Jurnal Politeknik Negeri Batam (PoliBatam)
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Design and Development of an iOS-Based AAC Application to Assist Nonverbal Autistic Children in Communication
Get PDFThe treatment of children with Autism Spectrum Disorder (ASD) in Indonesia is still very concerning. The lack of competent educators and therapists means that ASD children in Indonesia show slow development. Another limitation in Indonesia is the common view that children should be able to speak verbally, so many children with ASD are forced to undergo speech therapy, including tongue massage and other methods. Unfortunately, this approach often hinders their development, especially for children with non-verbal tendencies. This research aims to develop an Augmentative and Alternative Communication (AAC)-based application in Indonesian to help ASD children communicate with their surroundings. The method used is Challenge-Based Learning (CBL), which involves ASD therapists in Indonesia directly in the app development process. With the involvement of experts, the app was designed to fit the needs of ASD children based on practical and clinical considerations. The results showed that ASD children responded well and could use the AAC board effectively, optimizing the communication process in ASD children\u27s learning
Implementasi Fisher-Yates Shuffle dan Fuzzy Tsukamoto dalam Game Edukasi Nusantara
No full textThis research introduces "PINUS: Petualangan Ilmu Nusantara," an educational game designed to improve players\u27 knowledge and interest in Indonesian culture, flora, fauna, and national figures. The game incorporates the Fisher-Yates Shuffle algorithm to randomize questions and answers, ensuring variety, and the Fuzzy Tsukamoto algorithm to calculate scores based on player performance for fair and competitive assessment. Quantitative methods were employed, with data collected through interviews, literature reviews, and system testing via alpha testing (black- box) and beta testing (user acceptance testing or UAT). The One Group Pretest- Posttest Design method was also applied. The findings show that the Fisher-Yates Shuffle enhances challenge and engagement, while the Fuzzy Tsukamoto algorithm ensures balanced scoring, fostering motivation. UAT results indicate strong functional acceptance, with an average score of 84.9% ("Strongly Agree"). The pre- test and post-test analysis revealed a score improvement average of 0.307, categorized as moderate. These findings affirm PINUS effectiveness in enhancing learning comprehension by offering interactive features, educational content, and dynamic question variations. The game provides an engaging, accessible, and technology-driven learning medium, making it a valuable tool for supporting educational initiatives.Penelitian ini memperkenalkan "PINUS: Petualangan Ilmu Nusantara," sebuah game edukasi yang dirancang untuk meningkatkan pengetahuan dan minat pemain terhadap budaya, flora, fauna, dan tokoh nasional Indonesia. Game ini mengimplementasikan algoritma Fisher-Yates Shuffle untuk mengacak pertanyaan dan jawaban guna memastikan variasi, serta algoritma Fuzzy Tsukamoto untuk menghitung skor berdasarkan kinerja pemain agar penilaian lebih adil dan kompetitif. Penelitian ini menggunakan metode kuantitatif dengan pengumpulan data melalui wawancara, tinjauan literatur, serta pengujian sistem melalui uji alfa (black-box) dan uji beta (user acceptance testing atau UAT). Metode One Group Pretest-Posttest Design juga diterapkan. Hasil penelitian menunjukkan bahwa algoritma Fisher-Yates Shuffle meningkatkan tantangan dan keterlibatan pemain, sementara algoritma Fuzzy Tsukamoto memastikan penilaian skor yang seimbang sehingga meningkatkan motivasi. Hasil UAT menunjukkan tingkat penerimaan fungsional yang tinggi dengan skor rata-rata 84,9% ("Sangat Setuju"). Analisis pre-test dan post-test mengungkapkan peningkatan skor rata-rata sebesar 0,307, yang dikategorikan sebagai peningkatan moderat. Temuan ini menegaskan efektivitas PINUS dalam meningkatkan pemahaman pembelajaran melalui fitur interaktif, konten edukatif, dan variasi soal yang dinamis. Game ini menyediakan media pembelajaran yang menarik, mudah diakses, dan berbasis teknologi, sehingga menjadi alat yang berharga dalam mendukung inisiatif pendidikan
