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All Journal SITEKIN: Jurnal Sains, Teknologi dan Industri Jurnal Pendidikan Islam Iqra' Jurnal Kreativitas PKM Jurnal Teknik Informatika (JUTIF) Journal La Multiapp Indonesian Journal of Innovation Studies Jurnal Locus Penelitian dan Pengabdian Innovative: Journal Of Social Science Research Academia Open
Hasibuan, Alfiansyah
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Algorithm Comparison for Estimating Chili Pepper Production in North Sulawesi Province: Perbandingan Algoritma untuk Estimasi Produksi Cabai Rawit di Provinsi Sulawesi Utara Musung, Matthew Albert Alexander; Hasibuan, Alfiansyah
Indonesian Journal of Innovation Studies Vol. 26 No. 4 (2025): October
Publisher : Universitas Muhammadiyah Sidoarjo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21070/ijins.v26i4.1756

Abstract

Background: Chili pepper production in North Sulawesi Province plays a vital role in regional food supply yet experiences frequent fluctuations due to natural and seasonal factors. Specific Background: These production instabilities have led to difficulties in market price control and agricultural planning, prompting the need for accurate predictive models. Knowledge Gap: Previous studies have compared regression and neural network algorithms in various domains, but little research has focused on local agricultural commodities such as chili peppers in North Sulawesi. Aim: This study compares the performance of Multiple Linear Regression and Backpropagation algorithms in estimating chili pepper production using statistical data from the North Sulawesi Statistics Agency (2018–2023). Results: Evaluation using R-squared (R²) and Mean Absolute Percentage Error (MAPE) shows that Backpropagation achieved R² = 0.846 and MAPE = 3.235%, outperforming Multiple Linear Regression (R² = 0.228; MAPE = 6.875%). Novelty: The study uniquely applies machine learning algorithms to a regional agricultural context characterized by nonlinear and fluctuating production data. Implications: The findings demonstrate the potential of Backpropagation as a reliable predictive tool for developing intelligent agricultural systems that support production planning and food security policy in North Sulawesi. Highlights Backpropagation shows higher accuracy than Multiple Linear Regression. Estimation uses agricultural data from North Sulawesi Province. Model supports predictive systems for food production planning. Keywords Backpropagation, Chili Production, Multiple Linear Regression, Prediction Model, North Sulawesi
Analisis Klasifikasi Metode X-Means Pada Minat dan Bakat Anak Dimasa Pandemi Putra, Purwa Hasan; Hasibuan, Alfiansyah; Marpaung, Effenril Agung
SITEKIN: Jurnal Sains, Teknologi dan Industri Vol 19, No 2 (2022): Juni 2022
Publisher : Fakultas Sains dan Teknologi Universitas Islam Negeri Sultan Syarif Kasim Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24014/sitekin.v19i2.17889

Abstract

Algoritma X-Means merupakan algoritma yang digunakan untuk pengelompokan data.Algoritma x means merupakan pengembangan dari k-means.X-means  clustering  digunakan untuk menyelesaikan salah satunya kelemahan utama dari  K-means  clustering,  yaitu  perlunya  pengetahuan  sebelumnya  tentang  jumlah cluster (K). Dalam metode ini, nilai sebenarnya dari K diperkirakan dalam suatu yang tidak diawasi cara dan hanya berdasarkan set data itu sendiri. Adapun hasil penelitian dengan menggunakan algoritma X-Means dengan evaluasi Davies-Bouldin Index penentuan  jumlah Centroid  cluster  dilakukan  dengan  memodifikasi  metode  X-Means. Dalam pengelompokan data ini dilakukan pengclusteran pada setiap data sisw dari variabel-variabelyang telah dikumpulkan. Bakat dan minat setiap siswa akan dicocokkan dengan perguruan tinggi dan jurusan apa yang diminati dari setiap siswa
The Impact of Education Character on Learning Activity of Madrasah Aliyah Students in Manado Modeong, Merriam; Ratumbuisang, Keith Francis; Hasibuan, Alfiansyah
Jurnal Ilmiah Iqra' Vol 18, No 1 (2024)
Publisher : IAIN Manado

