Garuda - Garba Rujukan Digital

Plastic Waste Chips For Environmentally Friendly Soil Stabilization: Experimental Study On Clay Soil Improvement Using CBR Method Kaifan, Andrian; Irham, Irham; Aiyub, Aiyub; Gani, Fauzi A.; Munardy, Munardy; Ruhana, Ruhana
VOCATECH: Vocational Education and Technology Journal Vol 7, No 1 (2025): August
Publisher : Akademi Komunitas Negeri Aceh Barat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38038/vocatech.v7i1.226

AbstractClay soils are widely recognized for their poor engineering characteristics, particularly their low bearing capacity and high shrink-swell potential. These limitations make them unsuitable for use as foundation material in road construction and other geotechnical applications. This study aims to evaluate the potential of plastic waste chipping as an additive to improve the geotechnical properties of clay soil. The research was conducted using the California Bearing Ratio (CBR) method to assess bearing capacity. The experimental program involved mixing clay soil—sourced from Blang Pala Village, North Aceh—with varying contents of plastic waste chips (1%, 1.5%, and 2%) and different chip sizes (0.5×0.5 cm, 0.75×0.75 cm, and 1×1 cm). A series of laboratory tests were conducted, including specific gravity, Atterberg limits, standard proctor compaction, and CBR tests in both unsoaked and soaked conditions. The results revealed that the addition of plastic waste chips consistently improved the CBR values, with the most significant enhancement observed at 2% plastic content and 1×1 cm chip size. The unsoaked and soaked CBR values increased from 6.8% to 8.1% and from 3.8% to 5.9%, respectively. These findings suggest that plastic waste chips offers a promising, sustainable construction method for enhancing the performance of clay soils while contributing to plastic waste management.AbstrakTanah lempung dikenal secara luas karena memiliki sifat-sifat teknik yang kurang baik, terutama daya dukungnya yang rendah dan potensi kembang susut yang tinggi. Keterbatasan ini menjadikan tanah lempung tidak sesuai untuk digunakan sebagai bahan dasar pondasi dalam pembangunan jalan dan aplikasi geoteknik lainnya. Penelitian ini bertujuan untuk mengevaluasi potensi cacahan limbah plastik sebagai bahan tambahan guna meningkatkan sifat geoteknik tanah lempung. Penelitian dilakukan menggunakan metode California Bearing Ratio (CBR) untuk menghitung daya dukung tanah. Penelitian ini dimulai dari pencampuran tanah lempung yang bersumber dari Desa Blang Pala, Aceh Utara dengan variasi jumlah cacahan limbah plastik (1%, 1,5%, dan 2%) dan ukuran cacahan yang berbeda (0,5×0,5 cm, 0,75×0,75 cm, dan 1×1 cm). Serangkaian uji laboratorium yang dilakukan meliputi berat jenis, batas Atterberg, uji proctor standar, dan uji CBR dalam kondisi tidak direndam dan direndam. Hasil penelitian menunjukkan bahwa penambahan cacahan limbah plastik secara konsisten meningkatkan nilai CBR, dengan peningkatan paling signifikan pada kandungan plastik 2% dan ukuran cacahan 1×1 cm. Nilai CBR tidak direndam meningkat dari 6,8% menjadi 8,1% dan nilai CBR direndam meningkat dari 3,8% menjadi 5,9%. Hasil ini menunjukkan bahwa cacahan limbah plastik merupakan metode yang menjanjikan untuk konstruksi berkelanjutan untuk meningkatkan kinerja tanah lempung sekaligus turut berkontribusi dalam pengelolaan limbah plastik.

Identification of Environmental Impacts in Road Construction Projects Yusra, Cut Liliiza; Wiharja, Hery; Zarita, Santi Septiana; Agustian, Kusmira; Abdullah, Ahmad Zaidi Bin; Novriza, Ferdiansyah
VOCATECH: Vocational Education and Technology Journal Vol 7, No 1 (2025): August
Publisher : Akademi Komunitas Negeri Aceh Barat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38038/vocatech.v7i1.220

