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All Journal Explore IT : Jurnal Keilmuan dan Aplikasi Teknik Informatika JASIEK (Jurnal Aplikasi Sains, Informasi, Elektronika dan Komputer) JATI (Jurnal Mahasiswa Teknik Informatika) E-Link: Jurnal Teknik Elektro dan Informatika Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) Jurnal Abdimas Sangkabira Kohesi: Jurnal Sains dan Teknologi Jurnal Sains Student Research Jurnal Indonesia : Manajemen Informatika dan Komunikasi SINAR: Sinergi Pengabdian dan Inovasi untuk Masyarakat BIOS: Jurnal Informatika dan Sains
Arif Faizin
Prodi Teknik Informatika Universitas Yudharta Pasuruan
Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Languange, Linguistic, Communication & Media Library & Information Science Mathematics Public Health Social Sciences Other

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IMPLEMENTASI SISTEM MONITORING SUHU DAN KELEMBABAN RUANG PRODUKSI OBAT BERBASIS IoT DENGAN MENGGUNAKAN NodeMCU ESP32 Muhammad Ilman Mahmudi; Arif Faizin
JOURNAL SAINS STUDENT RESEARCH Vol. 3 No. 6 (2025): Jurnal Sains Student Research (JSSR) Desember
Publisher : CV. KAMPUS AKADEMIK PUBLISING

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61722/jssr.v3i6.6432

Abstract

The drug manufacturing process in the pharmaceutical industry must comply with Good Manufacturing Practices (GMP) standards, including temperature and humidity control to prevent product quality degradation. This study designed an Internet of Things (IoT)-based temperature and humidity monitoring system using NodeMCU ESP32, NTC MF52-103 (temperature) and DHT11 (humidity) sensors. The system is equipped with an alarm if parameters exceed standard limits and can be accessed remotely via an Android application based on MIT App Inventor. Test results show that the system is capable of reading, displaying, storing, and providing real-time notifications of production environment conditions. This implementation is expected to support more effective quality control of pharmaceutical production rooms.
KLASIFIKASI TINGKAT KEPARAHAN KECELAKAAN KERJA MENGGUNAKAN ALGORITMA RANDOM FOREST Izzah Afkarinah; Arif Faizin; Ahmad Zulham Fahamsyah Havy
JOURNAL SAINS STUDENT RESEARCH Vol. 3 No. 6 (2025): Jurnal Sains Student Research (JSSR) Desember
Publisher : CV. KAMPUS AKADEMIK PUBLISING

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61722/jssr.v3i6.6433

Abstract

This study aims to develop a classification model for the severity of workplace accidents using the Random Forest algorithm with OSHA–ITA data from January 2015 to September 2024. From 95,194 initial incident data, cleaning, missing value handling, removal of irrelevant variables, encoding, and the formation of Severity targets (Severe, Moderate, Mild) were carried out. The dataset was divided into 70% training data and 30% testing data with a total of 28,559 samples. The results showed that the initial model was biased towards the majority class, while the minority class was difficult to recognize. After applying SMOTE, the model's performance improved with more balanced predictions. The most influential features included Nature Title, Part of Body Title, Event Title, Source Title, Hospitalized, and Amputation. These findings emphasize the importance of selecting relevant features and data balancing techniques to improve the performance of Random Forest classification in occupational accidents.
ANALISIS SENTIMEN ULASAN APLIKASI DANA Di GOOGLE PLAY STORE MENGGUNAKAN ALGORITMA NAÏVE BAYES Pipit Ayu Mandasari; Arif Faizin
JOURNAL SAINS STUDENT RESEARCH Vol. 3 No. 5 (2025): Jurnal Sains Student Research (JSSR) Oktober
Publisher : CV. KAMPUS AKADEMIK PUBLISING

