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All Journal Jurnal Ilmu Komputer dan Informasi Jurnal Presipitasi : Media Komunikasi dan Pengembangan Teknik Lingkungan Journal of ICT Research and Applications Indonesia Symposium on Computing Indonesian Journal on Computing (Indo-JC) IJoICT (International Journal on Information and Communication Technology) JURNAL MEDIA INFORMATIKA BUDIDARMA Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control JITTER (Jurnal Ilmiah Teknologi Informasi Terapan) eProceedings of Engineering Bulletin of Social Informatics Theory and Application LOGIC: Jurnal Penelitian Informatika
Kemas Rahmat Saleh Wiharja
Telkom University
Agriculture, Biological Sciences & Forestry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Earth & Planetary Sciences Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Library & Information Science Mechanical Engineering Social Sciences

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Utilizing GP 2 for Restaurant Recommendation Nitamayega; Gia Septiana Wulandari; Kemas Rahmat Saleh Wiharja
Indonesian Journal on Computing (Indo-JC) Vol. 9 No. 1 (2024): April, 2024
Publisher : School of Computing, Telkom University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34818/INDOJC.2024.9.1.907

Abstract

The increasing diversity of food and beverage providers poses a challenge for people to find a restaurant that aligns with their preferences. Restaurant recommendation systems can address this problem by providing accurate and relevant suggestions. Although there are many previous studies have explored various recommendation methodologies, the utilization of knowledge graph implemented with GP 2 is still limited. Knowledge graphs can represent complex information in a structured way, while GP 2 is a graph-specific programming language that has a simple syntax. This research focuses on the implementation of a knowledge graph-based restaurant recommendation system with GP 2. The recommendation scheme built can provide the best accuracy, reaching 84.97%. This shows that the knowledge graph-based restaurant recommendation system with GP 2 can demonstrate the effectiveness of the system in providing accurate and relevant recommendations, showing the potential of knowledge graph and GP 2 for the development of recommendation systems in the future and being an effective solution to overcome recommendation problems.
SAFE NUSANTARA: A semi-automatic framework for engineering and populating a Nusantara Food Ontology Wiharja, Kemas Rahmat Saleh; Barawi, Mohamad Hardyman; Romadhony, Ade; Atastina, Imelda; Dharayani, Ramanti; Othman, Mohd Kamal
International Journal on Information and Communication Technology (IJoICT) Vol. 10 No. 2 (2024): Vol.10 No. 2 Dec 2024
Publisher : School of Computing, Telkom University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21108/ijoict.v10i2.1042

Abstract

Constructing a comprehensive food ontology, particularly for culturally diverse cuisines like Southeast East Asian (Nusantara), is hindered by the variability of online recipes and the scarcity of structured data. This research introduces SAFE Nusantara, a novel semi-automated system designed to build and populate a Nusantara food ontology by extracting relevant terms from diverse online sources in Indonesian and Malaysian languages. By leveraging a combination of techniques, including topic modelling, natural language processing, and knowledge graph techniques, SAFE Nusantara addresses the challenges of data format diversity and language specificity. The system has demonstrated significant improvements in the accuracy of food classification and has the potential to enhance food recommendation systems and cultural heritage preservation efforts.
Visualisasi Al- Qur’an Berbasis Knowledge graph dengan Ayat Sebagai Vertex Ayuningtyas, Shinta Cyntia; Wiharja, Kemas Rahmat Saleh; Nhita, Fhira
eProceedings of Engineering Vol. 10 No. 3 (2023): Juni 2023
Publisher : eProceedings of Engineering

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Abstrak-Al- Qur’an merupakan sumber utama ajaran agama islam yang memiliki derajat keterkaitan yang sangat tinggi diantara ayat-ayatnya. Cara yang paling natural untuk menyajikan keterkaitan antara ayat ini adalah dengan menyajikan Al-Qur’an dalam format knowledge graph. Penelitianini akan mencoba menyajikan Al-Qur’an dalam format Knowledge graph dengan setiap ayat yang akan dijadikan sebagai node dan hubungan antar setiap ayat yang dijadikan relasi (busur) pada Knowledge graph. Sebelumnya sudah ada penelitian yang menyajikan Al- Qur’an dalam bentuk Knowledge graph dengan menggunakan Neo4j yang berjudul ‘Visualisasi Tematik Al- Qur’an berbasis Knowledge Graph’. Berbeda dengan penelitian sebelumnya pada penelitian ini akan digunakan TigerGraph untuk proses penyajian knowledge graph. Pada proses pengujian dilakukan 2 tahap yaitu membandingkan antara penelitian ini dengan penelitian sebelumnya dalam hal kelengkapan keterhubungan ayat yang dihasilkan. dan melibatkan penguji (ahli Al - Qur’an) untuk menguji kelengkapan keterhubungan ayat yang dihasilkan. Hasil yang didapatkan dari penelitian ini adalah pada pengujian tipe pertama data yang dapat dimunculkan oleh sistem ini memiliki hasil tema yang lebih lengkap daripada penelitian sebelumnya karena menggunakan dataset yang berbeda. Pada pengujian tipe kedua memiliki hasil keterkaitan yang berbeda saat divalidasi oleh penguji dikarenakan data yang dihasilkan sesuai dengan data yang berasal dari sumber dataset, perbedaan hasil keterkaitan ini dikarenakan adanya beberapa perbedaan pendefinisian kata atau kalimat tertentu dari pengertian bahasa arab saat diterjemahkan kedalambahasa indonesia.Kata kunci -Al – Qur’an , knowledge graph , visualisasi tematik ,tigergraph.
Prediksi Diagnosis Hepatitis B Virus Menggunakan Gated Graph Neural Network Fadhil Wisnu Ramadhan; Wiharja, Kemas Rahmat Saleh
LOGIC: Jurnal Penelitian Informatika Vol. 3 No. 1 (2025): September 2025
Publisher : Universitas Telkom

