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All Journal Majalah Ilmiah Teknologi Elektro Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI) CommIT (Communication & Information Technology) Jurnal Transformatika JUITA : Jurnal Informatika Journal of Information Systems Engineering and Business Intelligence Indonesian Journal on Computing (Indo-JC) Jurnal Teknologi dan Sistem Komputer JOIV : International Journal on Informatics Visualization RABIT: Jurnal Teknologi dan Sistem Informasi Univrab Knowledge Engineering and Data Science JURNAL MEDIA INFORMATIKA BUDIDARMA JOURNAL OF APPLIED INFORMATICS AND COMPUTING DoubleClick : Journal of Computer and Information Technology Journal of Information Technology and Computer Engineering JURIKOM (Jurnal Riset Komputer) Logista: Jurnal Ilmiah Pengabdian Kepada Masyarakat KOMPUTIKA - Jurnal Sistem Komputer Jurnal Riset Informatika Jurnal Ilmiah Ilmu Komputer Fakultas Ilmu Komputer Universitas Al Asyariah Mandar Building of Informatics, Technology and Science JTIM : Jurnal Teknologi Informasi dan Multimedia RADIAL: JuRnal PerADaban SaIns RekAyasan dan TeknoLogi Jurnal Teknik Elektro dan Komputasi (ELKOM) Jurnal E-Komtek Indonesian Journal of Electrical Engineering and Computer Science Journal of Computer System and Informatics (JoSYC) Madani : Indonesian Journal of Civil Society Journal of Informatics, Information System, Software Engineering and Applications (INISTA) Jurnal Teknik Informatika (JUTIF) Journal of Informatics and Vocational Education Teknika ICTEE (Engineering Journals of Information, control, telecommunication and electrical) Insyst : Journal of Intelligent System and Computation Journal of Dinda : Data Science, Information Technology, and Data Analytics IJCOSIN : Indonesian Journal of Community Service and Innovation Journal of Embedded Systems, Security and Intelligent Systems El-Mujtama: Jurnal Pengabdian Masyarakat Majalah Ilmiah Teknologi Elektro JuTISI (Jurnal Teknik Informatika dan Sistem Informasi) RADIAL: Jurnal Peradaban Sains, Rekayasa dan Teknologi
Faisal Dharma Adhinata
Institut Teknologi Telkom Purwokerto
Religion Agriculture, Biological Sciences & Forestry Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Mechanical Engineering Social Sciences Other

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Website Desa Wisata Kedungbenda sebagai Media Promosi Wisatawan Nia Annisa Ferani Tanjung; Faisal Dharma Adhinata; Condro Kartiko
Indonesian Journal of Community Service and Innovation (IJCOSIN) Vol 2 No 1 (2022): Januari 2022
Publisher : LPPM IT Telkom Purwokerto

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (604.533 KB) | DOI: 10.20895/ijcosin.v2i1.413

