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All Journal TIN: TERAPAN INFORMATIKA NUSANTARA International Journal Software Engineering and Computer Science (IJSECS) ABDINE Jurnal Pengabdian Masyarakat
Kastum, Kastum
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Optimizing Contextual Features for Instagram Engagement Prediction using Long Short-Term Memory (LSTM) Aswad, Hazrul; Mulyana, Dadang Iskandar; Kastum, Kastum
TIN: Terapan Informatika Nusantara Vol 6 No 3 (2025): August 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/tin.v6i3.8166

Abstract

Instagram has become an important communication medium for academic institutions, enabling the dissemination of information, promotion of activities, and engagement with the campus community. At STIKOM CKI Jakarta, the official Instagram account plays a key role in academic communication, making it essential to optimize content strategies for higher audience interaction. This study analyzes 311 publicly available posts collected from July 2023 to July 2025 from the institution’s official account. Although relatively small for deep learning, the dataset provides representative patterns for the case study while highlighting the model’s capability under limited data conditions. A predictive framework based on Long Short-Term Memory (LSTM) was developed by integrating textual features from captions with contextual features such as posting time, content type, hashtag count, and interaction metrics. The aim is to accurately estimate engagement scores and provide actionable posting recommendations. The evaluation achieved an R² of 88.00%, MAE of 0.0450, and RMSE of 0.0720, indicating strong predictive performance. The contribution of this research lies in demonstrating that optimizing contextual features can significantly enhance academic social media engagement and in providing an adaptable methodology for institutions with limited historical data.
Pelatihan Penggunaan Tools WEKA untuk Kepentingan Proses Data Mining di ITS NU Pekalongan Tundo, Tundo; Betty Yel, Mesra; Sutisna, Nandang; Kastum, Kastum; Adrianto, Sopan
ABDINE: Jurnal Pengabdian Masyarakat Vol. 4 No. 1 (2024): ABDINE : Jurnal Pengabdian Masyarakat
Publisher : Sekolah Tinggi Teknologi Dumai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52072/abdine.v4i1.826

Abstract

Pada pelatihan ini, penggunaan WEKA akan fokus dalam hal data mining, yang artinya pengelolahan data dan menggali data menjadi suatu knowledge dan visualisasi yang memberikan manfaat informasi yang berguna. Banyak cara dalam mengelolah data dan menggali data untuk dijadikan sebuah visual, salah satunya dengan menggunakan aplikasi WEKA, dimana cara ini juga membantu mahasiswa dalam menentukan tema skripsi yang didalamnya mengandung algoritma dan metode data mining. Bentuk cara dalam membantu mahasiswa tersebut, salah satunya yaitu memberikan pelatihan penggunaan aplikasi WEKA untuk membantu mahasiswa dalam mengelolah data dan menggali data menjadi sebuah visual dan knowledge. Pelatihan dilakukan di ITS NU Pekalongan dengan tujuan menambahkan wawasan baru kepada seluruh mahasiswa terkait proses pembuatan visualisasi data dengan WEKA. Kegiatan pelatihan ini masih fokus ke pembuatan visualisasi data berupa rule dari algoritma decision tree J48. Kegiatan dilaksanakan dalam bentuk pendampingan dan praktik dalam penggunaan aplikasi WEKA mulai dari penyampaian materi data mining dan tools WEKA, dilanjutkan praktik cara membuat visualisasi data berupa rule otomatis. Berdasarkan hasil kuesioner menunjukkan bahwa 92% peserta merasa WEKA mudah digunakan untuk proses pengolahan data dan menggali data.
Mobile Application Development for Waste Management System with K-Means Clustering of Waste Collection Points in Jonggol and Sukamakmur Sub-Districts, Bogor Regency Aziz, Naufal; Mulyana, Dadang Iskandar; Kastum, Kastum
International Journal Software Engineering and Computer Science (IJSECS) Vol. 5 No. 3 (2025): DECEMBER 2025
Publisher : Lembaga Komunitas Informasi Teknologi Aceh (KITA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijsecs.v5i3.5250

Abstract

The disparity in the distribution of Temporary Disposal Sites (TPS) within Jonggol and Sukamakmur Districts of Bogor Regency results in inefficiencies in waste collection services, increases travel times, and creates an unequal operational burden on collection fleets. There is no mobile-based digital platform for residents to report TPS conditions in real-time, which further delays responses to waste management. The lack of interactive digital map visualization makes it hard for local sanitation managers to make informed decisions about space. A mobile waste management information system was created using Flutter and Firebase, with the K-Means algorithm used to cluster TPS locations based on their spatial coordinates. The clustering results are presented as an interactive digital map that is integrated with the Google Maps API; this application allows residents to input TPS condition reports, upload visual evidence, and receive notifications about the status in real-time. This project is an extension of our previous web-based work done during the practical internship (KKP) phase but has a larger scope due to a more advanced spatial approach integrated into mobile devices. The system will optimize the distribution efficiency of waste collection services while assisting spatial decision-making processes as well as motivating active participation from residents in maintaining their environment particularly within Jonggol and Sukamakmur Districts under Bogor Regency’s smart city program initiatives.
Co-Authors Aswad, Hazrul Aziz, Naufal Betty Yel, Mesra Dadang Iskandar Mulyana` SOPAN ADRIANTO Sutisna, Nandang Tundo, Tundo