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All Journal Jurnal Informatika Infotek : Jurnal Informatika dan Teknologi ABSYARA: Jurnal Pengabdian Pada Masyarakat Jurnal Teknologi Informasi untuk Masyarakat (Jurnal Teknokrat)
Yahya, Yahya
Universitas Hamzanwadi
Agriculture, Biological Sciences & Forestry Computer Science & IT Control & Systems Engineering Earth & Planetary Sciences Education Engineering Environmental Science Languange, Linguistic, Communication & Media Library & Information Science Mathematics Other

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Implementasi jaringan internet guna meningkatakan pelayanan pemerintah desa di Kecamatan Sembalun Muhamad Sadali; Yupi Kuspandi Putra; Yahya Yahya; Intan Komala Dewi
ABSYARA: Jurnal Pengabdian Pada Masayarakat Vol 2 No 2 (2021): ABSYARA: Jurnal Pengabdian Pada Masyarakat
Publisher : Universitas Hamzanwadi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29408/ab.v2i2.4356

Abstract

Internet network has become a basic need for all government offices, from central to village governments. This is because the Indonesian government has built an integrated online system. Therefore, this service aims to assist all village governments in Sembalun District in improving services for the community in information technology. The target of the activity is Sembalun District which is the leading partner. The target and outcome of this service are establishing an internet network facility of a village government in Sembalun District to improve services in information and communication technology. The method used is a participatory approach to community development or Participatory Rural Appraisal (PRA). The results of this service are: 1) The internet network facility greatly helps the village government, 2) Village officials can complete their work based online, 3) The village government can improve services in information and communication technology. With the community service that has been carried out, it is hoped that it can help all village governments in Sembalun District carry out their duties to the maximum and improve services for the community.
Implementasi Algoritma Naive Bayes Untuk Klasifikasi Penerima Beasiswa (Studi Kasus Universitas Hamzanwadi) Nur Ida Nurhidayati; Yahya Yahya Yahya; Fathurrahman Fathur Fathurrahman; L.M. Samsu Samsu L.M. Samsu; Wajizatul Amnia wajizatul Wajizatul Amnia
Infotek: Jurnal Informatika dan Teknologi Vol. 6 No. 1 (2023): Infotek : Jurnal Informatika dan Teknologi
Publisher : Fakultas Teknik Universitas Hamzanwadi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29408/jit.v6i1.7529

Abstract

Every year the University offers various types of scholarships to its students, including Hamzanwadi Selong University, East Lombok. One type of scholarship offered is the Bidikmisi scholarship (KIP/K) which is intended for students who have middle to lower economic levels but have good academic achievement or potential. Every year the number of applicants for this scholarship continues to increase, but the number received each year is limited. The large number of piles of files applying for scholarships and the manual selection process tends to be ineffective and efficient and the results of the selection are inaccurate, so a system is needed that is able to assist in the selection process quickly, easily and on target. The method used is CRIS-DM with the Naive Bayes Classifier algorithm modeling, this method is an approach that refers to the Bayes theorem which combines previous knowledge with new knowledge. The variables consist of 7 attributes, namely: Name, DTKS status, achievement, parents' occupation, total income of parents, home ownership, and number of family dependents[1]. Testing was carried out using k-fold cross validation, and the highest accuracy results were obtained from k-fold 4 of 91.43%, while the AUC was 0.996% with a very good diagnostic classification. Thus it can be interpreted that the Naive Bayes algorithm is very well used in the selection of scholarships for bidikmisi scholarships at Hamzanwadi University
Pelatihan Aplikasi Artificial Intelligence (AI) Bagi Siswa Jurusan Rekayasa Perangkat Lunak Pada Sekolah Menengah Kejuruan (SMK) 3 Selong Muh. Adrian Juniarta Hidayat; Yupi Kuspandi Putra; Yahya; Liana Rozita Muzarrofah
Jurnal Teknologi Informasi untuk Masyarakat Vol. 4 No. 1 (2026): Jurnal Teknologi Informasi untuk Masyarakat (Teknokrat)
Publisher : Universitas Hamzanwadi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29408/jt.v4i1.35328

