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ANALISIS PUSHOVER TERHADAP RESPON STRUKTUR DENGAN MENGGUNAKAN BASE ISOLATOR Fitry Hasdanita; Mochammad Afifuddin; Muttaqin Muttaqin
Jurnal Arsip Rekayasa Sipil dan Perencanaan Vol 1, No 1 (2018): Jurnal Arsip Rekayasa Sipil dan Perencanaan
Publisher : Prodi Magister Teknik Sipil Unsyiah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24815/jarsp.v1i1.10374

Abstract

The earthquake-resistant building is a concept in construction technology that is in line with technology evolution. The idea of this earthquake-resistant concept is to reduce the seismic force that might work to the building structure instead of strengthening the structure itself. The structural component for reducing the earthquake force is called as a base isolator or seismic isolation. During seismic loading, this component is expected to accept and minimize the earthquake forces at a certain level without any significant damage to structure. This research is conducted to evaluate the response of the structure with base isolator. Then, the influence of base isolator on building structure is justified. Two (2) different types of structures, fixed base and base- isolated structure with a variety of post-yield stiffness (K2), were developed. The used type of base isolator is Lead Rubber Bearing (LRB). The analysis is conducted in accordance with pushover analysis method using SAP2000 v.19 program. The result suggested that the building structure with base isolator extends the natural period of the structure up to 1,380 times. The interstory drift of the base-isolated structure is smaller than the fixed base structure. The use of base isolator reduces the top displacement to an average of 21.93% for x- and 18.506% for y-direction. The overall structure performance evaluation of fixed base and base-isolated structures is at Damage Control level.
EVALUASI SIMPANGAN ANTAR LANTAI (INTER STORY DRIFT) PADA GEDUNG BERTINGKAT DENGAN METODE RIWAYAT WAKTU Fitry Hasdanita; Delfian Masrura; Fachruddin Fachruddin
Jurnal Teknik Sipil dan Teknologi Konstruksi Vol 9, No 1 (2023): Jurnal Teknik Sipil dan Teknologi Konstruksi
Publisher : Universitas Teuku Umar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35308/jts-utu.v9i1.7239

Abstract

Aceh salah satu provinsi paling barat yang berada pada zona tektonik yang sangat aktif karena ada sembilan lempeng kecil lainnya yang membentuk jalur komplek selain tiga lempeng besar dunia. Peristiwa gempa yang terjadi di Aceh secara horizontal dan vertikal terjadi pada 26 Desember 2004 sebesar 9,2 Mw, 11 April 2012 dengan 8,6 Mw, 23 januari 2013 dengan 6,1 Mw dan Desember 2016 yang menyebabkan kerusakan serius pada bangunan dengan berbagai tipe pola keruntuhan. Ini merupakan faktor terpenting untuk evaluasi kerusakan bangunan dan desain seismik jika terjadi gempa. Simpangan antar lantai (inter story drift) menjadi faktor utama kerusakan bangunan akibat gempa. Nilai simpangan pada bangunan juga sebagai acuan untuk menentukan tingkat kerusakan pada suatu bangunan akibat gempa berdasarkan perencanaan berbasis kinerja. Penelitian ini bertujuan untuk menganalisis simpangan antar lantai (inter story drift) pada bangunan bertingkat untuk mengetahu tingkat kerusakan bangunan akibat gempa. Hal ini bertujuan untuk mengantisipasi atau melakukan upaya mitigasi pada saat terjadi gempa sehingga menguruangi kerugian materian dan korban jiwa. Hasil penelitian menunjukkan simpangan antar lantai maksimum sebesar 0.086 m akibat riwayat gempa Irpinia pada lantai 2 dalam arah X. Simpangan antar lantai maksimum arah Y sebesar 0,056 akibat gempa Irpinia. Nilai simpangan antar lantai maksimum memenuhi persyaratan SNI-1726-2019 tentang Tata Cara Perencaan Ketahanan Gempa Untuk Struktur Banguanan Geudng dan Non Gedung yaitu 0,548 m. Sehingga Gedung DPRA Kota Banda Aceh aman terhadap kegagalan simpangan antar lantai.<img 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
Perlakuan Joint Balok Kolom Standar PBI 1971 Setelah Perkuatan Awal Dengan Ferrocement Delfian Masrura; Fitry Hasdanita; Muhammad Ikhsan; Aulia Rahman
Jurnal Teknik Sipil dan Teknologi Konstruksi Vol 9, No 1 (2023): Jurnal Teknik Sipil dan Teknologi Konstruksi
Publisher : Universitas Teuku Umar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35308/jts-utu.v9i1.7145