AbstractEnvironmental Impact Assessment (EIA) is a crucial activity that must be conducted prior to the development of any project, whether it involves infrastructure, extractive industries, or tourism development. Every infrastructure development should account for potential impacts or effects caused by the activity through monitoring and root cause analysis, ensuring that issues are addressed to prevent the emergence of new problems in the future. The primary purpose of EIA is to protect, reduce, and prevent potential impacts of a project on the environment and society. Potential impacts are analysed by distributing questionnaires and conducting direct interviews with local communities around the project area. The data collected indicates that the perceived impacts include: 58% related to road facilities, 43% traffic flow disturbances, 65% noise pollution, 81% vibrations, 59% air pollution, 54% water pollution, and 15% soil contamination. In conclusion, the most significant effect perceived from the construction of the campus ring road project is noise, with a percentage of 65% Based on the results of the research that has been conducted, it is important to prioritize the analysis of environmental impacts before the implementation of a project in a certain area, so that the effects on the surrounding community can be minimized as much as possible.Keywords:Environmental impact analysis (AMDAL); campus ring road; construction project. AbstrakAnalisis Dampak Lingkungan (AMDAL) adalah kegiatan penting yang harus dilakukan sebelum pembangunan sebuah proyek, baik itu proyek infrastruktur, industri ekstraktif, atau pengembangan pariwisata. Setiap pembangunan infrastruktur harusnya perlu memperhitungkan kemungkinan dampak atau efek yang ditimbulkan oleh kegiatan tersebut dengan cara memantau dan mencari akar permasalahan sehingga permasalahan tersebut dapat diselesaikan dan tidak menimbulkan permasalahan baru kemasa yang akan datang. Tujuan utama AMDAL adalah untuk melindungi, mengurangi, dan mencegah potensi dampak yang mungkin ditimbulkan oleh suatu proyek terhadap lingkungan dan masyarakat. Potensi dampak dianalisis dengan cara mendistribusikan kuesioner dan melakukan wawancara langsung dengan masyarakat setempat di sekitar wilayah proyek. Dari hasil data yang didapat menunjukkan persentase dampak yang dirasakan terkait fasilitas jalan sebesar 58%, gangguan arus lalu lintas sebesar 43%, kebisingan sebesar 65%, getaran sebesar 81%, pencemaran udara sebesar 59%, pencemaran air sebesar 54%, dan kontaminasi tanah sebesar 15%. Dapat disimpulkan bahwa efek yang paling besar dirasakan dari pembangunan proyek jalan lingkar kampus adalah kebisingan yaitu sebesar 65%. Berdasarkan dari hasil penelitian yang sudah dilakukan, penting untuk lebih diprioritaskan analisis mengenai dampak lingkungan pada saat sebelum dilaksanakannya proyek di suatu lingkungan, agar dampak yang ditimbulkan untuk masyarakat sekitar dapat diminimalisir sekecil mungkin.Kata KunciAnalisis dampak lingkungan (AMDAL); jalan lingkar kampus; proyek konstruksi.

Pengembangan Aplikasi Mobile Learning Konstruksi Jalan dan Jembatan Untuk Optimalisasi Pembelajaran SMK Jurusan Bangunan Kota Surakarta Kusuma, Fajar Indra; Subiyantari, Ansheila Rusyda; Dian, Imam Fahmi; Fatima, Izma
VOCATECH: Vocational Education and Technology Journal Vol 7, No 1 (2025): August
Publisher : Akademi Komunitas Negeri Aceh Barat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38038/vocatech.v7i1.207

The integration of technology in education, particularly in Vocational High Schools (SMK), is increasingly necessary to support interactive and digital-based learning. This study aims to develop a mobile-based learning media application for the subject of road and bridge construction for students in the building engineering department of SMK. Based on preliminary observations and data, 86% of the 96 respondents stated that conventional teaching methods remain ineffective, and 96% expressed the need for more interactive media. This research uses the Research and Development (RD) method with the Alessi Trollip model, consisting of three stages: (1) Planning (needs analysis of students and teachers), (2) Design (development of user interface, curriculum content, and simulation features), and (3) Development (program implementation to produce a product ready for testing). Alpha testing involving media experts, subject matter experts, and practitioners yielded a rating of "Excellent" (score 85–100%). Meanwhile, beta testing with 96 students resulted in a score of 86.10%, indicating that the application is effective in enhancing understanding of the material through 3D simulation features, demonstration videos, and interactive quizzes. In conclusion, the application is suitable for implementation as an interactive learning solution in SMK, especially for technical subjects such as road and bridge construction. The implication is that the development of similar media can serve as a reference for educators in leveraging mobile technology to improve the quality of vocational education.

