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All Journal International Journal of Electrical and Computer Engineering International Journal of Reconfigurable and Embedded Systems (IJRES) International Journal of Advances in Applied Sciences Journal of Nonformal Education Telematika Jurnal Transformatika JUITA : Jurnal Informatika Jurnal The Messenger Jurnal Informatika Upgris Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Syntax Literate: Jurnal Ilmiah Indonesia Jurnal Pengembangan Rekayasa dan Teknologi KOMPUTIKA - Jurnal Sistem Komputer RANDANG TANA - Jurnal Pengabdian Masyarakat Abdimasku : Jurnal Pengabdian Masyarakat Computer Science and Information Technologies Jurnal Teknologi Informasi dan Komunikasi Information Science and Library Jurnal Teknologi Informasi Cyberku SEMINAR NASIONAL PENELITIAN DAN PENGABDIAN KEPADA MASYARAKAT Tematik International Journal of Information Technology and Business Jurnal DIMASTIK
April Firman Daru
Universitas Semarang
Humanities 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 Energy Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Nursing Physics Social Sciences Transportation Other

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MODEL PENGENDALI SUHU PEMANAS AIR UNTUK PEMBUAT KOPI MENGGUNAKAN KONSEP INTERNET OF THINGS  (IoT) Susanto, Susanto; Daru, April Firman
JURNAL TEKNOLOGI INFORMASI DAN KOMUNIKASI Vol. 16 No. 2 (2025): September
Publisher : UNIVERSITAS STEKOM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/jtikp.v16i2.1153

Abstract

The quality of coffee is determined by its taste, aroma, and flavor. These three factors are key attributes influencing the human multisensory perception of coffee. This multisensory perception can be affected by various factors, including the brewing method, roasting temperature, coffee variety, storage conditions, grinding process, and the quality of the brewing water. Manual coffee preparation poses the risk of water temperatures deviating from recommended standards. Therefore, this study proposes an efficient control device in the form of an IoT-based automatic coffee heater. The system integrates a temperature sensor to measure water temperature, an ESP32 microcontroller for processing, and the AI2 App Inventor application for control and monitoring purposes. The device is designed to maintain coffee at the ideal temperature range, preserving its freshness and sensory quality as if it had just been brewed. This is critical because the brewing temperature is a major factor influencing the flavor profile of coffee. According to the Specialty Coffee Association of America (SCAA), the recommended water temperature for brewing coffee is 92°C, with a technical requirement for beverages served to consumers to be no lower than 80°C and no higher than 85°C. The ideal serving temperature for coffee is between 62.8°C and 68.3°C. Based on comprehensive system testing, the device achieved an average success rate of 98.97%.
PEMANTAUAN TINGKAT KARBON MONOKSIDA DENGAN SENSOR MQ-9 STUDI KASUS UNIVERSITAS SEMARANG Hirzan, Alauddin Maulana; Adhiwibowo, Whisnumurti; Daru, April Firman
JURNAL TEKNOLOGI INFORMASI DAN KOMUNIKASI Vol. 15 No. 2 (2024): September
Publisher : UNIVERSITAS STEKOM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/jtikp.v15i2.741

Abstract

Emisi merupakan hal yang sangat serius untuk di atasi, emisi gas karbon monoksida merupakan sisa dari kombusi yang dilakukan oleh kendaraan bermotor seperti motor maupun mobil. Gas ini bersifat tidak berbau maupun berwarna, namun mematikan dalam dosis yang tinggi. Sehingga perlu penanganan serius untuk memantau gas jenis ini. Universitas Semarang merupakan salah satu universitas dengan jumlah mahasiswa terbanyak di Jawa Tengah, maka secara otomatis pengendara kendaraan bermotor pun ikut meningkatkan kandungan gas karbon monoksida di area parkir. Oleh karena itu, penelitian ini memiliki tujuan untuk mendesain sebuah purwarupa deteksi karbon monoksida dengan menggunakan teknologi Internet of Things yang dapat melaporkan ketika terdapat kandungan gas di udara. Model ini dilengkapi dengan sensor MQ-9 yang mampu mendeteksi gas karbon monoksida lebih akurat dibandingkan model-model sebelumnya. Berdasarkan hasil evaluasi yang dilakukan, model ini mampu mendeteksi gas dengan rata-rata 4,17 ppm dari 55 data deteksi yang ada dan tersimpan di Firebase Realtime Database. Dari semua data yang ada, model mendeteksi puncak tertinggi mencapai 18,365 ppm. Meskipun terdapat kenaikan kandungan gas, namun hasil ini masih di bawah batas aman yang dianjurkan. Selain itu, hasil terakhir yang didapatkan dari model ini adalah notifikasi pelaporan yang disampaikan melalui Telegram Bot.
ANALISIS DAN STRATEGI SUPPLY CHAIN DISTRIBUSI BARANG BERBASIS BLOCKCHAIN DAN ALGORITHMA GENETIKA Hartanto, Agus; Daru, April Firman
JURNAL TEKNOLOGI INFORMASI DAN KOMUNIKASI Vol. 16 No. 1 (2025): MARET
Publisher : UNIVERSITAS STEKOM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/eecgg233

