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All Journal Jurnal Infomedia Vocatech : Vocational Education and Technology Journal Jurnal Vokasi INFOKUM Jurnal Real Riset Jurnal Informatika dan Teknologi Komputer ( J-ICOM) jeti Sisfo: Jurnal Ilmiah Sistem Informasi Journal of Embedded Systems, Security and Intelligent Systems Journal Of Artificial Intelligence And Software Engineering Jurnal Polimesin International Journal of Wireless And Multimedia Communications Jurnal Teknologi Rekayasa Informasi dan Komputer International Journal of Applied Artificial Intelligence and Robotics (IJAIC)
Azhar Azhar
Jurusan Teknologi Informasi Dan Komputer Politeknik Negeri Lhokseumawe
Agriculture, Biological Sciences & Forestry Automotive Engineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Library & Information Science Materials Science & Nanotechnology Mechanical Engineering Social Sciences

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Sistem Perhitungan Sounding Tangki Timbun CPO dan Laporan Pengolahan Rendemen Minyak Kelapa Sawit Ptpn IV Pabatu Berbasis Android Mulyadi Mulyadi; Maulida Syadzwina; Azhar Azhar; Huzeini Huzeini; Said Aiyub
Jurnal Infomedia: Teknik Informatika, Multimedia, dan Jaringan Vol 8, No 1 (2023): Jurnal Infomedia
Publisher : Politeknik Negeri Lhokseumawe

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30811/jim.v8i1.4181

Abstract

Abstrak — PKS-PPIS Pabatu merupakan pabrik industri kelapa sawit yang mengolah Tandan Buah Segar (TBS) menjadi CPO. CPO yang ada dipabrik tersebut disimpan di dalam tangki timbun. Tangki timbun CPO setiap harinya dilakukan pengukuran yang dinamakan dengan sounding. Sounding dilakukan setiap dua kali per shif. Hasil sounding akan dilakukan perhitungan lanjutan yang disebut dengan rendemen. Rendemen melibatkan beberapa objek perhitungan diantaranya, sounding, TBS olah, dan jumlah pengiriman minyak. Tujuan penelitian ini dilakukan untuk pembuatan aplikasi berbasis android yang dapat dibawa kemana saja oleh pekerja yang bertanggung jawab dalam proses perhitungan sounding dan rendemen. Aplikasi ini digunakan atasan untuk memantau hasil sounding dan rendemen secara real-time, serta mengakses laporan pengolahan dengan mudah. Metode binary search diimplementasikan dalam pembuatan model aplikasi. Binary search digunakan untuk mencari data volume dan beda yang terdapat pada buku meterolgi tangki timbun serta mencari berat jenis yang ada pada tabel suhu Pengujian aplikasi menunjukkan hasil yang signifikan, di mana sistem perhitungan sounding dan pembuatan laporan pengolahan rendemen mengungguli kinerja perhitungan manual. Perbandingan rasio waktu yang dihasilkan adalah 1:7 dalam perhitungan sounding, 1:6 dalam perhitungan rendemen, dan 1:37 dalam pembuatan laporan. Pengimplementasikan algoritma binary search secara efektif, mampu memberikan peningkatan efisiensi dalam proses perhitungan dan pelaporan. Aplikasi ini memungkinkan pelaksanaan perhitungan yang lebih akurat dan cepat, serta memberikan akses informasi yang lebih mudah bagi menajer dan masinis kepala dalam memantau perhitngan sounding dan rendemen.Abstract — PKS-PPIS Pabatu is a palm oil industrial factory that processes Fresh Fruit Bunches (FFB) into CPO. The CPO in the factory is stored in storage tanks. The CPO storage tank is measured every day which is called sounding. Sounding is done twice per shift. The results of the sounding will be followed by further calculations called the yield. The yield involves several calculation objects including sounding, processed FFB, and the amount of oil shipped. The purpose of this research was to make an Android-based application that can be taken anywhere by workers who are responsible for the sounding and yield calculation processes. This application is used by superiors to monitor sounding and yield results in real-time, as well as easily access processing reports. The binary search method is implemented in making the application model. Binary search is used to find volume and difference data contained in the storage tank meterology book as well as look for the specific gravity in the temperature table. Application testing shows significant results, where the sounding calculation system and preparation of yield processing reports outperform the performance of manual calculations. The ratio of the resulting time is 1:7 in sounding calculations, 1:6 in yield calculations, and 1:37 in report generation. Implementing the binary search algorithm effectively, is able to provide increased efficiency in the calculation and reporting process. This application allows the execution of calculations that are more accurate and faster, as well as providing easier access to information for managers and chief machinists in monitoring sounding and yield calculations. 
Design of Natural Convection Solar Dryer for Coffee Beans with Monitoring System Based on Internet of Things Nurdin Nurdin; Irwin Syahri Cebro; Azhar Azhar; Hendrawati Hendrawati
Jurnal POLIMESIN Vol 20, No 1 (2022): February
Publisher : Politeknik Negeri Lhokseumawe