Abstract

The development of artificial intelligence (AI) technology provides opportunities to increase the effectiveness and productivity of learning in the field of software engineering. However, some students still lack adequate knowledge and skills in utilizing AI applications to support the learning process of programming and software development. This community service activity aims to improve the competence of students of the Software Engineering Department of SMKN 3 Selong in using AI applications as learning aids and software development. The method used is Participatory Learning and Action (PLA) which actively involves participants through material delivery, demonstrations, hands-on practice, and discussion sessions. The results of the activity show that participants are able to understand the basic concepts of AI and utilize various AI applications to help find programming solutions, create program codes, documentation, and design software. In addition, participants demonstrated improved skills in completing software development tasks more effectively and efficiently. This activity provides benefits in the form of increased technological literacy, learning productivity, and student readiness to face technological developments and the needs of the software industry that increasingly utilizes artificial intelligence.
Peningkatan Literasi Artificial Intelligence bagi Siswa SMA sebagai Bekal Menghadapi Era Society 5.0 Rio Juniyantara Putra; Yahya; Ramli Ahmad; Samsul Al Kifli
Jurnal Teknologi Informasi untuk Masyarakat Vol. 4 No. 1 (2026): Jurnal Teknologi Informasi untuk Masyarakat (Teknokrat)
Publisher : Universitas Hamzanwadi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29408/jt.v4i1.35590

Abstract

The rapid development of Artificial Intelligence (AI) in the Society 5.0 era requires improved technological literacy among high school students as preparation for digital transformation and future competency demands. This Community Service (PkM) activity aims to enhance students’ AI literacy through the introduction of basic AI concepts, ethical use of AI, and its application in supporting the learning process. The activity was conducted at SMA Darussolihin NW Kalijaga involving 23 students through interactive presentations, demonstrations, hands-on practice using ChatGPT, group discussions, and evaluation using pre-test and post-test assessments. The results show that students’ average AI literacy score increased from 64.80 before the activity to 77.87 after the activity, representing an improvement of 20.12%. In addition, students demonstrated improved understanding of basic AI concepts, awareness of ethical AI usage, the ability to utilize AI to support learning, and increased confidence in using technology responsibly. This activity was proven effective in enhancing AI literacy and students’ digital competencies, while also serving as a relevant strategy to strengthen critical thinking skills, encourage responsible technology use, and prepare the younger generation for the challenges and opportunities of the Society 5.0 era.
Analisis Sentimen Komentar Masyarakat di Twitter Menggunakan Algoritma Support Vector Machine Arnila Sandi; Yahya; Muhammad Qusaeri
Infotek: Jurnal Informatika dan Teknologi Vol. 9 No. 2 (2026): Infotek : Jurnal Informatika dan Teknologi
Publisher : Fakultas Teknik Universitas Hamzanwadi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29408/jit.v9i2.35290

Abstract

Social media has become the primary means for the public to express their opinions on a wide range of issues, one of which is smartphone products. The social media platforms used to express opinions include Facebook, Instagram, Twitter, WhatsApp and YouTube. Twitter is one of the most widely used platforms for expressing opinions in the form of comments, which may be positive, negative or neutral. This study aims to classify the sentiment of Twitter users’ comments regarding smartphones using the Support Vector Machine (SVM) algorithm. The research employs a quantitative methodology. The data used consists of comments or text data in CSV format, which is processed through a series of pre-processing steps, including data cleaning, tokenisation, stop-word removal and stemming. This will be followed by sentiment modelling and an evaluation of the model’s performance. The results of the study show that the SVM method achieved an accuracy of 82,28%, a recall of 82,26%, a precision of 82,25%, and an F1-score of 82,25%. Based on these results, it can be concluded that the SVM algorithm performs well in sentiment analysis of social media data, particularly Twitter.
Klasterisasi Status Stunting pada Balita Menggunakan Algoritma K-Means Yahya; Nurhidayati; Fathurrahman; Arnila Sandi
Infotek: Jurnal Informatika dan Teknologi Vol. 9 No. 2 (2026): Infotek : Jurnal Informatika dan Teknologi
Publisher : Fakultas Teknik Universitas Hamzanwadi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29408/jit.v9i2.35298