Comparative Analysis of Machine Learning and Artificial Intelligence Algorithms for Pharmaceutical Demand Forecasting in Hospital Supply Chains: A Case Study at Hospital X Purnomo, Doni; Sakti, Intan Widuri; Gustiana, Iyan
VOCATECH: Vocational Education and Technology Journal Vol 7, No 1 (2025): August
Publisher : Akademi Komunitas Negeri Aceh Barat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38038/vocatech.v7i1.218

AbstractHealthcare systems in Indonesia face unique challenges due to diverse geographical landscapes and high dependency on pharmaceutical imports, resulting in complex demand forecasting requirements. This study proposes an innovative approach to pharmaceutical demand forecasting by leveraging Machine Learning (ML) and Artificial Intelligence (AI) techniques to optimize hospital supply chains. A comparative evaluation of six forecasting algorithms was conducted using 650 days of pharmaceutical transaction data from Hospital X, encompassing 374,171 dispensing events. The study compared traditional time series methods (Simple Moving Average, Weighted Moving Average, Exponential Smoothing) with advanced ML algorithms (Linear Regression, Support Vector Regression, Deep Learning LSTM). Results demonstrate that the Deep Learning model achieved superior performance with MAPE of 2.35%, representing a 34.4% improvement over traditional methods. The integrated feature engineering architecture successfully captured temporal and seasonal patterns specific to tropical healthcare environments. Implementation of the ML-based forecasting system shows potential for 25-30% reduction in safety stock requirements while maintaining 99.5% service levels, translating to significant cost savings and improved drug availability in Indonesian hospital settings AbstrakSistem pelayanan kesehatan di Indonesia menghadapi tantangan kompleks yang dipengaruhi oleh kondisi geografis yang beragam serta tingginya ketergantungan terhadap impor produk farmasi. Hal ini berdampak langsung pada kompleksitas dalam proses peramalan permintaan obat di rumah sakit. Penelitian ini mengusulkan pendekatan inovatif dalam peramalan permintaan farmasi dengan memanfaatkan teknik Machine Learning (ML) dan Artificial Intelligence (AI) guna mengoptimalkan rantai pasok rumah sakit. Evaluasi komparatif terhadap enam algoritma peramalan dilakukan menggunakan data transaksi farmasi selama 650 hari dari Rumah Sakit X, yang mencakup 374.171 data pemberian obat.Metode yang dibandingkan mencakup pendekatan deret waktu konvensional (Simple Moving Average, Weighted Moving Average, dan Exponential Smoothing) serta algoritma pembelajaran mesin tingkat lanjut (Regresi Linier, Support Vector Regression, dan Long Short-Term Memory atau LSTM). Hasil penelitian menunjukkan bahwa model Deep Learning LSTM menghasilkan performa terbaik dengan nilai Mean Absolute Percentage Error (MAPE) sebesar 2,35%, atau meningkat 34,4% dibandingkan dengan metode konvensional. Arsitektur rekayasa fitur yang digunakan mampu mengidentifikasi pola musiman dan temporal yang khas di lingkungan kesehatan tropis. Implementasi sistem peramalan berbasis ML ini menunjukkan potensi pengurangan kebutuhan safety stock sebesar 25–30%, dengan tetap mempertahankan tingkat layanan sebesar 99,5%. Temuan ini menunjukkan peluang penghematan biaya yang signifikan dan peningkatan ketersediaan obat di rumah sakit Indonesia.

Penerapan Metode Analytical Hierarchy Process (AHP) Dalam Menentukan Faktor Dominan Penyebab Keluarga Berisiko Stunting di Kabupaten Aceh Utara Zuhra, Elviza; Fadlisyah, Fadlisyah
VOCATECH: Vocational Education and Technology Journal Vol 7, No 1 (2025): August
Publisher : Akademi Komunitas Negeri Aceh Barat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38038/vocatech.v7i1.234

