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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 CoreIT 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 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 Jurnal Komtika (Komputasi dan Informatika) Jurnal Kajian Ilmu dan Teknologi (JKIT)
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 Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Mathematics Mechanical Engineering Social Sciences Other

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TEKNIK SMOTE DAN GINI SCORE DALAM KLASIFIKASI KANKER PAYUDARA Ramadhan, Nur Ghaniaviyanto; Adhinata, Faisal Dharma
RADIAL : Jurnal Peradaban Sains, Rekayasa dan Teknologi Vol. 9 No. 2 (2021): RADIAL: JuRnal PerADaban SaIns RekAyasan dan TeknoLogi
Publisher : Universitas Bina Taruna Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37971/radial.v9i2.229

Abstract

Breast cancer is a malignancy in breast tissue that can originate from the epithelium of the ducts and lobules. WHO says 30% - 50% of cancer cases can be prevented. Breast cancer prevention can be done utilizing screening or early diagnosis. The purpose of the initial diagnosis is that if a lump appears, predictions can be made whether it is classified as malignant or benign. Breast cancer prediction can be done using a dataset containing cancer-related parameters. However, sometimes the dataset used also has problems such as the amount of data is not balanced and the use of irrelevant features. This study aims to improve breast cancer prediction results by balancing the number of data classes and using the rank feature. The method used is SMOTE for imbalanced data and Gini score for rank features. The classification model used is random forest and naïve Bayes. The results obtained by the random forest classification model are superior to Naïve Bayes.
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.
TEKNIK SMOTE DAN GINI SCORE DALAM KLASIFIKASI KANKER PAYUDARA Ramadhan, Nur Ghaniaviyanto; Adhinata, Faisal Dharma
RADIAL : Jurnal Peradaban Sains, Rekayasa dan Teknologi Vol. 9 No. 2 (2021): RADIAL: JuRnal PerADaban SaIns RekAyasan dan TeknoLogi
Publisher : Universitas Bina Taruna Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (453.223 KB) | DOI: 10.37971/radial.v9i2.229

Abstract

Breast cancer is a malignancy in breast tissue that can originate from the epithelium of the ducts and lobules. WHO says 30% - 50% of cancer cases can be prevented. Breast cancer prevention can be done utilizing screening or early diagnosis. The purpose of the initial diagnosis is that if a lump appears, predictions can be made whether it is classified as malignant or benign. Breast cancer prediction can be done using a dataset containing cancer-related parameters. However, sometimes the dataset used also has problems such as the amount of data is not balanced and the use of irrelevant features. This study aims to improve breast cancer prediction results by balancing the number of data classes and using the rank feature. The method used is SMOTE for imbalanced data and Gini score for rank features. The classification model used is random forest and naïve Bayes. The results obtained by the random forest classification model are superior to Naïve Bayes.
Model Deteksi Kebakaran Hutan dan Lahan Menggunakan Transfer Learning DenseNet201 Saputra, Rifqi Akmal; Adhinata, Faisal Dharma
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.
Web-based Information System for Processing Student Report Grade Using Waterfall Method (Study Case: SMPN 3 Talaga) Lisan, Fauzan Fashihul; Riadi, Daffa Rayhan; Nugraha, Aditya Rizkiawan; Shalma, Hastin Ajeng; Adhinata, Faisal Dharma
Jurnal CoreIT: Jurnal Hasil Penelitian Ilmu Komputer dan Teknologi Informasi Vol 9, No 2 (2023): December 2023
Publisher : Fakultas Sains dan Teknologi, Universitas Islam Negeri Sultan Syarif Kasim Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24014/coreit.v9i2.21954

Abstract

Assessment is an activity or method used by educators to measure students' abilities in the processes and learning outcomes at school. Junior Highschool 3 Talaga in its assessment process still uses the conventional method which causes delays in the assessment report process, not minimizing errors in writing on the assessment report is quite difficult. Based on the problems experienced, it is presented as an assessment information system that helps the student assessment process. This information system was created using the waterfall method which produces a ready-to-use system with sufficient features. The information system presented uses the PHP and MySQL programming languages to facilitate and lighten student assessment work. This assessment is used as a reference standard for achieving student competency and a basis for helping students. Not only that, but the assessment is also carried out continuously and aims to monitor the learning process and progress of students. With the existence of an information system, the assessment will be more efficient and can facilitate its implementation.
Sistem Pakar Diagnosa Penyakit pada Hewan Kucing Berbasis Web Ramadhan, Faiz Zaki; Aditya, Gilang; Nainggolan, Purnama Dileon Yamora; Adhinata, Faisal Dharma
Jurnal Komtika (Komputasi dan Informatika) Vol 5 No 2 (2021)
Publisher : Universitas Muhammadiyah Magelang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31603/komtika.v5i2.5301