Abstract

The development of the digital era demands a transformation in supply chain management to face increasingly complex challenges. Blockchain and genetic algorithms emerge as innovative solutions capable of enhancing efficiency, transparency, and resilience in the supply chain. Blockchain offers a secure and transparent decentralized system, while genetic algorithms provide an optimal approach for scheduling and coordination. The integration of these two technologies has the potential to create a more efficient, responsive, and sustainable supply chain system. This research aims to formulate a distribution strategy for goods based on blockchain and genetic algorithms, making a significant contribution to the development of supply chains in the Industry 4.0 era.
Internet of Things Based Automatic Heigh Detection with Ultrasonic Sensor: Using SMS Gateway for Detection Information April Firman Daru
International Journal of Information Technology and Business Vol. 5 No. 1 (2022): November: International Journal of Information Technology and Business
Publisher : Universitas Kristen Satya Wacana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24246/ijiteb.512022.08-13

Abstract

Man-made fish pond is an artificial pond filled with brackish water and located near seawater border to allow mixing with fresh water. These ponds were used as aquaculture for fish, shrimp, shellfish, and others. The success factors are determined by the quantity of brackish water in the pond. If the seawater level not reached 25cm-30cm above normal level, then the seawater can't be flowed into the river. In order to solve the problem, an Internet of Things based model is proposed to assist the onwer to obtain the seawater level information. This research utilized Arduino Uno microcontroller to control the sensor and communication module. This model able to send messages to owner in realtime. The main purpose of this model is to help fish pond owner to get seawater information easily without checking directly.
Twitter Sentiment Analysis Using Natural Language Processing (NLP) Method and Long Short Term Memory (LSTM) Algorithm in the 2024 Indonesian Presidential Election Basworo Ardi Pramono; April Firman Daru; Muhammad Bahrul Ulum
International Journal of Information Technology and Business Vol. 6 No. 2 (2024): April: International Journal of Information Technology and Business
Publisher : Universitas Kristen Satya Wacana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24246/ijiteb.622024.24-30

Abstract

Twitter is one of the media used by the Indonesian people to express their opinions regarding the 2024 Presidential Election. However, there is no scientific calculation that can determine the tone of public opinion regarding the 2024 presidential election. In this study, sentiment analysis was carried out on the tweets of the Indonesian people related to the 2024 Presidential Election (Pilpres 2024). The purpose of this study is to find out the opinions of Indonesian Twitter users regarding the 2024 Presidential Election using Natural Language Processing (NLP) Technology and Long Short Term Memory (LSTM) algorithms. NLP techniques are used to understand natural language and extract meaning from tweet copy, and LSTM is used to analyze the accuracy and accuracy of classification. The data used in this study was 1,004 tweets with the topic "Presidential Election", this data researchers obtained through the process of crawling using the tweet harvest library. In this study, 53.2% had positive emotions, 3.5% had neutral emotions, and 43.3% had negative emotions. 78% accuracy, 67% precision, and 67% recall.
Classification of Investment Opportunities in Semarang City Using the K-Nearest Neighbor Data Mining Method Bernadus Very Christioko; Daru, April Firman; Dyan Sinung Prabowo; Alaudin Maulana Hirzan
International Journal of Information Technology and Business Vol. 7 No. 2 (2025): April : International Journal of Information Techonology and Business
Publisher : Universitas Kristen Satya Wacana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24246/ijiteb.722025.01-08