Abstract

Sebuah konstruksi bangunan terdiri dari beberapa elemen, balok dan kolom adalah diantaranya. Elemen tersebut berfungsi sebagai penyangga beban konstruksi lainnya dan merupakan  salah satu komponen struktur utama pada sebuah bangunan. Untuk merencanakan bangunan yang tahan gempa, maka daerah yang perlu diperhatikan adalah pada titik pertemuan antara balok dan kolom agar energinya dapat terdisipasi dengan baik. Jika terjadi kegagalan pada daerah joint tersebut, maka  komponen lainnya akan merasakan dampaknya secara langsung. Maka, tujuan penelitian ini dilakukan adalah menganalisa kemampuan elemen joint balok kolom sebuah struktur bangunan yang dirancang sesuai dengan PBI 1971 yang sudah diberikan perkuatan sejak awal menggunakan ferrocement dalam menahan beban siklik yang diterima. Benda uji dirancang dengan menggunakan mutu beton sebesar 24,80 MPa dengan panjang balok 120 cm, lebar 30 cm dan tinggi 40 cm, serta kolom persegi bersisi 30 cm dengan tinggi 200 cm. Dimensi tulangan utama yang digunakan adalah 8Ø14 mm dan tulangan sengkang Ø10-100 mm. Terhadap benda uji diberikan pembebanan siklik, yang diberikan pada ujung balok dengan displacement masing-masing sebesar 0,75 mm; 1,5 mm; 3 mm; 6 mm; 12 mm; 24 mm dan pada akhirnya diberikan beban monotonik, yaitu pada benda uji diberikan beban sampai hancur. Diperoleh hasil setelah pengujian yaitu benda uji PBI 1971 dengan perkuatan menggunakan ferrocement sejak awal mampu menahan beban tekan sampai menghasilkan beban siklus yang terbesar adalah 7,71 tf, sedangkan untuk beban tarik yang paling besar diperoleh adalah 7,48 tf. Untuk displacement maksimum yang diperoleh adalah sebesar 48 mm. Hasil ini didapatkan pada saat dilakukan pembebanan secara monotonik terhadap benda uji tersebut.
Penanaman Mangrove Sebagai Upaya Perluasan Ekosistem Pesisir di Peunaga Cut Ujong, Aceh Barat Eka Lisdayanti; Nurul Najmi; Rahmawati Rahmawati; Fitry Hasdanita; Delfian Masrura
Jurnal ABDINUS : Jurnal Pengabdian Nusantara Vol 8 No 1 (2024): Volume 8 Nomor 1 Tahun 2024
Publisher : Universitas Nusantara PGRI Kediri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29407/ja.v8i1.21084

Abstract

Damage to mangroves on the West Aceh coast due to the disaster tsunami and the increasing utilization of economic activities towards the beach area makes mangrove planting activities necessary. Service activities aim to support the benefits of conservation and expansion of mangrove ecosystems on the Coas of Peunaga Cut Ujong, Meurebo District, West Aceh Regency. This planting activity is a collaborative activity between industry players, academics, and the surrounding community which was initiated by PT MIFA Bersaudara as a form of concern for the environment and concrete action in contributing to coastal ecosystem conservation, especially for achieving the SDGs. The types of mangroves planted were Rhizophora apiculata and Rhizophora mucronate. This planting uses a planting method with artificial regeneration which involves planting seeds, propagules, or mangrove seedlings by moving the seedlings to a new location. Mangrove planting activities in Peunaga Cut Ujong managed to get attention and attention from the village community. Not only involved directly in mangrove planting activities but also committed to the maintenance and monitoring of the planted mangroves. In addition, the success of mangrove planting is also evident from the low mortality rate (5%) of the seedlings. The addition of more leaves, height, and mangrove roots that have begun to appear in some mangrove stands was observed seven months after planting.
Edukasi Pembibitan Propagule Mangrove Berbasis Konservasi sebagai Peluang Usaha Masyarakat Peunaga Cut Ujong, Aceh Barat Lisdayanti, Eka; Najmi, Nurul; Rahmawati, Rahmawati; Wahyuni, Sri; Hasdanita, Fitry; Masrura, Delfian
Jurnal Pengabdian Pada Masyarakat Vol 9 No 2 (2024): Jurnal Pengabdian Pada Masyarakat
Publisher : Universitas Mathla'ul Anwar Banten

