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All Journal Jurnal Pendidikan Teknik Mesin Geological Engineering E-Journal Fountain of Informatics Journal BAREKENG: Jurnal Ilmu Matematika dan Terapan Bisma: Jurnal Bisnis dan Manajemen MATRIK : Jurnal Manajemen, Teknik Informatika, dan Rekayasa Komputer INTEK: Jurnal Penelitian Building of Informatics, Technology and Science Jurnal Optimalisasi Scholastica : Jurnal Pendidikan dan Kebudayaan Jurnal Ilmu Pendidikan Islam Tadris: Jurnal Pendidikan Islam Buletin Pengabdian Journal of Global Engineering Research & Science (J-GERS) Ta'amul: Journal of Islamic Economics
Lutfi Hakim
Program Studi Teknik Geologi Universitas Diponegoro, Semarang
Religion Agriculture, Biological Sciences & Forestry Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Mathematics Mechanical Engineering Physics Public Health Social Sciences Transportation Other

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Prediksi Tinggi Gelombang dan Kecepatan Angin di Pantai Menggunakan Metode BiGRU Putri Oktavia, Nabiilah; Hakim, Lutfi; Novitasari , Dian Candra Rini; Asyhar, Ahmad Hanif; Setiawan, Fajar
Fountain of Informatics Journal Vol. 10 No. 1 (2025): Mei
Publisher : Universitas Darussalam Gontor

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21111/fij.v10i1.13018

Abstract

Abstrak Indonesia terletak di antara Samudera Pasifik dan Samudera Hindia yang membuat Indonesia menjadi pusat jalur perdagangan internasional. Pada lokasi desa Karangduwur yang berlokasi di Jawa Tengah memiliki potensi ekonomi maritim yang kuat tetapi juga memiliki risiko cuaca yang besar juga. Oleh karena itu tujuan dari penelitian ini yaitu untuk memprediksi tinggi gelombang dan kecepatan angin.   Metode prediksi yang digunakan pada penelitian kali ini adalah BiGRU (Bidirectional Gated Recurrent Unit) karena BiGRU memiliki hasil prediksi yang baik dibanding metode deep learning yang lain. Penelitian ini menggunakan data time series    yang berisi data tinggi gelombang dan kecepatan angin. Data unsur cuaca diambil per 12 jam dari bulan Januari 2021 – bulan April 2024. Metode BiGRU dapat digunakan dalam memprediksi cuaca maritim dengan fungsi aktivasi paling optimal untuk prediksi tinggi gelombang dan kecepatan angin ialah Relu, serta untuk prediksi tinggi gelombang dan kecepatan angin memiliki jumlah Batch Size yang optimal terdapat pada Batch Size 16. Dengan hasil nilai MAPE untuk prediksi ketinggian gelombang sebesar 1.6434% dan untuk prediksi kecepatan angin sebesar 0.6560%. Nilai MAPE pada model BiGRU memiliki nilai yang kecil dimana kurang dari 10% maka model BiGRU dikatakan sangat baik untuk prediksi pada data cuaca maritim. Kata kunci: Cuaca, Kecepetan angin, Tinggi gelombang, BiGRU   Abstract [Prediction of Wave Height and Wind Speed ​​on the Coast Using the BiGRU Method] Indonesia is located between the Pacific Ocean and the Indian Ocean, which makes it the center of international trade routes. Karangduwur village, located in Central Java, has strong maritime economic potential but also has great weather risks. Therefore, the purpose of this research is to predict wave height and wind speed.   The prediction method used in this research is BiGRU (Bidirectional Gated Recurrent Unit) because BiGRU has good prediction results compared to other deep learning methods. This research uses time series data containing wave height and wind speed data. Weather element data is taken per 12 hours from January 2021 - April 2024. The BiGRU method can be used in predicting maritime weather with the most optimal activation function for predicting wave height and wind speed is Relu, and for predicting wave height and wind speed, the optimal number of Batch Size is Batch Size 16. With the results of the MAPE value for wave height prediction of 1.6434% and for wind speed prediction of 0.6560%. The MAPE value in the BiGRU model has a small value which is less than 10%, so the BiGRU model is said to be very good for prediction on maritime weather data. Keywords: Weather, Wind speed, Wave height, BiGRU
Evaluasi Pemanfaatan Sistem Informasi Desa (SID) di Kabupaten Gresik (Studi kasus di seluruh Desa pada Kecamatan Ujungpangkah) Syamsi, Nur; Indarto, Tomi; Kholifah, Anik Nur; Hakim, Lutfi; Sutarto, Auditya Purwandini; Suparno, Suparno; Afiyat, Nur
Jurnal Optimalisasi Vol 11, No 1 (2025): April
Publisher : Universitas Teuku Umar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35308/jopt.v11i1.11629