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30811/jpl.v20i1.2613

Abstract

The process of monitoring the drying of coffee beans so far is still done traditionally so that the effectiveness of the drying process is still low. The IoT-based drying monitoring process is expected to provide better effectiveness and time efficiency. This research designs and manufactures a solar dryer with natural convection heat transfer for coffee beans equipped with an Internet of Things-based monitoring system. The purpose of this study is to develop the performance of a solar dryer with natural convection with the addition of an IoT-based monitoring unit. The research begins with a technical plan for the main components of the dryer. Components whose shapes, dimensions, and materials have been planned will be outlined in the form of detailed technical drawings. Detailed technical drawings will be a guide in the dryer manufacturing process. The main components of the dryer are solar collectors, drying chambers, and an IoT-based monitoring system. The solar collector will function to capture heat from the sun which will flow naturally into the drying room. An IoT-based monitoring system will capture the temperature and humidity (DFRobot DHT22 sensor) in the solar collector, drying room, and the environment of the dryer. In addition, a Bh1750 sensor to capture the intensity of the sun is also embedded in this monitoring system. This monitoring system will be connected to the internet network where the data will be sent to a cloud data server. The recorded data can then be downloaded using a mobile device or personal computer connected to the internet network. This IoT-based monitoring system was chosen so that performance data from the dryer can be monitored in real-time and online. The results of this study are a prototype dryer with a household capacity of 9 Kg equipped with an IoT-based monitoring system has been built and can be implemented properly
Analysis of Long-Term Evolution (LTE) Propagation Pathloss Calculation and Pathloss Simulation in Lubuk Minturun Urban Village, Koto Tangah Sub-District, Padang Syaza Ibra Harlin; Nadita Wijayani Putri; Nasrul; Siska Aulia; Azhar
International Journal of Wireless And Multimedia Communications Vol. 1 No. 2 (2024): International Journal of Wireless And Multimedia Communications
Publisher : Politeknik Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62671/jowim.v1i2.42

Abstract

Good signal quality is characterized by the small amount of propagation path loss or path loss that occurs. These propagation path losses can be caused by the distance between the site and the receiver (mobile station), transmitter frequency, natural conditions, and weather conditions. The farther between the site and the receiver (mobile station), the greater the propagation path loss. The use of propagation models in planning a site development in an area can predict or consider the value of propagation path losses, such as the Okumura-Hatta and COST-231 propagation models. Measurement of signal quality received by the receiver (mobile station) in the making of this final project using the drive test method. Determination of site coordinates in the measurement makes it easier to calculate the distance between the site and the mobile station. The calculation of the Okumura-Hatta propagation model and the COST-231 propagation model will produce a better-received power level value compared to the received power level value in the measurement. This is because the calculation only considers the distance between the site and the receiver (mobile station) without any obstacles or barriers, while the value generated during measurement will be influenced by distance, obstacles or barriers, earth contours, and weather conditions. One of them is Lubuk Minturun Village where the measurement of propagation path loss (Pathloss) is carried out due to the poor quality of the 4G Long Term Evolution (LTE) network.
Desain Sistem Analisis Tingkat Kepuasan Terhadap Proses Belajar Mengajar Jurusan TIK PNL Rahmat Fazrian; Huzaeni Huzaeni; Azhar Azhar
Jurnal Teknologi Rekayasa Informasi dan Komputer Vol 7, No 1 (2024): JURNAL TRIK - POLITEKNIK NEGERI LHOKSEUMAWE
Publisher : Politeknik Negeri Lhokseumawe

