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All Journal JURNAL SISTEM INFORMASI BISNIS Jupiter Sistemasi: Jurnal Sistem Informasi Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) INTENSIF: Jurnal Ilmiah Penelitian dan Penerapan Teknologi Sistem Informasi JRST (Jurnal Riset Sains dan Teknologi) JURNAL TEKNIK INFORMATIKA DAN SISTEM INFORMASI Jurnal Sisfokom (Sistem Informasi dan Komputer) JURIKOM (Jurnal Riset Komputer) JURTEKSI Jurnal Abdimas PHB : Jurnal Pengabdian Masyarakat Progresif Humanis Brainstorming Jurnal Teknologi Dan Sistem Informasi Bisnis JATI (Jurnal Mahasiswa Teknik Informatika) JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) Jurnal Teknik Informatika (JUTIF) Jurnal Pengabdian Masyarakat Indonesia Jurnal Ilmiah Wahana Pendidikan Jurnal PkM (Pengabdian kepada Masyarakat) Jurnal Pengabdian Masyarakat : Pemberdayaan, Inovasi dan Perubahan IJCOSIN : Indonesian Journal of Community Service and Innovation Jurnal Tren Bisnis Global Jurnal INFOTEL Jurnal Informatika: Jurnal Pengembangan IT JPMTT (Jurnal Pengabdian Masyarakat Teknologi Terbarukan) Edu Komputika Journal JuTISI (Jurnal Teknik Informatika dan Sistem Informasi)
M Yoka Fathoni
Intitut Teknologi Telkom Purwokerto
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TEXT CLASSIFICATION OF BULLYING REPORTS USING NLP AND RANDOM FOREST. Aldo, Dasril; Paramadini, Adanti Wido; Fathoni, M. Yoka
Jurnal Teknik Informatika (Jutif) Vol. 6 No. 1 (2025): JUTIF Volume 6, Number 1, February 2025
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2025.6.1.4032

Abstract

Bullying is a great concern that needs to be dealt with as early as possible, be it in the form of physical, verbal, social or cyber bullying. Using NLP algorithms, this paper intends to classify bullying report using Natural Language Processing in conjunction with Bag of Words. The study employs quantitative methodology. A total of 4671 reports of bullying are in essence categorized into physical, verbal, social, cyber and non-cyber bullying. We split the dataset into 80% training set (3737 reports) and 20% testing set (934 reports). The above model has achieved an accuracy of 94,76%, with good values of recall, precision and F1-score: 94,64%, 95,02% and 94,97% respectively. The dataset is then analyzed using Random Forest algorithm and Report of the Bullying Survey The model is to be effective in automatic Detection of Textual Bullying Reports Automated. While there has been no such effort in our institutions so far, automatic reporting of bullying will prove to be effective. This is because the system will allow a school or institution to have a precise constant monitoring of bullying reports. It will also allow an instantaneous action to be taken to protect the victim without letting the situation escalate.
Analisis Sentimen Pengguna Terhadap Smart Ring Pada Data Twitter Menggunakan Naive Bayes Fauzi, Faiq; Ali, Nizar; Azzahra, Anisa; Fathoni, M Yoka
JUPITER (Jurnal Penelitian Ilmu dan Teknologi Komputer) Vol 17 No 1 (2025): Jurnal Penelitian Ilmu dan Teknologi Komputer (JUPITER)
Publisher : Teknik Komputer Politeknik Negeri Sriwijaya

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

Abstract

Smart ring is a ring-shaped wearable device equipped with advanced technology to monitor user activities. Smart ring technology can be used by analyzing user sentiment, a wearable device that is increasingly popular but still faces various challenges of public acceptance. This research is to find out the opinions of users on social media, especially Twitter, and how these sentiments affect consumers' views and purchase intentions. Data was collected by crawling techniques using Google Colab and tweet-harvest tools, after which it was analyzed using the Naive Bayes algorithm to classify sentiment into positive and negative. The results showed that of the 580 tweets collected, there were 147 positive sentiments and 63 negative sentiments after duplicate removal, with an accuracy of 76.19%. This research can help smart ring manufacturers develop products that are more in line with user needs.
Sentiment Analysis of Visitor Reviews on Baturaden Tourist Attraction Using Machine Learning Methods Mahazam Afrad; Dany Candra Febrianto; Sena Wijayanto; M. Yoka Fathoni
Edu Komputika Journal Vol. 11 No. 1 (2024): Edu Komputika Journal
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/edukom.v11i1.10561