Abstract

This study aims to evaluate the utilization of the Village Information System (Sistem Informasi Desa or SID) in Gresik Regency, with a case study involving all villages in the Ujungpangkah District. The Village Information System (SID) serves as a crucial tool for enhancing the efficiency of public services at the village level and promoting transparency and accountability in village governance. However, its implementation and utilization still face various challenges. This research employs both qualitative and quantitative approaches to obtain a comprehensive overview of the extent to which SID has been implemented and utilized by the villages in Ujungpangkah District. Data were collected through in-depth interviews, questionnaires, and field observations. The analysis was conducted using descriptive and inferential methods to identify the factors influencing SID utilization, including technical aspects, human resources, and government support. The findings indicate that the utilization of SID in these villages remains suboptimal, with the main obstacles being limited technological infrastructure, lack of training for village officials, and insufficient support from the local government. The recommendations derived from this study are expected to serve as a reference for local governments in improving the utilization of SID to achieve better village governance.
Community-based disaster mitigation in Sinambela Village, Humbang Hasundutan District, North Sumatra Province [Mitigasi bencana berbasis masyarakat di Desa Sinambela Kabupaten Humbang Hasundutan Provinsi Sumatera Utara] Syahputra, Orang Kaya Hasnanda; Samsuri, Samsuri; Hakim, Lutfi; Fadhilla, Suri
Buletin Pengabdian Bulletin of Community Services Vol 5, No 1 (2025): Bull. Community. Serv.
Publisher : The Institute for Research and Community Services (LPPM) Universitas Syiah Kuala (USK)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24815/bulpen.v5i1.44456

Abstract

Sinambela Village has a high potential for geological and hydrometeorological disasters. This is influenced by the biophysical conditions of the village. A significant portion of the community in Sinambela Village is not yet well educated about natural disasters and disaster mitigation. Therefore, disaster mitigation efforts are necessary, considering that floods and landslides have previously struck Simangulampe Village in Bakti Raja Sub-District, which is in the same district as Sinambela Village. This incident occurred on December 1, 2023, resulting in 12 people missing and one confirmed fatality. The primary cause of the flooding was heavy rainfall. In addition to hydrometeorological factors, flooding in Sinambela Village was also caused by various other factors, including sedimentation in the downstream section of the river, reduced vegetation cover in the upstream area, and river channel narrowing. Based on the situational analysis and the challenges faced by the community, it is crucial to build a society that is prepared for disasters, capable of anticipating them, and able to adapt to them an effort known as disaster mitigation. The proposed solution involves community involvement in disaster planning, emergency response, and post-disaster recovery. This community-based initiative is known as Disaster-Resilient Village (DESTANA). Given the increasing risks and challenges of hydrometeorological disasters, this study aims to ensure that the community remains alert and prepared to face potential hazards in their environment, enhances their ability to withstand threats, and strengthens their overall resilience.
PREDICTION OF THE ELECTRIC POWER BY OSCILLATING WATER COLUMN WAVE POWER PLANTS ON BAWEAN ISLAND USING LSTM Putri, Risma Madurahma; Hakim, Lutfi; Novitasari, Dian C Rini; Asyhar, Ahmad Hanif; Setiawan, Fajar
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 19 No 4 (2025): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol19iss4pp2287-2300