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30811/jtrik.v7i1.7439

Abstract

Jurusan TIK Politeknik Negeri Lhokseumawe merupakan program tinggi vokasi dengan mempelajari berbagai bidang keilmuwan teknologi dan komputer terkait dengan pembuatan dan pengembangan berbagai teknologi perangkat lunak. Sebagai unit Pendidikan vokasi yang mayoritas proses belajar mengajar yang diterapkan adalah 30% teori dan 70% merupakan praktik.Penelitian ini bertujuan untuk menganalisis tingkat kepuasan mahasiswa dalam proses belajar mengajar jurusan Teknologi Informasi dan Komputer PNL menggunakan metode Naive Bayes berbasis web. Metode ini digunakan untuk mengumpulkan, mengelola, dan menganalisis data dari mahasiswa untuk mengevaluasi sejauh mana kualitas pengajaran dan pembelajaran yang disediakan oleh jurusan.Penelitian ini melibatkan pengembangan sistem berbasis web yang memungkinkan mahasiswa untuk memberikan umpan balik dan penilaian terhadap berbagai aspek pengajaran, seperti kualitas materi, interaksi dosen-mahasiswa, dan ketersediaan sumber daya. Data umpan balik yang diperoleh digunakan sebagai masukan untuk algoritma Naive Bayes, yang menghasilkan analisis tingkat kepuasan mahasiswa. Hasil dari penelitian ini diharapkan dapat memberikan wawasan yang berharga bagi jurusan TIK PNL untuk meningkatkan kualitas pengajaran mereka dan meningkatkan kepuasan mahasiswa.Metode Naive Bayes dipilih karena kemampuannya dalam mengolah data berbasis teks dan menghasilkan prediksi berdasarkan informasi yang ada. Dengan pendekatan ini, penelitian ini berupaya memberikan pemahaman yang lebih mendalam tentang pandangan mahasiswa terhadap pengalaman belajar mereka, dan dengan demikian, membantu jurusan untuk terus memperbaiki proses pembelajaran mereka.
Application of the K-Nearest Neighbors (KNN) Algorithm for Diabetes Mellitus Classification: Evidence from Aceh Province, Indonesia Cut Aulia Safira Rahman; Rizky Wahyu Aulia; Azhar Azhar; Rahmad Hidayat
Jurnal Teknologi Rekayasa Informasi dan Komputer Vol 9, No 1 (2026): JURNAL TRIK - POLITEKNIK NEGERI LHOKSEUMAWE
Publisher : Politeknik Negeri Lhokseumawe

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30811/jtrik.v9i1.8721

Abstract

Diabetes mellitus is a non-communicable disease with a steadily increasing prevalence in Indonesia, including Aceh Province. Early detection using data-driven approaches is essential to minimize the risk of severe complications. This study aims to classify diabetes mellitus by implementing the K-Nearest Neighbors (KNN) algorithm. The dataset comprises 1,500 instances from the Pima Indians Diabetes Dataset obtained from Kaggle and an additional 100 instances collected from hospitals across Aceh Province. Data preprocessing involved normalization and label encoding, followed by data partitioning into training and testing sets using a 90:10 ratio. The KNN model was configured with a parameter value of K=5. Experimental results indicate that the proposed model achieved an accuracy of 85%, precision of 87%, recall of 82%, and an F1-score of 85% on the Kaggle dataset. For the hospital dataset, the model attained an accuracy of 76%, precision of 80.95%, recall of 68%, and an F1-score of 73.91%. These findings suggest that the KNN algorithm demonstrates adequate performance in classifying diabetes mellitus and may serve as a basis for the development of data-driven medical decision support systems.
Peningkatan Kualitas dan Produktivitas Keripik Pisang UMKM IBDA Lhoksukon dengan Menggunakan Mesin Pengiris Keripik Pisang Luthfi Luthfi; Herri Mahyar; Mursyidah Mursyidah; Azhar Azhar; Sumardi Sumardi
Jurnal Vokasi Vol 10, No 1 (2026): Maret
Publisher : Politeknik Negeri Lhokseumawe