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30984/jii.v18i1.2924

Abstract

The Impact of Education Character on Learning Activity of Madrasah Aliyah Students In Manado. This research aims to determine the impact of Education Character on the learning activities of Madrasah Aliyah (MA) students in Manado City. This is quantitative research, and the population of this study were all class XII MA students in Manado City. At the same time, the sample in this study consisted of 78 students, formulated using an accidental sampling technique. Data analysis uses simple linear regression analysis.The research results reveal that the variable Furthermore, the t-count value is 7.524, which means it is greater than the t table value = 1.665 with N=78 (7.524>1.665). Furthermore, it can be stated that this research rejects the H0 decision, which means that Education Character has a positive and significant impact on the learning activities of Madrasah Aliyah students in Manado City
IMPLEMENTATION OF THE FORWARD CHAINING METHOD FOR DETECTING SCHOOL READINESS IN CHILDREN Rorimpandey, Gladly C.; Mantik, Felitia Theona Geofani; Hasibuan, Alfiansyah
Jurnal Teknik Informatika (Jutif) Vol. 5 No. 4 (2024): JUTIF Volume 5, Number 4, August 2024 - SENIKO
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2024.5.4.2221

Abstract

Primary school education is the education of children aged 7 to 13 years as education at the basic level which is developed in accordance with educational units, regional potential and socio-culture. School readiness for children is no less important because in fact school readiness for children is very important for children because many children are found to be still not ready. attended school when but was already in elementary school. To overcome this problem, this research provides a solution by building an expert system for detecting school readiness in children using the forward chaining method, which is a technique in an expert system that begins with gathering information starting from collecting premises which is followed by a conclusion or derived information (then). From the results of testing using functional testing and usability testing, it is known that in implementing the forward chaining method, 24 symptoms of school readiness were identified based on knowledge obtained directly from psychologists. The results obtained in testing using usability testing based on the results obtained are assessed as final and then the average value is calculated. The final conclusion of the results determined through the SUS Score assessment is 84%. This shows that this system easy and useful in assessing children's school readiness. The implication of the results of this test is that the school readiness detection expert system can be a useful tool for parents, teachers to evaluate children's readiness to enter elementary school.
Implementasi Algoritma Regresi Liniear untuk Memprediksi Pendapatan Retribusi Pasar Dinas Perdagangan Koperasi dan UKM Kota-Kotamobagu Mokoginta, Fadlia; Kainde, Quido C.; Hasibuan, Alfiansyah
Innovative: Journal Of Social Science Research Vol. 4 No. 3 (2024): Innovative: Journal Of Social Science Research (Special Issue)
Publisher : Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/innovative.v4i3.11611

Abstract

Retribusi daerah adalah salah satu sumber Pendapatan asli PAD. Retribusi daerah mempunyai peran yangpenting pada pemasukan dan pembangunan untuk Peningkatan atau menjadikan daerah lebih maju. Kemampuan ekonomi suatu daerah adalah diukur melalui besarnya pendapatan PAD. Masalah pada penelitian ini pengelolaan retribusi di daerah Kotamobagu dilakukan secara manual kurang efisien, harusnya retribusi merupakan sumber Atau tulang punggung biaya daerah atau pendanaan yang perlu dikelola dengan baik. Permasalahan ini dapat diatasi dengan membangun sistem manajemen pasar yang memanfaatkan teknologi dan didukung oleh sistem berbasis web. Implementasi algoritma regresi linier sederhana dalam sistem manajemen ini juga akan membantu memperkirakan hasil pendapatan retribusi pasar di Daerah Kota Kotamobagu, khususnya untuk Dinas Perdagangan, Koperasi, dan UKM Kotamobagu. Kata Kunci: implemetasi Algoritma Regresi Liniear, Manajemen Pasar
Perancangan Design UI/UX Menggunakan Metode Design thinking Dalam Pengembangan Website Sistem Informasi Kepegawaian Musung, Matthew Albert Alexander; Hasibuan, Alfiansyah
Innovative: Journal Of Social Science Research Vol. 5 No. 4 (2025): Innovative: Journal Of Social Science Research
Publisher : Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/innovative.v5i4.17840