Increase Sales with Influencers and Word of Mouth: a Live Streaming Study on Cosmetics and Fashion Products at Shopee Batam Customers
Get PDFThis study tries to determine the impact of influencers and word of mouth on purchasing decisions with live streaming as a moderating variable on cosmetic and fashion products. This study uses the population of Batam City People who have used the Shopee application. This quantitative research uses the path analysis method as the data analysis technique. Data collection will be done by distributing questionnaires to the Batam City community. Using the Lemeshow formula, 150 respondents were obtained in Batam City. The research findings show that influencers have a positive and significant effect on purchasing decisions on cosmetic and fashion products, word of mouth has a positive and significant impact on buying decisions on cosmetic and fashion products, live streaming as a moderating variable weakens the influence of influencers on purchasing decisions on cosmetic and fashion products, and live streaming as a moderating variable strengthens the impact of word of mouth on buying decisions on cosmetic and fashion product
Implementasi Algoritma PID untuk Pengontrolan Suhu Pada Mesin Pengering Cabai
No full textPenelitian ini mengimplementasikan kontrol PID pada mesin pengering cabai untuk mempertahankan stabilitas suhu selama proses pengeringan. Pengaturan suhu optimal dicapai melalui mekanisme tuning PID dengan metode Ziegler–Nichols untuk mengatur parameter Kp, Ki, dan Kd yang dapat menghasilkan respon sistem yang stabil pada suhu setpoint. Mesin pengering terdiri dari sensor DHT22, pemanas, dan mikrokontroler ESP32, serta terintegrasi dengan aplikasi Home Assistant untuk pemantauan dan pengontrolan jarak jauh. Hasil pengujian menunjukkan bahwa pada suhu 60°C menghasilkan keseimbangan optimal antara kecepatan pengeringan dan kestabilan kelembaban. Implementasi kontrol PID berhasil menjaga suhu mendekati setpoint dengan steady-state error sebesar 0,98%, overshoot yang minimal dan settling time yang optimal. Proses pengeringan menghasilkan penurunan kadar air yang signifikan, dengan berat awal 1 kg menjadi 261 gr setelah pengeringan. Tuning PID menunjukkan efektivitas dalam meningkatkan kestabilan suhu dan kualitas akhir produk cabai kering, serta menjadi solusi dalam mengatasi kendala pengeringan cabai secara konvensional.Penelitian ini mengimplementasikan kontrol PID pada mesin pengering cabai untuk mempertahankan stabilitas suhu selama proses pengeringan, dengan tujuan memperpanjang umur simpan cabai dan menjaga kualitasnya. Pengaturan suhu optimal dicapai melalui mekanisme tuning kontrol PID yang memanfaatkan metode Ziegler - Nichols. Proses tuning ini mengatur parameter optimal Kp, Ki, dan Kd yang dapat menghasilkan respon sistem yang stabil pada suhu setpoint. Mesin Pengering terdiri dari komponen utama, termasuk sensor suhu DHT22, pemanas, dan mikrokontroler ESP32. Sistem ini terintegrasi dengan aplikasi Home Assistant untuk memungkinkan pemantauan dan pengontrolan jarak jauh. Pengujian dilaksanakan pada tiga setpoint suhu yaitu 50°C, 60°C, dan 70°C. Hasil pengujian menunjukkan bahwa suhu 60°C menghasilkan keseimbangan optimal antara kecepatan pengeringan dan kestabilan kelembaban. Implementasi pengendalian PID berhasil menjaga suhu mendekati setpoint dengan steady-state error sebesar 0,98%. Selain itu, sistem ini juga menghasilkan overshoot yang minimal dan waktu pencapaian suhu stabil (settling time) yang optimal. Proses pengeringan menghasilkan penurunan kadar air yang signifikan, dengan berat awal 1 kg berkurang menjadi sekitar 261gram setelah pengeringan selesai. Implementasi tuning PID pada mesin pengering cabai menunjukkan efektivitas dalam meningkatkan kestabilan suhu dan kualitas akhir produk cabai kering, serta memberikan solusi yang potensial bagi petani dalam mengatasi kendala pengeringan cabai secara konvensional
Analisis Pengaruh Variasi PV Terhadap Sistem Proteksi di Instalasi Listrik Pabrik Pengolahan Garam