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30811/vokasi.v10i1.8732

Abstract

Pisang merupakan salah satu buah yang banyak dikonsumsi masyarakat Indonesia dan sering diolah menjadi berbagai produk makanan, salah satunya keripik pisang. Namun, mitra kegiatan Pengabdian Kepada Masyarakat (PKM), yaitu UMKM IBDA yang dirintis oleh Teuku Muhammad Imam Shiddiq di Lhoksukon, menghadapi kendala dalam proses produksi karena pengirisan pisang masih dilakukan secara manual. Proses tersebut memakan waktu, melelahkan, serta berisiko melukai jari pekerja, sehingga produktivitas dan kualitas produk terbatas. Kegiatan PKM ini bertujuan meningkatkan produktivitas dan kualitas keripik pisang melalui hibah mesin pengiris pisang kepada mitra. Metode yang digunakan adalah participation approach, di mana mitra dilibatkan secara aktif dalam setiap tahap kegiatan meliputi identifikasi kebutuhan, pemilihan jenis mesin, uji coba, dan demonstrasi alat. Hasil kegiatan menunjukkan bahwa penggunaan mesin pengiris dapat menggantikan proses manual dengan kecepatan dan kualitas irisan yang setara. Selain itu, kapasitas produksi meningkat signifikan, dan mutu irisan menjadi lebih seragam sehingga berdampak positif terhadap keberlanjutan usaha mitra
Pembuatan Bio Komposit Ramah Lingkungan Dari Ampas Kopi dengan Menggunakan Resin Unsaturated Polyester Luthfi Luthfi; Teuku Riyadhsyah; Sumardi Sumardi; Azhar Azhar; Hamdani Hamdani
VOCATECH: Vocational Education and Technology Journal Vol 8, No 1 (2026): April
Publisher : Akademi Komunitas Negeri Aceh Barat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38038/vocatech.v8i1.317

Abstract

     AbstractIndonesia, as one of the world's largest coffee bean producers, generates substantial spent coffee ground (SCG) waste with untapped potential. Currently, SCG utilization remains suboptimal, with large quantities discarded without processing to enhance economic value. This study aimed to evaluate the feasibility of using arabica and robusta SCG as fillers in unsaturated polyester resin (UPR) composites to develop value-added products from this waste. Five SCG volume fractions (5%–50%) were tested for each SCG type. Composites were cut into three specimens per fraction and mechanically tested per ASTM D638 (tensile) and ASTM C1341-06 (bending). Results showed that both tensile and bending strengths decreased with increasing SCG content for both types. Arabica SCG composites exhibited higher strengths at lower fractions (10%–30%): tensile 1.38–1.72 kgf/mm² and bending 2.08–2.72 kgf/mm², versus robusta (tensile 0.58–0.75 kgf/mm²; bending 1.22–1.45 kgf/mm²). At higher fractions (40%–50%), robusta outperformed arabica: tensile 0.58–0.75 kgf/mm² and bending 1.22–1.45 kgf/mm², versus arabica (tensile 0.45–0.68 kgf/mm²; bending 0.47–1.19 kgf/mm²). These findings highlight SCG's potential in affordable composites, with performance varying by type and loading. Keywords:arabica; composite; robusta; spent coffee grounds; unsaturated polyester resin AbstrakIndonesia sebagai salah satu produsen biji kopi terbesar di dunia menghasilkan limbah ampas kopi bekas (spent coffee ground/SCG) dalam jumlah besar yang memiliki potensi belum dimanfaatkan secara optimal. Saat ini, pemanfaatan SCG masih belum optimal, dengan jumlah limbah yang dibuang secara besar-besaran tanpa pengolahan untuk meningkatkan nilai ekonomisnya. Penelitian ini bertujuan untuk mengevaluasi kelayakan penggunaan SCG arabika dan robusta sebagai pengisi dalam komposit resin poliester tak jenuh (unsaturated polyester resin/UPR) guna mengembangkan produk bernilai tambah dari limbah tersebut. Lima fraksi volume SCG (5%–50%) diuji untuk masing-masing jenis SCG. Komposit dipotong menjadi tiga spesimen per fraksi dan diuji mekanik sesuai ASTM D638 (tarik) dan ASTM C1341-06 (lentur). Hasil menunjukkan bahwa kekuatan tarik dan lentur menurun seiring meningkatnya kandungan SCG untuk kedua jenis. Komposit SCG arabika menunjukkan kekuatan lebih tinggi pada fraksi rendah (10%–30%): tarik 1,38–1,72 kgf/mm² dan lentur 2,08–2,72 kgf/mm², dibandingkan robusta (tarik 0,58–0,75 kgf/mm²; lentur 1,22–1,45 kgf/mm²). Pada fraksi tinggi (40%–50%), robusta unggul: tarik 0,58–0,75 kgf/mm² dan lentur 1,22–1,45 kgf/mm², dibandingkan arabika (tarik 0,45–0,68 kgf/mm²; lentur 0,47–1,19 kgf/mm²). Temuan ini menyoroti potensi SCG dalam komposit terjangkau, dengan kinerja yang bervariasi berdasarkan jenis dan fraksi muatan. Kata Kunci:             ampas kopi; arabika; komposit; robusta; unsaturated polyester resin
Aplikasi Pembelajaran Al-Mufradat Untuk Siswa Madrasah Ibtidaiyah Berbasis Android Mulyadi Mulyadi; Mila Rozana; Azhar Azhar
Sisfo: Jurnal Ilmiah Sistem Informasi Vol. 5 No. 2 (2021): Sisfo: Jurnal Ilmiah Sistem Informasi, Oktober 2021
Publisher : Universitas Malikussaleh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29103/sisfo.v5i2.6338

