promosi digital untuk WhatsApp dan media sosial. Hasil kegiatan menunjukkan peningkatan pemahaman literasi keuangan dari 66% menjadi 88%, keterampilan pencatatan keuangan dari 60% menjadi 85%, serta sikap dan motivasi kewirausahaan dari 70% menjadi 80%. Program ini mampu memperkuat literasi keuangan yang terintegrasi dengan motivasi kewirausahaan sehingga peserta mulai mampu memisahkan keuangan usaha dan rumah tangga serta mulai berani mempromosikan produknya secara mandiri.
Co-Authors Bella Okta Sari Miranda Bella Okta Sari Miranda Ega Adrianto Gumelar, Satya Fajar Imam Adiyana Imam Adiyana Isyiffah Falujjah Anugrah Putri Isyiffah Falujjah Anugrah Putri Jihan Nur Kencana Siwi Kurnia Indah Sumunar Kurnia Indah Sumunar Nisrina Hanifa Setiono Zara Zevira Wulandari