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All Journal BAREKENG: Jurnal Ilmu Matematika dan Terapan Lumbung Inovasi: Jurnal Pengabdian Kepada Masyarakat Equiva
Utomo, Muchammad Chandra Cahyo
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Humanities Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Education Energy Engineering Environmental Science Mathematics Mechanical Engineering Physics Social Sciences Transportation

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Peningkatan Literasi Digital di RT 029 Kelurahan Lamaru Melalui Sarasehan Penggunaan Internet Bijak, Sosialisasi Instagram, dan Pembuatan Website Administrasi Darmansyah, Darmansyah; Utomo, Muchammad Chandra Cahyo; Farezky, M Irghi; Amelia, Mila Yusi; Sasmito, Shafa Putri
Lumbung Inovasi: Jurnal Pengabdian kepada Masyarakat Vol. 9 No. 4 (2024): December
Publisher : Lembaga Penelitian dan Pemberdayaan Masyarakat (LITPAM)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36312/linov.v9i4.2282

Abstract

Meningkatnya penetrasi internet yang tidak selalu berbanding lurus dengan tingkat literasi digital masyarakat. Di tengah pesatnya perkembangan teknologi, literasi digital menjadi salah satu keterampilan yang sangat penting dan mendesak untuk dimiliki oleh setiap individu. Program pengabdian masyarakat di RT 029 Lamaru, Kecamatan Balikpapan Timur, bertujuan untuk meningkatkan literasi digital warga melalui penerapan empat pilar utama Peta Jalan Literasi Digital Nasional 2020-2024, yakni Digital Skill, Digital Ethics, Digital Safety, dan Digital Culture. Kegiatan ini bertujuan membekali warga dengan keterampilan yang dibutuhkan untuk menghadapi tantangan di era digital, seperti penggunaan media sosial yang produktif, pengelolaan website administrasi RT, serta pemahaman tentang keamanan dan etika digital. Metode yang digunakan dalam pengumpulan data adalah kuisioner, observasi, wawancara dan dokumentasi. Indikator keberhasilan  digunakan  untuk  mengukur tingkat pencapaian tujuan kegiatan. Indikator ini mencakup penyampaian materi dan kebermanfaatan program sosialisasi sosial media, penggunaan internet dengan bijak dan website administrasi RT .Evaluasi kegiatan menunjukkan bahwa penyampaian materi dinilai cukup baik dengan rata-rata skor 4,00 dari skala 5, sedangkan kebermanfaatan program memperoleh nilai 4,31 dari skala 5. Hal ini menunjukkan bahwa warga merasa bahwa program ini memberikan dampak positif dan bermanfaat, baik dari segi peningkatan keterampilan maupun pemahaman terhadap literasi digital. Improving Digital Literacy in RT 029 Lamaru Village through Internet Wise Use Workshop, Instagram Socialisation, and Administrative Website Creation Abstract Increasing internet penetration is not always directly proportional to the level of digital literacy of the community. In the midst of rapid technological development, digital literacy is one of the most important and urgent skills to be possessed by every individual. The community service programme in RT 029 Lamaru, East Balikpapan Sub-district, aims to improve the digital literacy of residents through the implementation of the four main pillars of the National Digital Literacy Roadmap 2020-2024, namely Digital Skill, Digital Ethics, Digital Safety, and Digital Culture. This activity aims to equip residents with the skills needed to face challenges in the digital era, such as productive use of social media, management of neighbourhood administration websites, and understanding of digital safety and ethics. The methods used in data collection were questionnaires, observation, interviews and documentation. Success indicators were used to measure the level of achievement of the activity objectives. These indicators include the delivery of material and the usefulness of the social media socialisation programme, the wise use of the internet and the RT administration website. The evaluation of the activity indicates that the material delivery was rated fairly well, with an average score of 4.00 out of 5, while the program’s usefulness received a score of 4.31 out of 5.. This shows that residents felt that the programme had a positive and beneficial impact, both in terms of improving skills and understanding of digital literacy.
Analisis Sentimen Media Sosial Twitter pada Kasus Pemberlakuan Pembatasan Kegiatan Masyarakat dengan menggunakan Metode Naïve Bayes Classifier Utomo, Muchammad Chandra Cahyo; Taukhid, Mukhamad; Mujahidin, Syamsul
Equiva Journal Vol 1 No 1 (2023)
Publisher : Jurusan Matematika dan Teknologi Informasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35718/equiva.v1i1.815