Abstract

Al-Mufrodat merupakan salah satu unsur dalam bahasa Arab. Setiap kalimat dalam bahasa Arab pasti tersusun dari beberapa al-mufrodat. Dalam pembelajaran bahasa Arab ada beberapa permasalahan yang dihadapi siswa Madrasah Ibtidaiyah diantaranya anak tidak mampu mengikuti pembejaran seperti yang diterapkan dikarenakan media pembelajaran yang kurang menarik dan membosankan dan biasanya kosakata diperkenalkan dalam bentuk buku-buku dan poster-poster yang dijual. Oleh karena itu dirancanglah aplikasi pembelajaran al-mufradat bahasa Arab menggunakan media visualisasi yang menampilkan teks, gambar dan audio (suara) berbasis android menggunakan metode string matching dengan algoritma brute force di pencarian kosakata dan algoritma fisher-yates shuffle dalam pengacakan soal. Didalam aplikasi ini user dapat mempelajari 7 materi yang sering dijumpai sehari-hari seperti materi angka, anggota tubuh, benda dikelas, buah-buahan, hewan, nama-nama hari dan warna.
Chatbot for Gastric Disease Consultation to Recommend a Healthy Diet Using KNN and NLP Methods Hendrawaty; Azhar Azhar; Rafli Abdul Aziz
International Journal of Applied Artificial Intelligence and Robotics Vol. 1 No. 1 (2025): First Volume and Issue of IJAIC Journal
Publisher : PT. Literasi Teknologi Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.67745/ijaic.v1i1.7

Abstract

Gastric disease is one of the most common health problems and requires special treatment, including proper dietary arrangements. This research aims to design and build a healthy diet recommendation system using chatbots that utilize Natural Language Processing (NLP) and K-Nearest Neighbor (KNN) methods This system is designed to help people with gastric diseases by providing appropriate dietary recommendations based on the symptoms they are experiencing. In the design stage, the system identifies the symptoms mentioned by the user through a conversation with the chatbot. NLP is used to extract relevant information from the user's input text, while KNN is used to classify symptoms and provide appropriate dietary recommendations. The system was tested using a dataset that had been adjusted to cases of gastric diseases. The test results show that this chatbot system has a classification accuracy of 96.36%, with a confusion matrix that shows good performance in identifying symptoms and providing recommendations. The system is able to understand the context of the conversation well through NLP, while KNN provides accurate classification based on the available datasets. With these results, this system is expected to be an effective tool for gastric disease sufferers in managing their diet better and appropriately.
Co-Authors Adieth Try Aulia Lastana Alfiya Zahara Amirullah Cut Aulia Safira Rahman Dimas Rama Nugraa Hamdani, Hamdani Hendrawati Hendrawati Hendrawati Hendrawaty Hendrawaty Herri Mahyar Huzaeni Huzeini Huzeini Irwin Syahri Cebro Luthfi Luthfi Maulida Syadzwina Mila Rozana Mulyadi Mursyidah . Musta’inul Abdi Nadita Wijayani Putri Nasrul Nurdin Nurdin Nurul Fatani Rafli Abdul Aziz Rahmat Fazrian Rizki Balia Rizky Wahyu Aulia Said Aiyub Simbolon, Zulfan Khairil Siska Aulia Sumardi Sumardi Syaza Ibra Harlin Syifa Zahrah Teuku Riyadhsyah Toni Toni yunita