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All Journal Jurnal Mahasiswa Fakultas Teknologi Informasi Jurnal EECCIS JPM (Jurnal Pemberdayaan Masyarakat) SMARTICS Journal METHOMIKA: Jurnal Manajemen Informatika & Komputerisasi Akuntansi J I M P - Jurnal Informatika Merdeka Pasuruan Martabe : Jurnal Pengabdian Kepada Masyarakat Conference on Innovation and Application of Science and Technology (CIASTECH) Kurawal - Jurnal Teknologi, Informasi dan Industri Infotronik : Jurnal Teknologi Informasi dan Elektronika Jurnal Informatika dan Rekayasa Perangkat Lunak Jurnal Pengabdian Masyarakat Khatulistiwa Patria : Jurnal Pengabdian Kepada Masyarakat Jurnal Pengabdian Masyarakat Asia Rainstek : Jurnal Terapan Sains dan Teknologi GANESHA: Jurnal Pengabdian Masyarakat AMMA : Jurnal Pengabdian Masyarakat BIMASAKTI Smatika Jurnal : STIKI Informatika Jurnal
Mohammad Ahsan
Universitas PGRI Kanjuruhan Malang
Agriculture, Biological Sciences & Forestry Arts Humanities Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Mathematics Nursing Public Health Social Sciences Other

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PENERAPAN METODE NAÏVE BAYES DAN SUPPORT VECTOR MACHINE PADA ANALISIS SENTIMEN NETIZEN DI TWITTER VOLLEY BALL INDONESIA Wismo Ginanjar; Alexius Endy Budianto; Moh Ahsan; Muhammad Priyono Tri Sulistyanto
Jurnal Fakultas Teknologi Informasi Vol 8 No 2 (2026): BIMASAKTI
Publisher : Prodi Teknik Informatika, Fakultas Sains dan Teknologi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21067/bimasakti.v8i2.12376

Abstract

Social media has become an integral part of modern society, offering a platform for public opinion expression. In Indonesia, volleyball is a very popular sport, and Volley Ball Indonesia is the main topic of discussion on social media, especially Twitter. This study aims to analyze the sentiment of netizen comments on the official Twitter account of Volley Ball Indonesia (@volleyball.indonesia) using the Naive Bayes method and Support Vector Machine (SVM). The data used amounted to 2,920 comments from 50 posts in the period of September 28, 2023 - May 10, 2024, focused on the U-23 and Senior Men's National Team matches. Naïve Bayes and SVM were chosen because both are effective methods in sentiment classification. Naïve Bayes uses a probabilistic approach, while SVM looks for the best hyperplane to separate data classes. The results of the study show that both methods can be used to analyze sentiment with a good level of accuracy. The test results on each training data and testing data with different presentations will provide different accuracy results. The test results of the Naive Bayes method obtained the highest accuracy value of 71% with a ratio of 70:30 and the Support Vector Machine obtained the highest accuracy value of 76% with a ratio of 80:20. So it can be concluded that the Support Vector Machine method gets a higher accuracy value than the Naive Bayes method.
PENERAPAN ALGORITMA LOGISTIC REGRESSION UNTUK KLASIFIKASI PENYAKIT STROKE Rachel Trivica Amelia; Danang Aditya Nugraha; Moh Ahsan
Jurnal Fakultas Teknologi Informasi Vol 8 No 2 (2026): BIMASAKTI
Publisher : Prodi Teknik Informatika, Fakultas Sains dan Teknologi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21067/bimasakti.v8i2.13201

Abstract

Stroke is one of the leading causes of death worldwide, ranking after heart disease and cancer. Early detection of stroke risk is essential to enable faster and more accurate treatment. The purpose of this study is to apply the Logistic Regression algorithm to classify stroke cases based on several risk factors, including gender, age, hypertension, heart disease, marital status, occupation, residence type, average glucose level, body mass index (BMI), smoking status, and stroke status. The dataset used in this research was obtained from Kaggle and consists of 5,110 patient records. The research process involves several stages, including data cleaning, data transformation, and normalization using the Min-Max Scaler method, followed by splitting the data into training and testing sets with various proportions (90%-10%, 85%-15%, 80%-20%, 70%-30%, and 65%-35%). The evaluation was conducted using a Confusion Matrix with performance metrics such as accuracy, precision, recall, and F1-score. The analysis results show that the 90%-10% data split achieved the highest accuracy of 76.17%, with precision and recall values indicating that the model performs well in identifying non-stroke cases. However, performance on the minority class (stroke) remains relatively low, suggesting the need for improvement through data imbalance handling. Overall, the application of the Logistic Regression algorithm proved to be effective for initial stroke classification, although accuracy can still be improved through resampling techniques or advanced model optimization.
Pemanfaatan Techno-Pest Control Berbasis IoT Untuk Membasmi Hama Padi di Area Persawahan Pondok Condongcatur Dianna Ratnawati; Setuju; Zamroni; Sigit Purnomo; Moh Ahsan
Jurnal Pemberdayaan Masyarakat Vol 5 No 2 (2020): November
Publisher : Direktorat Penelitian dan Pengabdian kepada Masyarakat (DPPM)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21067/jpm.v5i2.4699