AbstractIn an effort to address the risk of stunting in families in the Dewantara District, this study aims to design and implement a decision support system using the Analytical Hierarchy Process (AHP) method to provide information related to the highest factors causing families at risk of stunting in the Dewantara District. The data used in this study consisted of 250 data on families at risk of stunting in the Dewantara District for the period of 2023. The data was then normalized and processed through a web-based system developed using the Python programming language and SQLite database. The use of Python as a programming language, and SQLite as a database, created an effective and efficient system for processing data, as well as supporting the analysis required in this study. The results of the analysis showed that the number of children was the dominant factor causing families at risk of stunting in the Dewantara District with a value of (26.244), then followed by maternal age (15.015), latrine factor (14.102), welfare ranking factor (12.455), drinking water source factor (2.893), and birth spacing factor (0.525). This study concludes that the Analytical Hierarchy Process (AHP) method is effective in identifying the highest risk factors for families at risk of stunting based on data on families at risk of stunting and producing a clear ranking. The results are expected to serve as a reference in formulating policies and planning more targeted intervention programs, thereby supporting early prevention efforts and a sustainable reduction in stunting prevalence.Keywords: Decision Support System, Families at Risk of Stunting, AHP, Dewantara District, PythonAbstrakDalam upaya penanganan risiko stunting pada keluarga di wilayah Kecamatan Dewantara, penelitian ini bertujuan untuk merancang dan mengimplementasikan sistem pendukung keputusan menggunakan metode Analitycal Hierarchy Process (AHP) untuk memberikan informasi terkait faktor tertinggi penyebab keluarga berisiko stunting di Wilayah Kecamatan Dewantara. Data yang digunakan dalam penelitian ini terdiri dari 250 data keluarga berisiko stunting di Wilayah Kecamatan Dewantara periode tahun 2023. Data tersebut kemudian dinormalisasi dan diolah melalui sistem berbasis web yang dikembangkan menggunakan bahasa pemrograman Python dan database SQLite. Penggunaan Python sebagai bahasa pemrograman, dan SQLite sebagai database, menciptakan sistem yang efektif dan efisien untuk mengolah data, serta mendukung analisis yang diperlukan dalam penelitian ini. Hasil analisis menunjukkan bahwa faktor jumlah anak merupakan faktor dominan penyebab keluarga berisiko stunting di Wilayah Kecamatan Dewantara dengan nilai sebesar (26,244), kemudian diikuti faktor usia ibu (15,015), faktor jamban (14,102), faktor peringkat kesejahteraan (12,455), faktor sumber air minum (2,893), dan faktor jarak kelahiran (0,525). Penelitian ini menyimpulkan bahwa metode Analitycal Hierarchy Process (AHP) efektif dalam mengidentifikasi faktor tertinggi penyebab keluarga berisiko stunting berdasarkan data keluarga berisiko stunting dan menghasilkan perangkingan yang jelas. Hasil dari penelitian ini diharapkan dapat menjadi acuan dalam merumuskan kebijakan dan merencanakan program intervensi yang lebih terarah, sehingga mendukung upaya pencegahan dini serta penurunan prevalensi stunting yang berkelanjutan.Kata Kunci: Sistem Pendukung Keputusan, Keluarga Berisiko Stunting, AHP, Kecamatan Dewantara, Python.

Model Pembelajaran Berbasis Pengalaman untuk Penguatan Karakter Anti-Korupsi Mahasiswa Vokasi Hasan,, Riza; Fitrayansyah, Fitrayansyah
VOCATECH: Vocational Education and Technology Journal Vol 7, No 1 (2025): August
Publisher : Akademi Komunitas Negeri Aceh Barat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38038/vocatech.v7i1.224