Abstract

Pengabdian masyarakat ditujukan untuk memberikan dampak kepada masyarakat terkait aplikasi ilmu pengetahuan dosen kepada masyarakat. Di era digital ini, penggunaan teknologi internet sebagai media online sudah banyak dikembangkan untuk pemanfaatan berbagai sektor, salah satunya pariwisata. Desa Kedungbenda mempunyai beragam potensi wisata, mulai dari susur sungai, petilasan, dan kesenian budaya. Namun, pandemi virus corona membuat tempat wisata ditutup untuk sementara waktu, sehingga masyarakat yang ingin mengunjungi tempat wisata tidak diperbolehkan sementara waktu. Oleh karena itu, ide pembuatan website sistem informasi wisata desa Kedungbenda diharapkan dapat menjadi solusi permasalahan ini. Website dikembangkan menggunakan bahasa pemrograman PHP. Hasil dari website yang dibuat pada alamat https://www.deswitakedungbenda.com, terdapat beberapa fitur yang dapat diakses oleh wisatawan, yaitu galeri tempat wisata, artikel atau berita mengenai tempat wisata, dan peta lokasi menuju tempat wisata. Pada fitur administrator, admin dapat menambah, mengubah, dan menghapus galeri, gambar slideshow, foto 3600, artikel, dan kategori input. Diakhir kegiatan pelaksanaan pengabdian masyarakat, dilakukan survei kepuasan masyarakat. Hasil survei menunjukkan rata-rata 99% masyarakat desa Kedungbenda puas terhadap kegiatan pengabdian masyarakat yang dilakukan. Pengabdian masyarakat ditujukan untuk memberikan dampak kepada masyarakat terkait aplikasi ilmu pengetahuan dosen kepada masyarakat. Di era digital ini, penggunaan teknologi internet sebagai media online sudah banyak dikembangkan untuk pemanfaatan berbagai sektor, salah satunya pariwisata. Desa Kedungbenda mempunyai beragam potensi wisata, mulai dari susur sungai, petilasan, dan kesenian budaya. Namun, pandemi virus corona membuat tempat wisata ditutup untuk sementara waktu, sehingga masyarakat yang ingin mengunjungi tempat wisata tidak diperbolehkan sementara waktu. Oleh karena itu, ide pembuatan website sistem informasi wisata desa Kedungbenda diharapkan dapat menjadi solusi permasalahan ini. Website dikembangkan menggunakan bahasa pemrograman PHP. Hasil dari website yang dibuat pada alamat https://www.deswitakedungbenda.com, terdapat beberapa fitur yang dapat diakses oleh wisatawan, yaitu galeri tempat wisata, artikel atau berita mengenai tempat wisata, dan peta lokasi menuju tempat wisata. Pada fitur administrator, admin dapat menambah, mengubah, dan menghapus galeri, gambar slideshow, foto 3600, artikel, dan kategori input. Diakhir kegiatan pelaksanaan pengabdian masyarakat, dilakukan survei kepuasan masyarakat. Hasil survei menunjukkan rata-rata 99% masyarakat desa Kedungbenda puas terhadap kegiatan pengabdian masyarakat yang dilakukan.
Expert System for Identifying Pregnant Using Forward Chaining Gilang Aditia; Afzal Ziqri; Aldhan Tri Maulana; Faisal Dharma Adhinata
Journal of INISTA Vol 5 No 2 (2023): May 2023
Publisher : LPPM INSTITUT TEKNOLOGI TELKOM PURWOKERTO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20895/inista.v5i2.494

Abstract

Pregnancy is a biological process in which sperm and eggs meet each other to fertilize, and the fetus is formed in the uterus. But it's difficult; pregnant mothers sometimes have problems or discomfort during pregnancy. In addition, in areas far from the city, there are many obstacles to consulting an obstetrician. Therefore, it will be dangerous if mothers experience problems and find it difficult to get first aid. This research aims to create an expert system for pregnant women where it is not difficult for a mother to go to the doctor to ask about her complaints. The solution offered in this study is easy to access to the SP BUMIL website and automatically enters all mothers' complaints into the system. This system also provides a diagnosis and advice to pregnant women as to the best steps and an explanation of what the pregnant woman is suffering from. This expert system uses the forward chaining method, which has the advantage of producing a solution to a problem; in other words, being able to consider a problem and draw conclusions according to the facts. On this website, there is a disease information menu and also the results of the diagnosis
A Combination of Transfer Learning and Support Vector Machine for Robust Classification on Small Weed and Potato Datasets Faisal Dharma Adhinata; Nur Ghaniaviyanto Ramadhan; Muhammad Dzulfikar Fauzi; Nia Annisa Ferani Tanjung
JOIV : International Journal on Informatics Visualization Vol 7, No 2 (2023)
Publisher : Politeknik Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30630/joiv.7.2.1164

Abstract

Agriculture is the primary sector in Indonesia for meeting people's daily food demands. One of the agricultural commodities that replace rice is potatoes. Potato growth needs to be protected from weeds that compete for nutrients. Spraying using pesticides can cause environmental pollution, affecting cultivated plants. Currently, agricultural technology is being developed using an Artificial Intelligence (AI) approach to classifying crops. The classification process using AI depends on the number of datasets obtained. The number of datasets obtained in this research is not too large, so it requires a particular approach regarding the AI method used. This research aims to use a combination of feature extraction methods with local and deep feature approaches with supervised machine learning to classify of small datasets. The local feature method used in this research is Local Binary Pattern (LBP) and Histogram of Oriented Gradients (HOG), while the deep feature method used is MobileNet and MobileNetV2. The famous Support Vector Machine (SVM) uses the classification method to separate two data classes. The experimental results showed that the local feature HOG method was the fastest in the training process. However, the most accurate result was using the MobileNetV2 deep feature method with an accuracy of 98%. Deep features produced the best accuracy because the feature extraction process went through many neural network layers. This research can provide insight on how to analyze a small number of datasets by combining several strategies
Sentiment Analysis on Tiktok Application Reviews Using Natural Language Processing Approach Abdul Majid; Dian Nugraha; Faisal Dharma Adhinata
Journal of Embedded Systems, Security and Intelligent Systems Vol. 4 No. 1 (2023): Vol 4, No 1 (2023): May 2023
Publisher : Program Studi Teknik Komputer