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61722/jssr.v3i5.6436

Abstract

DANA sebagai dompet digital terkemuka di Indonesia, menerima banyak ulasan yang perlu dianalisis untuk memahami sentimen pengguna. Analisis sentimen sangat penting untuk mengkategorikan ulasan secara otomatis menjadi positif, negatif, dan netral. Penelitian ini bertujuan untuk menganalisis sentimen ulasan aplikasi DANA di Google Play Store menggunakan algoritma Naïve Bayes dan menguji efektivitasnya dalam mengklasifikasikan sentimen pengguna. Penelitian ini menggunakan algoritma Naïve Bayes, mencapai akurasi keseluruhan sebesar 88% dengan kinerja terbaik pada kelas positif (presisi 0,92, recall 0,94, F1-score 0,93). Kelas negatif menunjukkan hasil yang cukup baik (presisi 0,76, recall 0,83, F1-score 0,79), tetapi gagal mengenali kelas netral (presisi 0,67, recall 0,00, F1-score 0,01). Distribusi data tidak seimbang dengan 72,2% positif, 22,9% negatif, dan hanya 4,4% netral. Algoritma Naïve Bayes efektif untuk mengklasifikasikan sentimen ulasan aplikasi DANA ke dalam kelas positif dan negatif, tetapi tidak dapat mengenali kelas netral karena ketidakseimbangan data.
Forecasting Harga Saham PT. ABCD Menggunakan Algoritma Fuzzy Time Series Khaq, Muchamad Izzul; Faizin, Arif; Havy, Ahmad Zulham Fahamsyah
Jurnal Indonesia : Manajemen Informatika dan Komunikasi Vol. 7 No. 1 (2026): Januari
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat (LPPM) STMIK Indonesia Banda Aceh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63447/jimik.v7i1.1639

Abstract

High stock price fluctuations pose a significant challenge for investors and analysts in determining investment strategies. Price dynamics influenced by economic, political, and psychological market factors require forecasting methods that can accommodate uncertainty and non-linear historical data patterns. This study applies Cheng's Fuzzy Time Series algorithm to predict the stock price of PT. ABCD by going through the stages of universe set formation, interval determination, fuzzification, fuzzy logic relationship formation, and defuzzification to obtain prediction results. The method implementation was carried out using two approaches: manual calculation using Microsoft Excel and automatic calculation using the Orange application. The results show that Cheng's method is able to produce predictions very close to the actual value, with an accuracy level measured using the Mean Absolute Percentage Error (MAPE) indicator of 0.058787% on both platforms. The consistency of the results between Excel and Orange proves the reliability of Cheng's method, so it can be used as a reference in supporting investment decision-making in the Indonesian capital market.
Implementasi Pelatihan Bisnis Online bagi UMKM di Era Ekonomi Digital: Studi pada Kabupaten Probolinggo Yaqin, Moh. Ainol Yaqin; Arif Faizin
SINAR: Sinergi Pengabdian dan Inovasi untuk Masyarakat Vol 1 No 02 (2025): April
Publisher : CV. Laskar Karya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.65678/sinar.v1i02.121

Abstract

Transformasi digital telah membuka peluang besar bagi pelaku Usaha Mikro, Kecil, dan Menengah (UMKM) untuk memperluas jangkauan pasar melalui platform bisnis online. Namun, sebagian besar pelaku UMKM di Kabupaten Probolinggo belum memiliki kompetensi yang memadai dalam memanfaatkan marketplace digital seperti Shopee. Kegiatan pengabdian ini bertujuan untuk meningkatkan literasi digital dan keterampilan pemasaran online pelaku UMKM melalui pelatihan intensif penggunaan aplikasi Shopee. Metode yang digunakan adalah pelatihan langsung berbasis praktik dengan pendekatan demonstratif dan pendampingan personal. Hasil kegiatan menunjukkan peningkatan signifikan pada kemampuan peserta dalam mengelola akun, memajang produk, dan mempromosikan barang secara daring. Selain itu, peserta mampu memahami konsep dasar pemasaran digital dan teknik visualisasi produk yang menarik. Kesimpulan dari program ini menunjukkan bahwa pelatihan e-commerce berbasis marketplace mampu menjadi solusi efektif dalam meningkatkan daya saing UMKM lokal di tengah arus ekonomi digital.
IDENTIFICATION OF BOOK LABELING DESIGN IN LIBRARY USING RADIO FREQUENCY IDENTIFICATION (RFID) SYSTEM Agung Rachmatullah; Arif Faizin
BIOS: Jurnal Informatika dan Sains Vol. 1 No. 02 (2023): BIOS: Jurnal Informatika dan Sains, October 2023
Publisher : Sean Institute

