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All Journal Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) IJID (International Journal on Informatics for Development) Minda Baharu Amalee: Indonesian Journal of Community Research & Engagement
Dewi Wisnu Wardani
Sebelas Maret University (UNS) Surakarta, Indonesia
Humanities Computer Science & IT Engineering Public Health Social Sciences Other

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Semantic Commerce for Developing Country Wardani, Dewi Wisnu
IJID (International Journal on Informatics for Development) Vol 1, No 1 (2012): IJID May
Publisher : Universitas Islam Negeri Sunan Kalijaga Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (397.041 KB) | DOI: 10.14421/ijid.2012.01103

Abstract

The recent real challenges of semantic technology is not in the core of the technology but much more in implementing the semantic technology in the real problem. The common domain in any world is economics. One of the most important domain in economics is marketing. Company moreover small company from developing country desperated in increasing to make their company's product are known wider, around the world as well. Product from developing countries usually has a good quality, unique and cheaper but lack to be known. This paper present idea how semantic technology will give a benefit in marketing strategies for business in developing countries. The short goal is how the common famous search engine will be more understand the company both product and profile, thus present those information in better form and possible to the next processing in the others semantic technology.
Enhancing Participatory Learning at SMP Negeri 2 Jaten Karanganyar through the Integration of Technology Cahyono, Hasan Dwi; Wardani, Dewi Wisnu; Setiadi, Haryono; Wijayanto, Ardhi; Doewes, Afrizal
Amalee: Indonesian Journal of Community Research and Engagement Vol 5 No 1 (2024): Amalee: Indonesian Journal of Community Research and Engagement
Publisher : LP2M INSURI Ponorogo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37680/amalee.v5i1.4816

Abstract

The development of knowledge and technology significantly impacts literacy skills, essential for academic growth and school adaptation. Technology literacy is crucial for awareness and academic support, but a lack of technological knowledge can hinder education. To address this, the Indonesian government introduced the belajar.id platform, integrating Google Suite for Education (GSuite) to aid academic activities during the pandemic. Challenges like limited teacher-student interaction persist, necessitating the encouragement of electronic media and diverse educational material availability. They aimed to bridge teaching gaps, enhance technological skills, and ensure effective knowledge sharing, using participatory rural appraisal (PRA). The team of Research Group Data Information Knowledge and Engineering (RG DIKE) at the Universitas Sebelas Maret (UNS) Surakarta conducted a study on technology literacy's importance for students in SMP Negeri 2 Jaten Karanganyar. It emphasized technology's role in disaster management and prevention, striving for a strategic approach to technology-based education. Training sessions were conducted on August 15 and October 26, 2023, focused on belajar.id, GSE, and OBS integration. Teachers played a key role in guiding and updating their GSE and OBS knowledge. In summary, these sessions aimed to equip teachers and students with vital GSE and OBS skills, enhancing education quality and learning outcomes.
PENINGKATAN KEAMANAN LINGKUNGAN DENGAN PENERAPAN CCTV DI DUKUH SRIMULYO Cahyono, Hasan Dwi; Wardani, Dewi Wisnu; Hendrasuryawan, Brilyan; Setiadi, Haryono; Doewes, Afrizal; Anggrainingsih, Rini; Wijayanto, Ardhi
MINDA BAHARU Vol 8, No 2 (2024): Minda Baharu
Publisher : Universitas Riau Kepulauan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33373/jmb.v8i2.7015

Abstract

. Berdasarkan kegiatan Pengabdian kepada Masyarakat (PkM) yang sudah terlaksana, yakni penerapan closed-circuit television (CCTV) di Dukuh Srimulyo, Boyolali, didapatkan hasil bahwa dapat membantu menyelesaikan masalah mitra. Adapun permasalahan yang ditemukan adalah kurangnya pengawasan yang dapat memberikan rasa aman kepada warga. Hal ini terjadi akibat banyaknya jalur kendaraan yang dapat melintasi wilayah tersebut tetapi belum diterapkan adanya pengawasan secara real-time. PkM ini bertujuan untuk mengatasi masalah keterbatasan tersebut. Solusi yang ditawarkan kepada mitra adalah penerapan CCTV yang dapat merekam kejadian di titik yang penting. Pendampingan dilakukan dalam bentuk pelatihan penggunaan CCTV dan penyediaan fasilitas untuk pengawasan yang akan digunakan oleh mitra. Adapun hasil dari PkM ini adalah ditemukan bahwa para warga memberikan sambutan baik dengan diterapkannya CCTV ini pada kegiatan yang dilakukan berdasarkan umpan balik yang diberikan setelah kegiatan selesai. Selanjutnya CCTV yang terpasang pada titik penting berjumlah dua dan telah melalui proses penelaahan bersama dengan warga. Adapun dampak yang diperoleh secara nyata setelah PkM ini berakhir adalah sebagian besar peserta dapat melakukan pengawasan secara mandiri menggunakan aplikasi aplikasi CCTV yang telah terpasang
Comparing Correlation-Based Feature Selection and Symmetrical Uncertainty for Student Dropout Prediction Haryono Setiadi; Larasati, Indah Paksi; Esti Suryani; Wardani, Dewi Wisnu; Wardani, Hasan Dwi Cahyono; Ardhi Wijayanto
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 8 No 4 (2024): August 2024
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v8i4.5911

Abstract

Predicting student dropout is essential for universities dealing with high attrition rates. This study compares two feature selection (FS) methods—correlation-based feature selection (CFS) and symmetrical uncertainty (SU)—in educational data mining for dropout prediction. We evaluate these methods using three classification algorithms: decision tree (DT), support vector machine (SVM), and naive Bayes (NB). Results show that SU outperforms CFS overall, with SVM achieving the highest accuracy (98.16%) when combined with SU Moreover, this study identifies total credits in the fourth semester, cumulative GPA, gender, and student domicile as key predictors of student dropout. This study shows how using feature selection methods can improve the accuracy of predicting student dropout, helping educational institutions retain students better.
Co-Authors Afrizal Doewes, Afrizal Ardhi Wijayanto Esti Suryani Haryono Setiadi Hasan Dwi Cahyono Hendrasuryawan, Brilyan Larasati, Indah Paksi Rini Anggrainingsih Setiadi, Haryono Wardani, Hasan Dwi Cahyono Wijayanto, Ardhi