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All Journal Elkom: Jurnal Elektronika dan Komputer CESS (Journal of Computer Engineering, System and Science) Sinkron : Jurnal dan Penelitian Teknik Informatika JISTech (Journal of Islamic Science and Technology) IJISTECH (International Journal Of Information System & Technology) JURTEKSI JOURNAL OF SCIENCE AND SOCIAL RESEARCH Simtek : Jurnal Sistem Informasi dan Teknik Komputer Jutisi: Jurnal Ilmiah Teknik Informatika dan Sistem Informasi Technologia: Jurnal Ilmiah TIN: TERAPAN INFORMATIKA NUSANTARA Teknosains : Jurnal Sains,Teknologi dan Informatika Journal of Computer Networks, Architecture and High Performance Computing Journal of Intelligent Computing and Health Informatics (JICHI) Jurnal Teknologi Informasi dan Komunikasi IJISTECH Jurnal FASILKOM (teknologi inFormASi dan ILmu KOMputer) Journal of Dinda : Data Science, Information Technology, and Data Analytics Jurnal IPTEK Bagi Masyarakat Journal of Computer Science and Informatics Engineering Jurnal Ilmu Komputer dan Teknologi (IKOMTI) Jurnal Informatika Teknologi dan Sains (Jinteks) Sistem Pendukung Keputusan dengan Aplikasi DEVICE : JOURNAL OF INFORMATION SYSTEM, COMPUTER SCIENCE AND INFORMATION TECHNOLOGY Internet of Things and Artificial Intelligence Journal Jurnal Ekonomi, Teknologi dan Bisnis Jurnal Pengabdian Masyarakat VISA: Journal of Vision and Ideas
Aidil Halim Lubis
Universitas Islam Negeri Sumatera Utara
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Implementasi Algortima Support Vector Machine Dalam Klasifikasi Komentar Pengguna Produk Skintific di E-Commerce Artika, Priti Rindi; Lubis, Aidil Halim
Jutisi : Jurnal Ilmiah Teknik Informatika dan Sistem Informasi Vol 14, No 2: Agustus 2025
Publisher : STMIK Banjarbaru

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35889/jutisi.v14i2.3137

Abstract

The large number of consumer reviews of skincare products such as Skintific 5X Ceramide Barrier Repair Moisture Gel on e-commerce platforms raises the need for automated sentiment analysis. This study classifies 2,000 user comments from the Sociolla app using the Support Vector Machine (SVM) algorithm. Data were obtained through web scraping and processed through preprocessing, lexicon-based labeling, and word weighting using TF-IDF. SVM with a linear kernel was used to distinguish positive and negative comments. Performance evaluation using a confusion matrix resulted in an accuracy of 89.73%, a precision of 0.94, a recall of 0.75, and an F1-score of 0.83 for the positive class, and a precision of 0.88, a recall of 0.98, and an F1-score of 0.93 for the negative class. These results indicate that SVM is effective for sentiment classification in online beauty product reviews.Keywords: E-commerce; Support Vector Machine; Sentiment Analysis; TF-IDF; Sociolla; Skintific; Lexicon-based AbstrakBanyaknya ulasan konsumen terhadap produk perawatan kulit seperti Skintific 5X Ceramide Barrier Repair Moisture Gel di platform e-commerce menimbulkan kebutuhan akan analisis sentimen otomatis. Penelitian ini mengklasifikasikan 2000 komentar pengguna dari aplikasi Sociolla menggunakan algoritma Support Vector Machine (SVM). Data diperoleh melalui web scraping dan diproses dengan tahapan preprocessing, pelabelan berbasis lexicon, serta pembobotan kata menggunakan TF-IDF. SVM dengan linear kernel digunakan untuk membedakan komentar positif dan negatif. Evaluasi performa menggunakan confusion matrix menghasilkan akurasi sebesar 89,73%, precision 0,94, recall 0,75, dan F1-score 0,83 untuk kelas positif, serta precision 0,88, recall 0,98, dan F1-score 0,93 untuk kelas negatif. Hasil ini menunjukkan bahwa SVM efektif untuk klasifikasi sentimen pada ulasan produk kecantikan secara daring. 
Penerapan Metode Simple Additive Weighting pada Sistem Pendukung Keputusan Pemilihan Raket Bulu Tangkis Saragih, Ahmad Fadhly Sani; Muhammad Ikhsan; Lubis, Aidil Halim
Jurnal IT UHB Vol 6 No 3 (2025): Jurnal Ilmu Komputer dan Teknologi
Publisher : Universitas Harapan Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35960/ikomti.v6i3.1995

