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All Journal SELAPARANG: Jurnal Pengabdian Masyarakat Berkemajuan JOURNAL OF SCIENCE AND SOCIAL RESEARCH
Asha Sembiring
Universitas Satya Terra Bhinneka
Agriculture, Biological Sciences & Forestry Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Education Engineering Environmental Science Health Professions Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Medicine & Pharmacology Nursing Public Health Social Sciences Other

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Optimalisasi skill digital marketing berbasis ICT untuk siswa SMK jurusan akuntansi dan perkantoran Junerdi Nababan; Asha Sembiring; Zulfa Hazimah; Kusnadi Kusnadi; Mutiha Aristo Ravel
SELAPARANG: Jurnal Pengabdian Masyarakat Berkemajuan Vol 9, No 6 (2025): November
Publisher : Universitas Muhammadiyah Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31764/jpmb.v9i6.34283

Abstract

Abstrak Perkembangan teknologi digital menuntut peningkatan keterampilan digital marketing yang berbasis teknologi informasi bagi siswa SMK, khususnya jurusan Akuntansi dan Perkantoran. Program pengabdian kepada masyarakat ini bertujuan mengoptimalkan skill digital marketing berbasis ICT untuk siswa SMK Akuntansi dan Perkantoran SMK Negeri 1 Kutalimbaru. Kegiatan ini diikuti oleh 24 siswa sebagai mitra sasaran yang memperoleh pelatihan praktik pembuatan katalog produk digital menggunakan Canva, pembuatan laporan respons kampanye menggunakan Excel dan Google Sheets, analisis data pelanggan dari form pemesanan, serta penjadwalan konten dan follow-up pelanggan. Metode pelaksanaan menggunakan pendekatan Project Based Learning dengan kombinasi ceramah, praktik langsung, diskusi, dan evaluasi. Hasil pelatihan menunjukkan peningkatan kemampuan siswa dalam menguasai alat digital yang relevan dengan kebutuhan industri 5.0, tercermin dari kemampuan mereka membuat materi promosi digital yang profesional dan laporan analisis data kampanye yang informatif. Program ini berkontribusi pada peningkatan daya saing lulusan SMK dalam menghadapi tantangan dunia kerja digital dan mendukung transformasi pendidikan vokasi berbasis ICT. Kata kunci: pengabdian masyarakat; pelatihan; digital marketing; ICT; SMK akuntansi dan perkantoran. Abstract The development of digital technology requires an increase in information technology-based digital marketing skills for vocational school students, especially those majoring in accounting and office administration. This community service program aims to optimize ICT-based digital marketing skills for vocational high school students in the Accounting and Office Administration departments at State Vocational High School 1 Kutalimbaru. The program was attended by 24 students as target participants who received practical training in creating digital product catalogs using Canva, generating campaign response reports using Excel and Google Sheets, analyzing customer data from order forms, and scheduling content and customer follow-ups. The implementation method used a Project-Based Learning approach combined with lectures, hands-on practice, discussions, and evaluations. The training results demonstrated an improvement in students' ability to master digital tools relevant to Industry 5.0 needs, reflected in their ability to create professional digital promotional materials and informative campaign data analysis reports. This program contributes to enhancing the competitiveness of vocational school graduates in facing the challenges of the digital workplace and supports ICT-based vocational education transformation. Keywords: community service; training; digital marketing; ICT; vocational school of accounting and office administration.
Transformasi digital ibu posyandu : peningkatan kapasitas melalui konten kreatif media sosial untuk edukasi dan ekonomi kreatif Asha Sembiring; Mahlian Elyana
SELAPARANG: Jurnal Pengabdian Masyarakat Berkemajuan Vol 10, No 2 (2026): April
Publisher : Universitas Muhammadiyah Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31764/jpmb.v10i2.38630