Abstract

This study evaluates the performance of four machine learning models: Support Vector Machine (SVM), Random Forest, K-Nearest Neighbors (KNN), and Naive Bayes in analyzing visitor reviews of the Lokawisata Baturaden tourist attraction. Using 5-fold cross-validation, the study aims to determine which machine learning model best suits sentiment analysis on the Baturaden review data. This study was conducted through several stages, including data preprocessing, feature extraction, and the data training process. Case folding, text cleaning, tokenization, stopword removal, and stemming were performed during the data preprocessing stage. The feature extraction method used was TF-IDF. SMOTE was applied to increase data variation and address the data imbalance in the dataset. The results show that SVM provides the best performance with an accuracy of 0.937, an F1-score of 0.937, a precision of 0.943, and a recall of 0.937. Random Forest also performs well with an accuracy of 0.918 and an F1-score of 0.918, though slightly below SVM. KNN shows the lowest performance with an accuracy of 0.651 and an F1-score of 0.544, while Naive Bayes performs adequately with an accuracy of 0.845 and an F1-score of 0.841. Based on this evaluation, SVM is recommended as the best model for sentiment analysis of reviews, followed by Random Forest as a good alternative. The KNN model is not recommended due to its lower performance, while Naive Bayes can be considered for its speed and simplicity, although its results are not as good as SVM and Random Forest. These conclusions guide the selection of the optimal model to enhance understanding and visitor experience at the Baturaden tourist attraction.
Analisis Emosi Wisatawan Menggunakan Metode Lexicon Text Analysis Dea Caesy Rahmadani; Siti Khomsah; M Yoka Fathoni
Jurnal Teknik Informatika dan Sistem Informasi Vol 10 No 1 (2024): JuTISI
Publisher : Maranatha University Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28932/jutisi.v10i1.6690

Abstract

Travelers often write comments on the internet, usually about experiences, opinions, and even complaints. Comment data on the internet can provide information for stakeholders. This information can be extracted using text analysis methods such as positive and negative sentiments. Sentiments can be detailed into eight types of emotions. This study aims to extract emotions from tourists' comments on Google Map, especially on tourist-site accounts in BARLINGMASCAKEB. The dataset comments were crawled from ten tourism objects in BARLINGMASCAKEB. The method used is Lexicon Emotion Analysis. The results show that the majority of tourists have positive experiences. It is shown by the emotion "joy" and "trust." Emotions "joy" and "trust" have positive meanings, so it can be said that the majority of tourists feel positive emotions. There are sites that present highest emotions of "joy": Aquarium-Purbasari-Pancuran-Mas with 33.52%, Lembah-Asri-Serang with 30.85%, Sanggaluri-Reptile-Park by 30, 27%, Baturaden Botanical-Gardens with 27, 67 %, and Curug-Jenggala by 23.4%. At the same time, the highest types of "trust" emotions are Benteng-Pandem with 27.41%, Arjuna-Temple with 26.6%, Sikidang-Crater with 20.71%, and Menganti-Beach with 25, 74%. Only one site, the World Miniature Park, gives the highest "anticipation" emotion. Usually, caring words represent anticipation emotions, so they can still be categorized into positive emotions. The extraction of emotions is affected by the process of emotion-labeling of each comment, so further research is recommended to develop a lexicon emotion dictionary. The results of this study are expected to provide benefits for the development of the tourism industry in the BARLINGMASCAKEB area and for the academic world, especially regarding the application of text mining in the tourism sector
Obesity Status Prediction Through Artificial Intelligence and Balanced Label Distribution Using SMOTE Riyandi, Arif; Mahazam Afrad; M Yoka Fathoni; Yogo Dwi Prasetyo
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 9 No 3 (2025): June 2025
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v9i3.6204