Abstract

Tahun 2018 Rakuten Insight menyurvei hewan jinak di Asia. Survei diikuti 97.000 responden dari benua asia timur dan asia tenggara. bahwa 59% orang memiliki binatang peliharaan. Dari banyaknya peliharaan, kucing menjadi pilihan, terutama diIndonesia. sebanyak 47% orang memelihara kucing. Kucing terkadang sering terkena penyakit, dan kita suka bingung apa yang terjadi dengan hewan kita, dan bagaimana cara kita bisa mengobatinya, terutama kota yang tidak memiliki rumah perawatan hewan. Untuk mengetahui penyakit apa yang diderita kucing, diperlukan informasi medis untuk mengetahui itu, sedangkan yang kita tahu masih sangat terbatas. akibatnya dibutuhkan sistem guna menyampaikan pengetahuan seperti seseorang pakar, penulis membuat sistem dimana berisi pengetahuan seseorang ahli penyakit pada kucing, agar masyarakat yang awam dapat mengetahui jenis penyakit serta penyembuhanya, rancangan sistem pakar menggunakan metode Naïve Bayes dimana pengklasifikasian probabilitasnya sederhana. keuntunganya naïve bayes hanya membutuhkan data kecil pelatihan untuk proses klasifikasi yang diperlukkan untuk parameter dalam membantu membuat sistem identifikasi penyakit. hasil contoh, kita menginputkan gejala-gejala seperti bulu rontok, lingkaran merah pada kulit, serta bercak putih seperti ketombe, dimana merupakan gejala pernyakit kadas seperti yang ada disystem. Hasil penelitian menunjukkan diagnosa penyakit kucing menggunakan naïve bayes dapat menghasilkan akurasi 93%.
Perancangan Sistem Informasi Berbasis Web Wiskul Banyumas Sebagai Sarana Informasi dan Promosi Pariwisata, Kuliner, serta Penginapan Di Banyumas Wibowo, Satrio; Agustyn, Zulfa Basmallah; Hidayat, Wahrul; Adhinata, Faisal Dharma
Jurnal Kajian Ilmu dan Teknologi (JKIT) Vol. 1 No. 1 (2024): Jurnal Kajian Ilmu dan Teknologi (JKIT)
Publisher : Rumah Jurnal PT Citra Air Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.71200/jkit.v1i1.4

Abstract

Berdasarkan penelitian yang telah dilakukan, diperoleh hasil bahwa suatu sistem informasi berbasis web sebagai sarana promosi dan informasi wisata, kuliner, serta penginapan di Banyumas belum tersedia. Berdasarkan penelitian tersebut penulis berinisiatif untuk membuat sebuah rancangan sistem informasi berbasis web menggunakan Laravel. Penulis menggunakan Metode Waterfall sebagai metode pengembangan. Dengan adanya sistem informasi berbasis web yang telah penulis rancang diharapkan dapat memudahkan wisatawan dalam bepergian dan membantu kabupaten Banyumas di sektor pariwisata. Rancangan sistem informasi berbasis web yang penulis buat menggunakan Bahasa Pemrograman PHP versi 7.4 framework Laravel, dengan menggunakan database mysql. Penulis berharap dengan adanya perancangan sistem informasi berbasis web ini membuat tempat wisata, kuliner, serta penginapan di Banyumas dapat lebih dikenal oleh masyarakat.
A Combination of Transfer Learning and Support Vector Machine for Robust Classification on Small Weed and Potato Datasets Adhinata, Faisal Dharma; Ramadhan, Nur Ghaniaviyanto; Fauzi, Muhammad Dzulfikar; Tanjung, Nia Annisa Ferani
JOIV : International Journal on Informatics Visualization Vol 7, No 2 (2023)
Publisher : Society of Visual Informatics

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
Co-Authors Abdul Majid Abdurrahman Ibnul Rasidi Adam Nur Kridabayu Adil El-Faruqi Aditya Wijayanto Aditya, Gilang Afzal Ziqri Agustyn, Zulfa Basmallah 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 Hendrowati, Retno Herman Yuliansyah Hidayat, Wahrul Ibnul Rasidi, Abdurrahman Ikadhanny Yudyan Pratama Irsyad Zulfikar Jahfal Rizqi Putra Pradhana Kridabayu, Adam Nur Lisan, Fauzan Fashihul 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 Nainggolan, Purnama Dileon Yamora Narantyo Maulana Adhi Nugraha Naseh Hibban Nasution, Annio Indah Lestari Nia Annisa Ferani Tanjung Nike Prasetyo Nisrina Eka Salsabila Novi Rahmawati Novi Rahmawati Nugraha, Aditya Rizkiawan 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 Ramadhan, Faiz Zaki Renna Nur Injiyani Reva Rahardian Riadi, Daffa Rayhan Rifki Adhitama, Rifki Rifqi Akmal Saputra Rifqi Alfinnur Charisma Rival Fahmi Hidayat Rizki Rafiif Amaanullah Rohman Beny Riyanto Saputra, Rifqi Akmal Saputro, Satria Nur Satria Adi Nugraha Satrio Wibowo Sayyid Yakan Khomsi Pane Shalma, Hastin Ajeng 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