No full textPenggunaan energi terbaharukan seperti Photovoltaic (PV) semakin meningkat untuk mengurangi ketergantuan terhadap pembangkit yang membutuhkan bahan bakar fosil. Namun integrasi PV pada beban yang disuplai oleh PLN menggunakan jaringan distribusi tegangan menengah (JTM) dapat mempengaruhi selektivitas proteksi di sisi beban, terutama saat kondisi irradiasi tinggi. Tujuan dari penelitian ini menganalisis perubahan koordinasi sistem proteksi yang terdapak oleh PV pada beban motor di Pabrik pengolahan Garam. Variasi daya PLTS 12kW hingga 27 kW digunakan untuk percobaan agar dapat perbandingan dampak saat PV eksisting 4kW dan kemungkinan pengembangan. Software bantu untuk menunjang penelitian ini dengan menggunakan ETAP. Mode Load Flow, Static Motor Starting dan Star – Protective Device Coordination digunakan dalam penelitian ini berkaitan beban yang digunakan adalah motor induksi. Hasil yang didapat menunjukan kenaikan tegangan pada kondisi starting motor dengan kapasitas PLTS 12 kW sebesar 69,42 Volt dan perlu penggantian gawai proteksi dari 63 Ampere menjadi 125 Ampere agar sistem lebih optimal.Penggunaan energi terbaharukan seperti Photovoltaic (PV) semakin meningkat untuk mengurangi ketergantuan terhadap pembangkit yang membutuhkan bahan bakar fosil. Namun integrasi PV pada beban yang disuplai oleh PLN menggunakan jaringan distribusi tegangan menengah (JTM) dapat mempengaruhi selektivitas proteksi di sisi beban, terutama saat kondisi irradiasi tinggi. Tujuan dari penelitian ini menganalisis perubahan koordinasi sistem proteksi yang terdapak oleh PV pada beban motor di Pabrik pengolahan Garam. Variasi daya PLTS 12kW hingga 27 kW digunakan untuk percobaan agar dapat perbandingan dampak saat PV eksisting 4kW dan kemungkinan pengembangan. Software bantu untuk menunjang penelitian ini dengan menggunakan ETAP. Mode Load Flow, Static Motor Starting dan Star – Protective Device Coordination digunakan dalam penelitian ini berkaitan beban yang digunakan adalah motor induksi
Penerapan Visual Servoing Robot Lengan dengan Metode Color Recognition sebagai Pemindah Objek Dua Warna Berbeda
No full textPenerapan Visual servoing dengan metode color recognition merupakan sistem yang mengklasifikasikan objek berdasarkan warna dan posisi objek yang terdeteksi melalui kamera untuk menggerakkan servo pada robot lengan. Sistem ini menggunakan Huskylens sebagai kamera yang digunakan untuk mendeteksi warna dan posisi dari sebuah objek dan robot lengan untuk memindahkan objek yang sudah terdeteksi melalui kamera. Dari hasil pengujian, penerapan visual servoing robot lengan dengan metode color recognition dapat berfungsi dengan respon rata-rata 0,9 detik untuk mengejar objek ketika objek tidak berada di posisi pengambilan dan berfungsi dengan baik untuk mengambil dan meletakkan objek dengan dua warna yaitu biru dan merah ketika berada di posisi pengambilan dengan persentase akurasi deteksi objek 98% serta persentase akurasi pengambilan dan pemindahan objek 100% melalui rentang jarak deteksi minimal 18 – 22 cm diatas objek dan dengan pencahayaan yang terang.Penerapan Visual Servoing dengan Metode Color Recognition merupakan sistem yang mengklasifikasikan objek berdasarkan warna dan posisi objek yang terdeteksi melalui kamera untuk menggerakkan servo pada robot lengan. Sistem ini menggunakan Huskylens sebagai kamera yang digunakan untuk mendeteksi warna dan posisi dari sebuah objek dan robot lengan untuk memindahkan objek yang sudah terdeteksi melalui kamera. Dari hasil pengujian, penerapan visual servoing robot lengan dengan metode color recognition dapat berfungsi dengan respon rata-rata 0,9 detik untuk mengejar objek ketika objek tidak berada di posisi pengambilan dan berfungsi dengan baik untuk mengambil dan meletakkan objek dengan dua warna yaitu biru dan merah ketika berada di posisi pengambilan dengan persentase akurasi deteksi objek 98% serta persentase akurasi pengambilan dan pemindahan objek 100% melalui rentang jarak deteksi minimal 18 – 22 cm diatas objek dan dengan pencahayaan yang terang
Implementation of Apriori Algorithm in Identifying Purchase Relationships at Bluder Cokro Pakuwon Mall
