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All Journal Jurnal Teknologi Informasi dan Ilmu Komputer AdMathEduSt: Jurnal Ilmiah Mahasiswa Pendidikan Matematika Jurnal Khatulistiwa Informatika Insect (Informatics and Security) : Jurnal Teknik Informatika METHOMIKA: Jurnal Manajemen Informatika & Komputerisasi Akuntansi Jurnal Inotera Jurnal Inovasi Hasil Pengabdian Masyarakat (JIPEMAS) J-SAKTI (Jurnal Sains Komputer dan Informatika) IJISTECH (International Journal Of Information System & Technology) Jurnal Ilmiah Mandala Education (JIME) Jurnal Ilmiah Tatengkorang Jurnal Pengabdian Masyarakat Borneo IJISTECH Jurnal Ilmu Komputer dan Sistem Komputer Terapan (JIKSTRA) J-SAKTI (Jurnal Sains Komputer dan Informatika) Jurnal Pengabdian Masyarakat Jurnal Ilmu Komputer dan Teknologi (IKOMTI) Jurnal Algoritma Journal of Advanced Health Informatics Research Jurnal Informatika Polinema (JIP) Jurnal Multidisiplin Pengabdian Masyarakat (JMPM) Bhakti: Jurnal Pengabdian dan Pemberdayaan Masyarakat INFOKABIN
Hanif, Kharis Hudaiby
Universitas Borneo Tarakan
Religion Agriculture, Biological Sciences & Forestry Arts Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Immunology & microbiology Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Public Health Social Sciences Other

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Digitalisasi informasi dan promosi potensi desa melalui pengembangan website desa Fadllullah, Arif; Pradana, Awang; Harto, Dedy; Rudy; Hudaiby Hanif, Kharis; Perangin Angin, Nur Hasanah
Jurnal Inovasi Hasil Pengabdian Masyarakat (JIPEMAS) Vol 6 No 3 (2023)
Publisher : University of Islam Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33474/jipemas.v6i3.19413

Abstract

Pengelolaan website Desa Kelubir secara mandiri tentu memberikan kemudahan dalam memaksimalkan pelayanan informasi dan promosi potensi desa. Oleh karena itu, pengabdian ini mengusulkan tentang “Digitalisasi Informasi dan Promosi Potensi Desa Melalui Pengembangan Website Desa”. Metode pelaksanaan berbasis PAP (Project Action Plan) dengan tahapan: survei lokasi, pembuatan website, dan workshop pengelolaan website, serta metode pengujian berdasarkan empat indikator. Hasil survei menunjukkan desa Kelubir telah memiliki akses internet, tetapi masih belum memiliki website. Berdasarkan hasil pengujian diperoleh persentase keberhasilan pembuatan tampilan website sebesar 100%, persentase kehadiran peserta dalam workshop sebesar 86,7%, dan persentase ketersampaian materi sebesar 100%. Kemudian berdasarkan observasi, kemampuan peserta dalam memahami materi dan mengisi konten web dinilai baik. Hasil ini menunjukkan bahwa pengabdian yang telah dilaksanakan mampu meningkatkan literasi dan keterampilan digital bagi perangkat dan warga desa dalam mengisi konten website desa secara mandiri.
Peningkatan Literasi Teknologi Informasi Dan Komunikasi Siswa SMP Negeri 7 Tarakan Di Era Society 5.0 Hanif, Kharis Hudaiby; Aris, Ibrahim; Prasetyo, Eko; Faqih, Radiansyah; fath, Aqil Miftahul; Sabtiandy, Dhandy
Jurnal Pengabdian Masyarakat - PIMAS Vol. 3 No. 1 (2024): Februari
Publisher : LPPM Universitas Harapan Bangsa Purwokerto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35960/pimas.v3i1.1296