Abstract

Salah satu program yang dilaksanakan dalam membangun tata kelola kepegawaian ini adalah dengan penataan kelola data pegawai melalui Sistem Informasi Kepegawaian, Dalam era digital saat ini, badan kepegawaian di berbagai daerah pemerintahan harus mampu menyediakan sistem yang mudah diakses, responsif, dan efisien untuk mendukung administrasi kepegawaian. Desain UI/UX yang baik dapat memperbaiki interaksi pengguna dengan aplikasi kepegawaian, mengurangi kesalahan, serta mempercepat proses pelayanan. Artikel ini mengeksplorasi peran penting desain UI dalam menciptakan antarmuka yang user-friendly dan desain UX dalam memastikan pengalaman pengguna yang optimal. Dengan adanya perancangan Sistem Informasi Kepegawaian (SINIKE) menggunakan metode Design thinking menghasilkan perancangan desain user interface dan user experience Sistem Informasi Kepegawain (SINIKE) baru yang terdiri dari fitur: menu login, menu E-Konsultasi, menu kinerja unit kerja, menu , menu statistik. Hasil dari penerapan metode ini menunjukkan bahwa dengan menggunakan metode Design thinking, desain UI/UX website (SINIKE) meningkatkan kenyamanan, kemudahan akses, dan kepuasan pengguna secara keseluruhan.
Penerapan Teknologi Tepat Guna untuk Pengolahan Tanaman Eichhornia Crassipes sebagai Bahan Dasar Kerajinan Tangan Bernilai Ekonomi Serta Pembuatan Sistem Ecommerce sebagai Media Promosi dan Pemasaran Dari Hasil Produk Hasibuan, Alfiansyah; Olii, Djami; Mustafa, Mustafa
Jurnal Kreativitas Pengabdian Kepada Masyarakat (PKM) Vol 7, No 11 (2024): Volume 7 No 11 (2024)
Publisher : Universitas Malahayati Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33024/jkpm.v7i11.17610

Abstract

ABSTRAK Eceng gondok dapat mengganggu keseimbangan ekosistem air tawar dengan menghambat pertumbuhan tanaman air, mengurangi oksigen dalam air, dan merusak habitat ikan dan makhluk air lainnya. Ini dapat berdampak negatif pada keberlanjutan ekosistem air tawar. Kegiatan ini akan melibatkan Kelompok Pengrajin/UMKM yang ada di Kelurahan Kampung Jawa Tondano. Permasalahan yang dihadapi yaitu, Pertumbuhan dari tumbuhan Eichhornia crassipes tak terkendali sehingga menutupi aliran sungai maupun Danau, Akar yang tumbuh kebawah air mengakibatkan pendangkalan Danau dan Sungai sehingga dapat mengurangi debit air yang ditampung, Pertumbuhan yang sangat cepat sehingga mengakibatkan pendangkalan pada danau dan sungai sehingga dapat mengurangi daya tampung air pada Danau maupun sungai, Dampak yang ditimbulkan dari pendangkalan sungai dan danau yaitu air mengalir dan memenuhi jalan-jalan pemukiman disekitar danau dan sungai, Menghabat aliran air pada sungai, Menampung sampah yang dibuang masyarakat pada saluran air sungai, Akar dari tumbuhan Eichhornia crassipes membuat keramba ikan yang di budidaya menjadi rusak. Solusi yang akan diberikan dengan mengacu dari permasalahan prioritas adalah sebagai berikut, Membuat mesin untuk mengolah batang dari tumbuhan Eichhornia crassipes pada kegiatan ini teknologi tepat guna yang akan dibuat yaitu Mesin Pemilin Tali, Membuat mesin Pencacah dari akar, daun dan batang yang tidak digunakan untuk dijadikan sebagai bahan pembuatan pupuk organik, Tim pelaksana kegiatan akan membuat website sebagai media pemasaran dan promosi dari produk yang dihasilkan, Tim pelaksana kegiatan akan mengadakan pelatihan khusus dalam mengolah batang dari tumbuhan Eichhornia crassipes, tim pelaksana kegaitan juga akan memberikan pelatihan proses pengolahan akar, daun dan batang yang tidak di gunakan untuk menjadi pupuk organik, Tim juga akan memberikan pelatihan terkait manajemen dan pemasaran secara digital untuk produk yang telah dihasilkan, Tim pelaksana kegiatan pengabdian akan membuat Logo sebagai identitas yang akan digunakan pada hasil produksi. Kata Kunci: Eichhornia Crassipes, UMKM, Website Pemasaran ABSTRACT Water hyacinth or scientifically known as Eichhornia crassipes is a type of aquatic plant that is often found in fresh water in tropical and subtropical areas. This plant is a habitat that grows in fresh water and is home to several Water hyacinth can disrupt the balance of freshwater ecosystems by inhibiting the growth of aquatic plants, reducing oxygen in the water, and damaging the habitat of fish and other aquatic creatures. This can have a negative impact on the sustainability of freshwater ecosystems. This activity will involve the Craftsmen/UMKM Group in the Kampung Jawa Tondano Village. The problems faced are, The growth of Eichhornia crassipes plants is uncontrolled so that it covers the flow of rivers and lakes, The roots that grow underwater cause shallowing of lakes and rivers so that it can reduce the discharge of water that is stored, Very rapid growth causes shallowing of lakes and rivers so that it can reduce the capacity of water in lakes and rivers, The impacts caused by shallowing of rivers and lakes are that water flows and fills residential roads around lakes and rivers, Inhibits the flow of water in rivers, Accommodates waste dumped by the community in river channels, The roots of Eichhornia crassipes plants damage the fish cages that are being cultivated. The solutions that will be provided with reference to the priority problems are as follows, Making a machine to process stems from Eichhornia crassipes plants in this activity, the appropriate technology that will be made is a Rope Twisting Machine, Making a Shredder machine from roots, leaves and stems that are not used to be used as materials for making organic fertilizer, The activity implementation team will create a website as a marketing and promotional media for the products produced, The activity implementation team will hold special training in processing stems from Eichhornia crassipes plants, the activity implementation team will also provide training in the process of processing roots, leaves and stems that are not used to become organic fertilizer, The team will also provide training related to management and digital marketing for the products that have been produced, The service activity implementation team will create a Logo as an identity that will be used on the production results. Keywords: Eichhornia crassipes, UMKM, Marketing website
Leaf Type Recognition System Using Image Processing Method Using Convolutional Neural Network Algorithm Kolauw, Evan; Hasibuan, Alfiansyah; Kumajas, Sondy C
Journal La Multiapp Vol. 7 No. 2 (2026): Journal La Multiapp
Publisher : Newinera Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37899/journallamultiapp.v7i2.3057

