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All Journal Dinamika Informatika INTENSIF: Jurnal Ilmiah Penelitian dan Penerapan Teknologi Sistem Informasi Jurnal Komtika (Komputasi dan Informatika) JURNAL PENDIDIKAN TAMBUSAI Informasi Interaktif Respati Jurnal Teknik Informatika (JUTIF) Jurnal Ekonomi dan Teknik Informatika International Journal Artificial Intelligent and Informatics Techno SENTRI: Jurnal Riset Ilmiah SmartComp Jurnal Komtika (Komputasi dan Informatika)
Sudarmawan, Sudarmawan
UNiversitas AMIKOM Yogyakarta
Aerospace Engineering Humanities Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Law, Crime, Criminology & Criminal Justice Social Sciences

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Analisis Sentimen Twitter Kuliah Online Pasca Covid-19 Menggunakan Algoritma Support Vector Machine dan Naive Bayes Setiawan, Hendrik; Utami, Ema; Sudarmawan, Sudarmawan
Jurnal Komtika (Komputasi dan Informatika) Vol 5 No 1 (2021)
Publisher : Universitas Muhammadiyah Magelang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31603/komtika.v5i1.5189

Abstract

The World Health Organization (WHO) COVID-19 is an infectious disease caused by the Coronavirus which originally came from an outbreak in the city of Wuhan, China in December 2019 which later became a pandemic that occurred in many countries around the world. This disease has caused the government to give a regional lockdown status to give students the status of "at home" for students to enforce online or online lectures, this has caused various sentiments given by students in responding to online lectures via social media twitter. For sentiment analysis, the researcher applies the nave Bayes algorithm and support vector machine (SVM) with the performance results obtained on the Bayes algorithm with an accuracy of 81.20%, time 9.00 seconds, recall 79.60% and precision 79.40% while for the SVM algorithm get an accuracy value of 85%, time 31.60 seconds, recall 84% and precision 83.60%, the performance results are obtained in the 1st iteration for nave Bayes and the 423th iteration for the SVM algorithm
Implementasi Pengembangan Sistem Model Water Fall Untuk Data Warehouse Akademik Sofan Tohir, Arik Sofan Tohir; Kusrini, Kusrini; Sudarmawan, Sudarmawan
INTENSIF: Jurnal Ilmiah Penelitian dan Penerapan Teknologi Sistem Informasi Vol 1 No 2 (2017): Vol. 1 No. 2 Agustus 2017
Publisher : Universitas Nusantara PGRI Kediri

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (234.158 KB) | DOI: 10.29407/intensif.v1i2.837

Abstract

Data warehouse is a concept and a technology to store transactional data from several sources that have been through the process of filtering and selection of data. By using the Ectract, Transform and Load (ETL) process in the data warehouse, OLTP data is processed to produce good data and ready for use for the analysis process. For the design of this warehouse data will be built by using the Nine Step Method from Kimbal, so that the resulting warhouse data can be as expected. For the development of life flow system (SDLC) with waterfall model. By using the wate fall model will be built a prototype to implement the data warehouse design results.
Pemberdayaan Masyarakat Melalui Pengembangan Ekowisata Berbasis Kearifan Lokal Dalam Mewujudkan Pariwisata Berkelanjutan di Dusun Tuing Desa Mapur Kabupaten Bangka Sudarmawan, Sudarmawan; Hidayat, Wahyu
SENTRI: Jurnal Riset Ilmiah Vol. 4 No. 12 (2025): SENTRI : Jurnal Riset Ilmiah, Desember 2025
Publisher : LPPM Institut Pendidikan Nusantara Global

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55681/sentri.v4i12.5096

Abstract

This study analyzes community empowerment through the development of ecotourism based on local wisdom in Tuing Hamlet. The novelty of this research lies in its integrative examination of social, institutional, and governance dimensions of ecotourism-based empowerment at the hamlet level, emphasizing local wisdom as both a cultural asset and a participatory governance mechanism. The study addresses three research questions: (1) what natural and cultural potentials support ecotourism development in Tuing Hamlet, (2) how local wisdom is mobilized in community empowerment processes, and (3) what structural challenges constrain empowerment outcomes. A qualitative approach was employed using observation, in-depth interviews, and document analysis. Data were analyzed through thematic analysis, involving data reduction, coding, categorization, and interpretation to identify key patterns of empowerment and existing constraints. The findings indicate that Tuing Hamlet possesses significant potential for ecotourism development, supported by the establishment of the Kelompok Tani Hutan (KTH) Pulau Punggur as a formal management institution and active participation of community groups, including youth, traditional leaders, and women’s organizations (PKK), in decision-making processes. This participation has fostered an emerging sense of community agency. However, empowerment remains at an early stage due to several challenges: limited access to financial resources caused by dependence on a single investor and the absence of government support, restricted access to knowledge and training, weak and non-transparent governance resulting from the lack of binding technical regulations, and the absence of direct economic benefits as ecotourism activities are not yet fully operational. These findings imply that sustainable ecotourism-based community empowerment requires structural strengthening through diversified funding sources, continuous capacity building, inclusive partnerships, and transparent internal governance mechanisms.
Analisis Efisiensi Sistem Smart Charging Eksternal untuk Laptop Amrullah, Ahmad Afief; Setyanto, Arief; Sudarmawan, Sudarmawan
Smart Comp :Jurnalnya Orang Pintar Komputer Vol 12, No 3 (2023): Smart Comp: Jurnalnya Orang Pintar Komputer
Publisher : Politeknik Harapan Bersama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30591/smartcomp.v12i3.5044