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25124/logic.v3i1.9855

Abstract

Hepatitis merupakan infeksi virus pada hati dan dapat menyebabkan komplikasi terhadap penyakit lain yang dialami oleh pasien. Diagnosis dini dan penanganan yang tepat sangat penting untuk mencegah progresi penyakit dan komplikasi lebih lanjut. Diperlukan sebuah sistem prediksi diagnosis hepatitis yang akurat untuk menangani dan mengatasi kemungkinan terjangkitnya seseorang akan hepatitis. Penelitian ini melakukan prediksi model Gated Graph Neural Network terhadap pilihan data Hepatitis UCI Machine Learning Repository. Pada penelitian ini dilakukan pemodelan dan penelitian model dengan dua model graph neural network lainnya dan menghasilkan evaluasi yang baik pada prediksi klasifikasi node Hepatitis, dengan menggunakan Gated Graph Neural Network model menunjukan nilai yang superior terhadap 2 metode lain yaitu GAT dan GCN. Dimana GGNN mendapatkan nilai Accuracy, Precision, dan Recall diatas 90%.
PM2.5 Temporal Pattern in Jambi City: Meteorological Drivers and Air Mass Trajectory Analysis Fajar, Benedy; Damris, Muhammad; Wiharja, Kemas Rahmat Saleh; Mutmainnah, Elma; Mohamad, Noorlin; Handika, Rizki Andre
Jurnal Presipitasi : Media Komunikasi dan Pengembangan Teknik Lingkungan Article in Press 2026 (For Upcoming Issue)
Publisher : Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/presipitasi.v0i0.%p

Abstract

Air pollution, particularly particles with diameter of less or equal than 2.5 micrometers (PM2.5), has become important global health and environmental problem. Jambi City in Sumatra is highly susceptible to this issue, both locally and particularly influenced by forest fires. As early studies were conducted over a short period, this study examined the meteorological factors that influenced PM2.5 levels and estimated the pollutant transport pathways over two years in the post-COVID-19 period (2023-2024). The methods employed were time-series analysis, scatter-plot evaluation, multiple linear regression analysis, and backward trajectory modeling using HYSPLIT. The results show that the average PM2.5 concentration in 2023 (30.53 µg/m³) was higher than in 2024 (25.36 µg/m³), with night-time levels generally exceeding day-time levels. 3.69% of the days exceeded Indonesia’s daily air quality standard, while 90.83% surpassed the stricter WHO guideline. Meteorological factors explained only 23–38% of PM2.5, with temperature positively correlated, wind speed showing mixed effects, and humidity and rainfall negatively correlated.. The major PM₂.₅ sources influenced by the southeast–South Sumatra, particularly South Sumatra, highlighting the strong stimulus of transboundary emissions alongside local sources. In the future, studies focusing on chemistry-based source apportionment are needed to accurately separate each contributing source.
Co-Authors A. Nurul Istiqamah Ade Romadhony Adiwijaya Ahmad Ridwan Rezani Akbar Gozali Akbar Gozali Alfian Akbar Gozali Anisa Herdiani Aufa Bil Ahdi P Ayuningtyas, Shinta Cyntia Barawi, Mohamad Hardyman Dana Sulistiyo Kusumo Danang Triantoro Murdiansyah Defrianda Rizky Pranata Donny Faturrachman Emir Septian Sori Dongoran Fadhil Wisnu Ramadhan Fajar, Benedy Fauzi Aulia Rahman Fauzi Aulia Rahman Fhira Nhita Fikriansyah, Muhammad Arya Fitriyani Fitriyani Gede Agung Ary Wisudiawan Gia Septiana Wulandari Hadyan Arif Hafizh, Raihan Atsal Harris Febryantony Z Hegar Aryo Dewandaru Hegar Aryo Dewandaru I Gusti Bagus Ady Sutrisna Ibnu Asror Ilham Kamil Noviandi Imelda Atastina Irvan Nur Aziz Isjhar Kautsar Ludovica Gorganusa Lukman Arie Susanto Mira Kania Sabariah Mochammad Fitrah Eka Pramudita Mohamad Fauzy Mohamad, Noorlin Mohammad Fauzy Muhammad Damris Muhammad Ramadhan Gandidi Muhammad Zakiyullah Romdlony Mutmainnah, Elma Nitamayega Nitamayega Nungki Selviandro Nunit Prihatoni Siregar Nurzakiah, Azmi othman, mohd kamal Ramadhanti, Aisyah Dliya Ramanti Dharayani Riche Julianti Wibowo Rizki Andre Handika Shaufiah . Shinta Yulia Puspitasari Taufiqurrahman Taufiqurrahman Tiwa Ramdhani Wijaya, Dewa Made Wisnu Riyan Pratama Putra Yustiawan, Yoga