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All Journal Jurnal Mantik eProceedings of Engineering Jurnal Informatika: Jurnal Pengembangan IT
Dede Rohidin
Universitas Telkom
Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media

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Peta Pikiran Otomatis Teks Berbahasa Indonesia Menggunakan Word Co-occurrence Dan Bobot Kalimat Dika Atrariksa; Dede Rohidin; Gia Septiana
eProceedings of Engineering Vol 2, No 2 (2015): Agustus, 2015
Publisher : eProceedings of Engineering

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Abstract

Abstrak Pada penelitian ini dibuat sistem yang men-generate peta pikiran yang isi cabang-cabangnya merupakan kata kunci hasil ekstraksi dengan menggunakan word co-occurrence statistical information. Penelitian ini menyajikan perbandingan antara peta pikiran hasil sistem dengan pembobotan kalimat dan peta pikiran hasil sistem tanpa pembobotan kalimat. Penggunaan pembobotan kalimat adalah untuk melihat pengaruhnya terhadap kata kunci-kata kunci cabang-cabang peta pikiran. Sistem mampu men-generate peta pikiran dari sebuah dokumen, baik dengan maupun tanpa pembobotan kalimat. Sistem tanpa pembobotan kalimat menghasilkan peta pikiran dengan rata-rata jumlah kata kunci penting cabang utama sebesar 75% dan rata-rata jumlah cabang anak relevan dengan cabang utamanya 37,52%. Sedangkan, sistem dengan pembobotan kalimat menghasilkan peta pikiran dengan rata-rata jumlah kata kunci penting cabang utama sebesar 70,83% dan rata-rata jumlah cabang anak yang penting dan relevan dengan cabang utamanya 34,61%. Kata Kunci : peta pikiran, word co-occurrence, pembobotan kalimat, ekstraksi kata kunci
Analisis Pengenalan Emosi Pada Musik dengan Sistem Berbasis Fuzzy Emriliza Amarulhaq; Dede Rohidin; Mahmud Dwi
eProceedings of Engineering Vol 1, No 1 (2014): Desember, 2014
Publisher : eProceedings of Engineering

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Penyimpanan musik digital membutuhkan mekanisme pencarian yang lebih mudah, fleksibel dan lebih maju menyesuaikan dengan kebutuhan individual user. Oleh karena itu dibutuhkan indeks retrieval yang lebih sesuai dan indeks retrieval yang paling baik adalah yang memfasilitasi pencarian yang sesuai dengan fungsi psikologis dan sosialnya. Indeks yang dimaksud secara khusus akan fokus pada informasi mengenai gaya, mood dan kesamaan musik. Dari permasalahan diatas, telah banyak dikembangkan metode untuk information retrieval dari suatu musik dengan pemahaman yang telah didapat dari penelitian sebelumnya seperti pada genre classification dan speech recognition salah satunya adalah dengan pendekatan fuzzy. Subyektivitas persepsi manusia dalam mengklasifikasi emosi memberi kesan logika fuzzy adalah solusi kuat untuk permasalahan ini. Metode-metode berbasis fuzzy system memiliki kemampuan menghadapi masalah yang membutuhkan proses penalaran seperti pemodelan emosi dalam music emotion recognition. Akan digunakan fuzzy dengan dua metode learning berbeda untuk dianalisa hasilnya. Kata kunci : music emotion recognition, fuzzy inference system, music information retrieval, fuzzy k-nn, anfis
Peramalan Kelembapan Relatif di Kabupaten Bogor Menggunakan Model CNN-LSTM Thariq Abdullah; Achmad Lukman; Dede Rohidin
Jurnal Informatika: Jurnal Pengembangan IT Vol 11, No 2 (2026)
Publisher : Politeknik Harapan Bersama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30591/jpit.v11i2.10063

Abstract

 Air humidity is a parameter that influences the environment and human activities. Accurate air humidity prediction can be helpful for various purposes, including weather-based decision-making. However, a single model has limitations in capturing non-linear patterns and long-term dependencies in time-series data, making it difficult to predict data well, especially complex and time-series data such as weather. Therefore, a model with a hybrid approach is needed. Hybrid modeling is a combination of two or more learning methods. This study proposes a hybrid approach by combining Convolutional Neural Network (CNN) and Long Short-Term Memory (LSTM) layers to predict air humidity more accurately and effectively than a single model. CNN is used to extract temporal representations from historical weather data in the form of time sequences, while LSTM is for long-term memory. Prediction is carried out by collecting weather data, data preprocessing, feature transformation (including cyclic feature transformation), designing the CNN-LSTM architecture, model training, and evaluation using evaluation metrics such as mean absolute error (MAE), mean square error (MSE), root mean square error (RMSE), and coefficient of determination (R²). This study uses weather data from Bogor Regency for the period January 1, 2020 to October 31, 2025 obtained from the Citeko Meteorological Station at coordinates Latitude -6.70000, Longitude 106.85000, and an altitude of 920 meters. The results obtained are that the CNN-LSTM model has an average MAE value of 4.3596, MSE 29.9126, RMSE 5.4689, and R² 0.0756 show that the CNN-LSTM hybrid model is able to improve the accuracy of air humidity prediction compared to a single model.
Resistance and acceptance of posyandu cadres to the digitization of stunting recording: qualitative analysis of empowerment-based technology acceptance model (case study in Gegerkalong village, Bandung city) Anne Rahaju; Dede Rohidin
Jurnal Mantik Vol. 10 No. 1 (2026): May : Manajemen, Teknologi Informatika dan Komunikasi (Mantik)
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/mantik.v10i1.7211

Abstract

The transformation of maternal and child health data recording from manual methods to digital systems poses significant socio-technical challenges at the grassroots level. This study aims to analyze the dynamics of resistance and acceptance of Posyandu cadres in Gegerkalong Village, Sukasari District, Bandung City towards stunting recording technology, by integrating the Technology Acceptance Model (TAM) and the andragogy approach. Using a qualitative approach with a case study design, data collection was carried out through in-depth interviews, participatory observations, and Focus Group Discussions (FGD) involving 12 participants (senior cadres, young cadres, and health workers). The results of the study show that technological resistance is mainly triggered by the mismatch of interface design (User Interface) with the cognitive and visual capacity of adult learners, which leads to cognitive overload and low Perceived Ease of Use. On the other hand, revenue is driven by the perception of Perceived Usefulness when digital reporting is considered to be able to increase efficiency and raise the social status of cadres in society. This research underlines the importance of integrating the concept of lifelong education and peer tutoring methods in cadre mentoring. It is recommended that the design of future health information systems involve end users (cadres) in the development phase to realize inclusive technology
Co-Authors Achmad, Lukman Anne Rahaju Dika Atrariksa Emriliza Amarulhaq Gia Septiana Mahmud Dwi Thariq Abdullah