Abstract

Investment is an activity undertaken to allocate funds with the expectation of generating future returns. In a dynamic economic environment, identifying profitable investment opportunities can be a complex task. This study aims to determine potential investment opportunities in Semarang City using a classification method that facilitates business actors or investors in selecting appropriate business sectors. The study utilizes valid data to help investors make informed decisions when establishing a business in the region. Data collection was conducted through research at the Investment and One-Stop Integrated Services Agency (DPMPTSP) of Semarang City, employing a quantitative approach with the K-Nearest Neighbor (K-NN) method. The dataset was divided into training and testing sets with an 80:20 ratio. The experimental results show that the implementation of the K-NN algorithm, conducted using Google Colab, achieved an accuracy of 86% based on 60 testing data points. This demonstrates that the K-NN classification algorithm is effective and produces accurate predictions. Therefore, applying data mining classification techniques to identify investment opportunities can serve as a viable solution to support strategic decision-making for investors.their business development strategies with sector-specific prospects in Semarang City.
Arowana cultivation water quality forecasting with multivariate fuzzy timeseries and internet of things Alauddin Maulana Hirzan; April Firman Daru; Lenny Margaretta Huizen
Computer Science and Information Technologies Vol 6, No 2: July 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/csit.v6i2.p136-146

Abstract

Water quality plays a crucial role in the growth and survival of arowana fish, with imbalances in key parameters (pH, temperature, turbidity, dissolved oxygen, and conductivity) leading to increased mortality rates. While previous studies have introduced various monitoring models using Arduino IDE and intrinsic approaches, they lack predictive capabilities, leaving cultivators unable to take proactive measures. To address this gap, this study develops a predictive model integrating the internet of things (IoT) with a fuzzy time series (FTS) algorithm. Through rigorous evaluation and validation, the proposed FTS-multivariate T2 model demonstrated superior performance, achieving an exceptionally low error rate of 0.01704%, outperforming decision tree (0.13410%), FTS-multivariate T1 (0.88397%), and linear regression (20.91791%). These findings confirm that FTS-multivariate T2 not only accurately predicts water quality but also significantly reduces the mean absolute percentage error, providing a robust solution for sustainable arowana aquaculture.
An Adaptive AI-Driven Copywriting Framework: Design, Implementation, and Evaluation of a Web-Based GPT-Integrated Content Generation System April Firman Daru; Febrian Wahyu Christanto; Rastri Prathivi; Dimas Prasetyo; Eryan Ahmad Firdaus
International Journal of Information Technology and Business Vol. 8 No. 2 (2026): April : International Journal of Information Techonology and Business
Publisher : Universitas Kristen Satya Wacana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24246/ijiteb.822026.8-17

Abstract

The increasing demand for scalable and high-quality digital marketing content has exposed limitations in traditional manual copywriting processes, which are time-intensive and difficult to scale. This research proposes an adaptive AI-driven copywriting framework that integrates a full-stack web architecture with optimized prompt engineering strategies for automated content generation. The system is implemented using React.js for the frontend, Node.js with Express for backend services, and a GPT-based API for language generation. Unlike prior implementations, this research introduces a structured prompt optimization mechanism to enhance content relevance and consistency. Experimental evaluation was conducted using multiple datasets of marketing prompts, with comparisons against baseline GPT usage and manual copywriting. Quantitative results show that the proposed system achieves improvements in BLEU (+18.7%) and ROUGE-L (+21.3%) scores over baseline methods. Human evaluation involving 30 participants indicates a significant increase in perceived content quality, coherence, and persuasiveness (p < 0.05). System performance analysis demonstrates an average response time of 1.8–3.0 seconds and a GTmetrix performance score of 82%. The findings confirm that the proposed framework significantly enhances efficiency, scalability, and content quality, contributing to both applied AI systems and intelligent web-based content production.
PENINGKATAN PEMAHAMAN ETIKA PENGGUNAAN AI UNTUK PARA SISWA SMK WALISONGO SEMARANG Alauddin Maulana Hirzan; April Firman Daru; Whisnumurti Adhiwibowo; Agus Hartanto
Jurnal DIMASTIK Vol. 4 No. 2 (2026): Juli
Publisher : Universitas Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26623/dimastik.v4i2.15897