Abstract

Obesity, a global health challenge influenced by genetic and environmental factors, is characterized by excessive body fat that increases the risk of various diseases. With over two billion individuals affected worldwide, addressing this issue is crucial. This study investigated the application of Artificial Intelligence (AI) to predict obesity status using a dataset of 1,610 individuals, including demographic and anthropometric data. Four AI algorithms were analyzed: Artificial Neural Network (ANN), K-Nearest Neighbors (KNN), Random Forest, and Support Vector Machine (SVM). The Synthetic Minority Over-Sampling Technique (SMOTE) was applied to address dataset imbalance. The results demonstrate that SMOTE significantly enhanced the models' performance, especially in recall and F1-score for minority classes, such as obesity. Random Forest achieved the highest accuracy (92%) and recall (92%) post-SMOTE. The ANN showed substantial improvement in recall, increasing from 77% to 89%, whereas the SVM achieved the highest precision (89%), minimizing false positives. Despite these improvements, KNN remained the least effective. The findings underscore the critical role of SMOTE in improving AI model accuracy for obesity prediction and highlight Random Forest as the most reliable algorithm for clinical decision-making. Limitations, such as dataset representativeness, suggest future research directions, including expanding data diversity and advanced feature selection techniques. This study provides valuable insights into leveraging AI and preprocessing methods for obesity management.
Optimization Of Extreme Learning Machine Models Using Metaheuristic Approaches For Diabetes Classification Sulaeman, Gilang; Nur, Yohani Setiya Rafika Nur; Paramadini, Adanti Wido; Aldo, Dasril; Fathoni, M. Yoka
Jurnal Teknik Informatika (Jutif) Vol. 6 No. 3 (2025): JUTIF Volume 6, Number 3, Juni 2025
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2025.6.3.4690

Abstract

Proper classification of diabetes is a significant challenge in contemporary healthcare, especially related to early detection and clinical decision support systems. This study aims to optimize the Extreme Learning Machine (ELM) model with a metaheuristic approach to improve performance in diabetes classification. The data used was an open dataset containing the patient's medical attributes, such as age, gender, smoking status, body mass index, blood glucose level, and HbA1c. The initial process includes data cleansing, one-hot coding for categorical features, MinMax normalization, and unbalanced data handling with SMOTE. The ELM model was tested with four activation functions (Sigmoid, ReLU, Tanh, and RBF) each combined with three metaheuristic optimization strategies, namely Particle Swarm Optimization (PSO), Genetic Algorithm (GA), and Bat Algorithm. The results of the evaluation showed that the combination of the Tanh activation function with GA optimization obtained the highest accuracy of 87.98% and an F1-score of 0.5489. Overall, GA optimization appears to be superior to all other measurement configurations in consistent classification performance. The main contribution of this study is to offer a systematic approach to select the best combination of activation functions and optimization algorithms in ELM, as well as to provide empirical evidence to support the application of metaheuristic strategies to improve the accuracy of disease classification based on health data. This research has direct implications for the development of a more precise and data-based medical diagnostic classification system for diabetes.
Pemanfaatan TikTok sebagai Media Digital Marketing untuk Pemasaran Produk UMKM Desa Cingebul Wiedanto Prasetyo, Muhamad Awiet; Fathoni, M. Yoka; Safitri, Sisilia Thya; Fernandez, Sandhy; Wijayanto, Sena; Prasetyo, Yogo Dwi; Afrad, Mahazam
Jurnal Abdimas PHB : Jurnal Pengabdian Masyarakat Progresif Humanis Brainstorming Vol 8, No 3 (2025): Jurnal Abdimas PHB : Jurnal Pengabdian Masyarakat Progresif Humanis Brainstormin
Publisher : Politeknik Harapan Bersama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30591/japhb.v8i3.8910