Abstract

A digital image-based leaf recognition system is one of the modern solutions in the fields of botany and agriculture to identify plants automatically. This study developed a leaf recognition system using image processing methods and Convolutional Neural Network (CNN) algorithms. CNN was chosen because of its ability to independently extract features through convolution layers, thus capturing important visual patterns such as shape, edges, textures, and leaf veins without requiring manual feature engineering processes. The research dataset consists of a collection of leaf images from several types of plants obtained through direct photo-taking and public dataset sources. Each image goes through a pre-processing stage, including cropping, resizing, image quality enhancement, and pixel normalization to ensure data consistency before entering the training stage. The CNN model is designed with several convolutional layers, pooling, activation functions, and fully connected layers to produce optimal classification performance. Model training is carried out by dividing training and testing data, as well as augmentation techniques to increase image variation. System performance is evaluated using accuracy, precision, recall, and confusion matrix. The test results show that the CNN model is able to recognize leaf types with a high level of accuracy and is stable under various test conditions, including variations in lighting and shooting angles. Overall, this study proves that CNN is an effective and reliable approach in building an automatic leaf recognition system. This system has the potential to be applied in the fields of precision agriculture, mobile application-based plant identification, and botanical research that require speed and accuracy in plant classification.
Analisis Efektivitas Sistem Rekomendasi Berbasis Random Forest untuk Edukasi Rehabilitasi Narkoba di Masyarakat Kota Manado Silaarta, Hezeki Farell; Hasibuan, Alfiansyah; Kumajas, Sondy C.
Jurnal Locus Penelitian dan Pengabdian Vol. 5 No. 4 (2026): JURNAL LOCUS: Penelitian dan Pengabdian
Publisher : Riviera Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58344/locus.v5i4.5701