Abstract

Abstrak Program pengabdian ini bertujuan untuk meningkatkan kapasitas kader Posyandu Desa Pasar Melintang dalam pemanfaatan media sosial sebagai sarana edukasi kesehatan dan pemberdayaan ekonomi keluarga. Permasalahan utama yang dihadapi mitra adalah rendahnya literasi digital, dokumentasi kegiatan yang tidak terstruktur, dan belum optimalnya penyebaran pesan kesehatan melalui platform digital. Kegiatan dilaksanakan dengan pendekatan pelatihan partisipatif berbasis lokakarya satu hari yang memadukan prinsip community-based education dan learning by doing. Peserta dilatih untuk merencanakan pesan edukatif, memproduksi konten kreatif sederhana menggunakan aplikasi gratis (Canva, CapCut), serta menyusun kalender unggahan dan arsip digital bersama di Google Drive. Hasil kegiatan diukur secara kuantitatif melalui pre-test dan post-test yang menilai kemampuan peserta dalam merancang pesan kesehatan, membuat konten edukatif, dan mengelola distribusi informasi melalui media sosial. Hasil evaluasi menunjukkan adanya peningkatan kemampuan kader pada ketiga aspek tersebut. Selain itu, terbentuk sistem kerja digital sederhana berupa kalender unggahan dan struktur folder arsip yang mempermudah pengelolaan serta re-use konten lintas kegiatan. Program ini menunjukkan bahwa integrasi literasi digital dengan strategi konten kreatif berpotensi memperluas jangkauan edukasi kesehatan Posyandu, yang ditunjukkan melalui peningkatan produksi dan publikasi konten, sekaligus membuka peluang ekonomi keluarga melalui promosi produk rumah tangga yang etis dan bertanggung jawab. Kata kunci: literasi digital; posyandu; pelatihan partisipatif; konten kreatif; pemberdayaan ekonomi. Abstract This community engagement program aims to enhance the capacity of Posyandu cadres in Pasar Melintang Village to utilize social media as a medium for health education and family economic empowerment. The main problems faced by the community partner include low digital literacy, unstructured activity documentation, and the suboptimal dissemination of health messages through digital platforms. The program was implemented through a one-day participatory workshop that combined the principles of community-based education and learning by doing. Participants were trained to design educational messages, produce simple creative content using free applications such as Canva and CapCut, and develop a posting calendar and shared digital archive on Google Drive. The program outcomes were measured quantitatively through pre-tests and post-tests assessing participants’ ability to design health messages, create educational content, and manage information dissemination through social media. The evaluation results showed an improvement in cadres’ abilities across these three aspects. In addition, a simple digital work system was established in the form of a posting calendar and an archive folder structure that facilitated content management and cross-activity content reuse. This program shows that the integration of digital literacy and creative content strategies has the potential to expand the reach of Posyandu health education, as indicated by the increase in content production and publication, while also creating family economic opportunities through the ethical and responsible promotion of household products. Keywords: digital literacy; posyandu; participatory training; creative content; economic empowerment.
PERBANDINGAN PREDIKSI POLUSI UDARA MENGGUNAKAN LSTM DAN BILSTM Andre Pratama; Asha Sembiring; Junerdi Nababan; Muhammad Imam Zarkasyi; Novriza Rahayu
JOURNAL OF SCIENCE AND SOCIAL RESEARCH Vol. 8 No. 3 (2025): August 2025
Publisher : Smart Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54314/jssr.v8i3.3596