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

Abstract

Technology today is very developed, there are so many media that can be used to communicate, these media are very easy to use by connecting to the internet network. Research on the sentiment of this analysis can still be relatively small and new. The rapid development of technology today makes it very easy for humans to communicate with one of the modern technologies, namely smartphones. The initial stage of this research begins with the review to be analyzed, then continues with the collection of review data. Conducted on reviews that have been collected with and without an NLP approach resulting in 2 datasets, with an NLP approach and datasets without an NLP approach. The first step is to identify the problem with the research object. It then looked for related literature studies from both journals and review proceedings used as many as 1000 reviews, which have been labeled by 5 correspondents and resulted in positive reviews and negative reviews. The review is used as a dataset, then pre-processed with an NLP approach. Classification using the NLP approach got an accuracy of 76.92%, a precision of 80.00% and a recall of 74.07%, while without NLP it only got an accuracy of 69.23%, a precision of 80.00% and a recall of 64.52% At the preprocessing stage, the stemming feature, and stopword removal features were applied to each review. Word normalizer to handle variations in writing words that have the same meaning to be counted as a single term Furthermore, a stopword removal process is carried out to remove the stopword from the review.
A WEB-BASED INFORMATION SYSTEM FOR LECTURER'S PERFORMANCE APPRAISAL USING RATING SCALE METHODS Diovianto Putra Rakhmadani; Faisal Dharma Adhinata
Jurnal Riset Informatika Vol. 3 No. 2 (2021): March 2021 Edition
Publisher : Kresnamedia Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34288/jri.v3i2.65

Abstract

Online learning is widely used by every educational institution during the Covid-19 pandemic. Without face-to-face meetings, lecturers are required to present quality learning with feedback from students. The problem that arises is that EDOM is considered too long in terms of data processing, while lecturers are required to carry out quality teaching at each meeting. If students lose interest in a lecture due to the performance of the lecturer who is unable to make each virtual class attractive, the lecture activity will be ineffective. With the existence of a performance measurement system with the application of gamification that can measure the performance of lecturers at each meeting, lecturers can receive feedback while pursuing rewards or ratings on their performance. This study uses the waterfall model and produces a web-based information system that can be used as evaluation material in improving the quality of online learning.
Model Deteksi Kebakaran Hutan dan Lahan Menggunakan Transfer Learning DenseNet201 Rifqi Akmal Saputra; Faisal Dharma Adhinata
Intelligent System and Computation Vol 5 No 2 (2023): INSYST: Journal of Intelligent System and Computation
Publisher : Institut Sains dan Teknologi Terpadu Surabaya (d/h Sekolah Tinggi Teknik Surabaya)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52985/insyst.v5i2.317

Abstract

Kebakaran hutan dan lahan di Indonesia merupakan peristiwa yang sering terjadi dan menimbulkan kerugian yang signifikan dalam bidang kesehatan, ekologi, dan sosial. Faktor manusia dan alam berperan dalam memicu terjadinya kebakaran ini. Namun, penanganan kebakaran hutan dan lahan masih menghadapi kendala dalam memprediksi lokasi titik panas secara akurat, sehingga pengendalian yang optimal sulit dilakukan. Oleh karena itu, diperlukan pengembangan sistem cerdas untuk mendeteksi kebakaran hutan dan lahan dengan lebih efektif. Penelitian ini bertujuan untuk menciptakan sebuah model yang mampu mendeteksi kebakaran hutan dan lahan dengan menggunakan pendekatan transfer learning, dengan memanfaatkan arsitektur DenseNet201 guna meningkatkan akurasi deteksi. Dataset yang digunakan dalam penelitian ini berasal dari Fire Forest Dataset pada situs Kaggle. Proses ekstraksi fitur dilakukan menggunakan arsitektur DenseNet201, dan model yang dihasilkan diuji dengan menggunakan metode confusion matrix untuk mengklasifikasikan gambar menjadi dua kelas, yaitu kelas api dan non-api. Melalui pelatihan menggunakan arsitektur DenseNet201, diperoleh model yang efektif dalam mendeteksi kebakaran hutan dan lahan. Hasil pengujian dengan menggunakan data uji sebanyak 380 data menunjukkan tingkat akurasi sebesar 99% dalam mengenali gambar kebakaran hutan dan lahan. Penelitian ini memberikan kontribusi penting dalam pengembangan teknologi deteksi kebakaran hutan dan lahan. Penggunaan pendekatan transfer learning dengan arsitektur DenseNet201 memiliki potensi untuk meningkatkan akurasi deteksi kebakaran yang lebih baik. Diharapkan penelitian ini dapat memberikan landasan bagi pengembangan sistem cerdas yang lebih canggih dan efektif dalam mengatasi masalah kebakaran hutan dan lahan, serta melindungi lingkungan dan kesehatan masyarakat di Indonesia.
Jurnal Pencegahan dan Penanganan Kekerasan Seksual menggunakan Natural Languange Process dan Data Science Alissyah Putri; Dani Azka Faz; Anshari Rusmeniar R.A; Yuni nur fari'ah; Falah Arfani; Faisal Dharma Adhinata
El-Mujtama: Jurnal Pengabdian Masyarakat  Vol. 4 No. 3 (2024): El-Mujtama: Jurnal Pengabdian Masyarakat
Publisher : Intitut Agama Islam Nasional Laa Roiba Bogor