Abstract

Penyalahgunaan narkoba di Kota Manado menunjukkan tren peningkatan yang signifikan dan menjadi tantangan serius bagi upaya pencegahan serta edukasi rehabilitasi. Penelitian ini bertujuan menganalisis efektivitas sistem rekomendasi materi edukasi rehabilitasi berbasis algoritma Random Forest, yang dirancang untuk menyajikan konten pembelajaran terpersonalisasi sesuai karakteristik pengguna. Metode yang digunakan adalah Research and Development (R&D) dengan desain quasi-experimental melalui pretest-posttest control group design. Sampel penelitian terdiri atas 181 responden, terbagi dalam kelompok eksperimen (91 orang) dan kontrol (90 orang). Sistem dikembangkan menggunakan Python, Flask, dan PostgreSQL, dengan Random Forest sebagai algoritma klasifikasi berdasarkan variabel usia, jenis kelamin, minat edukasi, pekerjaan, dan skor pre-test. Hasil pengujian menunjukkan bahwa model Random Forest memiliki kinerja klasifikasi yang sangat tinggi, dengan akurasi, precision, recall, dan F1-score masing-masing mencapai 100%. Namun, uji efektivitas sistem memperlihatkan tidak adanya perbedaan signifikan antara kelompok eksperimen dan kontrol, baik pada nilai post-test (p = 0,3023) maupun gain score (p = 0,7503). Meskipun demikian, secara deskriptif kelompok eksperimen menunjukkan kecenderungan peningkatan skor lebih tinggi dibandingkan kelompok kontrol. Temuan ini mengindikasikan bahwa meskipun sistem rekomendasi bekerja optimal secara teknis, dampak intervensi terhadap peningkatan pemahaman belum signifikan secara statistik. Penelitian ini berkontribusi pada pengembangan sistem edukasi digital berbasis machine learning di bidang rehabilitasi narkoba, serta membuka peluang perbaikan melalui penambahan variabel prediktor, pengayaan level materi, dan perbandingan dengan algoritma lain pada penelitian selanjutnya.
Danantara YouTube Sentiment Shows Public Transparency Concerns: Sentimen YouTube Danantara Menunjukkan Kekhawatiran Transparansi Publik Wahani, Waraney Vincent Beckham; Hasibuan, Alfiansyah; Tinambunan, Medi Hermanto
Academia Open Vol. 11 No. 1 (2026): June
Publisher : Universitas Muhammadiyah Sidoarjo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21070/acopen.11.2026.14210

Abstract

General Background Social media comments offer valuable data for analyzing public discourse on policy issues. Specific Background This study investigates YouTube comments about Danantara, Indonesia's strategic investment body, using Natural Language Processing with 7,294 comments. Knowledge Gap Previous studies often analyze sentiment and topics separately, without integrated analysis or iterative labeling. Aims The study aims to classify sentiment using Support Vector Machine (SVM) and identify topics with Latent Dirichlet Allocation (LDA). Results 74.9% accuracy was achieved with SVM, classifying 58.0% of comments as negative, 29.3% neutral, and 12.8% positive. LDA revealed 6 topics for neutral, 4 for positive, and 3 for negative sentiment, with key concerns about transparency and corruption. Novelty This study integrates SVM and LDA with Human in the Loop labeling to capture both sentiment and topic substance. Implications Findings offer insights for improving transparency and public communication, while contributing to text mining in digital discourse. Highlights • The classifier achieved 74.9% accuracy after Human in the Loop labeling and manual verification.• Unfavorable polarity reached 58.0%, followed by neutral at 29.3% and positive at 12.8%.• Coherence scores selected 6 neutral, 4 positive, and 3 critical thematic clusters. Keywords Danantara; Sentiment Analysis; Topic Modeling; Support Vector Machine; Latent Dirichlet Allocation  
Co-Authors Djami Olii Gladly Caren Rorimpandey Keith Francis Ratumbuisang Kolauw, Evan Kumajas, Sondy C Kumajas, Sondy C. Mantik, Felitia Theona Geofani Marpaung, Effenril Agung Merriam Listiany Modeong Mokoginta, Fadlia Mustapa Mustapa Musung, Matthew Albert Alexander Putra, Purwa Hasan Quido Conferti Kainde Silaarta, Hezeki Farell Tinambunan, Medi Hermanto Wahani, Waraney Vincent Beckham