Abstract

Badminton is one of the most popular sports in Indonesia and a source of national pride due to the achievements of its athletes in international tournaments. The racket is the primary equipment used in badminton, and selecting the appropriate one is crucial for performance and comfort. However, many beginner players still find it difficult to choose a suitable racket according to the coach’s recommendation. Therefore, this study developed a Decision Support System (DSS) for badminton racket selection by applying the Simple Additive Weighting (SAW) method. Four alternatives—Yonex, Li-Ning, Flypower, and Victor—were evaluated using five criteria: price, racket weight, head type, shaft flexibility, and handle size. The integration of the SAW method into a web-based application produced ranking results for racket selection. The results showed that Li-Ning G Force Superlite 3900 achieved the highest score of 0.8845, indicating it as the most suitable racket for beginner players.
Penerapan Metode PID pada Sistem Pemberi Pakan Kucing Otomatis Berbasis IOT (Internet of Things) Fadiga, Muhammad; Kurniawan, Rakhmat; Lubis, Aidil Halim
VISA: Journal of Vision and Ideas Vol. 5 No. 1 (2025): Journal of Vision and Ideas (VISA)
Publisher : IAI Nasional Laa Roiba Bogor

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47467/visa.v5i1.5772

Abstract

An automatic feeding system that can be monitored and managed remotely is needed amidst the busy schedules of pet owners, especially for cats. As a result, an automatic cat feeder that can be operated and viewed remotely via the Internet of Things was developed in this research. By understanding the properties of loadcell sensors and servo motors, research in this case seeks to create an automatic cat feeding system that uses a PID approach to regulate food according to the cat's needs. For the convenience of remote use, the system also allows monitoring and control using the Telegram application. An ESP32 microcontroller, a servo for food release, a loadcell sensor for food weight measurement, and a camera for cat detection were all used in the development of this research system. An automatic cat feeding system that produces servo motor and load cell sensor calibration values with average error results of 1.84%, 3.86%, and accuracy of 96.14%, 98.16% was successfully developed in this research. With an error percentage of 1.67%, this research was able to produce food that matched the cat food dosage using the PID approach with trial and error tuning, especially with a cat food dosage of 60 grams. Based on the research findings, it can be said that this system works as planned and offers a practical way to feed cats food precisely and automatically.
Analisis Sentimen Masyarakat Terhadap Resesi Ekonomi Global 2023 Menggunakan Algoritma Naïve Bayes Classifier Sriani; Lubis, Aidil Halim; Harahap, Yunus Fadillah
Elkom: Jurnal Elektronika dan Komputer Vol. 16 No. 2 (2023): Desember : Jurnal Elektronika dan Komputer
Publisher : STEKOM PRESS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/elkom.v16i2.1673

Abstract

The global economic recession is a global economic downturn that affects the domestic economies of countries in the world. The stronger the economic dependence of one country on the global economy, the faster a recession will occur in that country. In 2020 the country of Indonesia and even the world are exposed to the COVID-19 virus which has an impact on the country's economic growth, even the world economy. This is the trigger for an economic recession. This has led to many different public perspectives on the occurrence of a global economic recession whose opinions or reactions are expressed on social media Youtube. The data was obtained by crawling techniques from social media Youtube with a total of 500 comments used. The data is then labeled (class) with a lexicon-based method with an Indonesian language dictionary. From the labeling results, it was obtained 185 positive labeled data (37%) and 315 negative opinions (63%). The data preprocessing stage is carried out in preparation for the data to be processed for sentiment analysis. Of the many opinions obtained, an analysis of public sentiment regarding the 2023 global economic recession will be carried out using the Naïve Bayes classification algorithm. This study also applied the TF-IDF word weighting method with the n-gram feature used, namely bigram (n=1). The system will be evaluated using a confusion matrix. The implementation results show a prediction model with a total of 500 opinion data with a comparison of training data and test data of 9:1, producing an accuracy value of 84.00%, a precision value of 75.00%, a recall of 30.00%, and an f1-score of 42.86%. The performance of the system model built in this study can be said to be good.
RANCANG BANGUN SISTEM KONTROL SUHU, KELEMBABAN DAN CAHAYA PADA RUMAH WALET MENGGUNAKAN FUZZY BERBASIS MIKROKONTROLER Sihombing, Rizki Andika; Kurniawan, Rakhmat; Lubis, Aidil Halim
JOURNAL OF SCIENCE AND SOCIAL RESEARCH Vol 8, No 4 (2025): November 2025
Publisher : Smart Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54314/jssr.v8i4.4684