Abstract

Social media is a medium used by users to introduce themselves, interact, collaborate, and share information with other users using the internet. One of the popular social media platforms in Indonesia is Twitter. Twitter is a social media that generally functions as a sender of messages which are usually referred to as tweets or tweets. One of the topics that has been widely discussed is the Policy on Enforcement of Restrictions on Community Activities (PPKM), due to the impact of an increase in cases due to the emergence of a new variant of COVID, namely the Omicron. One of the aims of this study is to find out the results of sentiment analysis regarding public opinion on the imposition of restrictions on community activities using the Naive Bayes method. There techniques machine learning for sentiment analysis, one of which is the Naive Bayes classifier, which is a machine learning technique based on probabilistic. NBC is a simple but very accurate and effective text classification method whose classification is heavily influenced by the training data process. The data used is taken via Twitter with 1594 tweets. The data set will be divided into training data and testing data by comparing 90% training and 10% testing. So, the details of the distribution of the data used in this study are 1594 tweets as training data and 160 tweets as test data. The NBC process crawling data pre-processing, data sharing, data labelling Bayes model naive classification, training data classification. The results of the analysis of public opinion sentiment regarding the imposition of restrictions on community activities using the Naive Bayes obtained a sentiment value of 71% sentiment negatif and 29% sentiment positif, accuracy value of 0.84, F1-Score 0.84, precision is 0.85, and recall is 0,84 ​.
Analisis Sentimen Pada Twitter Terhadap Isu Penundaan Pemilu 2024 Dengan Membandingkan Metode Long Short-Term Memory Dan Naïve Bayes Classifier Mahmuji Cholis, Fahmi; Utomo, Muchammad Chandra Cahyo; Fadhliana, Nisa Rizqiya
Equiva Journal Vol 1 No 2 (2023)
Publisher : Jurusan Matematika dan Teknologi Informasi

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Abstract

Negara Indonesia memiliki sistem pemerintahan yang berbentuk sistem demokrasi, oleh karena itu pada sistem demokrasi untuk memilih orang yang akan menjadi penjabat politik diperlukan adanya sebuah proses pemilihan. Proses tersebut dikenal dengan Pemilu (Pemilihan Umum). Menjelang pemilu pada 2024 muncul isu wacana penundaan Pemilu 2024. Di Indonesia, pengguna Twitter pada tahun 2022 sebanyak 18,45 juta. Dilihat dari banyaknya pengguna Twitter dengan munculnya isu penundaan pemilu, membuat banyak orang menyampaikan opininya di Twitter terkait isu tersebut. Penelitian ini untuk dapat mengetahui opini masyarakat secara umum pada Twitter terhadap isu penundaan Pemilu 2024 dengan membandingkan metode Long Short-Term Memory dan Naïve Bayes Classifier. Penelitian dilakukan dengan tahap crawling, pre-processing, pelabelan data, pembagian data train dan data test dengan perbandingan 9:1. Pada metode Long Short-Term Memory memperoleh nilai accuracy sebesar 92%, precision untuk kelas negatif sebesar 92% dan kelas positif sebesar 92%, Recall untuk kelas negatif sebesar 92% dan kelas positif sebesar 92%,F1-Score untuk kelas negatif sebesar 92% dan kelas positif sebesar 92%. Pada metode Naïve Bayes Classifier memperoleh nilai accuracy sebesar 80%, precision untuk kelas negatif sebesar 83% dan kelas positif sebesar 77%, Recall untuk kelas negatif sebesar 79% dan kelas positif sebesar 82%, F1-Score untuk kelas negatif sebesar 81% dan kelas positif sebesar 80%. Hasil analisis sentimen pada Twitter terhadap isu penundaan Pemilu 2024 dengan metode Long Short-Term Memory didapat sentimen positif sebesar 52.9% dan sentimen negatif sebesar 47.1%, sedangkan dengan metode Naïve Bayes Classifier didapat sentimen positif sebesar 32.5% dan sentimen negatif sebesar 67.5%.
Implementasi Kerangka Kerja Personal Extreme Programming pada Pengembangan Aplikasi Pelayanan Administrasi Masyarakat Kantor Desa Girimukti Berbasis Web Shafardan, Wahyu Achmad; Utomo, Muchammad Chandra Cahyo; Nugroho, Bowo
Equiva Journal Vol 1 No 2 (2023)
Publisher : Jurusan Matematika dan Teknologi Informasi

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Abstract

Pelayanan administrasi termasuk dalam pelayanan yang ada pada kantor desa. Kantor desa sangat membutuhkan sistem untuk membantu proses penulisan surat. Pelayanan administrasi Kantor Desa Girimukti merupakan salah satu hal yang perlu ditingkatkan agar proses pelayanan dapat diselesaikan dengan cepat dan mudah. Tujuan dari penelitian ini adalah merancang dan membangun aplikasi pelayanan administrasi kantor desa Girimukti berbasis web dengan menggunakan framework personal extreme programming. Pengembangan sistem dengan 86 story point dan 33 user story dan dilakukan dalam 5 iterasi berhasil untuk dilakukan. Tahap pengujian aplikasi berlangsung di setiap iterasi dan mendapatkan angka rata-rata 6.7, 7, 6.85, 7 dan 6.7. Tahap testing berhasil diselesaikan karena didapatkan skor melebihi 5 sebagai standar skor testing. Kerangka kerja Personal Extreme Programming berhasil diimplementasikan dalam penelitian ini. Dengan bantuan aplikasi pelayanan administrasi masyarakat pada kantor desa Girimukti diharapkan dapat mempermudah semua proses pendataan dan penulisan surat.
Pengembangan Sistem Informasi Manajemen Inkubator Bisnis Teknologi di Institut Teknologi Kalimantan berbasis Website menggunakan Metode Extreme Programming Aditya, Andhika; Utomo, Muchammad Chandra Cahyo; Mujahidin, Syamsul
Equiva Journal Vol 1 No 2 (2023)
Publisher : Jurusan Matematika dan Teknologi Informasi