Abstract

Society 5.0 is characterized by the rapid and disruptive development of technology. This demands that each individual have the ability to use information and communication technology (ICT) wisely and responsibly. However, ICT also has negative impacts, such as addiction and misuse. Therefore, there is a need to improve ICT literacy from an early age. The purpose of this activity is to improve ICT literacy of students of SMP Negeri 7 Tarakan in the era of Society 5.0. This activity uses the methods of presenting materials, watching, practicing, and evaluating through written tests. The results of this activity are to grow the understanding and skills of ICT literacy of students of SMP Negeri 7 Tarakan so that they are ready to face the development of technology in the future.
WORKSHOP PEMBUATAN PODCAST UNTUK MENINGKATKAN KETERAMPILAN KOMUNIKASI DAN KREATIVITAS ERA DIGITAL MAHASISWA POLITEKNIK KESEHATAN KALTARA DI UNIVERSITAS BORNEO TARAKAN Kharis Hudaiby Hanif; Nurul Audryan; Bisma Baghas Waluyo; Putri Maimunah; Nurul; Andi Zilvia Ayu Ardina; Muhammad Akmaluddin
BHAKTI: JURNAL PENGABDIAN DAN PEMBERDAYAAN MASYARAKAT Vol. 3 No. 02 (2024): Desember
Publisher : Universitas Islam Tribakti (UIT) Lirboyo Kediri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33367/bjppm.v3i02.6626

Abstract

Podcasts are a digital platform that plays an important role in disseminating information, especially in the field of health promotion. This community service program aims to increase the knowledge and skills of North Kalimantan Health Polytechnic students in using podcasts as a medium to convey health messages. Challenges faced in this activity include a lack of understanding of podcast creation techniques, and a lack of knowledge regarding the benefits in disseminating health information. This service is carried out using the following methods: 1) Presentation of material about making podcasts, 2) practical training in recording podcasts, and 3) teaching about the operation of technical devices such as microphones and editing software. The results achieved from this activity are an increase in students' ability to produce and create effective podcasts, as well as a better understanding of the importance of podcasts in disseminating health information to the public. This program also produces content that can be accessed by various groups.
Perbandingan Analisis Sentimen Komentar Mahasiswa Prodi Teknik Komputer Menggunakan Algoritma Decision Tree, Support Vector Machine (SVM), dan Random Forest Kharis Hudaiby Hanif; Muntiari, Novita Ranti; Harto, Dedy; Wiranata, Dimas Satrio
Insect (Informatics and Security): Jurnal Teknik Informatika Vol. 12 No. 01 (2026): Maret 2026
Publisher : Universitas Muhammadiyah Sorong

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33506/insect.v12i01.5144

Abstract

Penilaian terhadap kualitas pembelajaran melalui komentar mahasiswa menjadi salah satu elemen penting dalam evaluasi proses akademik di perguruan tinggi. Namun, komentar yang bersifat kualitatif sering kali sulit dianalisis secara manual dan cenderung memakan waktu. Penelitian ini dilakukan untuk mengembangkan model analisis sentimen yang mampu mengklasifikasikan komentar mahasiswa Program Studi Teknik Komputer secara lebih efisien dan akurat. Tiga algoritma pembelajaran mesin, yaitu Decision Tree, Random Forest, dan Support Vector Machine (SVM), digunakan untuk membandingkan kinerja klasifikasi. Data komentar terlebih dahulu diberi label secara manual dan diperkaya dengan sejumlah komentar negatif sintetis guna menyeimbangkan distribusi sentimen. Selanjutnya, data diolah menggunakan teknik Text Mining, TF-IDF untuk ekstraksi fitur, serta algoritma SMOTE untuk menangani ketidakseimbangan kelas. Pengujian dilakukan menggunakan skema train test split 70:30. Hasil penelitian menunjukkan bahwa ketiga model memiliki tingkat akurasi yang beragam: Decision Tree memperoleh akurasi 88,2%, Random Forest mencapai 92,7%, sedangkan SVM menjadi model dengan performa terbaik dengan akurasi 94,5%. Analisis confusion matrix dan kurva ROC mengonfirmasi bahwa SVM lebih konsisten dalam membedakan sentimen positif dan negatif. Temuan ini mengindikasikan bahwa pendekatan berbasis SVM dengan dukungan TF-IDF dan SMOTE sangat potensial untuk diterapkan sebagai alat otomatis dalam menilai sentimen mahasiswa, sehingga mampu membantu institusi dalam mengambil keputusan berbasis data secara lebih cepat dan objektif.
Penanganan Ketidakseimbangan Data Pada Klasifikasi Penyakit Campak Menggunakan Kombinasi Smote Dan Xgboost Novita Ranti Muntiari; Kharis Hudaiby Hanif; Muliyadi; Mufida
Jurnal Ilmu Komputer dan Sistem Komputer Terapan (JIKSTRA) Vol. 8 No. 1 (2026): Edisi April
Publisher : Universitas Harapan Medan