Abstract

Transformasi digital di sektor UMKM perdesaan masih menghadapi berbagai tantangan, terutama dalam hal pemanfaatan media sosial sebagai sarana pemasaran. Kegiatan pengabdian masyarakat ini bertujuan untuk meningkatkan kapasitas digital marketing pelaku UMKM di Desa Cingebul melalui pelatihan dan pendampingan pemanfaatan TikTok sebagai platform promosi. Metode pelaksanaan terdiri atas pemetaan kebutuhan, pelatihan teknis, praktik pembuatan konten, dan evaluasi performa. Hasil kegiatan menunjukkan adanya peningkatan signifikan dalam hal kepercayaan diri peserta, keterampilan membuat konten, serta konsistensi dalam membangun citra produk secara digital. Selain itu, muncul pula individu yang berperan sebagai pemimpin lokal (local leader) dalam mendampingi UMKM lain, yang menjadi indikator awal terbentuknya ekosistem digital desa. Temuan ini menguatkan pentingnya pendekatan partisipatif dan kontekstual dalam penguatan literasi digital masyarakat perdesaan.
Penerapan Teknologi Tepat Guna Berbasis IoT dan Panel Surya untuk Meningkatkan Produktivitas Penetasan Telur Ayam Kampung Fathoni, M. Yoka; Alika, Shintia Dwi; Aldo, Dasril; Maulida, Elsa; Ramadhan, Firman Adi
Jurnal Pengabdian Masyarakat: Pemberdayaan, Inovasi dan Perubahan Vol 5, No 5 (2025): JPM: Pemberdayaan, Inovasi dan Perubahan
Publisher : Penerbit Widina, Widina Media Utama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59818/jpm.v5i5.2081

Abstract

This community service program aims to address the low hatching success rate of native chicken eggs experienced by the partner, Petet Ayam Lestari Unit, in Muntang Village, Kemangkon District, Purbalingga Regency. The main problems identified were limited electricity supply, unstable incubator temperature and humidity, and manual production record-keeping. To overcome these issues, the team implemented the program “Integration of IoT and Renewable Energy in Automatic Incubators as Appropriate Technology for Farmer Empowerment and Mitigation of Hatching Failures”. The program was conducted from June to September 2025 using a participatory approach through several stages: socialization, training, technology implementation, mentoring, and evaluation. The technology introduced included an automatic incubator integrated with Internet of Things (IoT) sensors, powered by solar panels as an alternative energy source, and supported by digital systems for production and financial recording. The results demonstrated a significant improvement in the partner’s knowledge and skills. The average pretest score of 31% increased to 87% in the posttest, with an average improvement of +56%. The hatching success rate also rose from 50–70% to 75–85%. In addition, the partner satisfaction survey yielded an average score of 4.68, categorized as very satisfied. In conclusion, this program not only improved technical aspects such as hatching success and business management but also empowered the community, particularly women, and strengthened business sustainability through the adoption of renewable energy and digital record-keeping.ABSTRAKProgram pengabdian masyarakat ini bertujuan untuk mengatasi permasalahan rendahnya tingkat keberhasilan penetasan telur ayam kampung pada mitra Unit Usaha Petet Ayam Lestari di Desa Muntang, Kecamatan Kemangkon, Kabupaten Purbalingga. Permasalahan utama yang dihadapi mitra adalah keterbatasan suplai listrik, ketidakstabilan suhu dan kelembapan inkubator, serta pencatatan usaha yang masih manual. Untuk menjawab persoalan tersebut, tim melaksanakan kegiatan “Integrasi IoT dan Energi Terbarukan pada Mesin Tetas Otomatis sebagai Teknologi Tepat Guna untuk Pemberdayaan Peternak dan Mitigasi Kegagalan Penetasan”. Metode pelaksanaan program dilakukan sejak Juni hingga September 2025 dengan pendekatan partisipatif melalui tahapan sosialisasi, pelatihan, penerapan teknologi, pendampingan, dan evaluasi. Teknologi yang diterapkan berupa mesin tetas otomatis berbasis Internet of Things (IoT) dengan dukungan panel surya sebagai sumber energi alternatif, serta pencatatan produksi dan keuangan berbasis digital. Hasil pelaksanaan menunjukkan adanya peningkatan signifikan dalam keterampilan dan pemahaman mitra. Nilai rata-rata pretest sebesar 31% meningkat menjadi 87% pada posttest, dengan peningkatan rata-rata +56%. Tingkat keberhasilan penetasan juga meningkat dari 50–70% menjadi 75–85%. Selain itu, kuesioner kepuasan mitra memperoleh skor rata-rata 4,68 (kategori sangat puas). Kesimpulannya, program ini tidak hanya meningkatkan aspek teknis berupa keberhasilan penetasan dan manajemen usaha, tetapi juga memberdayakan masyarakat, khususnya perempuan, serta memperkuat keberlanjutan usaha melalui pemanfaatan energi terbarukan dan digitalisasi pencatatan.
Learning Management System Menggunakan Edmodo Pada SMK Ma’arif NU 1 Cilongok Fathoni, M Yoka; Kusumawardani, Dwi Mustika; Wijayanto, Sena; Prasetyo, Yogo Dwi; Fernandez, Sandhy; Wiedanto, Muhammad Awiet; Anwar, Toni
Jurnal Pengabdian Masyarakat Progresif Humanis Brainstorming Vol 6, No 3 (2023): Jurnal Abdimas PHB : Jurnal Pengabdian Masyarakat Progresif Humanis Brainstormin
Publisher : Politeknik Harapan Bersama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30591/japhb.v6i3.5295