Abstract[1] Vocational higher education in Indonesia bears a strategic responsibility to produce graduates with technical competence and integrity. This research aims to develop an experiential learning model in citizenship education to strengthen anti-corruption character among students at the State Community Academy of West Aceh and to analyze its implementation challenges. A qualitative approach with case study design was applied through triangulation of data collection techniques including in-depth interviews, participatory observation, documentation study, and focused group discussions with one lecturer, twenty students, and three stakeholders. The findings reveal that the learning model integrating four theoretical frameworks (experiential learning, moral character education, situational learning, and local wisdom) effectively strengthened students' anti-corruption character. The model was implemented through three systematic phases (awareness, internalization, application) which resulted in transformation across four character dimensions: cognitive, affective, behavioral, and spiritual-cultural. The integration of Acehnese local wisdom values (trustworthiness, justice, honesty, purity, patience) provided cultural resonance that strengthened the internalization of anti-corruption values. Implementation challenges encompassed structural-institutional, pedagogical, and contextual aspects which were addressed through lecturer competency development strategies, learning time optimization, and contextualization of simulations according to study programs.Keywords:[2] experiential learning; local wisdom; anti-corruption education; vocational education; experience-based learning Abstrak[3] .Pendidikan tinggi vokasi di Indonesia memiliki tanggung jawab strategis dalam menghasilkan lulusan dengan kompetensi teknis dan karakter berintegritas. Penelitian ini bertujuan mengembangkan model pembelajaran berbasis pengalaman dalam pendidikan kewarganegaraan untuk memperkuat karakter anti-korupsi mahasiswa di Akademi Komunitas Negeri Aceh Barat serta menganalisis tantangan implementasinya. Pendekatan kualitatif dengan desain studi kasus diterapkan melalui triangulasi teknik pengumpulan data yang meliputi wawancara mendalam, observasi partisipatif, studi dokumentasi, dan diskusi kelompok terfokus terhadap satu dosen pengampu, dua puluh mahasiswa, dan tiga pemangku kepentingan. Hasil penelitian mengungkapkan bahwa model pembelajaran yang mengintegrasikan empat kerangka teoretis (experiential learning, pendidikan karakter moral, pembelajaran situasional, dan kearifan lokal) terbukti efektif memperkuat karakter anti-korupsi mahasiswa. Implementasi model dilakukan melalui tiga fase sistematis (penyadaran, penghayatan, penerapan) yang menghasilkan transformasi pada empat dimensi karakter: kognitif, afektif, behavioral, dan spiritual-kultural. Integrasi nilai-nilai kearifan lokal Aceh (amanah, adil, jujur, bersih, sabara) memberikan resonansi kultural yang memperkuat internalisasi nilai anti-korupsi. Tantangan implementasi mencakup aspek struktural-institusional, pedagogis, dan kontekstual yang dapat diatasi melalui strategi pengembangan kompetensi dosen, optimalisasi waktu pembelajaran, dan kontekstualisasi simulasi sesuai program studi. Kata Kunci: [4] experiential learning; kearifan lokal; pendidikan anti-korupsi; pendidikan vokasi; pembelajaran berbasis pengalaman

Location Entity Recognition in Instagram Captions Using Support Vector Machine Algorithm Arifa, Cut Hilma; Adek, Rizal Tjut; Afrillia, Yesy
VOCATECH: Vocational Education and Technology Journal Vol 7, No 1 (2025): August
Publisher : Akademi Komunitas Negeri Aceh Barat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38038/vocatech.v7i1.238