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30653/jppm.v9i2.762

Abstract

Penanaman dan penyulaman bibit mangrove untuk perluasan ekosistem pesisir telah dilakukan sejak tahun 2022 di Gampong Peunaga Cut Ujong Aceh Barat. Partisipasi masyarakat pada kegiatan tersebut mendorong dilakukannya edukasi pembibitan mangrove agar mengetahui potensi peluang usaha berbasis konservasi bagi masyarakat pesisir. Juga untuk memaksimalkan fungsi ekosistem mangrove utamanya untuk peningkatan ekonomi. Kegiatan pengabdian ini bertujuan untuk memberikan edukasi berupa sosialisasi dan demonstrasi secara langsung penanaman propagule mangrove dari jenis Rhizophora apiculata, R. mucronata dan Bruguiera gymnorrhiza. Tahapan pelaksanaan kegiatan melibatkan masyarakat mulai dari tahap persiapan, penanaman dan evaluasi. Hasil evaluasi menunjukkan bahwa peluang usaha penanaman propagule mangrove dapat dilakukan dengan persentase tingkat kematian bibit mangrove 0% sampai 39 hari pasca penanaman. Keikutsertaan dan keaktifan masyarakat secara langsung dalam pengabdian ini menentukan tingkat keberhasilan penanaman mangrove. Planting and transplanting mangrove seedlings for the expansion of coastal ecosystems has been carried out since 2022 in Gampong Peunaga Cut Ujong, West Aceh. Community participation in these activities encourages mangrove nursery education to find conservation-based business opportunities in coastal communities. Also, to maximize the potential of the mangrove ecosystem, especially for economic improvement. This service activity aims to provide education in the form of socialization and direct demonstration of mangrove propagule planting of Rhizophora apiculata, R. mucronata, and Bruguiera gymnorrhiza species. The stages of activity implementation involve the community starting from the preparation, planting, and evaluation stages. The evaluation results show that the business opportunity of planting mangrove propagules can be done with a percentage of mangrove seedling mortality rate of 0% until 39 days after planting. The participation and activeness of the community directly in this service determines the success rate of mangrove planting.
Bimbingan Program Magang Industri Bersertifikat Studi Kasus GIS Implementation Intern Fachruddin, Fachruddin; Yusra, Andi; Hasdanita, Fitry; Ikhsan, Muhammad; Masrura, Delfian; Sanusi; Alimuddin; Fadhilah, Nurul
Inovasi Teknologi Masyarakat (INTEKMAS) Vol. 2 No. 1 (2024): June 2024
Publisher : Wadah Inovasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53622/intekmas.v2i1.263

Abstract

Infrastructure memberikan pengalaman berharga dalam membimbing dan mendukung mahasiswa MSIB (Magang Studi Independen Bersertifikat) selama penempatan magang. Program magang ini bertujuan untuk menjembatani kesenjangan antara pengetahuan akademis dan praktik industri, sehingga memungkinkan mahasiswa untuk mendapatkan pengalaman praktis di bidang pengembangan infrastruktur. Tanggung Jawab Utama: Memberi saran dan bimbingan kepada mahasiswa MSIB selama program magang. Memberikan panduan tentang aspek teknis yang terkait dengan proyek infrastruktur. Memfasilitasi komunikasi antara mahasiswa, mentor magang, dan universitas peserta mahasiswa. Memantau kemajuan mahasiswa dan memastikan keberhasilan penyelesaian tujuan magang. Mengevaluasi kinerja mahasiswa dan memberikan umpan balik kepada universitas. Pembelajaran Utama: Memperoleh wawasan tentang industri pembangunan infrastruktur khususnya terkait GIS Implementation Intern di Indonesia. Mengembangkan keterampilan dalam koordinasi program, bimbingan, dan komunikasi. Meningkatkan pemahaman tentang tantangan dan peluang yang dihadapi oleh mahasiswa MSIB yang sedang bertransisi dari dunia akademis ke dunia kerja. Secara keseluruhan, peran sebagai pembimbing program magang di PT. Nusantara Infrastructure terbukti menjadi pengalaman berharga yang mendorong pengembangan profesional dan berkontribusi pada keberhasilan integrasi pengetahuan dan skil mahasiswa ke dalam dunia kerja.
Strengthening Coastal Construction Safety Through Community-Based OHS Socialization, Education, and Training in West Aceh Zakia, Zakia; Sariani, Meylis; Yuri Salena, Inseun; Rafshanjani, M.Arrie; Febrianty, Dian; Hasdanita, Fitry
Jurnal Karya Abdi Masyarakat Vol. 8 No. 2 (2024): Jurnal Karya Abdi Masyarakat
Publisher : LPPM Universitas Jambi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22437/jkam.v8i2.37428

