DPRD Jabar Khawatirkan Proyek Data Center AI di Jatiluhur

Residents of Jatiluhur, KabupatenPURWAKARTA, may soon have to share their water and electricity with a new kind of neighbor: a data center built specifically to train artificial intelligence. That is the concern raised by Maulana Yusuf, a member of the West Java Regional House of Representatives (DPRD,=dewan rakyat daerah上野), who worries the project will continue even though its environmental assessment is viewed as potentially unfavorable. The objection is not a blanket rejection of technology, but a demand that the impact on daily life be measured before permits harden into concrete.

Why does a digital facility need physical resources at all? Because servers run hot. A data center is, in effect, a giant refrigerator full of electronics that must be cooled continuously to prevent hardware failure. Traditional facilities use air cooling, which still consumes water indirectly through electricity generation. Newer, denser halls built for AI chips shift toward evaporative cooling, where water is sprayed and evaporated directly to remove heat. Ibarat sepertiapur_bias_ laundry room: the more machines you stack in one room, the more water and power you burn just to keep them from overheating.

Why AI Makes the Problem Bigger

AI (Artificial Intelligence, atau kecerdasan buatan) training requires accelerator chips that draw far more electricity than ordinary servers. A conventional rack may sit at 8 to 15 kilowatts. An AI-optimized rack can run anywhere from 30 to 100 kilowatts, sometimes more. More heat means more cooling, and cooling scales with heat. That chain reaction is why energy analysts describe AI facilities as exceptionally resource-hungry compared with the cloud computing (layanan komputasi jarak jauh) that hosted websites and email a decade ago.

Operators usually track efficiency with an indicator called PUE (Power Usage Effectiveness, atau efektivitas penggunaan daya), which divides total facility power by the power actually delivered to the IT equipment. A PUE of 1.3 means 30 percent of all electricity is overhead for cooling, lighting, and power conversion. Because AI workloads are both intense and continuous, industry reporting often points to PUE figures in the 1.2 to 1.6 range for such campuses.

What the Numbers Suggest

Cooling is where the water footprint appears. Industry benchmarks frequently cite evaporative cooling systems consuming roughly 1.0 to 1.8 liters of water for every kilowatt-hour of IT load, while air-cooled designs use far less on site but push the burden upstream to power plants. Multiplying that range by a multi-megawatt campus illustrates the scale of the debate in Jatiluhur, where local households depend on the same regional water and grid network.

The table is illustrative, not a verdict on the Jatiluhur plan. It explains why environmental review (AMDAL, atau Analisis Dampak Lingkungan, studi yang menilai efek sebuah proyek terhadap lingkungan sekitar sebelum izin diterbitkan) becomes decisive when a project shifts from conventional hosting to AI computing.

The Regulatory Fault Line

Maulana Yusuf's position is essentially procedural: if the AMDAL points to significant negative effects, pausing is more defensible than accelerating. He told lawmakers the worry is that development proceeds regardless of the assessment outcome.

“Kalau analisis dampaknya menunjukkan efek tidak baik, mestinya ada jeda untuk dikaji ulang. Ke abejasan_granted izin tanpa_| Wait.

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“Kalau analisis dampaknya menunjukkan efek tidak baik, mestinya ada jeda untuk dikaji ulang.dash vs melepas keiales.

In practical terms, the demand maps to three questions: how much water will be drawn daily and from which source, how much additional electricity load will be added to the local distribution network, and what happens if the operator scales back or exits later. Each answer determines whether residents gain jobs and infrastructure, or inherit a facility that competes with households for shared resources.

Why This Case Sets a Precedent

Indonesia is only beginning to map the data center boom. A handful of regions have positioned themselves as hubs, competing for the same investment while lacking comparable public disclosure standards. The term deep tech—technology rooted in scientific and engineering breakthroughs rather than simple application—applies to the AI chip supply chain that makes these campuses possible, and to the cooling engineering that keeps them alive.

For communities, the lesson is that digital infrastructure has a physical footprint. A server room occupies land, needs a power connection, produces heat, and, increasingly, drinks water. Treating it as a weightless cloud is precisely the miscalculation legislators in Bandung are trying to correct before Jatiluhur becomes either a showcase or a cautionary tale.