Abstract

Kegiatan pengabdian ini dilatarbelakangi oleh pentingnya mengoptimalkan pembelajaran menggunakan teknologi di Era Revolusi Industri 4.0 dan Society 5.0 yang mengharuskan pembelajaran berkonversi dari manual menuju digital. Tantangan guru menghadapi keterbatasan situasi pandemi Covid-19 untuk berlatih pembelajaran secara daring. Pengembangan Learning Management System (LMS) berbasis website bertujuan untuk membantu guru-guru dalam metode pengajaran, kepraktisan berdasarkan angket respon peserta didik serta keefektifan modul berdasarkan ketuntasan belajar peserta didik. Penelitian ini menggunakan desain berdasarkan  hasil  observasi  pada  tenaga  pengajar  di  SMK Ma’arif NU 1 Cilongok  dapat  diketahui  bahwa guru masih belum dapat membangun pembelajaran dengan memanfaatkan teknologi yang ada yaitu komputer dan internet. Sehingga hasil pembelajaran dirasa kurang maksimal. Oleh karena itu, perlu kiranya dikembangkan Tutorial Edmodo untuk Tenaga Pengajar yang berisi tutorial penggunaan dan pemanfaatan Edmodo dalam pembelajaran agar dapat digunakan tenaga pengajar untuk untuk memecahkan masalah tersebut.
Strategi Pemasaran Produk UMKM Desa Cikakak Berbasis Teknologi Fathoni, M Yoka; Wijayanto, Sena; Fernandez, Sandhy; Aldo, Dasril; Darmansah, Darmansah
Jurnal Pengabdian Masyarakat Progresif Humanis Brainstorming Vol 6, No 1 (2023): Jurnal Abdimas PHB : Jurnal Pengabdian Masyarakat Progresif Humanis Brainstormin
Publisher : Politeknik Harapan Bersama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30591/japhb.v6i1.4520