Abstract

The implementation of Occupational Health and Safety (OHS) in port embankment construction is crucial for improving the security and durability of coastal infrastructure. The main goal of OHS is to prevent, reduce, or eliminate workplace accidents, which is particularly important given the potentially serious consequences of such incidents. This research focuses on the distribution and training of OHS practices, particularly stressing the proper use of personal protective equipment (PPE) to reduce accident risks. The program involved forming two groups of five people each, who participated in a structured socialization and training session. To assess the effectiveness of the program, participants were given pre- and post-activity questionnaires to measure their knowledge of OHS and safety building principles related to port embankment construction. The findings show that applying OHS principles led to significant improvements in safety measures and a reduction in workplace accidents. However, challenges persist, especially regarding the local community’s comprehension of OHS protocols and consistent PPE usage. Ongoing training and more stringent supervision are recommended to improve OHS implementation further. These enhancements would ensure the safety and well-being of workers on construction sites more effectively.
Perbedaan Dimensi Benda Uji Terhadap Kuat Tekan Beton Erliana, Hilma; Yusra, Cut Liliiza; Dwinta, Ade; Hasdanita, Fitry
VOCATECH: Vocational Education and Technology Journal Vol 6, No 1 (2024): October
Publisher : Akademi Komunitas Negeri Aceh Barat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38038/vocatech.v6i1.182

Abstract

AbstractConcrete is one of the most widely used construction materials in various types of buildings and infrastructure. One of the critical factors in the quality of concrete is its compressive strength, which is measured through testing using cube- or cylinder-shaped specimens. Although testing standards have been established, the test results between these two specimen shapes often show significant differences. Therefore, this study aims to analyze the influence of specimen dimensions and shapes on the results of concrete compressive strength tests. The research was conducted at the Foundation Construction, Concrete, and Road Paving Laboratory at the Aceh Barat State Community Academy, using materials such as Andalas Portland cement, concrete sand, gravel, and water from the laboratory. The tests were performed according to SNI methods on cube and cylinder specimens at different concrete ages (7, 14, and 28 days). The results showed that the average compressive strength of both cylinder and cube samples increased with the age of the concrete. At 28 days, the average compressive strength of the cylinder was 17.243 MPa, while the cube reached 20.821 MPa. The ratio between the compressive strengths of the cylinder and the cube (f'c/f'ck) ranged from 0.825 to 0.837, indicating that the cylinder's compressive strength was about 83% of the cube's. The difference in compressive strength between the cylinder and cube specimens is influenced by stress distribution during testing, which is affected by the shape and dimensions of the specimens. Meanwhile, the compressive strength ratio between these two specimen shapes remained stable across different concrete ages, suggesting that the difference in specimen shape consistently affects the compressive strength test results.Keywords:  Specimen dimensions, Compressive strength, Cube, Cylinder AbstrakBeton merupakan salah satu bahan konstruksi yang paling sering digunakan dalam berbagai jenis bangunan dan infrastruktur. Salah satu faktor penting dalam kualitas beton adalah kuat tekan, yang diukur melalui pengujian menggunakan benda uji berbentuk kubus atau silindris. Meskipun standar pengujian telah ditetapkan, hasil uji antara kedua bentuk benda uji ini sering menunjukkan perbedaan signifikan. Oleh karena itu, penelitian ini bertujuan untuk menganalisis pengaruh dimensi dan bentuk benda uji terhadap hasil pengujian kuat tekan beton. Penelitian ini dilakukan di Laboratorium Konstruksi Pondasi, Beton, dan Pengaspalan Jalan pada Akademi Komunitas Negeri Aceh Barat, menggunakan material seperti semen Portland Andalas, pasir beton, split, dan air dari laboratorium tersebut. Pengujian dilakukan dengan menggunakan metode SNI untuk benda uji kubus dan silinder pada berbagai usia beton (7, 14, dan 28 hari).  Hasil menunjukkan bahwa kuat tekan rata-rata sampel berbentuk silinder dan kubus meningkat seiring dengan bertambahnya umur beton. Pada umur 28 hari, kuat tekan rata-rata silinder adalah 17,243 MPa, sementara kubus mencapai 20,821 Mpa. Rasio antara kuat tekan silinder dan kubus (f'c/f'ck) berada pada kisaran 0,825 hingga 0,837, menunjukkan bahwa kuat tekan silinder sekitar 83% dari kuat tekan kubus. Perbedaan kuat tekan menunjukkan bahwa antara benda uji silinder dan kubus dipengaruhi oleh distribusi tegangan selama pengujian, yang disebabkan oleh perbedaan bentuk dan dimensi sedangkan Rasio kuat tekan antara kedua bentuk benda uji ini tetap stabil pada berbagai usia beton, menunjukkan bahwa perbedaan bentuk benda uji memberikan pengaruh yang konsisten terhadap hasil uji kuat tekan.Kata Kunci:Dimensi benda uji, Kuat tekan, kubus, silinder 
Evaluasi Kinerja Jaringan Daerah Irigasi (D.I) Jeuram Kabupaten Nagan Raya Hasdanita, Fitry; Dinda, Raina Parmitalia
Jurnal Teknik Sipil dan Teknologi Konstruksi Vol 10, No 2 (2024): JURNAL TEKNIK SIPIL DAN TEKNOLOGI KONSTRUKSI
Publisher : Universitas Teuku Umar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35308/jts-utu.v10i2.11596