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

Abstract

Data imbalance is one of the main challenges in developing disease classification models, as it can cause algorithms to recognize the majority class more dominantly and perform less optimally in detecting positive cases. This study aims to analyze the application of the combination of Synthetic Minority Over-sampling Technique (SMOTE) and XGBoost in measles disease classification. The data used consisted of 1,000 records with clinical features including age, immunization history, fever, cough, runny nose, conjunctivitis, skin rash, and measles status. The research data were divided into two subsets, namely 80% for the model training process and 20% for testing. The SMOTE technique was applied to the training data to address class distribution imbalance, while the XGBoost algorithm was used to build the classification model. Model performance was then evaluated using a confusion matrix and the metrics of accuracy, precision, recall, and F1-score. The results showed that XGBoost without SMOTE achieved an accuracy of 94.0%, precision of 83.3%, recall of 50.0%, and F1-score of 62.5%. After applying SMOTE, the performance improved, with an accuracy of 97.0%, precision of 79.2%, recall of 95.0%, and F1-score of 86.4%. These results indicate that the combination of SMOTE and XGBoost is more effective in improving the detection capability of positive measles cases in imbalanced data..
Implementasi Sistem Pakar Untuk Diagnosis Hama Tanaman Kelapa Sawit Dengan Metode Certainty Factor Felisia Silalahi; Kharis Hudaiby Hanif; Arif Fadllullah
INFOKABIN (Informatika, Komputasi, Aplikasi dan Bisnis) Vol 1 No 1 (2026): Januari 2026
Publisher : Universitas Al-Irsyad Cilacap

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36760/ifkb.v1i1.719

Abstract

This study proposes the development of an expert system based on the Certainty Factor method for rapid and accurate diagnosis of oil palm pests. The system is designed to help farmers identify four main types of pests (rats, termites, caterpillars, and bagworms) based on 18 specific symptoms and provide control recommendations. Data were obtained from interviews with agricultural experts, literature studies, and field observations in a 2.5-hectare oil palm plantation in Tanjung Selor. Users expressed their confidence level using a five-point scale (none, slightly confident, fairly confident, confident, and very confident). The Certainty Factor method calculates the confidence level of the diagnosis by combining the observed symptoms. The system was implemented as an offline desktop application based on Python and PyQt5. Functional testing (Black Box Testing) on ​​14 scenarios showed that all features functioned according to specifications. Performance evaluation included diagnostic accuracy (confusion matrix), Certainty Factor validation, and usability (System Usability Scale). The results showed 100% accuracy, precision, recall, and F1-Score in 20 sample cases. An average SUS score of 85.125 (Acceptable category approaching Excellent) from 40 respondents indicated ease of use. The system has proven effective in supporting decision-making for farmers and extension workers. Further development is recommended for secondary pests, plant diseases, and web and mobile platforms. Penelitian ini mengusulkan pengembangan sistem pakar berbasis metode Certainty Factor untuk diagnosis hama tanaman kelapa sawit secara cepat dan akurat. Sistem dirancang membantu petani mengidentifikasi empat jenis hama utama (tikus, rayap, ulat api, ulat kantong) berdasarkan 18 gejala spesifik serta memberikan rekomendasi pengendalian. Data diperoleh dari wawancara pakar pertanian, studi literatur, dan observasi lapangan di perkebunan kelapa sawit seluas 2,5 hektar di Tanjung Selor. Pengguna menyatakan tingkat keyakinan melalui lima skala (tidak ada, sedikit yakin, cukup yakin, yakin, sangat yakin). Metode Certainty Factor menghitung tingkat kepercayaan diagnosis dengan mengombinasikan gejala yang diamati. Sistem diimplementasikan sebagai aplikasi desktop offline berbasis Python dan PyQt5. Pengujian fungsional (Black Box Testing) terhadap 14 skenario menunjukkan semua fitur berfungsi sesuai spesifikasi. Evaluasi kinerja mencakup akurasi diagnosis (confusion matrix), validasi Certainty Factor, dan usabilitas (System Usability Scale). Hasil menunjukkan akurasi, presisi, recall, dan F1-Score 100% pada 20 kasus sampel. Skor SUS rata-rata 85,125 (kategori Acceptable mendekati Excellent) dari 40 responden mengindikasikan kemudahan penggunaan. Sistem terbukti efektif sebagai pendukung keputusan petani dan penyuluh. Pengembangan lanjutan disarankan untuk hama sekunder, penyakit tanaman, serta platform web dan mobile.
Prototype Sistem Ventilasi Pengendalian Kualitas Udara Ruang Laundry Menggunakan Rule-Based Berbasis IoT Kharis Hudaiby Hanif; Widya Ambarwati; Dedy Harto
Jurnal Algoritma Vol 23 No 1 (2026): Jurnal Algoritma
Publisher : Institut Teknologi Garut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33364/algoritma/v.23-1.3245