No full textBluder Cokro Store, located at Pakuwon Mall, specializes in traditional bluder bread with a wide range of flavor variations. This study aims to identify consumer purchasing patterns at the store to enhance promotional strategies and optimize product placement. The research applies the Cross Industry Standard Process for Data Mining (CRISP-DM) methodology, which includes phases such as business understanding, data understanding, data preparation, modeling, evaluation, and deployment. The dataset used consists of 4,371 transactions from October to December 2024. This study uses the Apriori algorithm to find patterns of association between products, with the goal of determining the scope of correlation between products and frequently co- purchased items. The results reveal nine significant association rules, with the strongest relationship observed between coklat keju and keju, having a support value of 0.100394 and a lift of 1.31. These findings indicate that strategic product placement and bundling promotions can enhance sales performance. Optimizing the store layout by placing coklat keju near coklat can increase purchase likelihood, while targeted discounts, such as "Buy coklat keju, get 10% off keju," can drive transaction values. This study serves as a recommendation framework rather than an experimental validation, offering insights on how transaction data and association rule mining can inform business decisions. The findings offer actionable insights for improving store layouts and promotional effectiveness, making this research valuable for retailers
Augmented Reality Development for Creating Interactive Experiences in Tourism Places
No full textTechnology, hardware and software are developing rapidly as time goes by. One of the results of this rapid technological development is Augmented Reality (AR) technology. Current tools in augmented reality (AR) were offered by Vuforia Software Development Kit (SDK). However, with the rapid development of Unity Engine, now we can integrated OpenCV in Unity Engine. This integration presents ideas for the development of AR technology. This study uses an approach that uses research and development (R&D) methodology. The model that will be used is the utilization of the ADDIE development framework. We encountered three main problems, problems faced are "How many stages of implementing AR with mediapipe in Unity Engine?", “How people satisfaction while using this product?” and " What is the maximum distance and time required to conduct the interaction process?". From the research conducted, we found that there are four important AR development stages that must be carried using Unity Engine and OpenCV. Next for RQ2 we got a level of approval from users of 86.53% or strongly agree with what we are doing. Then for the last RQ, we got the results for optimal hand detection distance is 3 meters, and the speed with the fastest value is 0.098s
Implementation of YOLO v11 for Image-Based Litter Detection and Classification in Environmental Management Efforts
No full textThis research implements YOLO v11 for image-based waste detection and classification to improve waste management efficiency. The model recognizes four categories of waste: inorganic, organic, hazardous and residual. The training results showa [email protected] of 0.989 and a maximum F1 of 0.98 at an optimal confidence level of 0.669. The model had high precision on the Organic (0.995) and B3 (0.991) classes, but faced difficulties in classifying the Residue category. The confusion matrix revealed most of the predictions were accurate, despite some misclassification. The model also showed stable performance under various lighting and background conditions. With this reliability, YOLO v11 can be applied in automated sorting systems to improve recycling efficiency and support sustainable environmental management, although further improvements to data augmentation and class weight adjustment are still needed.This research implements YOLO v11 for image-based waste detection and classification to improve waste management efficiency. The model recognizes four categories of waste: inorganic, organic, hazardous and residual. The training results showa [email protected] of 0.989 and a maximum F1 of 0.98 at an optimal confidence level of 0.669. The model had high precision on the Organic (0.995) and B3 (0.991) classes, but faced difficulties in classifying the Residue category. The confusion matrix revealed most of the predictions were accurate, despite some misclassification. The model also showed stable performance under various lighting and background conditions. With this reliability, YOLO v11 can be applied in automated sorting systems to improve recycling efficiency and support sustainable environmental management, although further improvements to data augmentation and class weight adjustment are still needed