Abstract

Pemanfaatan Artificial Intelligence (AI) dalam kegiatan pembelajaran memberikan peluang bagi siswa untuk memperoleh informasi dan menyelesaikan berbagai aktivitas akademik secara lebih efektif. Namun, penggunaan AI tanpa pemahaman etika yang memadai dapat menimbulkan permasalahan, seperti penggunaan informasi tanpa verifikasi, pelanggaran integritas akademik, penyalahgunaan data pribadi, dan pelanggaran hak kekayaan intelektual. Kegiatan Pengabdian kepada Masyarakat (PkM) ini bertujuan meningkatkan pemahaman siswa mengenai etika penggunaan AI dalam mendukung proses pembelajaran di SMK Walisongo Semarang. Kegiatan dilaksanakan menggunakan pendekatan pelatihan partisipatif yang meliputi penyampaian materi, diskusi interaktif, analisis studi kasus, dan praktik penggunaan AI secara bertanggung jawab. Evaluasi dilakukan melalui pre-test dan post-test yang terdiri atas 10 butir pertanyaan dan diikuti oleh 21 siswa. Materi evaluasi mencakup pemahaman konsep AI, prinsip etika penggunaan AI, kejujuran akademik, perlindungan data pribadi, hak kekayaan intelektual, dan verifikasi informasi yang dihasilkan AI. Hasil evaluasi menunjukkan adanya peningkatan pemahaman peserta setelah pelatihan. Berdasarkan data hasil kuesioner, skor rata-rata peserta meningkat dari 6,24 pada pre-test menjadi 8,33 pada post-test, atau mengalami peningkatan sebesar 2,09 poin (33,49%). Pada evaluasi berdasarkan aspek materi, pemahaman konseptual mencapai 84%, pemahaman prompt mencapai 88%, sedangkan aspek sentence mencapai 62% setelah pelatihan. Hasil tersebut menunjukkan bahwa pelatihan memberikan dampak positif terhadap peningkatan pemahaman siswa mengenai penggunaan AI secara etis dan bertanggung jawab. Kegiatan ini dapat menjadi salah satu pendekatan edukatif untuk memperkuat literasi AI dan integritas digital siswa pada jenjang pendidikan menengah kejuruan. Kata Kunci: Artificial Intelligence, etika AI, literasi AI, siswa SMK, Pengabdian kepada Masyarakat
Peningkatan Kemampuan Teknologi Internet of Things Untuk Para Siswa SMA Sint Louis Alauddin Maulana Hirzan; April Firman Daru; Lenny Margaretta Huizen
Jurnal DIMASTIK Vol. 3 No. 2 (2025): Juli
Publisher : Universitas Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26623/dimastik.v3i2.11754

Abstract

Dalam era digital yang semakin berkembang, teknologi Internet of Things (IoT) memiliki peran krusial dalam mendorong efisiensi dan inovasi. Namun, pemahaman siswa SMA Sint Louis tentang IoT masih terbatas, yang dapat menghambat kesiapan mereka dalam menghadapi tantangan teknologi masa depan. Untuk mengatasi hal ini, sebuah kegiatan pengabdian masyarakat dilaksanakan dengan tujuan memperkenalkan konsep dan aplikasi IoT kepada siswa. Metode yang digunakan meliputi penyampaian materi teoretis dan demonstrasi perangkat IoT, yang dilakukan selama dua hari. Evaluasi melalui kuesioner menunjukkan peningkatan signifikan dalam pemahaman siswa tentang IoT, dari 51% sebelum pelatihan menjadi 79% setelah pelatihan. Peningkatan ini mencakup pemahaman konseptual, kemampuan konfigurasi perangkat, dan keterampilan pemecahan masalah. Kegiatan ini diharapkan dapat memperluas wawasan siswa tentang IoT serta mempersiapkan mereka untuk menghadapi perkembangan teknologi di masa depan.
Co-Authors Agus Edy Cahyono Agus Hartanto Agus Hartanto Agus Hartanto Alauddin Maulana Hirzan Alaudin Maulana Hirzan Aria Hendrawan, Aria Arif Kurniawan Astrid Novita Putri Atmoko Nugroho Atmoko Nugroho Basworo Ardi Pramono Cholil, Saifur Rohman Didik Kurniawan Didin Herlinudinkhaji, Didin Dimas Prasetyo Dominicus Ferdian Wendy Pratama Dyan Sinung Prabowo Edi Widodo Edi Widodo Erlangga, Erwin Eryan Ahmad Firdaus Farizal Rachman Febrian Wahyu Christanto Handayani, Sri Heddy Tyas Darmawan Hindriyanto Dwi Purnomo Irwan Desyantoro Khoirudin Khoirudin Khoirudin Khoirudin Kristoko Dwi Hartomo Lenny Margaretta Huizen Mohammad Burhan Hanif Muhammad Bahrul Ulum Muhammad Burhan Hanif Muhammad Faizal Agung Widodo nofiati nofiati Nurtriana Hidayati Putriniantami, Bertha Sonia Rastri Prathivi Sara Sharifzadeh Setiaji, Galet Guntoro Shona Chayy Bilqisth Slamet Ashadi Stefanus Santosa Sugiarti, Rini Surono Susanto, Susanto Vensy Vydia Veronika, Nofita Whisnumurti Adhiwibowo