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47467/elmujtama.v4i3.2428

Abstract

Violence against women is something that is often heard and discussed in society. Women are often victims of discrimination, harassment and violence. Sexual harassment and violence in Indonesia is certainly not only experienced by adult women, but can also be experienced by children and adult men. Although in many cases it is more experienced by women. Of all respondents who were victims of sexual violence, almost all preferred or decided not to report the sexual violence and harassment they experienced. The cause is a psychological problem because of what happened to him, which makes him confused, embarrassed, afraid and even feels self-blame for what he experienced. This is the basis for the author to build a Chatbot and Recommendation System as a form of care and also a solution for victims of sexual violence by presenting a website "preventing and handling sexual violence". Chatbots serve as a forum for information related to sexual violence such as definitions, boundaries of sexual violence categories, complaint reporting services, and as a legal umbrella that can be used to protect themselves and criminals who commit sexual violence. The data source was obtained from the Law on the Elimination of Sexual Violence. By having easily accessible legal information and official data sources, the author hopes that this can help victims to have the courage to take steps to report the acts of violence they have experienced. The recommender system provides recommendation results in the form of information on legal services and psychological consultations. Not a few victims of sexual violence certainly experience psychological problems such as feelings of confusion, shame towards other people, fear of the perpetrator, not to mention feelings of guilt that seem to blame themselves for what they have experienced. Information on psychological services is available for victims who need psychological recovery.
A Comparative Analysis of Transfer Learning Architecture Performance on Convolutional Neural Network Models with Diverse Datasets Putra, Muhammad Daffa Arviano; Winanto, Tawang Sahro; Hendrowati, Retno; Primajaya, Aji; Adhinata, Faisal Dharma
Komputika : Jurnal Sistem Komputer Vol 12 No 1 (2023): Komputika: Jurnal Sistem Komputer
Publisher : Computer Engineering Departement, Universitas Komputer Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34010/komputika.v12i1.8626

Abstract

Deep learning is a branch of machine learning with many highly successful applications. One application of deep learning is image classification using the Convolutional Neural Network (CNN) algorithm. Large image data is required to classify images with CNN to obtain satisfactory training results. However, this can be overcome with transfer learning architectural models, even with small image data. With transfer learning, the success rate of a model is likely to be higher. Since there are many transfer learning architecture models, it is necessary to compare each model's performance results to find the best-performing architecture. In this study, we conducted three experiments on different datasets to train models with various transfer learning architectures. We then performed a comprehensive comparative analysis for each experiment. The result is that the DenseNet-121 architecture is the best transfer learning architecture model for various datasets.
Expert System to Diagnose Diseases in Durian Plants using Naïve Bayes Nugraha, Narantyo Maulana Adhi; Rahardian, Reva; Kridabayu, Adam Nur; Adhinata, Faisal Dharma; Ramadhan, Nur Ghaniaviyanto
Building of Informatics, Technology and Science (BITS) Vol 3 No 3 (2021): December 2021
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (599.891 KB) | DOI: 10.47065/bits.v3i3.1077

Abstract

Durian is a fruit that is very popular and very easy to find throughout Indonesia. Durian fruit is a thorny fruit with a very pungent smell with a distinctive taste, and for some durian fans, the distinctive taste of durian is what makes durian unique compared to other fruits. However, it is unfortunate that the production and quality of durian fruit in Indonesia is currently still low due to the limited knowledge of farmers in caring for and maintaining durian plants from pests and diseases on durian plants. So far, in detecting pests and diseases, farmers still carry out pest and disease detection manually, and of course, this is very dependent on pest and disease observers/experts. For this reason, so that later the level of production and quality of durian in Indonesia can increase, we create an expert system to diagnose a disease in durian plants to help farmers overcome problems around pests and diseases commonly occur in durian plants. This study uses the Naïve Bayes method as a determinant of durian disease. The experimental results yield an accuracy of 82%, which indicates the proposed method is quite good in diagnosing durian disease.
YOLO Algorithm for Detecting People in Social Distancing System Adhinata, Faisal Dharma; Rakhmadani, Diovianto Putra; Segara, Alon Jala Tirta
Jurnal Transformatika Vol. 19 No. 1 (2021): July 2021
Publisher : Jurusan Teknologi Informasi Universitas Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26623/transformatika.v19i1.3582