Abstract

Evaluation of irrigation systems will become more important in improving the performance of irrigation networks to achieve optimal productivity in the context of increasing food needs and competition for limited water resources. Performance assessment is used to ascertain the current state of schemes relative to benchmarks and helps uncover the underlying reasons for poor performance, thereby suggesting opportunities for improvement. two main approaches to performance evaluation are considered: how well the service is delivered and irrigation outcomes in terms of efficiency and productivity of water resource use. This research aims to obtain the performance of the D.I Jeuram network, understand the problem of water loss, and improvement efforts that will be made to address the problem of rice field water needs. Apart from that, to increase Operation and Maintenance activities at D.I Jeuram. The research method was carried out using a survey and inventory of D.I. Jeuram using direct observation, guided by PUPR Ministerial Decree No. 12/PRT/M/2015. Based on the results of observations and inventory, irrigation performance evaluations were then carried out to assess physical infrastructure, plant productivity, supporting facilities, personnel organization and documentation. The results of D.I Jeram's performance assessment were 59.32% in the poor category and really need attention. This condition affects plant productivity. The cross-section of the primary channel is still able to accommodate water discharge to flow to the rice fields. The condition of the primary channel is in the category of moderate to severe damage, as well as uncontrolled sedimentation. This also affects plant productivity, so it is necessary to repair, operate and maintain irrigation either routinely or periodically.
SOSIALISASI DAN PENANAMAN MANGROVE SEBAGAI UPAYA PERBAIKAN LINGKUNGAN DAN PENCEGAHAN ABRASI DI DESA PEUNAGA CUT UJONG Yusuf, Alfisyahrin; Masrura, Delfian; Hasdanita, Fitry; Kasaf, Michel; Arief Diana, Muhammad; Rizqi Maysyarah Hadi, Tjut; Lisdayanti, Eka; Rahmawati; Yunisa Fahmi, Nadya; Najmi, Nurul
Jurnal Masyarakat Berdikari dan Berkarya (Mardika) Vol 3 No 2 (2025): Jurnal Masyarakat Berdikari dan Berkarya (MARDIKA)
Publisher : Fakultas Teknik, Universitas Samudra

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55377/mardika.v3i2.11678

Abstract

This community service initiative aims to enhance awareness and encourage active participation among the residents of Peunaga Cut Ujong Village, Meureubo Subdistrict, West Aceh Regency, in environmental conservation efforts through mangrove planting. Located in a coastal area vulnerable to erosion and exposed to air pollution due to coal-burning activities, this village faces significant environmental challenges. Employing an educational and participatory approach, the program involved raising awareness about the ecological functions of mangroves and conducting direct planting activities in a mangrove forest area approximately 100 meters from the shoreline. The outcomes of the initiative indicated a positive response from the community, demonstrated by increased environmental awareness and active involvement in conservation efforts. Mangrove planting is expected to function as a coastal protection barrier, an air pollutant absorber, and a potential site for ecotourism and aquaculture development. This initiative highlights the importance of synergy between academia, the local community, and the industrial sector in creating sustainable environmental solutions. Continuous evaluation and the replication of similar programs are strongly recommended to enhance their long-term impact.