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Abstract

The Kalimantan Institute of Technology has several organizations, one of which is a technology business incubator (IBT). The technology business incubator at ITK does not yet have an information system that can disseminate information regarding registration, selection and training information. IBT ITK requires media to be able to fulfill the need for information publication related to technology business incubators in ITK. Based on the previous problems, it is necessary to build a website-based management information system to facilitate the dissemination of information. The management information system that was built requires a systematic and structured method for its development, so the Extreme Programming method is used with the Laravel framework and MySQL as the database. The Extreme Programming method consists of several stages, namely observation, planning, iteration initialization, design, implementation (unit testing, code, refactor), system testing, retrospective. The results of the research show that the Extreme Programming method is capable of producing an information system that can meet the needs of stakeholders as shown from the test results.
CLUSTERING ANALYSIS FOR GROUPING SUB-DISTRICTS IN BOJONEGORO DISTRICT WITH THE K-MEANS METHOD WITH A VARIETY OF APPROACHES Nurdiansyah, Denny; Ma'ady, Mochamad Nizar Palefi; Sukmawaty, Yuana; Utomo, Muchammad Chandra Cahyo; Mutiani, Tia
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 18 No 2 (2024): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol18iss2pp1095-1104

Abstract

Population data is an important piece of information that is useful for regional planning and development. Insight into the state of an area is more straightforward to observe if there are grouped sub-districts. In this case, data mining techniques can identify patterns and relationships in population data. The K-Means algorithm is a clustering technique that divides data into groups or clusters based on similar characteristics. This research aims to apply the K-Means method with various approaches to clustering sub-districts in the Bojonegoro district according to population data. The research method used is a quantitative method with an exploratory study in the application of the K-Means method with a variety of approaches, namely the use of the Kernel K-Means method by utilizing the mapping function to map data to a higher dimension before the clustering process. In addition, the Fast K-Means method is used, which reduces the model training time to improve the cluster-centered recalibration problem as the amount of data increases. The data source used in this research is secondary population data in the form of birth, death, migrant, and moving variables obtained from the Satu Data Bojonegoro website developed by the Bojonegoro Regency Government. It is found that the best K-Means approach is the Kernel K-Means method with a number of clusters of 5. The performance of the cluster method is evaluated by measuring the average distance within the cluster. The data coordinate pattern in the Kernel K-means method clustering shows a smooth initial trend when the value of the number of clusters is 5 so that the clusters formed are obtained clearly. The conclusion from this study's results is that the K-Means method's best approach in grouping sub-districts in Bojonegoro district is the Kernel K-Means approach.
IMPLEMENTATION OF THE SEM-PLS APPROACH TO ANALYZE THE IMPACT OF SOCIAL AID AND APBD ON POVERTY IN THE BOJONEGORO DISTRICT Nurdiansyah, Denny; Novitasari, Diah Ayu; Ridho, Sari Lestari Zainal; Utomo, Muchammad Chandra Cahyo; Oktafiya, Dewi Putri Nur
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 19 No 1 (2025): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol19iss1pp525-536

Abstract

Poverty is the socio-economic condition of individuals or groups whose fundamental rights to maintain and develop a decent life are unmet. The poverty rate in Bojonegoro was 12.21% in 2022. In order to solve this problem, a poverty model is needed to serve as a reference for the further development of Bojonegoro district. This study aimed to determine the impact of social aid and APBD on poverty in Bojonegoro district. The methodology used in this study is his SEM-PLS quantitative research modeling of poverty using the WarpPLS application. The data sources for this study are the following secondary data in the form of Bojonegoro District Poverty Data, Area Appropriations Budget (APBD), and Social Aid (Bansos) from 2019 to 2022. Survey data were accessed online through the official website. Information from the Central Bureau of Statistics (BPS) and Satu Data Bojonegoro website. The results of this study show that SEM-PLS was applied correctly, and satisfactory results were obtained in terms of overall fit size, measured fit size, and structural fit size. The analysis results show that the variable APBD significantly impacts poverty with a proportion of -0.91. It means that the higher the realization of APBD, the lower the existing poverty rate. Social Aid variables up to -0.09 do not significantly impact poverty. It means that the amount of social benefits you receive does not affect poverty. The conclusion is that the factors that influence poverty in Bojonegoro district are its APBD variables.
Co-Authors Aditya, Andhika Amelia, Mila Yusi Denny Nurdiansyah Fadhliana, Nisa Rizqiya Farezky, M Irghi Mahmuji Cholis, Fahmi Mochamad Nizar Palefi Ma’ady Mutiani, Tia Novitasari, Diah Ayu Nugroho, Bowo Oktafiya, Dewi Putri Nur Ridho, Sari Lestari Zainal Sasmito, Shafa Putri Shafardan, Wahyu Achmad Solly Aryza Sukmawaty, Yuana Syamsul Mujahidin, Syamsul Taukhid, Mukhamad