Evaluation of the Effectiveness of Lightweight Encryption Algorithms on Data Performance and Security on IoT Devices
No full textData security remains a major concern in the Internet of Things (IoT) landscape due to the inherent limitations in computational power, memory capacity, and energy availability of IoT devices. To address these challenges, lightweight encryption algorithms have emerged as alternatives to conventional cryptographic methods, aiming to balance performance and security. This study evaluates the effectiveness of five encryption algorithms—SIMON64/128, SPECK64/128, XTEA64/128, PRESENT64/128, and AES128—on IoT devices through experimental analysis of their security strength, execution time, CPU utilization, memory usage, and power efficiency. The experiments were conducted on a Raspberry Pi 3B+ using C-based implementations to emulate realistic IoT scenarios. The findings reveal that AES128 offers the strongest security characteristics, including the highest Avalanche Effect (39.29%) and Differential Resistance Score (6.76/10), but at the expense of significant resource consumption. In contrast, SIMON64/128 and SPECK64/128 deliver superior performance in terms of speed and resource efficiency, making them ideal for low-power environments, albeit with concerns about potential cryptographic backdoors. XTEA64/128 emerges as a practical compromise, delivering moderate security and low power consumption without known vulnerabilities. Based on these results, AES128 is suitable for high-capacity IoT platforms prioritizing strong encryption, while SIMON and SPECK are preferable for resource-constrained devices, with XTEA serving as a balanced alternative. This research contributes a comparative framework to guide the selection of encryption algorithms for IoT systems, ensuring an optimal trade-off between security and operational efficiency.Data security remains a major concern in the Internet of Things (IoT) landscape due to the inherent limitations in computational power, memory capacity, and energy availability of IoT devices. To address these challenges, lightweight encryption algorithms have emerged as alternatives to conventional cryptographic methods, aiming to balance performance and security. This study evaluates the effectiveness of five encryption algorithms—SIMON64/128, SPECK64/128, XTEA64/128, PRESENT64/128, and AES128—on IoT devices through experimental analysis of their security strength, execution time, CPU utilization, memory usage, and power efficiency. The experiments were conducted on a Raspberry Pi 3B+ using C-based implementations to emulate realistic IoT scenarios. The findings reveal that AES128 offers the strongest security characteristics, including the highest Avalanche Effect (39.29%) and Differential Resistance Score (6.76/10), but at the expense of significant resource consumption. In contrast, SIMON64/128 and SPECK64/128 deliver superior performance in terms of speed and resource efficiency, making them ideal for low-power environments, albeit with concerns about potential cryptographic backdoors. XTEA64/128 emerges as a practical compromise, delivering moderate security and low power consumption without known vulnerabilities. Based on these results, AES128 is suitable for high-capacity IoT platforms prioritizing strong encryption, while SIMON and SPECK are preferable for resource-constrained devices, with XTEA serving as a balanced alternative. This research contributes a comparative framework to guide the selection of encryption algorithms for IoT systems, ensuring an optimal trade-off between security and operational efficiency