AbstractThe rapid advancement of digital technology has significantly influenced productivity and facilitated access to information in daily life, particularly through the widespread use of social media. Instagram is one of the most popular platforms, where text in captions often contains location-related information that can be utilized for spatial analysis. This study aims to identify and classify location entities in Instagram captions using Support Vector Machine algorithm combine with rule-based Named Entity Recognition approach. The method involved linguistic feature extraction based on explicit spatial context, data labeling, model training, and performance evaluation using standard classification metrics: accuracy, precision, recall, and f1-score. Dataset consists of 400 captions primarily written in Indonesian, though some contain mixed-language elements such as foreign term or regional dialect. The dataset is divided into 70% training data ad 30% testing data. Experimental results show that model achieved an accuracy of 90,83%, precision of 97,01%, recall of 87,84%, and f1-score of 92,90%. Evaluation of three NER rules (exact match keyword, prepositional patterns, and descriptive structures) indicates that the combination of all rules yields the highest f1-score (89%), while the best-performing individual rule is the prepositioning pattern (74%). These results demonstrated strong performance in processing varied and unstructured Instagram captions. The combinations of SVM and NER rule-based prove effective in identifying and classifying spatial information into two classes Contains Location and No Location. This approach shows potential for implementation in text-based spatial analysis systems, such as location-based recommendation systems, geographic mapping, and location-based decision support systems. AbstrakPerkembangan teknologi digital yang pesat secara signifikan berpengaruh meningkatkan produktivitas dan kemudahan akses informasi dalam kehidupan sehari-hari, salah satunya penggunaan media sosial yang semakin meluas. Instagram merupakan salah satu platform yang banyak digunakan, dimana teks dalam caption memiliki informasi terkait lokasi yang dapat dimanfaatkan untuk analisis spasial. Penelitian ini bertujuan untuk mengidentifikasi dan mengklasifikasikan entitas lokasi dalam caption Instagram menggunakan algoritma Support Vector Machine (SVM) dengan pendekatan Named Entity Recognition (NER) rule-based. Metode yang digunakan meliputi ekstraksi fitur berbasis linguistik dengan konteks spasial eksplisit, lebelisasi data, pelatihan model, serta evaluasi kinerja model menggunakan matriks klasifikasi: akurasi, presisi, recall dan f1-score. Dataset terdiri dari 400 caption umumnya berbahasa Indonesia, namun terdapat unsur bahasa campuran seperti istilah asing atau bahasa daerah. Fokus utama penelitian diarahkan pada pengolahan dan pemahaman teks berbahasa Indonesia. Dataset dibagi menjadi 70% data training dan 30% data testing. Hasil pengujian menunjukkan bahwa model mendapatkan akurasi sebesar 90,83%, presisi 97,01%, recall 87,84% dan f1-score 92,90%. Evaluasi terhadap tiga rule NER (exact match keyword, pola preposisi, dan struktur deskriptif) menunjukkan bahwa pengenalan entitas berdasarkan gabungan seluruh rule memberikan f1-score tertinggi (89%), sementara rule individual terbaik adalah pola preposisi (74%). Nilai ini menunjukkan kinerja yang cukup baik dalam pengolahan caption Instagram yang variatif dan tidak terstruktur. Kombinasi metode SVM dan NER rule-based terbukti efektif dalam mengidentifikasi dan mengklasifikasi informasi spasial dalam dua kelas Contain Location dan No Location. Pendekatan ini berpotensi diterapkan pada sistem analisis spasial berbasis teks, seperti sistem rekomendasi lokasi, pemetaan geografis, dan pendukung keputusan berbasis lokasi.

Perancangan SPK Rekomendasi Smartphone di Toko Evi Ponsel Dengan Kombinasi AHP dan MFEP Daryanti, Daryanti; Yusda, Riki Andri; Sirait, Zulkarnain
VOCATECH: Vocational Education and Technology Journal Vol 7, No 1 (2025): August
Publisher : Akademi Komunitas Negeri Aceh Barat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38038/vocatech.v7i1.230

AbstractThe rapid advancement of technology has led to an increase in smartphone demand, but the wide variety of specifications and prices makes it difficult for consumers to make the right choice. This study aims to design a Decision Support System (DSS) that provides optimal smartphone recommendations for customers at Evi Ponsel Store. The system was developed using a combination of the Analytical Hierarchy Process (AHP) and the Multi Factor Evaluation Process (MFEP). AHP was used to determine the weight of each criterion, while MFEP was used to evaluate and rank smartphone alternatives. The criteria considered include price, RAM, internal memory, camera, battery, screen size, and OS version. The results show that price is the most influential factor, indicating that customers prioritize affordability. Based on MFEP results, the most recommended smartphone is Redmi 14C, followed by Redmi 13C and Infinix Hot 50. The system effectively provides efficient, objective, and user-aligned recommendations. AbstrakPerkembangan teknologi yang pesat telah mendorong peningkatan permintaan terhadap smartphone, namun beragamnya spesifikasi dan harga membuat konsumen kesulitan dalam menentukan pilihan. Penelitian ini bertujuan untuk merancang sistem pendukung keputusan (SPK) yang dapat memberikan rekomendasi smartphone terbaik kepada konsumen di Toko Evi Ponsel. Sistem dirancang menggunakan kombinasi metode Analytical Hierarchy Process (AHP) dan Multi Factor Evaluation Process (MFEP). AHP digunakan untuk menentukan bobot masing-masing kriteria, sementara MFEP digunakan untuk mengevaluasi dan menentukan peringkat alternatif smartphone. Kriteria yang digunakan meliputi harga, RAM, memori internal, kamera, baterai, ukuran layar, dan versi OS. Data diperoleh melalui observasi dan wawancara langsung dengan pihak toko untuk memastikan bahwa kriteria dan alternatif yang dipilih relevan dengan kebutuhan pasar. Hasil penelitian menunjukkan bahwa kriteria harga memiliki bobot tertinggi, menunjukkan bahwa aspek harga menjadi pertimbangan utama konsumen. Berdasarkan metode MFEP, smartphone yang paling direkomendasikan adalah Redmi 14C, diikuti oleh Redmi 13C dan Infinix Hot 50. Sistem ini terbukti mampu memberikan rekomendasi secara efisien, objektif, dan sesuai dengan preferensi pengguna, serta dapat menjadi alat bantu pengambilan keputusan yang bermanfaat bagi pihak toko maupun konsumen dalam menentukan produk terbaik.