Abstract

Social distancing is an effort to prevent the spread of the coronavirus. Several systems for monitoring social distancing have been developed. People detection is an essential step in implementing a social distancing system. Failure to detect people causes the social distancing system to be inaccurate. Two people who communicate cannot occur violations of social distancing because one person is not detected. Therefore, we propose a precise person detection method for the social distancing system. The proposed social distancing system uses the YOLOv3 method for people detection and Euclidean Distance for measuring the distance of social distancing. YOLOv3 can detect people's objects precisely, even people who are caught small by the camera. Experiments on two outdoor video datasets result in an F1 value of more than 0.8. This proposed system can serve as a reference for future social distancing research.
Co-Authors Abdul Majid Abdurrahman Ibnul Rasidi Adam Nur Kridabayu Adil El-Faruqi Aditya Wijayanto Afzal Ziqri Ahmad Muslih Syafi’i Ajeng Fitria Rahmawati Akhmad Jayadi Aldhan Tri Maulana Alfan Adi Chandra Alissyah Putri Alon Jala Tirta Segara Alya Aulia Hanafi Ananda Aulia Rizky Ananda Aulia Rizky Andra Aulia Rizaldy Anshari Rusmeniar R.A Apri Junaidi, Apri Arief Rais Bahtiar Arif Amrulloh Ariq Cahya Wardhana Bagus Bayu Sasongko Christoph Quix Christyan, Timothy Condro Kartiko Dani Azka Faz Darmawan, Bagus Tri Yulianto Dayal Gustopo Setiadjit Dian Nugraha Diovianto Putra Rakhmadani Emmanuel Genesius Evan Devara Fadlan Raka Satura Fajar Malik Falah Arfani Fauzi, Muhammad Dzulfikar Fawwaz Muhammad Zulfikar Febry Ardiansyah Firdonsyah, Arizona Fitran Dwi Pramakrisna Fitran Dwi Pramakrisna Gilang Aditia GITA FADILA FITRIANA Gracia Rizka Pasfica Herman Yuliansyah Ibnul Rasidi, Abdurrahman Ikadhanny Yudyan Pratama Irsyad Zulfikar Jahfal Rizqi Putra Pradhana Kridabayu, Adam Nur M Alfian Maulana Al Azhar Merlinda Wibowo Metha Khafifah Isty Rikhanah Mohammad Rifqi Zein Muhammad Arif Saputra Muhammad Fajar Ahadi Muhammad Ikhsan Muhammad Iqbal Rasyid Muhammad Pajar Kharisma Putra Narantyo Maulana Adhi Nugraha Naseh Hibban Nasution, Annio Indah Lestari Nia Annisa Ferani Tanjung Nike Prasetyo Nisrina Eka Salsabila Novi Rahmawati Novi Rahmawati Nugraha, Narantyo Maulana Adhi Nur Ghaniaviyanto Ramadhan Nur Syahela Hussien Nursatio Nugroho Pasaribu, Yolanda Al Hidayah Purnama Dileon Yamora Nainggolan Putra, Muhammad Daffa Arviano Rachma Wukir Purwitasari Rahardian, Reva Rahmanda Trinova Putra Renna Nur Injiyani Retno Hendrowati Reva Rahardian Rifki Adhitama, Rifki Rifqi Akmal Saputra Rifqi Akmal Saputra Rifqi Alfinnur Charisma Rival Fahmi Hidayat Rizki Rafiif Amaanullah Rohman Beny Riyanto Saputro, Satria Nur Satria Adi Nugraha Sayyid Yakan Khomsi Pane Sofiyudin Pamungkas Teguh Rijanandi Teguh Rijanandi Teguh Rijanandi Tri Dimas Cipto Satrio Wibowo Try Susanto Ummi Athiyah Utama, Safitri Yuliana Utami, Annisaa Vincent Nathaniel Wahyono Wahyono Widi Widayat Wijayanto, Danur Winanto, Tawang Sahro Yaqutina Marjani Santosa Yohani Setiya Rafika Nur Yolanda Al Hidayah Pasaribu Yuni nur fari'ah Zanuar Rahmat Saputra Ziqri, Afzal