Abstract

The demand for electricity in Indonesia continues to increase in line with population growth and the expansion of economic development. This increase is not matched by the diminishing electricity resources, as fossil fuels, which are non-renewable, are being used. Therefore, there is a need for renewable energy sources that can be utilized as long-term electricity resources. The abundant marine areas in Indonesia make it a potential source of alternative energy, one form of its utilization is the Ocean Wave Power Plant using the Oscillating Water Column (OWC) method. Bawean Island in Gresik is one of the regions that has this potential, while also facing long-standing electricity supply limitations that have resulted in uneven electricity distribution among the community. The problem does not stop at power generation but also extends to the transmission system between supply and demand. This research is conducted to predict the electricity generated by the ocean wave power plant to help avoid mismatches when supplying electricity. This study uses time series data from January 1st, 2021, to May 5th, 2024, which includes wave height, length, period, and amplitude. Electricity prediction based on these parameters can be performed using deep learning-based methods that can effectively process sequential time series data, such as the Long Short Term Memory (LSTM) method, by experimenting with the number of neurons, epochs, and batch sizes. The best prediction results for the variables of height, length, period, and amplitude of the waves obtained MAPE values of 0.3657%, 0.1637%, 0.0888%, and 0.3480%, respectively. The electricity prediction results from the best parameters obtained a MAPE of 0.3549%.
E-Ticket Application as Supporting Technology During COVID-19 Pandemic in Baluran National Park Kristanto, Sepyan Purnama; Yusuf, Dianni; Hakim, Lutfi; Rifqi, Mochamad Misbahur
INTEK: Jurnal Penelitian Vol 8 No 1 (2021): April 2021
Publisher : Politeknik Negeri Ujung Pandang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31963/intek.v8i1.2307

Abstract

The COVID-19 outbreak has a major impact, especially on tourism. Closure of tourist attractions must be enforced to prevent the spread of the virus. People are required to maintain a safe distance and avoid crowds (physical distancing). Some policies and guidelines are created to adapt to the new normal era to drive and stabilize the people's economy during this pandemic. Tourist attractions start operating with government guidelines, including limiting the number of visitors and implementing supporting technology to prevent queues of visitors when purchasing entrance tickets. This study develops a web-based system to facilitate ordering tickets through a web-based system, uploading proof of transfer, and obtaining e-tickets to be shown to ticket officers. Extreme Programming model was used. The e-ticket system has been tested at Baluran National Park using the Blackbox method, showing that the system has the functionality to meet user needs.
Modeling the Farmer Exchange Rate in Indonesia Using the Vector Error Correction Model Method Farida, Yuniar; Hamidah, Afanin; Sari, Silvia Kartika; Hakim, Lutfi
MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer Vol. 23 No. 2 (2024)
Publisher : Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/matrik.v23i2.3407

Abstract

The agricultural sector plays a crucial role in the Indonesian economy. However, the farm sector still has serious problems, including agricultural product prices, which often fall when the harvest supply is abundant. So often, the income obtained is not proportional to the price spent by farmers, which has an impact on decreasing the welfare of farmers. An indicator to observe changes in the interest of Indonesian farmers is the Farmer Exchange Rate Index (NTP). This study aims to form a model and project the welfare level of farmers in Indonesia, focusing on NTP indicators, which are caused by the influence of variables such as inflation, Gross Domestic Product (GDP), interest rates, and the rupiah exchange rate. The method used is the Vector Error Correction Model (VECM), used when there are indications that the research variables do not show stability at the initial level and there is a cointegration relationship. The results of this study show that in the long run, significant factors affecting NTP are inflation, interest rates, and the rupiah exchange rate. Meanwhile, in the short term, the variables that have an impact are GDP and the rupiah exchange rate. The resulting VECM model shows a MAPE error rate of 1.79%, indicating excellent performance, as the MAPE error rate is below 10%. The implication of this research is provides information related to NTP projection that can be used to formulate strategies to strengthen Indonesia's agricultural sector.
Co-Authors Abdul Muid Afiyat, Nur Ahmad Hanif Asyhar Akh Syaiful Rijal Ala'uddin, M. Alimin Alimin, Alimin Anwar, Farikhul Bagus Zaqqie Berti Ibmagara, Afridha Dianni Yusuf Dwi Wijanarko Fadhilla, Suri FAJAR SETIAWAN Gusminto, Eka Bambang Hadi Paramu Hadromi - Hamidah, Afanin Indarto, Tomi Khalim, Abdul Khoiriyah, Robihatul Kholifah, Anik Nur M. Najib Novitasari , Dian Candra Rini Novitasari, Dian C Rini Nur Syamsi Prakosa Rachwibowo Putri Oktavia, Nabiilah Putri, Risma Madurahma Rifqi, Mochamad Misbahur Samsuri Samsuri Sari, Ribut Nawang Sari, Silvia Kartika Sepyan Purnama Kristanto Sukatja Suparno Suparno Sutarto, Auditya Purwandini Syahputra, Orang Kaya Hasnanda Widiarso Dian Agus Yuniar Farida, Yuniar