Abstract

Abstract: Air pollution has become a serious problem in densely populated urban areas such as DKI Jakarta. To mitigate its negative impacts, an accurate air pollution prediction system is necessary. This study compares the performance of two deep learning models, Long Short-Term Memory (LSTM) and Bidirectional Long Short-Term Memory (BiLSTM), in predicting PM10 concentration using air quality data from DKI Jakarta between 2016 and 2019. The research process includes data collection and preprocessing, model training, and model evaluation. Both models were tested with various parameters such as the number of hidden neurons, dropout rate, epochs, and batch size. The results consistently show that BiLSTM outperforms LSTM, achieving lower Root Mean Square Error (RMSE) values across 54 testing scenarios. The best BiLSTM configuration, with 64 hidden neurons, 0.2 dropout rate, 50 epochs, and batch size 16, yielded an RMSE of 9.311401. Meanwhile, the best LSTM configuration, with 128 hidden neurons, 0.1 dropout rate, 100 epochs, and batch size 16, produced an RMSE of 9.330554. The advantage of BiLSTM lies in its ability to process data bidirectionally, making it more effective in capturing temporal patterns for air pollution prediction compared to LSTM. Keywords: air pollution prediction, pollutant, deep learning, LSTM, BiLSTM Abstrak: Pencemaran udara menjadi masalah serius di wilayah perkotaan padat seperti DKI Jakarta. Untuk mengurangi dampak negatifnya, diperlukan sistem prediksi polusi udara yang akurat. Penelitian ini membandingkan performa dua model deep learning, Long Short-Term Memory (LSTM) dan Bidirectional Long Short-Term Memory (BiLSTM), dalam memprediksi konsentrasi PM10 menggunakan data kualitas udara DKI Jakarta tahun 2016-2019. Proses penelitian mencakup pengumpulan dan praproses data, pelatihan model, serta evaluasi model. Kedua model diuji dengan berbagai parameter seperti jumlah hidden neuron, dropout rate, epoch, dan batch size. Hasil menunjukkan BiLSTM lebih unggul secara konsisten dengan nilai Root Mean Square Error (RMSE) lebih rendah melalui 54 skenario pengujian. Konfigurasi terbaik BiLSTM menggunakan 64 hidden neuron, dropout rate 0.2, 50 epoch, dan batch size 16 menghasilkan RMSE 9.311401. Sedangkan konfigurasi LSTM terbaik pada 128 hidden neuron, dropout rate 0.1, 100 epoch, dan batch size 16 menghasilkan RMSE 9.330554. Keunggulan BiLSTM terletak pada kemampuannya memproses data dua arah, sehingga lebih efektif dalam menangkap pola temporal untuk prediksi polusi udara dibandingkan LSTM.  Kata kunci: prediksi polusi udara, polutan, deep learning, LSTM, BiLSTM
ANALISIS SENTIMEN PENGGUNA INSTAGRAM TERHADAP STATEMENT MENTERI KEUANGAN TENTANG "KEBIJAKAN GAJI GURU DAN DOSEN" MENGGUNAKAN NAIVE BAYES M. Imam Santoso; Nia Mardiah; Asha Sembiring
JOURNAL OF SCIENCE AND SOCIAL RESEARCH Vol. 8 No. 4 (2025): November 2025
Publisher : Smart Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54314/jssr.v8i4.4385

