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All Journal PengabdianMu: Jurnal Ilmiah Pengabdian kepada Masyarakat Jurnal Saintekom : Sains, Teknologi, Komputer dan Manajemen Jurnal Sistem Informasi, Manajemen dan Teknologi Informasi
Maura Widyaningsih, Maura
Unknown Affiliation
Agriculture, Biological Sciences & Forestry Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Law, Crime, Criminology & Criminal Justice Public Health Social Sciences

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Identifikasi Kematangan Buah Apel Dengan Gray Level Co-Occurrence Matrix (GLCM) Widyaningsih, Maura
Jurnal Saintekom : Sains, Teknologi, Komputer dan Manajemen Vol 6 No 1 (2016): Maret 2016
Publisher : STMIK Palangkaraya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1584.457 KB) | DOI: 10.33020/saintekom.v6i1.7

Abstract

Digital image processing is part of the technological developments in the concepts and reasoning, the human wants the machine (computer) can recognize images like human vision. Recognizing the image is one way to distinguish the traits that exist in the image. Texture is one of the characteristics that distinguish the image, is the basic characteristic of the image identification. Gray Level Co-Occurrence Matrix (GLCM) is one method of obtaining characteristic texture image by calculating the probability of adjacency relationship between two pixels at a certain distance and direction. The characteristics of texture obtained from GLCM methods include contrast, correlation, homogeneity, and energy. The extracted features are then used for identification with the nearest distance calculations (Eucledian Distance). The final results analysis program to identify the category of apples raw, half-ripe or overripe. Training data used are 12 images apple, consisting of 4 is crude, 4 is half-cooked, and 4 is ripe, 7 data used for testing. Testing GLCM with 00 angle feature extraction results of the test images can be recognized by a factor Eucledian Distance to the query image. Identification of test data is information all the data can be recognized. Eucledian Distance is a method that helps the introduction of a test object data.
Dempster Shafer Untuk Sistem Diagnosa Gejala Penyakit Kulit Pada Kucing Widyaningsih, Maura; Gunadi, Rio
Jurnal Saintekom : Sains, Teknologi, Komputer dan Manajemen Vol 7 No 1 (2017): March 2017
Publisher : STMIK Palangkaraya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1237.787 KB) | DOI: 10.33020/saintekom.v7i1.24

Abstract

Expert System which is a branch of Artifical Intelligence, who learned about the estimation or decision-making ability of an expert. Methods and concepts are still needed in solving the problem of diagnosis, with engineering calculations involve computing systems., given the level of need for information and resolving cases. The application development is aimed at implementing the knowledge of an expert into a program that can help in diagnosing the symptoms of skin health problems in cats. Dempster Shafer (DS) is a method that is non monotonous in solving the problem of uncertainty due to the addition or subtraction of new facts.The system is made to diagnose the type of skin disease in cats after applying the method of DS. The system can also perform data management if there is a data change disease, symptoms, treatment solutions, as well as the rules of the disease. The diagnosis system with DS according to analysis from experts.
Analisis Sistem Helpdesk untuk Optimalisasi Efektivitas Pelayanan Publik di Biro Pengadaan Kalimantan Tengah Widyaningsih, Maura; Putri, Anisa Febriyana; Pebrianto, Rendi; Maysena, Nisa
Jurnal Sistem Informasi, Manajemen dan Teknologi Informasi Vol. 3 No. 1 (2025): Januari
Publisher : STMIK Palangkaraya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33020/jsimtek.v3i1.785