Abstract

Stunting is a growth and development disorder in children due to chronic malnutrition and repeated infections characterized by below-standard height. Cadres conduct monthly Posyandu data collection by weighing and measuring toddlers. However, the Posyandu data results only become piles of paper in the cadres' homes. Based on these conditions, it is necessary to process data for clustering that can help the village government in grouping toddler data so that the government knows the number of stunted and normal toddlers, which can later be used as evaluation material in the future in taking action to reduce, prevent and overcome stunting cases. This study aims to group stunted and normal toddlers based on age, weight, and height variables. The method applied is data clustering using the K-Means Algorithm. The results of this study are clusters divided into 2 clusters, in cluster 1 there are 406 toddlers with normal status as many as 119 toddlers and toddlers with stunting status as many as 287 toddlers, while in cluster 2 there are 326 toddlers with normal status as many as 52 toddlers and toddlers with stunting status as many as 274 toddlers. A total of 171 toddlers with normal status, representing 23.4%, and 561 toddlers with stunting, representing 76.6%. These results demonstrate the critical need for support from integrated health posts (Posyandu) and relevant community health centers (Puskesmas) to parents of toddlers to reduce or even eliminate stunting in the following period.
Penerapan Algoritma K-Means Dalam Mengelompokkan Ruang Pasien BPJS Untuk Menentukan Pola Perawatan Kesehatan Yang Efektif Amri Muliawan Nur; Yahya; Rodhiyah FIlkhaer; Suhartini
Infotek: Jurnal Informatika dan Teknologi Vol. 9 No. 1 (2026): Infotek : Jurnal Informatika dan Teknologi
Publisher : Fakultas Teknik Universitas Hamzanwadi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29408/jit.v9i1.33079

Abstract

The National Health Insurance organizer managed by BPJS Kesehatan plays a crucial role in ensuring equitable and quality healthcare services for all Indonesian citizens. The increasing number of BPJS participants encourages healthcare facilities to implement more efficient data-driven management. Fakhira Clinic in East Lombok still faces challenges in managing treatment rooms and formulating service strategies due to suboptimal use of data analysis, causing decisions to often be made reactively.This study aims to apply the K-Means clustering algorithm to group BPJS patient rooms. The K-Means algorithm is used to cluster BPJS patients based on their characteristics and service needs, such as gender, age, type of illness, visit frequency, duration of treatment, and payment method. Analysis of 500 BPJS patient data resulted in three main clusters: 217 patients with light treatment patterns, 158 patients with moderate care needs, and 125 patients with intensive care requirements. Each cluster shows different tendencies regarding age, length of hospital stay, and diagnosis. This information can be utilized as a basis for arranging treatment rooms, accelerating service processes, and formulating more effective and targeted care strategies.
Co-Authors Arnila Sandi Bahtiar, Hariman Fathurrahman Fathurrahman, Imam Hidayanti, Winda Puspita Intan Komala Dewi L M Samsu Liana Rozita Muzarrofah Mahpuz, Mr. Mahpuz Martua Hamonangan Nasution Muh. Adrian Juniarta Hidayat Muhammad Qusaeri Muhammad Wasil Muhammad, Saiful Mulyawan Nur, Amri Nur, Amri Muliawan nurhidayati, nur ida Ramli Ahmad Reni Zuliana Rio Juniyantara Putra Rodhiyah FIlkhaer Sadali, Muhamad Samsul Al Kifli Suhartini, Suhartini Wajizatul Amnia wajizatul Wajizatul Amnia Winda Puspita Hidayanti Yupi Kuspandi Putra Zuliana, Reni