Abstract

Abstract: Swiftlet nests have a high market value because the saliva used to make them has many benefits, including treating illnesses. They can also promote a healthy reproductive system and strengthen the lungs. Therefore, a system is needed to simplify swiftlet farming. This involves designing a microcontroller-based fuzzy control system for temperature, humidity, and light in swiftlet houses as a solution for swiftlet breeders. The device will utilize two sensors: a DHT11 sensor and an LDR sensor. The DHT11 sensor maintains the stability of the room's temperature and humidity, while the LDR sensor maintains the light intensity of the swiftlet house. The conditions that have been determined based on 12 fuzzy logic rules, from the DHT11 sensor conditions, namely cold temperatures with a range of 0 - 15, moderate temperatures with a range of 15-30, and hot temperatures with a range of 30 - 45, in humidity conditions with a dry range of 0-50 and humid 0 - 95 while in the LDR sensor conditions, namely bright with an ADC value range on the LDR of 0 - 500 and dark conditions in the range of 500 - 1024. The defuzzification output value obtained is [0 10] where 0 is OFF and 10 is on for 10 minutes.Keyword: Swiftlet, Fuzzy Logic, DHT11, LDRAbstrak: Sarang burung walet mempunyai nilai jual yang tinggi karena air liur yang digunakan untuk membuat sarang memiliki banyak manfaat salah satunya adalah mengobati penyakit. Selain itu bisa juga untuk menyehatkan sistem reproduksi dan memperkuat paru-paru. Sehingga di butuhkan suatu sistem agar peternakan burung walet semakin lebih mudah dengan membuat perancangan suatu sistem kontrol suhu kelembaban dan cahaya pada rumah walet menggunakan fuzzy berbasis mikrokontroler sebagai solusi bagi para peternak burung walet. Dimana alat yang akan dibuat menggunakan dua sensor yaitu sensor DHT11 dan sensor LDR. Sensor DHT11 berfungsi untuk menjaga kestabilan suhu dan kelembaban ruangan sedangkan sensor LDR berfungsi unutuk menjaga intensitas cahaya dari rumah walet tersebut. Kondisi yang telah di tentukan berdasarkan 12 rule logika fuzzy, dari kondisi sensor DHT11 yaitu suhu dingin dengan range 0 15, suhu sedang dengan range 15-30, dan suhu panas dengan range 30 45, pada kondisi kelembaban dengan range kering 0 50 dan lembab 0 - 95 sedangkan pada kondisi Sensor LDR yaitu terang dengan range nilai ADC pada LDR sebesar 0 - 500 dan kondisi gelap pada range 500 1024. Nilai ouput defuzzifikasi yang didapat adalah [0 10] dimana 0 dengan kondisi OFF dan 10 dengan kondisi output hitup selama 10 menit.Kata kunci: Burung Walet, Fuzzy , DHT 11, LDR
SISTEM PENGUKURAN DAN OTOMATISASI DAYA LISTRIK RUMAH TANGGA MENGGUNAKAN LOGIKA FUZZY TSUKAMOTO Siregar, Rizki Abdul Hakim; Ikhsan, Muhammad; Lubis, Aidil Halim
JOURNAL OF SCIENCE AND SOCIAL RESEARCH Vol 8, No 2 (2025): May 2025
Publisher : Smart Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54314/jssr.v8i2.3166