Analisa Kegagalan Elevator Nerak Tipe WB 250 Untuk Mengangkut Sulfur Granulation Di PT. Medco E&P Malaka Hamdani, Hamdani; Fakhriza, Fakhriza; Saputra, Hendra; Bahri, Samsul; Saputra, Edi
VOCATECH: Vocational Education and Technology Journal Vol 7, No 1 (2025): August
Publisher : Akademi Komunitas Negeri Aceh Barat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38038/vocatech.v7i1.233

AbstractPT. Medco EP Malaka operates one unit of the Nerak WB 250 elevator located in the Sulfur Granulation Unit (SGU), which functions as a material handling system for transferring granulated sulfur from the steel belt conveyor to the sulfur silo. This elevator is driven by an electric motor and gearbox connected to the driver idler shaft (head pulley). The driver idler rotates the rubber chain equipped with buckets containing sulfur granules, allowing the material to be transported vertically to the sulfur silo. However, frequent failures have occurred in several elevator components such as the rubber chain, snap ring, bucket rod, clamping sleeve, chain bushing, bucket, tension idler, as well as the upper and lower idlers. To analyze these failures, the Root Cause Analysis (RCA) method was employed using the Why-Why-Why Analysis (W3A) approach, which is a commonly used method at PT. Medco EP Malaka. Based on field observations and W3A analysis results, the main causes of failure were identified as misalignment in the elevator system due to worn idler bushings, detached snap rings, and malfunctioning proximity sensors—further aggravated by suboptimal preventive and predictive maintenance activities. Additional contributing factors include clumped sulfur accumulation, which increases the system load. Based on these findings, corrective actions were taken and improvements were made to strengthen both the Predictive Maintenance (PdM) and Preventive Maintenance (PM) programs in order to ensure the reliability of the NERAK WB 250 elevator system at the SGU.Keywords:Elevator Nerak; Sulfur Granulation; Maintenance; Root Cause Analysis (RCA) AbstrakPT. Medco EP Malaka mempunyai 1 unit mesin elevator Nerak WB 250 yang ada pada Sulfur Granulation Unit (SGU) yang berfungsi sebagai alat pemindah sulfur yang sudah berbentuk granul dari steel belt conveyor menuju sulfur silo. Elevator ini digerakkan menggunakan motor listrik beserta gearbox yang terhubung ke shaft driver idler (head pulley). Driver idler memutar rubber chain yang dilengkapi dengan bucket berisi sulfur granul sehingga material dipindahkan secara vertikal menuju sulfur silo. Namun, sering terjadi kerusakan pada komponen elevator seperti rubber chain, snap ring, bucket rod, clamping sleeve, chain bushing, bucket, tension idler, upper dan lower idler. Untuk menganalisis kegagalan tersebut, digunakan metode Root Cause Analysis (RCA) dengan pendekatan Why-Why-Why Analysis (W3A), yang merupakan metode yang lazim digunakan di PT. Medco EP Malaka. Berdasarkan temuan lapangan dan hasil analisa W3A, diketahui bahwa penyebab utama kegagalan adalah misalignment pada sistem elevator akibat ausnya bushing idler, lepasnya snap ring, serta tidak berfungsinya proximity sensor, yang diperburuk oleh kurang optimalnya kegiatan preventive dan predictive maintenance. Faktor lain seperti tumpukan sulfur yang menggumpal dan menyebabkan beban lebih juga turut berkontribusi terhadap kegagalan sistem. Berdasarkan hasil analisa tersebut, dilakukan tindakan perbaikan serta penguatan program Predictive Maintenance (PdM) dan Preventive Maintenance (PM) agar keandalan sistem elevator NERAK tipe WB 250 di SGU dapat terjaga dengan baikKata Kunci: Pemilihan tindakan; Perawatan; Root Cause Analysis (RCA)