Abstract

Poor air quality in laundry rooms is generally caused by high temperature and humidity levels as well as potential exposure to carbon monoxide (CO) gas from equipment operations, which can reduce working comfort and increase health risks if not properly managed. This study proposes a prototype of an automatic ventilation system based on the Internet of Things (IoT) using a rule-based approach to support adaptive air quality control. The contribution of this research lies in the design of decision rules that integrate gas concentration, temperature, and humidity parameters into three condition levels (normal, alert, and danger), as well as in the comprehensive evaluation of system performance as a reference for the development of similar systems. The system was developed using an ESP32 microcontroller with MQ-135 and DHT22 sensors, equipped with an exhaust fan actuator and warning devices, and real-time monitoring through the Blynk IoT platform. Testing was conducted over three days with 360 measurement data points. The results show that the DHT22 sensor achieved measurement accuracy of 97.84% for temperature and 84.65% for humidity, while the MQ-135 sensor reached 92.44%. IoT communication performance was also stable, with 0% packet loss and an average latency of 194.25 ms. In the applied testing scenarios, the rule-based classification demonstrated full conformity with the predefined criteria; however, generalization of the findings still requires further validation under broader operational conditions and environmental variations. Overall, the findings indicate that the proposed system is responsive and reliable, and has the potential to serve as a practical and relatively low-cost solution for monitoring and controlling air quality in laundry rooms.
Co-Authors Abdul Fadlil Abdul Fadlil Adrian Premy Ashary Andi Zilvia Ayu Ardina Annida Zakkiah, Annida Zakkiah Anton Yudhana Arif Fadllullah Aris, Ibrahim Asma Asma Awang Pradana, Awang Bisma Baghas Waluyo Dedy Harto Dewi Astria Faroek Eko Prasetyo Fadllullah, Fadllullah Faqih, Radiansyah fath, Aqil Miftahul Felisia Silalahi Hafidz, Muhammad Nasir Harina Fitriyani Herawati, Lily Indah Chairun Nisa Irgi Ahmad Fahrezi Mochammad Imron Awalludin Mufida Muhammad Aditya, Muhammad Aditya Muhammad Akmaluddin Muliyadi Muntiari, Novita Ranti Murdianto, Deny Noviani, Doris Nur Hasanah Perangin Angin, Nur Hasanah Perangin Angin Nurul Nurul Audryan Perangin Angin, Nur Hasanah Purwono P Putri Ananda Ramadhani Putri Maimunah Rahmatullah Rahmatullah Ririn Ariyanti, Ririn Rudy Rusydi Umar Sabtiandy, Dhandy Sakti, Fijaya Bima Dwi susi susi Umami, Nurrahmi Wahdana, Wahdana Wahyuni Arsianti, Rika Widya Ambarwati Wiranata, Dimas Satrio