Abstract

Pada saat ini strategi pemasaran berbasis teknologi merupakan suatu alternative pilihan masyarakat untuk berbelanja secara online. Metode yang dipakai dalam penjualan yang digunakan untuk pemasaran sebelumnya seperti melalui media whatsapp/ Instagram. Dengan adanya marketplace sebagai media penjualan mampu membuat sistem pemasaran menjadi lebih efektif, efisien dan mudah sehingga Masyarakat Desa Cikakak dapat mengenal marketplace sebagai media penjualan online.  Tujuan dari pengabdian ini merupakan untuk menambah wawasan masyarakat Desa Cikakak dari fungsi media promosi dan penjualan elektronik untuk mengetahui kendala yang dihadapi dalam memperkenalkan product UMKM ke dalam media marketplace. Jenis pengabdian masyarakat ini dilakukan dengan cara pelatihan langsung ke Desa Cikakak. Hasil pengabdian berupa pembuatan toko online di marketplace dengan menggunakan media promosi seperti Shopee, Tiktokshop dan Google My Business yang dapat membantu serta mempermudah mengurangi biaya yang dikeluarkan, dapat menyampaikan informasi secara detail dan cepat mengenai produk kepada pelanggan, sehingga produk dari UMKM desa Cikakak dapat dikenal lebih luas. Berdasarkan hasil pengabdian masyarakat ini diharapkan dapat membantu Desa Cikakak untuk mendapatkan hasil yang lebih maksimal serta dapat bersaing dengan toko offline maupun online yang sejenis.
Co-Authors 12.5202.0161 Daniel Yeri Kristiyanto Adanti Wido Paramadini Ade Tiara Rosalinda Alfarisi, Gitasari Kurnia Ali, Nizar Alika, Shintia Dwi Apriliana Puspitaningrum Ardi Susanto Arif Riyandi Aruga Yudish Firmansyah Ayu Kusumaningtyas Azzahra, Anisa Cahyo Prihantoro Dading Qolbu Adi Dairoh Dairoh Dandi Sunardi Dany Candra Febrianto Darmansah Darmansah, Darmansah Dasril Aldo Dea Caesy Rahmadani Dedy Agung Prabowo Dega Surono Wibowo Dwi Januarita Dwi Januarita Dwi Mustika Kusumawardani, Dwi Mustika Farkhan Hariyadi Berbudi Bowoleksono Fauzi, Faiq Firmansyah, Muhammad Raafi'u Garin Indra Prameswara Hutanti Setyodewi Ike Kurnia Putri Irwan Susanto Jihan Shinta Celina Lina Fatimah Lishobrina Linda Ayu Kusuma Ningrum Logiandani Logiandani M Nishom M Nishom Mahazam Afrad Maulida, Elsa Miftahul Jannah Monsya Juansen Muhamad Albirra Arsyi Rizqi Muhamad Awiet Wiedanto Prasetyo Muhammad Fikri Hidayattullah Muhammad Imanullah Nabila Azahra Naufal Ibrahim Nevandra Putra Andyka Ni Wayan Wardani Nicolaus Euclides Wahyu Nugroho Nindi Ilmiyati Fajriyah Nunik Oktaviani Olivia Sari Purba, Yessi Pahrizal, Pahrizal Pero Roberto Kristovic Radiyana Aniq Friliyani Raihan Zidane Ramadhan Ramadhan, Firman Adi Ramadhani S, Bunga Rona Nisa Sofia Amriza RR Hutanti Setyodewi Safhira Nanda Rahmadhani Salsabila Cahya Alifia Sandhy Fernandes Sandhy Fernandez Sayyidah Jasinda Amalia Selly Anggraeni Sena Wijayanto Sisilia Thya Safitri Siti Khomsah, Siti Sudianto Sukmadiningtyas Sulaeman, Gilang Syabrian, Izma Syifa Nur Fadhilah Tegar Wahyudi Adha Tomy Nanda Putra Toni Anwar Toni Anwar Toyib, Rozali Waliulu, Raditya Faisal Wiedanto, Muhammad Awiet Yedija Maarende, Tigris Yogo Dwi Prasetyo Yogo Dwi Prasetyo Yohani Setiya Rafika Nur Yulia Darmi Yustia Hapsari Zahra Fikri Ayu Nirwana