Clustering Village Zones Based On Nutritional Status of Toddlers Using The K-Medoids Method Amelia, Ulva; Yunizar, Zara; Rosnita, Lidya
VOCATECH: Vocational Education and Technology Journal Vol 7, No 1 (2025): August
Publisher : Akademi Komunitas Negeri Aceh Barat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38038/vocatech.v7i1.223

AbstractIn order to improve the effectiveness of nutrition intervention planning in the operational area of the Kuta Blang Health Center, this study aims to develop a village zoning model based on the nutritional status of toddlers using the K-Medoids algorithm. The primary data includes the distribution of nutritional statuses (good, overnutrition, undernutrition, severe malnutrition, obesity) from 41 villages collected during the January–December 2023 period. Data were normalized and processed using a web-based system developed in PHP and MySQL. The clustering process resulted in five zones: Green (optimal nutrition), Yellow (within acceptable limits), Orange (requires monitoring), Red (worst condition), and Purple (critical challenges). Field validation showed strong alignment between clustering results and real conditions. This study concludes that the K-Medoids method can accurately group villages based on nutrition data and produce a practical zoning map. The resulting zones allow for more efficient resource allocation and targeted intervention, especially in Red and Purple zones. Future improvements may include incorporating socioeconomic and healthcare access variables for more comprehensive analysis. AbstrakDalam rangka meningkatkan efektivitas perencanaan intervensi gizi di wilayah kerja Puskesmas Kuta Blang, penelitian ini bertujuan untuk mengembangkan model zonasi desa berdasarkan status gizi balita menggunakan algoritma K-Medoids. Data primer meliputi distribusi status gizi balita (gizi baik, gizi lebih, gizi kurang, gizi buruk, obesitas) dari 41 desa yang dikumpulkan selama periode Januari–Desember 2023. Data tersebut dinormalisasi dan diolah dalam sistem berbasis web menggunakan bahasa pemrograman PHP dan database MySQL. Proses klasterisasi menghasilkan lima zona: Hijau (gizi optimal), Kuning (masih dalam batas wajar), Oranye (perlu pemantauan), Merah (terburuk), dan Ungu (tantangan signifikan). Validasi lapangan menunjukkan kesesuaian tinggi antara hasil klasterisasi dan kondisi nyata. Penelitian ini menyimpulkan bahwa metode K-Medoids mampu mengelompokkan desa secara akurat berdasarkan data gizi dan menghasilkan peta zonasi yang aplikatif. Zona yang dihasilkan memungkinkan alokasi sumber daya dan intervensi yang lebih terarah, khususnya pada zona Merah dan Ungu. Perbaikan di masa depan dapat mencakup integrasi variabel sosial ekonomi dan akses layanan kesehatan untuk analisis yang lebih komprehensif

Home Page

OAI Link

Editorial Team

Contact

Reviewer

Google Scholar

Contact Name
Tanzir Masykar

Contact Email
tanzir@aknacehbarat.ac.id

Phone
+6285277752225

Journal Mail Official
vocatech@aknacehbarat.ac.id

Editorial Address
Komplek STTU, Jl. Alue Peunyareng, Ujong Tanoh Darat, Meureubo, West Aceh Regency, Aceh 23681

Location
Kab. aceh barat,

Aceh

INDONESIA

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Home Page

OAI Link

Editorial Team

Contact

Reviewer

Google Scholar

Contact Name Tanzir Masykar

Contact Email tanzir@aknacehbarat.ac.id

Phone +6285277752225

Journal Mail Official vocatech@aknacehbarat.ac.id

Editorial Address Komplek STTU, Jl. Alue Peunyareng, Ujong Tanoh Darat, Meureubo, West Aceh Regency, Aceh 23681

Location Kab. aceh barat, Aceh INDONESIA

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Contact Name
Tanzir Masykar

Contact Email
tanzir@aknacehbarat.ac.id

Phone
+6285277752225

Journal Mail Official
vocatech@aknacehbarat.ac.id

Editorial Address
Komplek STTU, Jl. Alue Peunyareng, Ujong Tanoh Darat, Meureubo, West Aceh Regency, Aceh 23681

Location
Kab. aceh barat,

Aceh

INDONESIA