Abstract

Abstract: The Minister of Finance's statement regarding the teacher and lecturer salary policy sparked mixed public reactions, particularly on social media. This study aims to analyze the sentiment of the Indonesian public, particularly Instagram users, regarding this statement using the Nae Bayes algorithm. Data was collected through scraping using Instant Data Scrapper in August 2025, totaling 939 data points. Preprocessing steps included cleansing, tokenizing, stopword removal, and stemming. The data were then classified into two sentiment categories: positive and negative. The results showed that the majority of Instagram user sentiment tended to be negative (859 data points, representing 91.5%), while positive sentiment accounted for 89 data points, representing 9.5%. The Nae Bayes model achieved an accuracy of 0.87 in classifying public opinion. These findings indicate that the Nae Bayes algorithm is effective in analyzing public opinion on sensitive issues on social media. Furthermore, the results of this study can serve as a reference for the government and policymakers in understanding public perception and formulating more appropriate communication strategies related to education policy. Keyword: Sentiment Analysis, Nae Bayes, Minister of Finance, Instagram, Text Analysis. Abstrak: Pernyataan Menteri Keuangan tentang kebijakan gaji guru dan dosen memicu beragam reaksi publik, khususnya di media sosial. Penelitian ini bertujuan untuk menganalisis sentimen masyarakat Indonesia, terutama pengguna Instagram, terhadap pernyataan tersebut dengan menggunakan algoritma Nae Bayes. Data dikumpulkan melalui proses scraping menggunakan Instant Data Scrapper pada Agustus 2025 dengan jumlah 939 data. Kemudian dilakukan tahap praproses meliputi cleansing, tokenizing, stopword removal, dan stemming. Selanjutnya, data diklasifikasikan ke dalam dua kategori sentimen, yaitu positif dan negatif. Hasil penelitian menunjukkan bahwa mayoritas sentimen pengguna Instagram cenderung Negatif (859 data dengan persentase 91,5%), sedangkan sentimen positif berjumlah 89 data dengan persentase 9,5%. Model Nae Bayes mencapai tingkat akurasi sebesar 0,87 dalam mengklasifikasikan opini publik. Temuan ini mengindikasikan bahwa algoritma Nae Bayes efektif dalam menganalisis opini publik pada isu sensitif di media sosial. Selain itu, hasil penelitian ini dapat menjadi acuan bagi pemerintah dan pemangku kebijakan dalam memahami persepsi publik serta merumuskan strategi komunikasi yang lebih tepat terkait kebijakan pendidikan. Kata kunci: Sentimen Analisis, Nae Bayes, Menteri Keuangan, Instagram, Analisis Teks.
SINERGI BUDAYA DAN TEKNOLOGI DALAM DESAIN WEBSITE KATALOG BATIK BERBASIS E-COMMERCE Asha Sembiring; Alfan Ramadhan Sembiring; Junerdi Nababan; Kusnadi Kusnadi; Putri Putri
JOURNAL OF SCIENCE AND SOCIAL RESEARCH Vol. 9 No. 1 (2026): February 2026
Publisher : Smart Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54314/jssr.v9i1.5754

Abstract

Abstract: Batik is a valuable cultural heritage of Indonesia, combining artistic and historical significance. In the digital era, integrating Batik into an online catalog website can enhance cultural promotion and product sales. This study focuses on designing a Batik catalog website that merges traditional cultural values with modern digital technology to create an engaging, user-friendly experience. Using a comparative qualitative approach, several existing Batik catalog websites were analyzed to identify design strengths, weaknesses, and opportunities. Thematic and SWOT analysis were applied to examine visual design, navigation, and interactive features. Findings suggest that an optimal Batik catalog website should balance Batik’s visual aesthetics with functional e-commerce features, provide interactive elements, and ensure responsive purchasing processes. This approach improves user experience while promoting Batik as a cultural product. Keywords: Batik; website catalog; digital design; user experience; cultural heritage Abstrak: Batik merupakan warisan budaya Indonesia yang memiliki nilai seni dan sejarah yang tinggi. Di era digital, integrasi Batik ke dalam website katalog online dapat meningkatkan promosi budaya sekaligus penjualan produk. Penelitian ini bertujuan untuk merancang website katalog Batik yang menggabungkan nilai budaya tradisional dengan teknologi digital modern guna menciptakan pengalaman pengguna yang menarik dan mudah digunakan. Dengan menggunakan pendekatan kualitatif komparatif, beberapa website katalog Batik yang ada dianalisis untuk mengidentifikasi kekuatan, kelemahan, dan peluang desain. Analisis tematik dan SWOT digunakan untuk menilai desain visual, navigasi, serta fitur interaktif. Hasil penelitian menunjukkan bahwa website katalog Batik yang optimal harus mampu menyeimbangkan estetika visual Batik dengan fitur e-commerce yang fungsional, menyediakan elemen interaktif, serta memastikan proses pembelian yang responsif. Pendekatan ini meningkatkan pengalaman pengguna sekaligus mempromosikan Batik sebagai produk budaya. Kata kunci: Batik; katalog website; desain digital; pengalaman pengguna; warisan budaya
Co-Authors Alfan Ramadhan Sembiring Andre Pratama Junerdi Nababan Kusnadi Kusnadi M. Imam Santoso Mahlian Elyana Muhammad Imam Zarkasyi Mutiha Aristo Ravel Nia Mardiah Novriza Rahayu Putri Putri Zulfa Hazimah