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

Abstract

The library, as an essential institution in education and knowledge, continually seeks innovation to enhance operational efficiency and visitor services. One technology that has garnered attention is Radio Frequency Identification (RFID). This research aims to identify the optimal design for book labeling in libraries by leveraging RFID systems. This technology offers a potential automation solution for processes like borrowing, returning, and inventory management of books. The implementation of RFID in libraries can yield significant benefits. Key advantages include increased efficiency in serving borrowers, reduced human errors in data recording, and the ability to gather accurate data for book collection analysis and borrowing trends. However, the implementation of RFID also involves several challenges, including initial implementation costs, integration with existing infrastructure, as well as privacy and data security aspects. Additionally, the reading range of the RFID RC522 sensor is limited to 10 cm, which can be reduced to 1 cm to 6 cm if obstructed by objects, and if obstructed by solid objects like metal, it might not be read even at a 1 cm distance due to thickness. A solution that can be employed is using a plastic cover for the sensor with a thickness that is not excessively high.
IMPLEMENTASI KOMBINASI CAESAR CIPHER DAN POLYALPHABETIC CIPHER UNTUK KEAMANAN DATA PRIBADI PADA E-VOTING DALAM PEMILIHAN KETUA HUMANIKA Raka Pratama; Arif Faizin; Ahmad Zulham Fahamsyah Havy
E-Link: Jurnal Teknik Elektro dan Informatika Vol. 20 No. 2: Oktober 2025
Publisher : Universitas Muhammadiyah Gresik

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30587/e-link.v20i2.10429

Abstract

Perkembangan teknologi digital yang pesat menuntut peningkatan keamanan data, terutama pada sistem e-voting yang rentan terhadap serangan siber. Penelitian ini mengimplementasikan kombinasi algoritma kriptografi Caesar Cipher (mod 10) dan Polyalphabetic Cipher (mod 26 berbasis Tabula Recta) untuk mengamankan data pribadi mahasiswa seperti nama dan NIM dalam pemilihan Ketua Himpunan Mahasiswa Teknik Informatika (HUMANIKA) di Universitas Yudharta Pasuruan. Metode ini dirancang untuk melindungi data dari kebocoran dan manipulasi melalui proses enkripsi dan dekripsi berlapis.Hasil penelitian menunjukkan bahwa kombinasi kedua algoritma ini menghasilkan sistem enkripsi yang efisien dan efektif dalam meminimalkan risiko serangan brute force serta analisis frekuensi. Caesar Cipher digunakan untuk mengenkripsi data numerik (NIM), sementara Polyalphabetic Cipher diterapkan pada data teks (nama). Pengujian keamanan dengan berbagai skenario kunci membuktikan bahwa sistem ini mampu menjaga kerahasiaan dan integritas data pemilih. Implementasi pada sistem e-voting berbasis web juga menunjukkan kemudahan penggunaan dan kecepatan proses tanpa mengorbankan keamanan.
Co-Authors Achmad Hidayat Achmyatari Agung Rachmatullah Ahmad Zulham Fahamsyah Havy Amirullah, Alfian Nur Izzah Afkarinah Khaq, Muchamad Izzul Moch. Bakhrul Ulum Moch. Lutfi Moh. Lutfi Muh. Aniar Hari Swasono Muhammad Ilman Mahmudi Pipit Ayu Mandasari Raka Pratama Rochim Musa, Abdur Rozikhin, Zainoel Sahab, Fahmi Tri Arsanto, Arief Wahyu Agung Nurcahyo Yaqin, Moh. Ainol Yaqin