Abstract

Smart charging dalam penelitian-penelitian terdahulu terkait dengan piranti seperti laptop lebih banyak fokus pada persoalan usia baterai dan kerusakannya. Di sisi lain, terdapat penelitian yang memperlebar konteks smart charging kepada kendali berdasarkan kondisi kelistrikan dengan indikator berupa frekuensi. Akan tetapi, efisiensi belum jelas antara model sistem per piranti dibandingkan terpusat. Oleh karena itu penulis hendak menginvestigasi dan fokus pada efisiensi tersebut. Dalam penelitian berjudul “Analisis Efisiensi Sistem Smart Charging Eksternal untuk Laptop” ini penulis menggunakan perangkat dan data-data yang relatif serupa dengan penelitian terdahulu, namun dengan pendekatan dan teknologi yang relatif berbeda. Data diolah dengan beberapa filter sehingga data cukup optimal dipergunakan, khususnya terkait dengan persentase, waktu dan laju pengisian. Data kemudian dipergunakan untuk menghitung nilai efisiensi yang dicari. Adapun data lain yang berkaitan dipergunakan untuk melihat performa dan kecenderungan sistem. Berdasarkan data yang diperoleh dari hasil analisis, disimpulkan bahwa sistem dengan skema individual relatif lebih efisien dibandingkan dengan skema terpusat. Adapun dalam hal performa, sistem dengan skema individual juga relatif lebih baik, karena tidak ditemukan galat selama percobaan. Kata Kunci— smart charging, laptop, frekuensi
Efektivitas Kebijakan Lima Hari Kerja pada Bidang Pelayanan Publik di Kantor Desa Penyamun Kecamatan Pemali Kabupaten Bangka Resti, Resti; Sofyan, Agus; Sudarmawan, Sudarmawan
SENTRI: Jurnal Riset Ilmiah Vol. 5 No. 2 (2026): SENTRI : Jurnal Riset Ilmiah, Februari 2026
Publisher : LPPM Institut Pendidikan Nusantara Global

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55681/sentri.v5i2.5717

Abstract

This study aims to determine the effectiveness of the five-day workday policy on public services at the Penyamun Village Office, Pemali District, Bangka Regency. The study used a descriptive qualitative approach, with data collection techniques through observation, interviews, and documentation. The results indicate that the five-day workday policy has been implemented in accordance with the Bangka Regent's Circular Letter of 2024 and has been able to maintain the continuity of public services by adjusting working days and hours. Village officials have been able to adapt to the new work system, although there are still disciplinary challenges and differences in public satisfaction levels. The five-day workday policy is considered effective and has had a positive impact on public services at the Penyamun Village Office. This study implies that the village government needs to improve apparatus discipline and evaluate the five-day workday policy to optimize public services.
OPTIMIZING SENTIMENT ANALYSIS OF PRODUCT REVIEWS ON MARKETPLACE USING A COMBINATION OF PREPROCESSING TECHNIQUES, WORD2VEC, AND CONVOLUTIONAL NEURAL NETWORK Fahry, Fahry; Utami, Ema; Sudarmawan, Sudarmawan
Jurnal Teknik Informatika (Jutif) Vol. 4 No. 1 (2023): JUTIF Volume 4, Number 1, February 2023
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2023.4.1.815

Abstract

This research attempts to identify the most accurate and effective model in performing sentiment analysis on product reviews in marketplaces using preprocessing techniques, word2vec, and CNN. We collected 20,986 reviews from 720 products in a marketplace using scrap method, then cleaned and labeled the data to include 515 positive reviews, 490 negative reviews. We then performed preprocessing on the data using four different scenarios and identified word vector representation using word2vec. Subsequently, we applied the results of word2vec to the CNN architecture to classify sentiment in product reviews. After trying various variations of each technique, we found that a combination of the third preprocessing technique (case folding, punctuation removal, word normalization, and stemming), the second word2vec parameter combination (size 50, window 2, hs 0, and negative 10), and the fourth CNN parameter combination (kernel size 2, dropout 0.2, and learning rate 0.01) had the best accuracy of 99.00%, precision of 98.96%, and recall of 98.96%. We also found that the word normalization technique greatly helped to increase model accuracy by correcting improperly written or incorrect words in the reviews. Based on the evaluation of word2vec, the hs 0 method produced a higher average accuracy compared to the hs 1 method because the hs 0 method used negative sampling which helped the model understand the context of the trained words. In the CNN parameter, higher learning rates can cause the model to learn faster, but can also cause the model to be unstable, while lower learning rates can make the model more stable but can also cause the model's learning process to be slower.
Co-Authors Abdillah, M A Abidarin Rosidi Adiwisanghagni, Mohammad Agung Mulyono Agung, Kris Agus Sofyan Ahmad Zarkasih Amrullah, Ahmad Afief Arief Setyanto Arif Rahman Arik Sofan Tohir Bambang Soedijono W A, Bambang Soedijono Eko Purwanto Ema Utami Fahry, Fahry Fatkhurohman, Ari Hendrik Setiawan, Hendrik Hermanto (STMIK AMIKOM Yogyakarta) JOKO PRAYITNO Kusrini Kusrini Kusrini Kusrini Kusrini, Kusrini Listyanto, Ahmad Wildan Mohammad Suyanto Napianto, Riduwan Nugroho, Muhammad Agung Nurmalasari, Maulidya Dwi Putra, Afrizal Yudano Perdana Resti Resti Rumini - Sukasna, Sukasna Suryadin, Imam Tri Tri Yusnanto Wahyu Hidayat