Abstract

Abstract: The need for an accurate household electrical power measurement and control system is becoming increasingly urgent to prevent equipment damage due to power fluctuations and to optimize energy consumption. This study tested a system with 15, 20, 25, 30, and 40-watt lamp loads using the ZMPT101B sensor for voltage and ACS712 for current, which were integrated with an Arduino Uno. Fuzzy logic was applied to control the relay based on sensor measurements, taking into account parameters such as voltage, current, and power. This fuzzy logic allows the system to make power regulation decisions automatically and adaptively in response to changes in load conditions, thereby increasing system efficiency and reliability. The results show that the system successfully achieved design and automation goals. Measurements on a 15-watt load resulted in a voltage of 218 V, a current of 0.068 A, and a power of 15.33 watts; on a 20-watt load, the voltage was 221 V, the current was 0.091 A, and the power was 19.80 watts; on a 25-watt load, the voltage was 220 V, the current was 0.114 A, and the power was 24.95 watts; on a 30-watt load, the voltage was 219 V, the current was 0.136 A, and the power was 29.84 watts; and on a 40-watt load, the voltage was 219 V, the current was 0.182 A, and the power was 40.36 watts.   Keyword: Power Measurement System, Household Energy Control, ZMPT101B Sensor, ACS712 Sensor, Arduino Uno, Fuzzy Logic Abstrak: Kebutuhan sistem pengukuran dan kontrol daya listrik rumah tangga yang akurat semakin mendesak untuk menghindari kerusakan peralatan akibat fluktuasi daya dan mengoptimalkan konsumsi energi. Penelitian ini menguji sistem dengan beban lampu 15, 20, 25, 30, dan 40watt menggunakan sensor ZMPT101B untuk tegangan dan ACS712 untuk arus, yang diintegrasikan dengan Arduino Uno. Logika fuzzy diterapkan untuk mengontrol relay berdasarkan pengukuran sensor, dengan mempertimbangkan parameter tegangan, arus, dan daya. Logika fuzzy ini memungkinkan sistem untuk membuat keputusan pengaturan daya secara otomatis dan adaptif terhadap perubahan kondisi beban, sehingga meningkatkan efisiensi dan keandalan sistem. Hasil menunjukkan bahwa sistem berhasil dalam perancangan dan otomatisasi. Pengukuran pada beban 15 watt menghasilkan tegangan 218 V, arus 0,068 A, dan daya 15,33 watt pada beban 20 watt, tegangan 221 V, arus 0.091 A, dan daya 19,80 watt pada beban 25 watt, tegangan 220 V, arus 0,114 A, dan daya 24,95 watt; pada beban 30 watt, tegangan 219 V, arus 0,136 A, dan daya 29,84 watt serta pada beban 40 watt, tegangan 219 V, arus 0,182 A, dan daya 40,36 watt.Kata kunci: Daya Listrik, Kontrol Energi Rumah Tangga, Sensor ZMPT101B, Sensor ACS712, Arduino Uno, Logika Fuzzy  
Co-Authors Abdul Halim Hasugian Adjie Prakasa Viragupty Algifahri, Muhammad Dzar Annisa Aprilia Armansyah Artika, Priti Rindi As’Ary Sahlul Irsyad Darisma Daulay Desmi Roma Putra Lubis Dimas, Dimas Erma Julita, Erma Fadiga, Muhammad Faris Jihad Galang Desdwiansyah Harahap, Yunus Fadillah Hazizah Ulfa Nasution Husein Nur Ansyari Ilka Zufria istiqomah istiqomah Jihan Ulfa Deski Kiki Widya Pratiwi Lia Putri Ashari Lubis M Alif Fahrezy Mhd Furqan Monica Situmeang Muhammad Alwi Baihaqi Muhammad Ihsan Nugraha Muhammad Ikhsan Muhammad Ikhsan Muhammad Siddik Hasibuan Muhammad Zarlis, Muhammad Ningrum, Indri Ayu Nurmaiyah, Nurmaiyah Pandu Wicaksono Putra, Donny Dwi Qori Siagian Rahman, Anisa Rahman, Elsa Azila Rakhmat Kurniawan R Ridho Rizky Nasution Rizky Pulungan, Miftahul Santoso, Heri Saragih, Ahmad Fadhly Sani Shella Fahdilla Sari Sihombing, Rizki Andika Siregar, Muhaimi Rizki Siregar, Rizki Abdul Hakim Siregar, Romadon Goring Sri Wahyuni Sriani Sriani Sriani Suhardi Suhardi, Suhardi Supiyandi Supiyandi Tasya, Yulianda Wahyudi Wahyudi Yunus Fadillah Harahap Yusuf Ramadhan Nasution Zulfi, Tio Fahreza Zulfi