Abstract

Planthopper and grasshopper pests that attack rice plants in the Padukuhan Pondok rice fields, Condongcatur have an impact on decreasing productivity of rice farmers. The objectives of this community service are: (1) to produce an IoT-based techno-pest control device by utilizing solar cells as power supply; (2) increasing the skills of farmers in using efficient technology that is economical, modern and environmentally friendly. The methods used include experimentation, socialization and training. This community service activity is the manufacture of IoT-based techno-pest control tools and tool dissemination. The dissemination activity was successfully held and attended by 50 participants from the farmer's group of culinary sources, the participants actively asked questions and were enthusiastic in practicing the operation of the tools. 85% of participants can operate the equipment in groups. Techno-pest control tools can eradicate planthoppers and grasshoppers at a radius of 6m within 4 hours via 40kHz ultrasonic waves. This tool is integrated on the internet to monitor the situation of rice fields by accessing the website http://pkm.ptm.ustjogja.ac.id.
OPTIMALISASI ANALISIS SENTIMEN FILM PADA YOUTUBE DENGAN ALGORITMA CHI-SQUARE PADA NAÏVE BAYES DAN SUPPORT VECTOR MACHINE Oky Kurnia Wardana; Alexius Endy Budianto; Moh Ahsan
Jurnal Fakultas Teknologi Informasi Vol 8 No 1 (2025): BIMASAKTI
Publisher : Prodi Teknik Informatika, Fakultas Sains dan Teknologi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21067/bimasakti.v8i2.12377

Abstract

The management of correspondence and monthly reports in educational administration environments still faces efficiency issues due to workflows that do not align with user needs and insufficient attention to usability aspects. These conditions result in suboptimal performance and low effectiveness in the use of digital systems. This study aims to analyze the usability of the web-based SIRATU application using the User-Centered Design (UCD) approach in accordance with the ISO 9241-210 standard. The research method includes analysis of the context of use, user identification, interface design, and usability evaluation using the System Usability Scale (SUS). The study is limited to the primary users of the SIRATU application, namely administrative staff, school operators, and the head of the district education office, with a focus solely on usability aspects. The evaluation results show an increase in the average SUS score from 60.6 to 87.4, which falls into the excellent category. The contribution of this study lies in the application of a UCD methodological framework that has proven effective in improving the usability of the SIRATU application.
ANALISIS PERANCANGAN UI/UX PADA SISTEM TERINTEGRASI DATA PENDUDUK KABUPATEN MALANG (SI-CANTIK) MENGGUNAKAN METODE HUMAN CENTERED DESIGN Ahmad Yudha Presetia; Alexius Endy Budianto; Moh Ahsan
Jurnal Fakultas Teknologi Informasi Vol 8 No 1 (2025): BIMASAKTI
Publisher : Prodi Teknik Informatika, Fakultas Sains dan Teknologi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21067/bimasakti.v8i2.12517

Abstract

The management of correspondence and monthly reports in educational administration environments still faces efficiency issues due to workflows that do not align with user needs and insufficient attention to usability aspects. These conditions result in suboptimal performance and low effectiveness in the use of digital systems. This study aims to analyze the usability of the web-based SIRATU application using the User-Centered Design (UCD) approach in accordance with the ISO 9241-210 standard. The research method includes analysis of the context of use, user identification, interface design, and usability evaluation using the System Usability Scale (SUS). The study is limited to the primary users of the SIRATU application, namely administrative staff, school operators, and the head of the district education office, with a focus solely on usability aspects. The evaluation results show an increase in the average SUS score from 60.6 to 87.4, which falls into the excellent category. The contribution of this study lies in the application of a UCD methodological framework that has proven effective in improving the usability of the SIRATU application.
Co-Authors Abdul Aziz Ady Atna Sihmahfudha Agus Setyawan Agustin Rita Lestari Ahmad Yudha Presetia Ainia Walidaroyani Ajeng Intan Nur Rahmawati Amak Yunus Anis Kusniati Budianto, Alexius Endy C Lenny Danang Aditya Nugraha Devi Permatasari Dianna Ratnawati Dina Fatma Dewi Eko Prasetyo, Amak Yunus Endi Sarwoko Febrian Kusuma Fery Agung Prastyo Harry Soekotjo Dachlan Ibnu Arivin Iva Nurdiana Iva Nurdiana Nurfaida Iva Nurdiana Nurfarida Ivan Yusuf Rahadika Katharina Devi Hilda Leny Latifah M Haris Adiansyah Mayang Ramadhanti Meme Susilowati Muhammad Priyono Tri Sulistyanto Niko Achmad Nila Restu Wardani Oky Kurnia Wardana Purnomo Budi Santoso Rachel Trivica Amelia Radinal Apriyanto Rahman Riady Retno Marsitin Riski Nur Istiqomah Dinnullah Robbi Tri Murdani Romadhon Romadhon San Vitores Jemalut Setuju Sigit Purnomo Sri Umi Mintarti Sulistyanto, Muhammad Priyono Tri Susanti, Romia Hari Syahminan Syahminan Tutik Indrawati Wahyudi Arianto Wedha Adistianaya Dewa Wismo Ginanjar Yudhi Kurniawan Yulia Windi Astuti Yulianti & Ninik Indawati Hartatik Yusuf Rahardika, Ivan Zamroni