Abstract

Pelayanan publik merupakan kewajiban utama instansi pemerintahan untuk memenuhi kebutuhan masyarakat sesuai dengan peraturan yang berlaku. Biro Pengadaan Barang dan Jasa (PBJ) Provinsi Kalimantan Tengah memegang peran penting dalam pengelolaan pengadaan barang/jasa. Namun, tantangan terkait transparansi, kecepatan respons, dan kepuasan masyarakat sering kali menghambat efektivitas pelayanan. Penelitian ini bertujuan untuk menganalisis bagaimana implementasi sistem helpdesk dapat meningkatkan efektivitas pelayanan publik melalui evaluasi tingkat kepuasan pengunjung. Penelitian menggunakan metode analisis SWOT untuk mengidentifikasi kekuatan, kelemahan, peluang, dan ancaman sistem helpdesk berdasarkan data survei kepuasan. Hasil survei menunjukkan mayoritas responden merasa puas dengan pelayanan yang diberikan, terutama dalam aspek kecepatan, keramahan staf, dan tidak adanya biaya pelayanan. Namun, ditemukan kelemahan berupa rendahnya partisipasi masyarakat umum dan keterbatasan sosialisasi terkait informasi pelayanan. Penelitian juga mengidentifikasi peluang pengembangan layanan berbasis teknologi serta peningkatan partisipasi publik melalui edukasi dan sosialisasi. Rekomendasi strategis meliputi penguatan sistem informasi, penyampaian transparan terkait persyaratan, serta penyesuaian kebijakan untuk memperluas jangkauan layanan. Dengan mengatasi kelemahan dan ancaman yang ada serta memanfaatkan peluang, Biro PBJ dapat terus meningkatkan efektivitas dan kualitas pelayanannya untuk memenuhi ekspektasi publik secara berkelanjutan.
Optimalisasi Kinerja Pembelajaran Guru SMKN dengan Pendekatan Partisipatif melalui Integrasi ChatGPT dari OpenAI: Optimizing SMKN Teacher Learning Performance with a Participatory Approach through ChatGPT Integration from OpenAI Widyaningsih, Maura; Pratama, Bayu; Herkules, Herkules; Hendartie, Susi
PengabdianMu: Jurnal Ilmiah Pengabdian kepada Masyarakat Vol. 10 No. 3 (2025): PengabdianMu: Jurnal Ilmiah Pengabdian kepada Masyarakat
Publisher : Institute for Research and Community Services Universitas Muhammadiyah Palangkaraya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33084/pengabdianmu.v10i3.7796

Abstract

The mastery of constantly evolving technology is a difficult challenge for teachers at SMK Negeri 2 Palangka Raya. To overcome this, self-development through training is necessary, such as using ChatGPT to make learning more effective. ChatGPT helps find educational resources with clear commands and supports the preparation of study plans, performance objectives, and task completion. This training was held at the Digital Marketing Laboratory of SMK Negeri 2 Palangka Raya and included preparation, implementation, and evaluation. Initial evaluation showed that 65% of participants did not know about ChatGPT, 15% were somewhat knowledgeable, and 20% were knowledgeable. After the training, understanding significantly increased, with the average correct answers rising from 52% to 85%. Recommendations for sustainability include focusing on difficult material, evaluating and revising training materials, and using interactive teaching methods. Implementation of interactive teaching through approaches such as group discussions, simulations, and case studies as well as direct practice.
Analisis Simulasi Routing AODV Adaptif dengan Learning Automata untuk Komunikasi V2V Effendi, Muhamad Denhas; Bintoro, Ketut Bayu; Widyaningsih, Maura
Jurnal Saintekom : Sains, Teknologi, Komputer dan Manajemen Vol 15 No 1 (2025): Maret 2025
Publisher : STMIK Palangkaraya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33020/saintekom.v15i1.820

Abstract

The study addresses the limitations of the Ad Hoc On-Demand Distance Vector (AODV) protocol in vehicle-to-vehicle (V2V) communication, explicitly targeting issues such as low data transfer rates, increased delay times, reduced throughput, and data congestion due to dynamic network topologies. The research introduces a novel protocol called Learning Automata Ad Hoc On-Demand (LAAODV) to enhance these areas. Utilizing NS3 and SUMO for dynamic traffic simulations, LAAODV demonstrated superior performance compared to AODV. Key findings include a higher packet delivery success rate with a Packet Loss Ratio (PLR) of 95%, lower than AODV's 96%, and a Packet Delivery Ratio (PDR) of 4.5% compared to AODV's 3.25%, indicating its effectiveness in reducing packet loss. The study also highlights significant improvements in PDR and Average Throughput, showcasing LAAODV's enhanced performance in dynamic traffic conditions. LAAODV provides an effective solution to the shortcomings of existing routing protocols, significantly enhancing V2V network performance. This research underscores the importance of developing robust and adaptive routing solutions to meet the evolving demands of dynamic vehicular environments, contributing to more efficient and reliable V2V communication protocols.
Co-Authors Bayu Pratama, Bayu Bintoro, Ketut Bayu Effendi, Muhamad Denhas Gunadi, Rio Gunadi, Rio Herkules Herkules, Herkules Maysena, Nisa Pebrianto, Rendi Putri, Anisa Febriyana Susi Hendartie